{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Transforming Vertical Coordinates\n",
    "\n",
    "A common need in the analysis of ocean and atmospheric data is to transform the vertical coordinate from its original coordinate (e.g. depth) to a new coordinate (e.g. density).\n",
    "Xgcm supports this sort of one-dimensional coordinate transform on `Axis` and `Grid` objects using the `transform` method.\n",
    "Two algorithms are implemented:\n",
    "\n",
    "- _Linear interpolation:_ Linear interpolation is designed to interpolate intensive quantities (e.g. temperature) from one coordinate to another. This method is suitable when the target coordinate is monotonically increasing or decreasing and the data variable is intensive. For example, you want to visualize oxygen on density surfaces from a z-coordinate ocean model.\n",
    "    - _Logarithmic interpolation:_ Logarithmic interpolation (which is linear interpolation done after applying a logarithm to the target coordinate) is also available. This method is suitable when variation of the intensive quantity is best related to the logarithm of the target coordinate, rather than the target coordinate itself. For example, you want to analyze data from a sigma-coordinate atmospheric model on isobaric (constant pressure) surfaces.\n",
    "- _Conservative remapping:_ This algorithm is designed to conserve extensive quantities (e.g. transport, heat content). It requires knowledge of cell bounds in both the source and target coordinate. It also handles non-monotonic target coordinates.\n",
    "\n",
    "On this page, we explain how to use these coordinate transformation capabilities."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from xgcm import Grid\n",
    "import xarray as xr\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1D Toy Data Example\n",
    "\n",
    "First we will create a simple, one-dimensional dataset to illustrate how the `transform` function works.\n",
    "This dataset contains\n",
    "\n",
    "- a coordinate called `z`, representing the original depth coordinate\n",
    "\n",
    "- a data variable called `theta`, a function of `z`, which we want as our new vertical coordinate\n",
    "\n",
    "- a data variable called `phi`, also a function of `z`, which represents the data we want to transform into this new coordinate space\n",
    "\n",
    "In an oceanic context `theta` might be density and `phi` might be oxygen.\n",
    "In an atmospheric context, `theta` might be potential temperature and `phi` might be potential vorticity."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
       "<defs>\n",
       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
       "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
       "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
       "</symbol>\n",
       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
       "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
       "<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "</symbol>\n",
       "</defs>\n",
       "</svg>\n",
       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
       " *\n",
       " */\n",
       "\n",
       ":root {\n",
       "  --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
       "  --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
       "  --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
       "  --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
       "  --xr-background-color: var(--jp-layout-color0, white);\n",
       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
       "}\n",
       "\n",
       "html[theme=dark],\n",
       "body.vscode-dark {\n",
       "  --xr-font-color0: rgba(255, 255, 255, 1);\n",
       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
       "  --xr-border-color: #1F1F1F;\n",
       "  --xr-disabled-color: #515151;\n",
       "  --xr-background-color: #111111;\n",
       "  --xr-background-color-row-even: #111111;\n",
       "  --xr-background-color-row-odd: #313131;\n",
       "}\n",
       "\n",
       ".xr-wrap {\n",
       "  display: block !important;\n",
       "  min-width: 300px;\n",
       "  max-width: 700px;\n",
       "}\n",
       "\n",
       ".xr-text-repr-fallback {\n",
       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-header {\n",
       "  padding-top: 6px;\n",
       "  padding-bottom: 6px;\n",
       "  margin-bottom: 4px;\n",
       "  border-bottom: solid 1px var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-header > div,\n",
       ".xr-header > ul {\n",
       "  display: inline;\n",
       "  margin-top: 0;\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-obj-type,\n",
       ".xr-array-name {\n",
       "  margin-left: 2px;\n",
       "  margin-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-obj-type {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-sections {\n",
       "  padding-left: 0 !important;\n",
       "  display: grid;\n",
       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: '►';\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:  (z: 10)\n",
       "Coordinates:\n",
       "  * z        (z) int64 2 3 4 5 6 7 8 9 10 11\n",
       "Data variables:\n",
       "    phi      (z) float64 1.633 1.165 1.233 1.637 ... 1.657 1.358 1.423 1.133\n",
       "    theta    (z) float64 0.6931 1.099 1.386 1.609 ... 2.079 2.197 2.303 2.398</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-13844fd6-bd21-479f-9f9a-90ce1310b759' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-13844fd6-bd21-479f-9f9a-90ce1310b759' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>z</span>: 10</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-10f53929-2650-4f51-a3af-46c84580c9eb' class='xr-section-summary-in' type='checkbox'  checked><label for='section-10f53929-2650-4f51-a3af-46c84580c9eb' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>z</span></div><div class='xr-var-dims'>(z)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>2 3 4 5 6 7 8 9 10 11</div><input id='attrs-17a1555c-2b63-4afc-9686-772ce07c308d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-17a1555c-2b63-4afc-9686-772ce07c308d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2a9fe0c0-1702-49b1-9a91-07a2db68a39c' class='xr-var-data-in' type='checkbox'><label for='data-2a9fe0c0-1702-49b1-9a91-07a2db68a39c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 2,  3,  4,  5,  6,  7,  8,  9, 10, 11])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-b8c923d8-8adf-40ab-b6e1-c6ed6b0b1d97' class='xr-section-summary-in' type='checkbox'  checked><label for='section-b8c923d8-8adf-40ab-b6e1-c6ed6b0b1d97' class='xr-section-summary' >Data variables: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>phi</span></div><div class='xr-var-dims'>(z)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.633 1.165 1.233 ... 1.423 1.133</div><input id='attrs-be97d6b3-3788-4536-aad9-3742bd943184' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-be97d6b3-3788-4536-aad9-3742bd943184' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a120f794-8d63-496d-9ffd-b512afe9ca66' class='xr-var-data-in' type='checkbox'><label for='data-a120f794-8d63-496d-9ffd-b512afe9ca66' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1.63287665, 1.16507553, 1.23304642, 1.63660282, 1.53322135,\n",
       "       1.19352428, 1.65746418, 1.35807084, 1.42273616, 1.13307975])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>theta</span></div><div class='xr-var-dims'>(z)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.6931 1.099 1.386 ... 2.303 2.398</div><input id='attrs-8a60b03d-98dc-4f49-8038-e1e32ff7de69' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8a60b03d-98dc-4f49-8038-e1e32ff7de69' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-287fad2e-95ee-4bd0-a760-56d4c9304855' class='xr-var-data-in' type='checkbox'><label for='data-287fad2e-95ee-4bd0-a760-56d4c9304855' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0.69314718, 1.09861229, 1.38629436, 1.60943791, 1.79175947,\n",
       "       1.94591015, 2.07944154, 2.19722458, 2.30258509, 2.39789527])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-4b749d96-24ac-4e17-aa33-5112f9a8cc4a' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-4b749d96-24ac-4e17-aa33-5112f9a8cc4a' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:  (z: 10)\n",
       "Coordinates:\n",
       "  * z        (z) int64 2 3 4 5 6 7 8 9 10 11\n",
       "Data variables:\n",
       "    phi      (z) float64 1.633 1.165 1.233 1.637 ... 1.657 1.358 1.423 1.133\n",
       "    theta    (z) float64 0.6931 1.099 1.386 1.609 ... 2.079 2.197 2.303 2.398"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "z = np.arange(2, 12)\n",
    "theta = xr.DataArray(np.log(z), dims=['z'], coords={'z': z})\n",
    "phi = xr.DataArray(np.flip(np.log(z)*0.5+ np.random.rand(len(z))), dims=['z'], coords={'z':z})\n",
    "ds = xr.Dataset({'phi': phi, 'theta': theta})\n",
    "ds"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's plot this data. Note that, for a simple 1D profile, we can easily visualize `phi` in `theta` space by simply plotting `phi` vs. `theta`. This is essentially a form of linear interpolation, performed automatically by matplotlib when it draws lines between the discrete points of our data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x360 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "def plot_profile():\n",
    "    fig, (ax1, ax2, ax3) = plt.subplots(ncols=3, figsize=[8,5])\n",
    "    ds.theta.plot(ax=ax1, y='z', marker='.', yincrease=False)\n",
    "    ds.phi.plot(ax=ax2, y='z', marker='.', yincrease=False)\n",
    "    ds.swap_dims({'z': 'theta'}).phi.plot(ax=ax3, y='theta', marker='.', yincrease=False)\n",
    "    fig.subplots_adjust(wspace=0.5)\n",
    "    return ax3\n",
    "\n",
    "plot_profile();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Linear transformation\n",
    "\n",
    "Ok now lets transform `phi` to `theta` coordinates using linear interpolation.\n",
    "A key part of this is to define specific `theta` levels onto which we want to interpolate the data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
       "<defs>\n",
       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
       "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
       "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
       "</symbol>\n",
       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
       "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
       "<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "</symbol>\n",
       "</defs>\n",
       "</svg>\n",
       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
       " *\n",
       " */\n",
       "\n",
       ":root {\n",
       "  --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
       "  --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
       "  --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
       "  --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
       "  --xr-background-color: var(--jp-layout-color0, white);\n",
       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
       "}\n",
       "\n",
       "html[theme=dark],\n",
       "body.vscode-dark {\n",
       "  --xr-font-color0: rgba(255, 255, 255, 1);\n",
       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
       "  --xr-border-color: #1F1F1F;\n",
       "  --xr-disabled-color: #515151;\n",
       "  --xr-background-color: #111111;\n",
       "  --xr-background-color-row-even: #111111;\n",
       "  --xr-background-color-row-odd: #313131;\n",
       "}\n",
       "\n",
       ".xr-wrap {\n",
       "  display: block !important;\n",
       "  min-width: 300px;\n",
       "  max-width: 700px;\n",
       "}\n",
       "\n",
       ".xr-text-repr-fallback {\n",
       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-header {\n",
       "  padding-top: 6px;\n",
       "  padding-bottom: 6px;\n",
       "  margin-bottom: 4px;\n",
       "  border-bottom: solid 1px var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-header > div,\n",
       ".xr-header > ul {\n",
       "  display: inline;\n",
       "  margin-top: 0;\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-obj-type,\n",
       ".xr-array-name {\n",
       "  margin-left: 2px;\n",
       "  margin-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-obj-type {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-sections {\n",
       "  padding-left: 0 !important;\n",
       "  display: grid;\n",
       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: '►';\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;phi&#x27; (theta: 20)&gt;\n",
       "array([       nan,        nan,        nan,        nan,        nan,\n",
       "       1.52174096, 1.33957156, 1.16664694, 1.20395286, 1.29590695,\n",
       "       1.5814605 , 1.56436105, 1.30629331, 1.56431596, 1.36623482,\n",
       "       1.22265461,        nan,        nan,        nan,        nan])\n",
       "Coordinates:\n",
       "  * theta    (theta) float64 0.0 0.1579 0.3158 0.4737 ... 2.526 2.684 2.842 3.0</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'phi'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>theta</span>: 20</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-4f6b86f2-8bfc-4e8d-b967-22fde06e56b4' class='xr-array-in' type='checkbox' checked><label for='section-4f6b86f2-8bfc-4e8d-b967-22fde06e56b4' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>nan nan nan nan nan 1.522 1.34 ... 1.564 1.366 1.223 nan nan nan nan</span></div><div class='xr-array-data'><pre>array([       nan,        nan,        nan,        nan,        nan,\n",
       "       1.52174096, 1.33957156, 1.16664694, 1.20395286, 1.29590695,\n",
       "       1.5814605 , 1.56436105, 1.30629331, 1.56431596, 1.36623482,\n",
       "       1.22265461,        nan,        nan,        nan,        nan])</pre></div></div></li><li class='xr-section-item'><input id='section-b7b8e496-ced8-40ae-9164-0e47935216b7' class='xr-section-summary-in' type='checkbox'  checked><label for='section-b7b8e496-ced8-40ae-9164-0e47935216b7' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>theta</span></div><div class='xr-var-dims'>(theta)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.1579 0.3158 ... 2.842 3.0</div><input id='attrs-5974b592-8fb1-449b-928a-72b07a8f168e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5974b592-8fb1-449b-928a-72b07a8f168e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-23f5195f-1a1c-4a73-8ece-7ce10192c6f4' class='xr-var-data-in' type='checkbox'><label for='data-23f5195f-1a1c-4a73-8ece-7ce10192c6f4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0.      , 0.157895, 0.315789, 0.473684, 0.631579, 0.789474, 0.947368,\n",
       "       1.105263, 1.263158, 1.421053, 1.578947, 1.736842, 1.894737, 2.052632,\n",
       "       2.210526, 2.368421, 2.526316, 2.684211, 2.842105, 3.      ])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-55c05492-4a58-448c-ab83-cb9d66bb0f08' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-55c05492-4a58-448c-ab83-cb9d66bb0f08' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'phi' (theta: 20)>\n",
       "array([       nan,        nan,        nan,        nan,        nan,\n",
       "       1.52174096, 1.33957156, 1.16664694, 1.20395286, 1.29590695,\n",
       "       1.5814605 , 1.56436105, 1.30629331, 1.56431596, 1.36623482,\n",
       "       1.22265461,        nan,        nan,        nan,        nan])\n",
       "Coordinates:\n",
       "  * theta    (theta) float64 0.0 0.1579 0.3158 0.4737 ... 2.526 2.684 2.842 3.0"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# First create an xgcm grid object\n",
    "grid = Grid(ds, coords={'Z': {'center':'z'}}, periodic=False)\n",
    "\n",
    "# define the target values in density, linearly spaced\n",
    "theta_target = np.linspace(0, 3, 20)\n",
    "\n",
    "# and transform\n",
    "phi_transformed = grid.transform(ds.phi, 'Z', theta_target, target_data=ds.theta)\n",
    "phi_transformed"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now let's see what the result looks like."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fc864c01c90>]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x360 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = plot_profile()\n",
    "phi_transformed.plot(ax=ax, y='theta', marker='.')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Not too bad. We can increase the number of interpolation levels to capture more of the small scale structure."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fc864af5450>]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x360 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "target_theta = np.linspace(0,3, 100)\n",
    "phi_transformed = grid.transform(ds.phi, 'Z', target_theta, target_data=ds.theta)\n",
    "ax = plot_profile()\n",
    "phi_transformed.plot(ax=ax, y='theta', marker='.')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note that by default, values of `theta_target` which lie outside the range of `theta` have been masked (set to `NaN`).\n",
    "To disable this behavior, you can pass `mask_edges=False`; values outside the range of `theta` will be filled with the nearest valid value."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fc85b30f3a0>]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x360 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "target_theta = np.linspace(0,3, 60)\n",
    "phi_transformed = grid.transform(ds.phi, 'Z', target_theta, target_data=ds.theta, mask_edges=False)\n",
    "ax = plot_profile()\n",
    "phi_transformed.plot(ax=ax, y='theta', marker='.')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Conservative transformation\n",
    "\n",
    "Conservative transformation is designed to preseve the total sum of `phi` over the `Z` axis.\n",
    "It presumes that `phi` is an _extensive quantity_, i.e. a quantity that is already volume weighted, with respect to the Z axis: for example, units of `Kelvins * meters` for heat content, rather than just `Kelvins`.\n",
    "The conservative method requires more input data at the moment.\n",
    "You have to not only specify the coordinates of the cell centers, but also the cell faces (or bounds/boundaries). In xgcm we achieve this by defining the bounding coordinates as the `outer` axis position.\n",
    "The target `theta` values are likewise intepreted as cell boundaries in `theta`-space.\n",
    "In this way, conservative transformation is similar to calculating a histogram."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
       "<defs>\n",
       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
       "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
       "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
       "</symbol>\n",
       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
       "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
       "<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "</symbol>\n",
       "</defs>\n",
       "</svg>\n",
       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
       " *\n",
       " */\n",
       "\n",
       ":root {\n",
       "  --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
       "  --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
       "  --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
       "  --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
       "  --xr-background-color: var(--jp-layout-color0, white);\n",
       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
       "}\n",
       "\n",
       "html[theme=dark],\n",
       "body.vscode-dark {\n",
       "  --xr-font-color0: rgba(255, 255, 255, 1);\n",
       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
       "  --xr-border-color: #1F1F1F;\n",
       "  --xr-disabled-color: #515151;\n",
       "  --xr-background-color: #111111;\n",
       "  --xr-background-color-row-even: #111111;\n",
       "  --xr-background-color-row-odd: #313131;\n",
       "}\n",
       "\n",
       ".xr-wrap {\n",
       "  display: block !important;\n",
       "  min-width: 300px;\n",
       "  max-width: 700px;\n",
       "}\n",
       "\n",
       ".xr-text-repr-fallback {\n",
       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-header {\n",
       "  padding-top: 6px;\n",
       "  padding-bottom: 6px;\n",
       "  margin-bottom: 4px;\n",
       "  border-bottom: solid 1px var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-header > div,\n",
       ".xr-header > ul {\n",
       "  display: inline;\n",
       "  margin-top: 0;\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-obj-type,\n",
       ".xr-array-name {\n",
       "  margin-left: 2px;\n",
       "  margin-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-obj-type {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-sections {\n",
       "  padding-left: 0 !important;\n",
       "  display: grid;\n",
       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: '►';\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:  (z: 10, zc: 11)\n",
       "Coordinates:\n",
       "  * z        (z) int64 2 3 4 5 6 7 8 9 10 11\n",
       "  * zc       (zc) float64 1.5 2.5 3.5 4.5 5.5 6.5 7.5 8.5 9.5 10.5 11.5\n",
       "Data variables:\n",
       "    phi      (z) float64 1.633 1.165 1.233 1.637 ... 1.657 1.358 1.423 1.133\n",
       "    theta    (z) float64 0.6931 1.099 1.386 1.609 ... 2.079 2.197 2.303 2.398</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-50f02f7e-506e-413f-9603-79abac2a5dc3' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-50f02f7e-506e-413f-9603-79abac2a5dc3' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>z</span>: 10</li><li><span class='xr-has-index'>zc</span>: 11</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-d9d312ea-b077-493b-95d6-9223d8ff6517' class='xr-section-summary-in' type='checkbox'  checked><label for='section-d9d312ea-b077-493b-95d6-9223d8ff6517' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>z</span></div><div class='xr-var-dims'>(z)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>2 3 4 5 6 7 8 9 10 11</div><input id='attrs-ed16adca-618f-42e7-95a9-13fa7fd67181' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ed16adca-618f-42e7-95a9-13fa7fd67181' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-18bc0875-4eb3-4a49-9c47-ac7fc316c6ef' class='xr-var-data-in' type='checkbox'><label for='data-18bc0875-4eb3-4a49-9c47-ac7fc316c6ef' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 2,  3,  4,  5,  6,  7,  8,  9, 10, 11])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>zc</span></div><div class='xr-var-dims'>(zc)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.5 2.5 3.5 4.5 ... 9.5 10.5 11.5</div><input id='attrs-d7fb8ee0-dc8c-40bb-8cef-207775941682' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d7fb8ee0-dc8c-40bb-8cef-207775941682' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-50e044bc-1beb-4bb4-a481-89aef55e90f1' class='xr-var-data-in' type='checkbox'><label for='data-50e044bc-1beb-4bb4-a481-89aef55e90f1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 1.5,  2.5,  3.5,  4.5,  5.5,  6.5,  7.5,  8.5,  9.5, 10.5, 11.5])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-c354fa2b-c250-46c9-9e01-047f8f1f73b5' class='xr-section-summary-in' type='checkbox'  checked><label for='section-c354fa2b-c250-46c9-9e01-047f8f1f73b5' class='xr-section-summary' >Data variables: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>phi</span></div><div class='xr-var-dims'>(z)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.633 1.165 1.233 ... 1.423 1.133</div><input id='attrs-b5d1fb23-80ea-4015-9dfd-5a83a5c54fa7' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b5d1fb23-80ea-4015-9dfd-5a83a5c54fa7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-86e31956-c2ec-4720-8e02-762cc6e1a210' class='xr-var-data-in' type='checkbox'><label for='data-86e31956-c2ec-4720-8e02-762cc6e1a210' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1.63287665, 1.16507553, 1.23304642, 1.63660282, 1.53322135,\n",
       "       1.19352428, 1.65746418, 1.35807084, 1.42273616, 1.13307975])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>theta</span></div><div class='xr-var-dims'>(z)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.6931 1.099 1.386 ... 2.303 2.398</div><input id='attrs-bb0e1505-7626-4231-a621-51bd2e89dcf8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-bb0e1505-7626-4231-a621-51bd2e89dcf8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e29b93ec-30ab-44fe-b4de-a70fbc71ac3d' class='xr-var-data-in' type='checkbox'><label for='data-e29b93ec-30ab-44fe-b4de-a70fbc71ac3d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0.69314718, 1.09861229, 1.38629436, 1.60943791, 1.79175947,\n",
       "       1.94591015, 2.07944154, 2.19722458, 2.30258509, 2.39789527])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-c7678f64-713c-42a4-a9a1-b74f7edd353f' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-c7678f64-713c-42a4-a9a1-b74f7edd353f' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:  (z: 10, zc: 11)\n",
       "Coordinates:\n",
       "  * z        (z) int64 2 3 4 5 6 7 8 9 10 11\n",
       "  * zc       (zc) float64 1.5 2.5 3.5 4.5 5.5 6.5 7.5 8.5 9.5 10.5 11.5\n",
       "Data variables:\n",
       "    phi      (z) float64 1.633 1.165 1.233 1.637 ... 1.657 1.358 1.423 1.133\n",
       "    theta    (z) float64 0.6931 1.099 1.386 1.609 ... 2.079 2.197 2.303 2.398"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# define the cell bounds in depth\n",
    "zc = np.arange(1,12)+0.5\n",
    "\n",
    "# add them to the existing dataset\n",
    "ds = ds.assign_coords({'zc': zc})\n",
    "ds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<xgcm.Grid>\n",
       "Z Axis (not periodic, boundary=None):\n",
       "  * center   z --> outer\n",
       "  * outer    zc --> center"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Recreate the grid object with a staggered `center`/`outer` coordinate layout\n",
    "grid = Grid(ds, coords={'Z':{'center':'z', 'outer':'zc'}},\n",
    "            periodic=False)\n",
    "grid"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Currently the `target_data`(`theta` in this case) has to be located on the `outer` coordinate for the conservative method (compared to the `center` for the linear method).\n",
    "\n",
    "We can easily interpolate `theta` on the outer coordinate with the grid object."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
       "<defs>\n",
       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
       "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
       "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
       "</symbol>\n",
       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
       "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
       "<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "</symbol>\n",
       "</defs>\n",
       "</svg>\n",
       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
       " *\n",
       " */\n",
       "\n",
       ":root {\n",
       "  --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
       "  --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
       "  --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
       "  --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
       "  --xr-background-color: var(--jp-layout-color0, white);\n",
       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
       "}\n",
       "\n",
       "html[theme=dark],\n",
       "body.vscode-dark {\n",
       "  --xr-font-color0: rgba(255, 255, 255, 1);\n",
       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
       "  --xr-border-color: #1F1F1F;\n",
       "  --xr-disabled-color: #515151;\n",
       "  --xr-background-color: #111111;\n",
       "  --xr-background-color-row-even: #111111;\n",
       "  --xr-background-color-row-odd: #313131;\n",
       "}\n",
       "\n",
       ".xr-wrap {\n",
       "  display: block !important;\n",
       "  min-width: 300px;\n",
       "  max-width: 700px;\n",
       "}\n",
       "\n",
       ".xr-text-repr-fallback {\n",
       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-header {\n",
       "  padding-top: 6px;\n",
       "  padding-bottom: 6px;\n",
       "  margin-bottom: 4px;\n",
       "  border-bottom: solid 1px var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-header > div,\n",
       ".xr-header > ul {\n",
       "  display: inline;\n",
       "  margin-top: 0;\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-obj-type,\n",
       ".xr-array-name {\n",
       "  margin-left: 2px;\n",
       "  margin-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-obj-type {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-sections {\n",
       "  padding-left: 0 !important;\n",
       "  display: grid;\n",
       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: '►';\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;theta_outer&#x27; (zc: 11)&gt;\n",
       "array([0.34657359, 0.89587973, 1.24245332, 1.49786614, 1.70059869,\n",
       "       1.86883481, 2.01267585, 2.13833306, 2.24990484, 2.35024018,\n",
       "       1.19894764])\n",
       "Coordinates:\n",
       "  * zc       (zc) float64 1.5 2.5 3.5 4.5 5.5 6.5 7.5 8.5 9.5 10.5 11.5</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'theta_outer'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>zc</span>: 11</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-4584c571-6e63-4c26-8a34-fd645615150f' class='xr-array-in' type='checkbox' checked><label for='section-4584c571-6e63-4c26-8a34-fd645615150f' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>0.3466 0.8959 1.242 1.498 1.701 1.869 2.013 2.138 2.25 2.35 1.199</span></div><div class='xr-array-data'><pre>array([0.34657359, 0.89587973, 1.24245332, 1.49786614, 1.70059869,\n",
       "       1.86883481, 2.01267585, 2.13833306, 2.24990484, 2.35024018,\n",
       "       1.19894764])</pre></div></div></li><li class='xr-section-item'><input id='section-d99e2b26-e0d1-4a65-b326-65d7a5005b76' class='xr-section-summary-in' type='checkbox'  checked><label for='section-d99e2b26-e0d1-4a65-b326-65d7a5005b76' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>zc</span></div><div class='xr-var-dims'>(zc)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.5 2.5 3.5 4.5 ... 9.5 10.5 11.5</div><input id='attrs-0cc13ffc-275b-490d-a18e-2a7c172887fa' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0cc13ffc-275b-490d-a18e-2a7c172887fa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c0735fd7-cd67-4fce-a556-a581e17fe6d5' class='xr-var-data-in' type='checkbox'><label for='data-c0735fd7-cd67-4fce-a556-a581e17fe6d5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 1.5,  2.5,  3.5,  4.5,  5.5,  6.5,  7.5,  8.5,  9.5, 10.5, 11.5])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-b575e569-1968-4eea-8cd7-2b260e81dc1c' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-b575e569-1968-4eea-8cd7-2b260e81dc1c' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'theta_outer' (zc: 11)>\n",
       "array([0.34657359, 0.89587973, 1.24245332, 1.49786614, 1.70059869,\n",
       "       1.86883481, 2.01267585, 2.13833306, 2.24990484, 2.35024018,\n",
       "       1.19894764])\n",
       "Coordinates:\n",
       "  * zc       (zc) float64 1.5 2.5 3.5 4.5 5.5 6.5 7.5 8.5 9.5 10.5 11.5"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds['theta_outer'] = grid.interp(ds.theta, 'Z', boundary='fill')\n",
    "ds['theta_outer']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now lets transform the data using the conservative method. Note that the target values will now be interpreted as cell bounds and not cell centers as before."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/jthielen/develop/xgcm/xgcm/transform.py:247: FutureWarning: ``output_sizes`` should be given in the ``dask_gufunc_kwargs`` parameter. It will be removed as direct parameter in a future version.\n",
      "  out = xr.apply_ufunc(\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
       "<defs>\n",
       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
       "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
       "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
       "</symbol>\n",
       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
       "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
       "<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "</symbol>\n",
       "</defs>\n",
       "</svg>\n",
       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
       " *\n",
       " */\n",
       "\n",
       ":root {\n",
       "  --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
       "  --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
       "  --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
       "  --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
       "  --xr-background-color: var(--jp-layout-color0, white);\n",
       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
       "}\n",
       "\n",
       "html[theme=dark],\n",
       "body.vscode-dark {\n",
       "  --xr-font-color0: rgba(255, 255, 255, 1);\n",
       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
       "  --xr-border-color: #1F1F1F;\n",
       "  --xr-disabled-color: #515151;\n",
       "  --xr-background-color: #111111;\n",
       "  --xr-background-color-row-even: #111111;\n",
       "  --xr-background-color-row-odd: #313131;\n",
       "}\n",
       "\n",
       ".xr-wrap {\n",
       "  display: block !important;\n",
       "  min-width: 300px;\n",
       "  max-width: 700px;\n",
       "}\n",
       "\n",
       ".xr-text-repr-fallback {\n",
       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-header {\n",
       "  padding-top: 6px;\n",
       "  padding-bottom: 6px;\n",
       "  margin-bottom: 4px;\n",
       "  border-bottom: solid 1px var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-header > div,\n",
       ".xr-header > ul {\n",
       "  display: inline;\n",
       "  margin-top: 0;\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-obj-type,\n",
       ".xr-array-name {\n",
       "  margin-left: 2px;\n",
       "  margin-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-obj-type {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-sections {\n",
       "  padding-left: 0 !important;\n",
       "  display: grid;\n",
       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: '►';\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;phi&#x27; (theta_outer: 19)&gt;\n",
       "array([0.        , 0.        , 0.37785116, 0.46936054, 0.46936054,\n",
       "       0.48939379, 0.53079432, 0.62434095, 0.91765916, 1.18077243,\n",
       "       1.46775848, 1.57323631, 1.6610291 , 2.16457924, 2.03956194,\n",
       "       0.        , 0.        , 0.        , 0.        ])\n",
       "Coordinates:\n",
       "  * theta_outer  (theta_outer) float64 0.07895 0.2368 0.3947 ... 2.763 2.921</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'phi'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>theta_outer</span>: 19</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-0acd4388-be9d-4e02-91bd-131fc2cf421c' class='xr-array-in' type='checkbox' checked><label for='section-0acd4388-be9d-4e02-91bd-131fc2cf421c' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>0.0 0.0 0.3779 0.4694 0.4694 0.4894 ... 2.165 2.04 0.0 0.0 0.0 0.0</span></div><div class='xr-array-data'><pre>array([0.        , 0.        , 0.37785116, 0.46936054, 0.46936054,\n",
       "       0.48939379, 0.53079432, 0.62434095, 0.91765916, 1.18077243,\n",
       "       1.46775848, 1.57323631, 1.6610291 , 2.16457924, 2.03956194,\n",
       "       0.        , 0.        , 0.        , 0.        ])</pre></div></div></li><li class='xr-section-item'><input id='section-d42a9692-00c8-4993-9285-abfb053b39a1' class='xr-section-summary-in' type='checkbox'  checked><label for='section-d42a9692-00c8-4993-9285-abfb053b39a1' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>theta_outer</span></div><div class='xr-var-dims'>(theta_outer)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.07895 0.2368 ... 2.763 2.921</div><input id='attrs-784b8e65-bad8-4031-88bc-bcffe51040c4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-784b8e65-bad8-4031-88bc-bcffe51040c4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a4239f61-3648-4b83-b615-ea8e2442c2fb' class='xr-var-data-in' type='checkbox'><label for='data-a4239f61-3648-4b83-b615-ea8e2442c2fb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0.078947, 0.236842, 0.394737, 0.552632, 0.710526, 0.868421, 1.026316,\n",
       "       1.184211, 1.342105, 1.5     , 1.657895, 1.815789, 1.973684, 2.131579,\n",
       "       2.289474, 2.447368, 2.605263, 2.763158, 2.921053])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-89faf91d-a67f-42e6-ac09-58713e8bb778' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-89faf91d-a67f-42e6-ac09-58713e8bb778' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'phi' (theta_outer: 19)>\n",
       "array([0.        , 0.        , 0.37785116, 0.46936054, 0.46936054,\n",
       "       0.48939379, 0.53079432, 0.62434095, 0.91765916, 1.18077243,\n",
       "       1.46775848, 1.57323631, 1.6610291 , 2.16457924, 2.03956194,\n",
       "       0.        , 0.        , 0.        , 0.        ])\n",
       "Coordinates:\n",
       "  * theta_outer  (theta_outer) float64 0.07895 0.2368 0.3947 ... 2.763 2.921"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# define the target values in density\n",
    "theta_target = np.linspace(0,3, 20)\n",
    "\n",
    "# and transform\n",
    "phi_transformed_cons = grid.transform(ds.phi,\n",
    "                                      'Z',\n",
    "                                      theta_target,\n",
    "                                      method='conservative',\n",
    "                                      target_data=ds.theta_outer)\n",
    "phi_transformed_cons"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fc85b1c52a0>]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "phi_transformed_cons.plot(y='theta_outer', marker='.', yincrease=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There is no point in comparing `phi_transformed_cons` directly to `phi` or the results of linear interoplation, since here we have reinterpreted `phi` as an extensive quantity.\n",
    "However, we can verify that the sum of the two quantities over the Z axis is exactly the same."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(13.96569797)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds.phi.sum().values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(13.96569797)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "phi_transformed_cons.sum().values"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "### Logarithmic Interpolation\n",
    "\n",
    "Since logarithmic interpolation is most often used when tranforming to pressure (isobaric) coordinates, let's use a new set of example data:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "ds = xr.Dataset(\n",
    "    {\n",
    "        'temperature': ('sigma', [271.75452, 272.79956, 274.8517, 279.22043, 296.48782]),\n",
    "        'pressure': ('sigma', [100180.625, 96250.0, 87369.14, 72186.66, 53718.586]),\n",
    "    },\n",
    "    {\n",
    "        'sigma': [0.9969, 0.9558, 0.8631, 0.7046, 0.5117]\n",
    "    }\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's now transform `temperature` to `pressure` coordinates. As before, a key part of this is to define specific `pressure` levels onto which we want to interpolate the data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
       "<defs>\n",
       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
       "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
       "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
       "</symbol>\n",
       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
       "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
       "<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "</symbol>\n",
       "</defs>\n",
       "</svg>\n",
       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
       " *\n",
       " */\n",
       "\n",
       ":root {\n",
       "  --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
       "  --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
       "  --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
       "  --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
       "  --xr-background-color: var(--jp-layout-color0, white);\n",
       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
       "}\n",
       "\n",
       "html[theme=dark],\n",
       "body.vscode-dark {\n",
       "  --xr-font-color0: rgba(255, 255, 255, 1);\n",
       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
       "  --xr-border-color: #1F1F1F;\n",
       "  --xr-disabled-color: #515151;\n",
       "  --xr-background-color: #111111;\n",
       "  --xr-background-color-row-even: #111111;\n",
       "  --xr-background-color-row-odd: #313131;\n",
       "}\n",
       "\n",
       ".xr-wrap {\n",
       "  display: block !important;\n",
       "  min-width: 300px;\n",
       "  max-width: 700px;\n",
       "}\n",
       "\n",
       ".xr-text-repr-fallback {\n",
       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-header {\n",
       "  padding-top: 6px;\n",
       "  padding-bottom: 6px;\n",
       "  margin-bottom: 4px;\n",
       "  border-bottom: solid 1px var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-header > div,\n",
       ".xr-header > ul {\n",
       "  display: inline;\n",
       "  margin-top: 0;\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-obj-type,\n",
       ".xr-array-name {\n",
       "  margin-left: 2px;\n",
       "  margin-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-obj-type {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-sections {\n",
       "  padding-left: 0 !important;\n",
       "  display: grid;\n",
       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: '►';\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;temperature&#x27; (pressure: 3)&gt;\n",
       "array([271.80163709, 275.48086957, 281.01789905])\n",
       "Coordinates:\n",
       "  * pressure  (pressure) float64 1e+05 8.5e+04 7e+04</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'temperature'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>pressure</span>: 3</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-2537f081-c6ef-40ec-8674-b1b0db431eca' class='xr-array-in' type='checkbox' checked><label for='section-2537f081-c6ef-40ec-8674-b1b0db431eca' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>271.8 275.5 281.0</span></div><div class='xr-array-data'><pre>array([271.80163709, 275.48086957, 281.01789905])</pre></div></div></li><li class='xr-section-item'><input id='section-bfddcf8c-305b-407c-b80c-4e7b75daed73' class='xr-section-summary-in' type='checkbox'  checked><label for='section-bfddcf8c-305b-407c-b80c-4e7b75daed73' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>pressure</span></div><div class='xr-var-dims'>(pressure)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1e+05 8.5e+04 7e+04</div><input id='attrs-d1d2a643-ae43-46fe-b53e-3d21165aba80' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d1d2a643-ae43-46fe-b53e-3d21165aba80' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8d535a92-8ccd-4abc-aac0-8f4230782563' class='xr-var-data-in' type='checkbox'><label for='data-8d535a92-8ccd-4abc-aac0-8f4230782563' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([100000.,  85000.,  70000.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-6d2a458b-19ff-48d2-84c8-3086510810be' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-6d2a458b-19ff-48d2-84c8-3086510810be' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'temperature' (pressure: 3)>\n",
       "array([271.80163709, 275.48086957, 281.01789905])\n",
       "Coordinates:\n",
       "  * pressure  (pressure) float64 1e+05 8.5e+04 7e+04"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Create an xgcm grid object\n",
    "grid = Grid(ds, coords={'Z': {'center':'sigma'}}, periodic=False)\n",
    "\n",
    "# Define isobaric levels of interest (a few standard levels)\n",
    "isobaric_target_levels = np.array([1.0e5, 8.5e4, 7.0e4])\n",
    "\n",
    "# and transform\n",
    "temperature_isobaric = grid.transform(ds.temperature, 'Z', isobaric_target_levels, target_data=ds.pressure, method='log')\n",
    "temperature_isobaric"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "And finally, let's see what the result looks like."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x360 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, (ax1, ax2, ax3) = plt.subplots(ncols=3, figsize=[8,5])\n",
    "ds.pressure.plot(ax=ax1, y='sigma', marker='.', yincrease=False)\n",
    "ds.temperature.plot(ax=ax2, y='sigma', marker='.', yincrease=False)\n",
    "ds.swap_dims({'sigma': 'pressure'}).temperature.plot(ax=ax3, y='pressure', marker='.', yincrease=False)\n",
    "temperature_isobaric.plot(ax=ax3, y='pressure', marker='.')\n",
    "\n",
    "fig.subplots_adjust(wspace=0.7)\n",
    "\n",
    "plt.show();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Realistic Data Example"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "To illustrate these features in a more realistic example, we use data from the CNRM CMIP6 model.\n",
    "These data are available from the [Pangeo Cloud Data Library](https://pangeo-data.github.io/pangeo-cmip6-cloud/accessing_data.html#loading-an-esm-collection).\n",
    "We can see that this is a full, global, 4D ocean dataset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "--> The keys in the returned dictionary of datasets are constructed as follows:\n",
      "\t'activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.zstore.dcpp_init_year.version'\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "\n",
       "<style>\n",
       "    /* Turns off some styling */\n",
       "    progress {\n",
       "        /* gets rid of default border in Firefox and Opera. */\n",
       "        border: none;\n",
       "        /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
       "        background-size: auto;\n",
       "    }\n",
       "    .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
       "        background: #F44336;\n",
       "    }\n",
       "</style>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "\n",
       "    <div>\n",
       "      <progress value='4' class='' max='4' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
       "      100.00% [4/4 00:00<00:00]\n",
       "    </div>\n",
       "    "
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import intake\n",
    "col = intake.open_esm_datastore(\"https://storage.googleapis.com/cmip6/pangeo-cmip6.json\")\n",
    "cat = col.search(\n",
    "    source_id = 'CNRM-ESM2-1',\n",
    "    member_id = 'r1i1p1f2',\n",
    "    experiment_id = 'historical',\n",
    "    variable_id= ['thetao','so','vo','areacello'],\n",
    "    grid_label = 'gn'\n",
    ")\n",
    "ddict = cat.to_dataset_dict(zarr_kwargs={'consolidated':True, 'use_cftime':True}, aggregate=False)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
       "<defs>\n",
       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
       "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
       "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
       "</symbol>\n",
       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
       "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
       "<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "</symbol>\n",
       "</defs>\n",
       "</svg>\n",
       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
       " *\n",
       " */\n",
       "\n",
       ":root {\n",
       "  --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
       "  --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
       "  --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
       "  --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
       "  --xr-background-color: var(--jp-layout-color0, white);\n",
       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
       "}\n",
       "\n",
       "html[theme=dark],\n",
       "body.vscode-dark {\n",
       "  --xr-font-color0: rgba(255, 255, 255, 1);\n",
       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
       "  --xr-border-color: #1F1F1F;\n",
       "  --xr-disabled-color: #515151;\n",
       "  --xr-background-color: #111111;\n",
       "  --xr-background-color-row-even: #111111;\n",
       "  --xr-background-color-row-odd: #313131;\n",
       "}\n",
       "\n",
       ".xr-wrap {\n",
       "  display: block !important;\n",
       "  min-width: 300px;\n",
       "  max-width: 700px;\n",
       "}\n",
       "\n",
       ".xr-text-repr-fallback {\n",
       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-header {\n",
       "  padding-top: 6px;\n",
       "  padding-bottom: 6px;\n",
       "  margin-bottom: 4px;\n",
       "  border-bottom: solid 1px var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-header > div,\n",
       ".xr-header > ul {\n",
       "  display: inline;\n",
       "  margin-top: 0;\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-obj-type,\n",
       ".xr-array-name {\n",
       "  margin-left: 2px;\n",
       "  margin-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-obj-type {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-sections {\n",
       "  padding-left: 0 !important;\n",
       "  display: grid;\n",
       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: '►';\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:       (y: 294, x: 362, nvertex: 4, lev: 75, axis_nbounds: 2,\n",
       "                   time: 1980, y_c: 294)\n",
       "Coordinates: (12/13)\n",
       "    bounds_lat    (y, x, nvertex) float64 dask.array&lt;chunksize=(294, 362, 4), meta=np.ndarray&gt;\n",
       "    bounds_lon    (y, x, nvertex) float64 dask.array&lt;chunksize=(294, 362, 4), meta=np.ndarray&gt;\n",
       "    lat           (y, x) float64 dask.array&lt;chunksize=(294, 362), meta=np.ndarray&gt;\n",
       "  * lev           (lev) float64 0.5058 1.556 2.668 ... 5.698e+03 5.902e+03\n",
       "    lev_bounds    (lev, axis_nbounds) float64 dask.array&lt;chunksize=(75, 2), meta=np.ndarray&gt;\n",
       "    lon           (y, x) float64 dask.array&lt;chunksize=(294, 362), meta=np.ndarray&gt;\n",
       "    ...            ...\n",
       "    time_bounds   (time, axis_nbounds) object dask.array&lt;chunksize=(1980, 2), meta=np.ndarray&gt;\n",
       "    bounds_lat_v  (y_c, x, nvertex) float64 dask.array&lt;chunksize=(294, 362, 4), meta=np.ndarray&gt;\n",
       "    bounds_lon_v  (y_c, x, nvertex) float64 dask.array&lt;chunksize=(294, 362, 4), meta=np.ndarray&gt;\n",
       "    lat_v         (y_c, x) float64 dask.array&lt;chunksize=(294, 362), meta=np.ndarray&gt;\n",
       "    lon_v         (y_c, x) float64 dask.array&lt;chunksize=(294, 362), meta=np.ndarray&gt;\n",
       "    areacello     (y, x) float32 dask.array&lt;chunksize=(294, 362), meta=np.ndarray&gt;\n",
       "Dimensions without coordinates: y, x, nvertex, axis_nbounds, y_c\n",
       "Data variables:\n",
       "    thetao        (time, lev, y, x) float32 dask.array&lt;chunksize=(4, 75, 294, 362), meta=np.ndarray&gt;\n",
       "    so            (time, lev, y, x) float32 dask.array&lt;chunksize=(5, 75, 294, 362), meta=np.ndarray&gt;\n",
       "    vo            (time, lev, y_c, x) float32 dask.array&lt;chunksize=(3, 75, 294, 362), meta=np.ndarray&gt;\n",
       "Attributes: (12/57)\n",
       "    CMIP6_CV_version:        cv=6.2.3.0-7-g2019642\n",
       "    Conventions:             CF-1.7 CMIP-6.2\n",
       "    EXPID:                   CNRM-ESM2-1_historical_r1i1p1f2\n",
       "    activity_id:             CMIP\n",
       "    arpege_minor_version:    6.3.2\n",
       "    branch_method:           standard\n",
       "    ...                      ...\n",
       "    xios_commit:             1442-shuffle\n",
       "    status:                  2019-11-05;created;by nhn2@columbia.edu\n",
       "    netcdf_tracking_ids:     hdl:21.14100/9c34b796-c31d-4c1f-be90-21d032267f6...\n",
       "    version_id:              v20181206\n",
       "    intake_esm_varname:      None\n",
       "    intake_esm_dataset_key:  CMIP.CNRM-CERFACS.CNRM-ESM2-1.historical.r1i1p1f...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-6ac0a74a-fb61-41a0-b3d9-4e70b57916b8' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-6ac0a74a-fb61-41a0-b3d9-4e70b57916b8' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span>y</span>: 294</li><li><span>x</span>: 362</li><li><span>nvertex</span>: 4</li><li><span class='xr-has-index'>lev</span>: 75</li><li><span>axis_nbounds</span>: 2</li><li><span class='xr-has-index'>time</span>: 1980</li><li><span>y_c</span>: 294</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-02fd7604-c07e-4515-9cf8-f13e9bc10325' class='xr-section-summary-in' type='checkbox'  checked><label for='section-02fd7604-c07e-4515-9cf8-f13e9bc10325' class='xr-section-summary' >Coordinates: <span>(13)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>bounds_lat</span></div><div class='xr-var-dims'>(y, x, nvertex)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(294, 362, 4), meta=np.ndarray&gt;</div><input id='attrs-89f256b8-e7ea-4e81-bd20-f5ec600f0b32' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-89f256b8-e7ea-4e81-bd20-f5ec600f0b32' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7f51ffd9-7b58-47f3-982b-afb08b273c89' class='xr-var-data-in' type='checkbox'><label for='data-7f51ffd9-7b58-47f3-982b-afb08b273c89' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table>\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 3.25 MiB </td>\n",
       "                        <td> 3.25 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (294, 362, 4) </td>\n",
       "                        <td> (294, 362, 4) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 2 Tasks </td>\n",
       "                        <td> 1 Chunks </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> float64 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"143\" height=\"227\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"67\" y2=\"57\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"10\" y1=\"120\" x2=\"67\" y2=\"177\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"10\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"67\" y1=\"57\" x2=\"67\" y2=\"177\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"10.0,0.0 67.32856678583036,57.328566785830354 67.32856678583036,177.32856678583036 10.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"35\" y2=\"0\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"67\" y1=\"57\" x2=\"93\" y2=\"57\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"67\" y2=\"57\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"35\" y1=\"0\" x2=\"93\" y2=\"57\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"10.0,0.0 35.89690899898957,0.0 93.22547578481993,57.328566785830354 67.32856678583036,57.328566785830354\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"67\" y1=\"57\" x2=\"93\" y2=\"57\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"67\" y1=\"177\" x2=\"93\" y2=\"177\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"67\" y1=\"57\" x2=\"67\" y2=\"177\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"93\" y1=\"57\" x2=\"93\" y2=\"177\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"67.32856678583036,57.328566785830354 93.22547578481993,57.328566785830354 93.22547578481993,177.32856678583036 67.32856678583036,177.32856678583036\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"80.277021\" y=\"197.328567\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >4</text>\n",
       "  <text x=\"113.225476\" y=\"117.328567\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,113.225476,117.328567)\">362</text>\n",
       "  <text x=\"28.664283\" y=\"168.664283\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,28.664283,168.664283)\">294</text>\n",
       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>bounds_lon</span></div><div class='xr-var-dims'>(y, x, nvertex)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(294, 362, 4), meta=np.ndarray&gt;</div><input id='attrs-eeb05730-da5c-4a07-af7d-45d0a7db833d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-eeb05730-da5c-4a07-af7d-45d0a7db833d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3ae359d5-43a9-4009-b994-bdf60d0aeca2' class='xr-var-data-in' type='checkbox'><label for='data-3ae359d5-43a9-4009-b994-bdf60d0aeca2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table>\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 3.25 MiB </td>\n",
       "                        <td> 3.25 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (294, 362, 4) </td>\n",
       "                        <td> (294, 362, 4) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 2 Tasks </td>\n",
       "                        <td> 1 Chunks </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> float64 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"143\" height=\"227\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"67\" y2=\"57\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"10\" y1=\"120\" x2=\"67\" y2=\"177\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"10\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"67\" y1=\"57\" x2=\"67\" y2=\"177\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"10.0,0.0 67.32856678583036,57.328566785830354 67.32856678583036,177.32856678583036 10.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"35\" y2=\"0\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"67\" y1=\"57\" x2=\"93\" y2=\"57\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"67\" y2=\"57\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"35\" y1=\"0\" x2=\"93\" y2=\"57\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"10.0,0.0 35.89690899898957,0.0 93.22547578481993,57.328566785830354 67.32856678583036,57.328566785830354\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"67\" y1=\"57\" x2=\"93\" y2=\"57\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"67\" y1=\"177\" x2=\"93\" y2=\"177\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"67\" y1=\"57\" x2=\"67\" y2=\"177\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"93\" y1=\"57\" x2=\"93\" y2=\"177\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"67.32856678583036,57.328566785830354 93.22547578481993,57.328566785830354 93.22547578481993,177.32856678583036 67.32856678583036,177.32856678583036\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"80.277021\" y=\"197.328567\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >4</text>\n",
       "  <text x=\"113.225476\" y=\"117.328567\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,113.225476,117.328567)\">362</text>\n",
       "  <text x=\"28.664283\" y=\"168.664283\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,28.664283,168.664283)\">294</text>\n",
       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(294, 362), meta=np.ndarray&gt;</div><input id='attrs-68741d19-0c69-42b3-9a76-62e01b0e81fe' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-68741d19-0c69-42b3-9a76-62e01b0e81fe' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e0bf9072-65a5-4f89-a89f-097dc11e5b08' class='xr-var-data-in' type='checkbox'><label for='data-e0bf9072-65a5-4f89-a89f-097dc11e5b08' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>bounds_lat</dd><dt><span>long_name :</span></dt><dd>Latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table>\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 831.47 kiB </td>\n",
       "                        <td> 831.47 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (294, 362) </td>\n",
       "                        <td> (294, 362) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 2 Tasks </td>\n",
       "                        <td> 1 Chunks </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> float64 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"170\" height=\"147\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"0\" y1=\"97\" x2=\"120\" y2=\"97\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"97\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"97\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,97.4585635359116 0.0,97.4585635359116\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"60.000000\" y=\"117.458564\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >362</text>\n",
       "  <text x=\"140.000000\" y=\"48.729282\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,48.729282)\">294</text>\n",
       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lev</span></div><div class='xr-var-dims'>(lev)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.5058 1.556 ... 5.902e+03</div><input id='attrs-dfb8a834-f896-449d-8cce-97ab008f4c35' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dfb8a834-f896-449d-8cce-97ab008f4c35' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9e5efd7f-8277-4445-ace3-0e8ddf222f6b' class='xr-var-data-in' type='checkbox'><label for='data-9e5efd7f-8277-4445-ace3-0e8ddf222f6b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>lev_bounds</dd><dt><span>long_name :</span></dt><dd>Vertical T levels</dd><dt><span>name :</span></dt><dd>lev</dd><dt><span>positive :</span></dt><dd>down</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([5.057600e-01, 1.555855e+00, 2.667682e+00, 3.856280e+00, 5.140361e+00,\n",
       "       6.543034e+00, 8.092518e+00, 9.822750e+00, 1.177368e+01, 1.399104e+01,\n",
       "       1.652532e+01, 1.942980e+01, 2.275762e+01, 2.655830e+01, 3.087456e+01,\n",
       "       3.574020e+01, 4.118002e+01, 4.721189e+01, 5.385064e+01, 6.111284e+01,\n",
       "       6.902168e+01, 7.761116e+01, 8.692943e+01, 9.704131e+01, 1.080303e+02,\n",
       "       1.200000e+02, 1.330758e+02, 1.474062e+02, 1.631645e+02, 1.805499e+02,\n",
       "       1.997900e+02, 2.211412e+02, 2.448906e+02, 2.713564e+02, 3.008875e+02,\n",
       "       3.338628e+02, 3.706885e+02, 4.117938e+02, 4.576256e+02, 5.086399e+02,\n",
       "       5.652923e+02, 6.280260e+02, 6.972586e+02, 7.733683e+02, 8.566789e+02,\n",
       "       9.474479e+02, 1.045854e+03, 1.151991e+03, 1.265861e+03, 1.387377e+03,\n",
       "       1.516364e+03, 1.652568e+03, 1.795671e+03, 1.945295e+03, 2.101027e+03,\n",
       "       2.262422e+03, 2.429025e+03, 2.600380e+03, 2.776039e+03, 2.955570e+03,\n",
       "       3.138565e+03, 3.324641e+03, 3.513446e+03, 3.704657e+03, 3.897982e+03,\n",
       "       4.093159e+03, 4.289952e+03, 4.488155e+03, 4.687581e+03, 4.888070e+03,\n",
       "       5.089479e+03, 5.291683e+03, 5.494575e+03, 5.698061e+03, 5.902058e+03])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lev_bounds</span></div><div class='xr-var-dims'>(lev, axis_nbounds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(75, 2), meta=np.ndarray&gt;</div><input id='attrs-6b414a56-c479-472c-be76-31de82bc7f3f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6b414a56-c479-472c-be76-31de82bc7f3f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a692de1a-c992-48d5-81f2-0e088fd462b6' class='xr-var-data-in' type='checkbox'><label for='data-a692de1a-c992-48d5-81f2-0e088fd462b6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table>\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 1.17 kiB </td>\n",
       "                        <td> 1.17 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (75, 2) </td>\n",
       "                        <td> (75, 2) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 2 Tasks </td>\n",
       "                        <td> 1 Chunks </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> float64 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"80\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"30\" y2=\"0\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"0\" y1=\"120\" x2=\"30\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"30\" y1=\"0\" x2=\"30\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"0.0,0.0 30.690372229553788,0.0 30.690372229553788,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"15.345186\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2</text>\n",
       "  <text x=\"50.690372\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,50.690372,60.000000)\">75</text>\n",
       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(294, 362), meta=np.ndarray&gt;</div><input id='attrs-f167c809-46e3-42d0-8def-52d6f513e6fa' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f167c809-46e3-42d0-8def-52d6f513e6fa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ecfcfddd-8d6a-4f11-8467-cbcafbba993f' class='xr-var-data-in' type='checkbox'><label for='data-ecfcfddd-8d6a-4f11-8467-cbcafbba993f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>bounds_lon</dd><dt><span>long_name :</span></dt><dd>Longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table>\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 831.47 kiB </td>\n",
       "                        <td> 831.47 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (294, 362) </td>\n",
       "                        <td> (294, 362) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 2 Tasks </td>\n",
       "                        <td> 1 Chunks </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> float64 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"170\" height=\"147\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"0\" y1=\"97\" x2=\"120\" y2=\"97\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"97\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"97\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,97.4585635359116 0.0,97.4585635359116\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"60.000000\" y=\"117.458564\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >362</text>\n",
       "  <text x=\"140.000000\" y=\"48.729282\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,48.729282)\">294</text>\n",
       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>1850-01-16 12:00:00 ... 2014-12-...</div><input id='attrs-5d78702f-a29b-471a-8f4b-f30ffb1c43c6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5d78702f-a29b-471a-8f4b-f30ffb1c43c6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9e869dae-bf59-4090-ad94-95c22b503e9d' class='xr-var-data-in' type='checkbox'><label for='data-9e869dae-bf59-4090-ad94-95c22b503e9d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>bounds :</span></dt><dd>time_bounds</dd><dt><span>long_name :</span></dt><dd>Time axis</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>time_origin :</span></dt><dd>1850-01-01 00:00:00</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeGregorian(1850, 1, 16, 12, 0, 0, 0, has_year_zero=False),\n",
       "       cftime.DatetimeGregorian(1850, 2, 15, 0, 0, 0, 0, has_year_zero=False),\n",
       "       cftime.DatetimeGregorian(1850, 3, 16, 12, 0, 0, 0, has_year_zero=False),\n",
       "       ...,\n",
       "       cftime.DatetimeGregorian(2014, 10, 16, 12, 0, 0, 0, has_year_zero=False),\n",
       "       cftime.DatetimeGregorian(2014, 11, 16, 0, 0, 0, 0, has_year_zero=False),\n",
       "       cftime.DatetimeGregorian(2014, 12, 16, 12, 0, 0, 0, has_year_zero=False)],\n",
       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time_bounds</span></div><div class='xr-var-dims'>(time, axis_nbounds)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1980, 2), meta=np.ndarray&gt;</div><input id='attrs-8cf3acdb-fe28-43c6-8ae2-c6395bff9614' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8cf3acdb-fe28-43c6-8ae2-c6395bff9614' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-765a579d-b0a2-48f0-bc3a-d762f7f51656' class='xr-var-data-in' type='checkbox'><label for='data-765a579d-b0a2-48f0-bc3a-d762f7f51656' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table>\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 30.94 kiB </td>\n",
       "                        <td> 30.94 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (1980, 2) </td>\n",
       "                        <td> (1980, 2) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 2 Tasks </td>\n",
       "                        <td> 1 Chunks </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> object </td>\n",
       "                    <td> numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"75\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"25\" y2=\"0\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"0\" y1=\"120\" x2=\"25\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"25\" y1=\"0\" x2=\"25\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"0.0,0.0 25.412616514582485,0.0 25.412616514582485,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"12.706308\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2</text>\n",
       "  <text x=\"45.412617\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,45.412617,60.000000)\">1980</text>\n",
       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>bounds_lat_v</span></div><div class='xr-var-dims'>(y_c, x, nvertex)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(294, 362, 4), meta=np.ndarray&gt;</div><input id='attrs-07e5c124-a062-4e6b-ab22-eca84ecc72ee' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-07e5c124-a062-4e6b-ab22-eca84ecc72ee' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7e362e93-3311-4312-b2ac-4268865d0d2e' class='xr-var-data-in' type='checkbox'><label for='data-7e362e93-3311-4312-b2ac-4268865d0d2e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table>\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 3.25 MiB </td>\n",
       "                        <td> 3.25 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (294, 362, 4) </td>\n",
       "                        <td> (294, 362, 4) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 2 Tasks </td>\n",
       "                        <td> 1 Chunks </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> float64 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"143\" height=\"227\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"67\" y2=\"57\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"10\" y1=\"120\" x2=\"67\" y2=\"177\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"10\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"67\" y1=\"57\" x2=\"67\" y2=\"177\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"10.0,0.0 67.32856678583036,57.328566785830354 67.32856678583036,177.32856678583036 10.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"35\" y2=\"0\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"67\" y1=\"57\" x2=\"93\" y2=\"57\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"67\" y2=\"57\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"35\" y1=\"0\" x2=\"93\" y2=\"57\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"10.0,0.0 35.89690899898957,0.0 93.22547578481993,57.328566785830354 67.32856678583036,57.328566785830354\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"67\" y1=\"57\" x2=\"93\" y2=\"57\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"67\" y1=\"177\" x2=\"93\" y2=\"177\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"67\" y1=\"57\" x2=\"67\" y2=\"177\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"93\" y1=\"57\" x2=\"93\" y2=\"177\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"67.32856678583036,57.328566785830354 93.22547578481993,57.328566785830354 93.22547578481993,177.32856678583036 67.32856678583036,177.32856678583036\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"80.277021\" y=\"197.328567\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >4</text>\n",
       "  <text x=\"113.225476\" y=\"117.328567\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,113.225476,117.328567)\">362</text>\n",
       "  <text x=\"28.664283\" y=\"168.664283\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,28.664283,168.664283)\">294</text>\n",
       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>bounds_lon_v</span></div><div class='xr-var-dims'>(y_c, x, nvertex)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(294, 362, 4), meta=np.ndarray&gt;</div><input id='attrs-35cf3808-52e3-4521-a2fc-1781fb76c21a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-35cf3808-52e3-4521-a2fc-1781fb76c21a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b61d9706-b1bf-4c7b-b37e-65c3306b6da8' class='xr-var-data-in' type='checkbox'><label for='data-b61d9706-b1bf-4c7b-b37e-65c3306b6da8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table>\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 3.25 MiB </td>\n",
       "                        <td> 3.25 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (294, 362, 4) </td>\n",
       "                        <td> (294, 362, 4) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 2 Tasks </td>\n",
       "                        <td> 1 Chunks </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> float64 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"143\" height=\"227\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"67\" y2=\"57\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"10\" y1=\"120\" x2=\"67\" y2=\"177\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"10\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"67\" y1=\"57\" x2=\"67\" y2=\"177\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"10.0,0.0 67.32856678583036,57.328566785830354 67.32856678583036,177.32856678583036 10.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"35\" y2=\"0\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"67\" y1=\"57\" x2=\"93\" y2=\"57\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"67\" y2=\"57\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"35\" y1=\"0\" x2=\"93\" y2=\"57\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"10.0,0.0 35.89690899898957,0.0 93.22547578481993,57.328566785830354 67.32856678583036,57.328566785830354\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"67\" y1=\"57\" x2=\"93\" y2=\"57\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"67\" y1=\"177\" x2=\"93\" y2=\"177\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"67\" y1=\"57\" x2=\"67\" y2=\"177\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"93\" y1=\"57\" x2=\"93\" y2=\"177\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"67.32856678583036,57.328566785830354 93.22547578481993,57.328566785830354 93.22547578481993,177.32856678583036 67.32856678583036,177.32856678583036\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"80.277021\" y=\"197.328567\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >4</text>\n",
       "  <text x=\"113.225476\" y=\"117.328567\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,113.225476,117.328567)\">362</text>\n",
       "  <text x=\"28.664283\" y=\"168.664283\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,28.664283,168.664283)\">294</text>\n",
       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat_v</span></div><div class='xr-var-dims'>(y_c, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(294, 362), meta=np.ndarray&gt;</div><input id='attrs-a08a5584-4818-46f4-9849-5c5b7b4d7100' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a08a5584-4818-46f4-9849-5c5b7b4d7100' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-33cbaf6c-e809-4584-a676-7b5c06b62d07' class='xr-var-data-in' type='checkbox'><label for='data-33cbaf6c-e809-4584-a676-7b5c06b62d07' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>bounds_lat</dd><dt><span>long_name :</span></dt><dd>Latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table>\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 831.47 kiB </td>\n",
       "                        <td> 831.47 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (294, 362) </td>\n",
       "                        <td> (294, 362) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 2 Tasks </td>\n",
       "                        <td> 1 Chunks </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> float64 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"170\" height=\"147\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"0\" y1=\"97\" x2=\"120\" y2=\"97\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"97\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"97\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,97.4585635359116 0.0,97.4585635359116\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"60.000000\" y=\"117.458564\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >362</text>\n",
       "  <text x=\"140.000000\" y=\"48.729282\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,48.729282)\">294</text>\n",
       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon_v</span></div><div class='xr-var-dims'>(y_c, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(294, 362), meta=np.ndarray&gt;</div><input id='attrs-0ca8b8aa-bd80-4a68-a96d-31363b856cb2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0ca8b8aa-bd80-4a68-a96d-31363b856cb2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-05be2707-9991-4a2c-b865-3f6fbfc9f505' class='xr-var-data-in' type='checkbox'><label for='data-05be2707-9991-4a2c-b865-3f6fbfc9f505' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>bounds_lon</dd><dt><span>long_name :</span></dt><dd>Longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table>\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 831.47 kiB </td>\n",
       "                        <td> 831.47 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (294, 362) </td>\n",
       "                        <td> (294, 362) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 2 Tasks </td>\n",
       "                        <td> 1 Chunks </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> float64 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"170\" height=\"147\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"0\" y1=\"97\" x2=\"120\" y2=\"97\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"97\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"97\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,97.4585635359116 0.0,97.4585635359116\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"60.000000\" y=\"117.458564\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >362</text>\n",
       "  <text x=\"140.000000\" y=\"48.729282\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,48.729282)\">294</text>\n",
       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>areacello</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(294, 362), meta=np.ndarray&gt;</div><input id='attrs-b62473eb-5e8a-46ae-8568-8db04e55b150' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b62473eb-5e8a-46ae-8568-8db04e55b150' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3fe9476a-65cf-4ced-8070-65f45665c2ef' class='xr-var-data-in' type='checkbox'><label for='data-3fe9476a-65cf-4ced-8070-65f45665c2ef' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>area: sum</dd><dt><span>description :</span></dt><dd>Cell areas for any grid used to report ocean variables and variables which are requested as used on the model ocean grid (e.g. hfsso, which is a downward heat flux from the atmosphere interpolated onto the ocean grid). These cell areas should be defined to enable exact calculation of global integrals (e.g., of vertical fluxes of energy at the surface and top of the atmosphere).</dd><dt><span>history :</span></dt><dd>none</dd><dt><span>long_name :</span></dt><dd>Grid-Cell Area</dd><dt><span>online_operation :</span></dt><dd>once</dd><dt><span>standard_name :</span></dt><dd>cell_area</dd><dt><span>units :</span></dt><dd>m2</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table>\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 415.73 kiB </td>\n",
       "                        <td> 415.73 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (294, 362) </td>\n",
       "                        <td> (294, 362) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 5 Tasks </td>\n",
       "                        <td> 1 Chunks </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> float32 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"170\" height=\"147\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"0\" y1=\"97\" x2=\"120\" y2=\"97\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"97\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"97\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,97.4585635359116 0.0,97.4585635359116\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"60.000000\" y=\"117.458564\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >362</text>\n",
       "  <text x=\"140.000000\" y=\"48.729282\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,48.729282)\">294</text>\n",
       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-d2d6ea74-42cf-4f18-92fc-4a87dcde1b8f' class='xr-section-summary-in' type='checkbox'  checked><label for='section-d2d6ea74-42cf-4f18-92fc-4a87dcde1b8f' class='xr-section-summary' >Data variables: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>thetao</span></div><div class='xr-var-dims'>(time, lev, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(4, 75, 294, 362), meta=np.ndarray&gt;</div><input id='attrs-e58d14b0-7b93-4ad1-8eec-8e015123e12a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e58d14b0-7b93-4ad1-8eec-8e015123e12a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-256d5131-e7ab-498a-b9d1-bc69ada63dc8' class='xr-var-data-in' type='checkbox'><label for='data-256d5131-e7ab-498a-b9d1-bc69ada63dc8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: areacello volume: volcello</dd><dt><span>cell_methods :</span></dt><dd>area: mean where sea time: mean</dd><dt><span>description :</span></dt><dd>Diagnostic should be contributed even for models using conservative temperature as prognostic field.</dd><dt><span>history :</span></dt><dd>none</dd><dt><span>interval_operation :</span></dt><dd>1800 s</dd><dt><span>interval_write :</span></dt><dd>1 month</dd><dt><span>long_name :</span></dt><dd>Sea Water Potential Temperature</dd><dt><span>online_operation :</span></dt><dd>average</dd><dt><span>standard_name :</span></dt><dd>sea_water_potential_temperature</dd><dt><span>units :</span></dt><dd>degC</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table>\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 58.88 GiB </td>\n",
       "                        <td> 121.80 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (1980, 75, 294, 362) </td>\n",
       "                        <td> (4, 75, 294, 362) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 496 Tasks </td>\n",
       "                        <td> 495 Chunks </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> float32 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"490\" height=\"109\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"25\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"3\" y1=\"0\" x2=\"3\" y2=\"25\" />\n",
       "  <line x1=\"7\" y1=\"0\" x2=\"7\" y2=\"25\" />\n",
       "  <line x1=\"11\" y1=\"0\" x2=\"11\" y2=\"25\" />\n",
       "  <line x1=\"14\" y1=\"0\" x2=\"14\" y2=\"25\" />\n",
       "  <line x1=\"18\" y1=\"0\" x2=\"18\" y2=\"25\" />\n",
       "  <line x1=\"22\" y1=\"0\" x2=\"22\" y2=\"25\" />\n",
       "  <line x1=\"26\" y1=\"0\" x2=\"26\" y2=\"25\" />\n",
       "  <line x1=\"29\" y1=\"0\" x2=\"29\" y2=\"25\" />\n",
       "  <line x1=\"33\" y1=\"0\" x2=\"33\" y2=\"25\" />\n",
       "  <line x1=\"37\" y1=\"0\" x2=\"37\" y2=\"25\" />\n",
       "  <line x1=\"41\" y1=\"0\" x2=\"41\" y2=\"25\" />\n",
       "  <line x1=\"44\" y1=\"0\" x2=\"44\" y2=\"25\" />\n",
       "  <line x1=\"48\" y1=\"0\" x2=\"48\" y2=\"25\" />\n",
       "  <line x1=\"52\" y1=\"0\" x2=\"52\" y2=\"25\" />\n",
       "  <line x1=\"56\" y1=\"0\" x2=\"56\" y2=\"25\" />\n",
       "  <line x1=\"59\" y1=\"0\" x2=\"59\" y2=\"25\" />\n",
       "  <line x1=\"63\" y1=\"0\" x2=\"63\" y2=\"25\" />\n",
       "  <line x1=\"67\" y1=\"0\" x2=\"67\" y2=\"25\" />\n",
       "  <line x1=\"71\" y1=\"0\" x2=\"71\" y2=\"25\" />\n",
       "  <line x1=\"74\" y1=\"0\" x2=\"74\" y2=\"25\" />\n",
       "  <line x1=\"78\" y1=\"0\" x2=\"78\" y2=\"25\" />\n",
       "  <line x1=\"82\" y1=\"0\" x2=\"82\" y2=\"25\" />\n",
       "  <line x1=\"86\" y1=\"0\" x2=\"86\" y2=\"25\" />\n",
       "  <line x1=\"89\" y1=\"0\" x2=\"89\" y2=\"25\" />\n",
       "  <line x1=\"93\" y1=\"0\" x2=\"93\" y2=\"25\" />\n",
       "  <line x1=\"97\" y1=\"0\" x2=\"97\" y2=\"25\" />\n",
       "  <line x1=\"101\" y1=\"0\" x2=\"101\" y2=\"25\" />\n",
       "  <line x1=\"104\" y1=\"0\" x2=\"104\" y2=\"25\" />\n",
       "  <line x1=\"108\" y1=\"0\" x2=\"108\" y2=\"25\" />\n",
       "  <line x1=\"112\" y1=\"0\" x2=\"112\" y2=\"25\" />\n",
       "  <line x1=\"116\" y1=\"0\" x2=\"116\" y2=\"25\" />\n",
       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,25.412616514582485 0.0,25.412616514582485\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"60.000000\" y=\"45.412617\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >1980</text>\n",
       "  <text x=\"140.000000\" y=\"12.706308\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,140.000000,12.706308)\">1</text>\n",
       "\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"190\" y1=\"0\" x2=\"209\" y2=\"19\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"190\" y1=\"40\" x2=\"209\" y2=\"59\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"190\" y1=\"0\" x2=\"190\" y2=\"40\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"209\" y1=\"19\" x2=\"209\" y2=\"59\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"190.0,0.0 209.29473120513035,19.294731205130354 209.29473120513035,59.9519811188784 190.0,40.657249913748046\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"190\" y1=\"0\" x2=\"231\" y2=\"0\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"209\" y1=\"19\" x2=\"250\" y2=\"19\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"190\" y1=\"0\" x2=\"209\" y2=\"19\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"231\" y1=\"0\" x2=\"250\" y2=\"19\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"190.0,0.0 231.6218409980321,0.0 250.91657220316245,19.294731205130354 209.29473120513035,19.294731205130354\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"209\" y1=\"19\" x2=\"250\" y2=\"19\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"209\" y1=\"59\" x2=\"250\" y2=\"59\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"209\" y1=\"19\" x2=\"209\" y2=\"59\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"250\" y1=\"19\" x2=\"250\" y2=\"59\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"209.29473120513035,19.294731205130354 250.91657220316245,19.294731205130354 250.91657220316245,59.9519811188784 209.29473120513035,59.9519811188784\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"230.105652\" y=\"79.951981\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >362</text>\n",
       "  <text x=\"270.916572\" y=\"39.623356\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,270.916572,39.623356)\">294</text>\n",
       "  <text x=\"189.647366\" y=\"70.304616\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,189.647366,70.304616)\">75</text>\n",
       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>so</span></div><div class='xr-var-dims'>(time, lev, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(5, 75, 294, 362), meta=np.ndarray&gt;</div><input id='attrs-485ab168-8359-4775-981b-2ea2a4cc2871' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-485ab168-8359-4775-981b-2ea2a4cc2871' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a632fdc9-eb48-49db-b81b-abba637ef226' class='xr-var-data-in' type='checkbox'><label for='data-a632fdc9-eb48-49db-b81b-abba637ef226' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: areacello volume: volcello</dd><dt><span>cell_methods :</span></dt><dd>area: mean where sea time: mean</dd><dt><span>description :</span></dt><dd>Sea Water Salinity</dd><dt><span>history :</span></dt><dd>none</dd><dt><span>interval_operation :</span></dt><dd>1800 s</dd><dt><span>interval_write :</span></dt><dd>1 month</dd><dt><span>long_name :</span></dt><dd>Sea Water Salinity</dd><dt><span>online_operation :</span></dt><dd>average</dd><dt><span>standard_name :</span></dt><dd>sea_water_salinity</dd><dt><span>units :</span></dt><dd>0.001</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table>\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 58.88 GiB </td>\n",
       "                        <td> 152.25 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (1980, 75, 294, 362) </td>\n",
       "                        <td> (5, 75, 294, 362) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 397 Tasks </td>\n",
       "                        <td> 396 Chunks </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> float32 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"490\" height=\"109\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"25\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"3\" y1=\"0\" x2=\"3\" y2=\"25\" />\n",
       "  <line x1=\"7\" y1=\"0\" x2=\"7\" y2=\"25\" />\n",
       "  <line x1=\"11\" y1=\"0\" x2=\"11\" y2=\"25\" />\n",
       "  <line x1=\"14\" y1=\"0\" x2=\"14\" y2=\"25\" />\n",
       "  <line x1=\"18\" y1=\"0\" x2=\"18\" y2=\"25\" />\n",
       "  <line x1=\"22\" y1=\"0\" x2=\"22\" y2=\"25\" />\n",
       "  <line x1=\"26\" y1=\"0\" x2=\"26\" y2=\"25\" />\n",
       "  <line x1=\"30\" y1=\"0\" x2=\"30\" y2=\"25\" />\n",
       "  <line x1=\"33\" y1=\"0\" x2=\"33\" y2=\"25\" />\n",
       "  <line x1=\"37\" y1=\"0\" x2=\"37\" y2=\"25\" />\n",
       "  <line x1=\"41\" y1=\"0\" x2=\"41\" y2=\"25\" />\n",
       "  <line x1=\"44\" y1=\"0\" x2=\"44\" y2=\"25\" />\n",
       "  <line x1=\"48\" y1=\"0\" x2=\"48\" y2=\"25\" />\n",
       "  <line x1=\"52\" y1=\"0\" x2=\"52\" y2=\"25\" />\n",
       "  <line x1=\"56\" y1=\"0\" x2=\"56\" y2=\"25\" />\n",
       "  <line x1=\"60\" y1=\"0\" x2=\"60\" y2=\"25\" />\n",
       "  <line x1=\"63\" y1=\"0\" x2=\"63\" y2=\"25\" />\n",
       "  <line x1=\"67\" y1=\"0\" x2=\"67\" y2=\"25\" />\n",
       "  <line x1=\"71\" y1=\"0\" x2=\"71\" y2=\"25\" />\n",
       "  <line x1=\"74\" y1=\"0\" x2=\"74\" y2=\"25\" />\n",
       "  <line x1=\"78\" y1=\"0\" x2=\"78\" y2=\"25\" />\n",
       "  <line x1=\"82\" y1=\"0\" x2=\"82\" y2=\"25\" />\n",
       "  <line x1=\"86\" y1=\"0\" x2=\"86\" y2=\"25\" />\n",
       "  <line x1=\"90\" y1=\"0\" x2=\"90\" y2=\"25\" />\n",
       "  <line x1=\"93\" y1=\"0\" x2=\"93\" y2=\"25\" />\n",
       "  <line x1=\"97\" y1=\"0\" x2=\"97\" y2=\"25\" />\n",
       "  <line x1=\"101\" y1=\"0\" x2=\"101\" y2=\"25\" />\n",
       "  <line x1=\"104\" y1=\"0\" x2=\"104\" y2=\"25\" />\n",
       "  <line x1=\"108\" y1=\"0\" x2=\"108\" y2=\"25\" />\n",
       "  <line x1=\"112\" y1=\"0\" x2=\"112\" y2=\"25\" />\n",
       "  <line x1=\"116\" y1=\"0\" x2=\"116\" y2=\"25\" />\n",
       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,25.412616514582485 0.0,25.412616514582485\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"60.000000\" y=\"45.412617\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >1980</text>\n",
       "  <text x=\"140.000000\" y=\"12.706308\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,140.000000,12.706308)\">1</text>\n",
       "\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"190\" y1=\"0\" x2=\"209\" y2=\"19\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"190\" y1=\"40\" x2=\"209\" y2=\"59\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"190\" y1=\"0\" x2=\"190\" y2=\"40\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"209\" y1=\"19\" x2=\"209\" y2=\"59\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"190.0,0.0 209.29473120513035,19.294731205130354 209.29473120513035,59.9519811188784 190.0,40.657249913748046\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"190\" y1=\"0\" x2=\"231\" y2=\"0\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"209\" y1=\"19\" x2=\"250\" y2=\"19\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"190\" y1=\"0\" x2=\"209\" y2=\"19\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"231\" y1=\"0\" x2=\"250\" y2=\"19\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"190.0,0.0 231.6218409980321,0.0 250.91657220316245,19.294731205130354 209.29473120513035,19.294731205130354\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"209\" y1=\"19\" x2=\"250\" y2=\"19\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"209\" y1=\"59\" x2=\"250\" y2=\"59\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"209\" y1=\"19\" x2=\"209\" y2=\"59\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"250\" y1=\"19\" x2=\"250\" y2=\"59\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"209.29473120513035,19.294731205130354 250.91657220316245,19.294731205130354 250.91657220316245,59.9519811188784 209.29473120513035,59.9519811188784\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"230.105652\" y=\"79.951981\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >362</text>\n",
       "  <text x=\"270.916572\" y=\"39.623356\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,270.916572,39.623356)\">294</text>\n",
       "  <text x=\"189.647366\" y=\"70.304616\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,189.647366,70.304616)\">75</text>\n",
       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vo</span></div><div class='xr-var-dims'>(time, lev, y_c, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 75, 294, 362), meta=np.ndarray&gt;</div><input id='attrs-74e7ce8d-2390-4a54-b77d-c6e491b7db5f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-74e7ce8d-2390-4a54-b77d-c6e491b7db5f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-852dd43d-75a9-4427-972f-672124463c5c' class='xr-var-data-in' type='checkbox'><label for='data-852dd43d-75a9-4427-972f-672124463c5c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>description :</span></dt><dd>Prognostic y-ward velocity component resolved by the model.</dd><dt><span>history :</span></dt><dd>none</dd><dt><span>interval_operation :</span></dt><dd>1800 s</dd><dt><span>interval_write :</span></dt><dd>1 month</dd><dt><span>long_name :</span></dt><dd>Sea Water Y Velocity</dd><dt><span>online_operation :</span></dt><dd>average</dd><dt><span>standard_name :</span></dt><dd>sea_water_y_velocity</dd><dt><span>units :</span></dt><dd>m s-1</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table>\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 58.88 GiB </td>\n",
       "                        <td> 91.35 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (1980, 75, 294, 362) </td>\n",
       "                        <td> (3, 75, 294, 362) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 661 Tasks </td>\n",
       "                        <td> 660 Chunks </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> float32 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"490\" height=\"109\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"25\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"3\" y1=\"0\" x2=\"3\" y2=\"25\" />\n",
       "  <line x1=\"7\" y1=\"0\" x2=\"7\" y2=\"25\" />\n",
       "  <line x1=\"11\" y1=\"0\" x2=\"11\" y2=\"25\" />\n",
       "  <line x1=\"14\" y1=\"0\" x2=\"14\" y2=\"25\" />\n",
       "  <line x1=\"18\" y1=\"0\" x2=\"18\" y2=\"25\" />\n",
       "  <line x1=\"22\" y1=\"0\" x2=\"22\" y2=\"25\" />\n",
       "  <line x1=\"26\" y1=\"0\" x2=\"26\" y2=\"25\" />\n",
       "  <line x1=\"30\" y1=\"0\" x2=\"30\" y2=\"25\" />\n",
       "  <line x1=\"33\" y1=\"0\" x2=\"33\" y2=\"25\" />\n",
       "  <line x1=\"37\" y1=\"0\" x2=\"37\" y2=\"25\" />\n",
       "  <line x1=\"41\" y1=\"0\" x2=\"41\" y2=\"25\" />\n",
       "  <line x1=\"44\" y1=\"0\" x2=\"44\" y2=\"25\" />\n",
       "  <line x1=\"48\" y1=\"0\" x2=\"48\" y2=\"25\" />\n",
       "  <line x1=\"52\" y1=\"0\" x2=\"52\" y2=\"25\" />\n",
       "  <line x1=\"56\" y1=\"0\" x2=\"56\" y2=\"25\" />\n",
       "  <line x1=\"60\" y1=\"0\" x2=\"60\" y2=\"25\" />\n",
       "  <line x1=\"63\" y1=\"0\" x2=\"63\" y2=\"25\" />\n",
       "  <line x1=\"67\" y1=\"0\" x2=\"67\" y2=\"25\" />\n",
       "  <line x1=\"71\" y1=\"0\" x2=\"71\" y2=\"25\" />\n",
       "  <line x1=\"74\" y1=\"0\" x2=\"74\" y2=\"25\" />\n",
       "  <line x1=\"78\" y1=\"0\" x2=\"78\" y2=\"25\" />\n",
       "  <line x1=\"82\" y1=\"0\" x2=\"82\" y2=\"25\" />\n",
       "  <line x1=\"86\" y1=\"0\" x2=\"86\" y2=\"25\" />\n",
       "  <line x1=\"90\" y1=\"0\" x2=\"90\" y2=\"25\" />\n",
       "  <line x1=\"93\" y1=\"0\" x2=\"93\" y2=\"25\" />\n",
       "  <line x1=\"97\" y1=\"0\" x2=\"97\" y2=\"25\" />\n",
       "  <line x1=\"101\" y1=\"0\" x2=\"101\" y2=\"25\" />\n",
       "  <line x1=\"104\" y1=\"0\" x2=\"104\" y2=\"25\" />\n",
       "  <line x1=\"108\" y1=\"0\" x2=\"108\" y2=\"25\" />\n",
       "  <line x1=\"112\" y1=\"0\" x2=\"112\" y2=\"25\" />\n",
       "  <line x1=\"116\" y1=\"0\" x2=\"116\" y2=\"25\" />\n",
       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,25.412616514582485 0.0,25.412616514582485\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"60.000000\" y=\"45.412617\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >1980</text>\n",
       "  <text x=\"140.000000\" y=\"12.706308\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,140.000000,12.706308)\">1</text>\n",
       "\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"190\" y1=\"0\" x2=\"209\" y2=\"19\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"190\" y1=\"40\" x2=\"209\" y2=\"59\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"190\" y1=\"0\" x2=\"190\" y2=\"40\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"209\" y1=\"19\" x2=\"209\" y2=\"59\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"190.0,0.0 209.29473120513035,19.294731205130354 209.29473120513035,59.9519811188784 190.0,40.657249913748046\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"190\" y1=\"0\" x2=\"231\" y2=\"0\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"209\" y1=\"19\" x2=\"250\" y2=\"19\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"190\" y1=\"0\" x2=\"209\" y2=\"19\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"231\" y1=\"0\" x2=\"250\" y2=\"19\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"190.0,0.0 231.6218409980321,0.0 250.91657220316245,19.294731205130354 209.29473120513035,19.294731205130354\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"209\" y1=\"19\" x2=\"250\" y2=\"19\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"209\" y1=\"59\" x2=\"250\" y2=\"59\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"209\" y1=\"19\" x2=\"209\" y2=\"59\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"250\" y1=\"19\" x2=\"250\" y2=\"59\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"209.29473120513035,19.294731205130354 250.91657220316245,19.294731205130354 250.91657220316245,59.9519811188784 209.29473120513035,59.9519811188784\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"230.105652\" y=\"79.951981\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >362</text>\n",
       "  <text x=\"270.916572\" y=\"39.623356\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,270.916572,39.623356)\">294</text>\n",
       "  <text x=\"189.647366\" y=\"70.304616\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,189.647366,70.304616)\">75</text>\n",
       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-6022f709-f2b9-461e-843f-35e52324b797' class='xr-section-summary-in' type='checkbox'  ><label for='section-6022f709-f2b9-461e-843f-35e52324b797' class='xr-section-summary' >Attributes: <span>(57)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>CMIP6_CV_version :</span></dt><dd>cv=6.2.3.0-7-g2019642</dd><dt><span>Conventions :</span></dt><dd>CF-1.7 CMIP-6.2</dd><dt><span>EXPID :</span></dt><dd>CNRM-ESM2-1_historical_r1i1p1f2</dd><dt><span>activity_id :</span></dt><dd>CMIP</dd><dt><span>arpege_minor_version :</span></dt><dd>6.3.2</dd><dt><span>branch_method :</span></dt><dd>standard</dd><dt><span>branch_time_in_child :</span></dt><dd>0.0</dd><dt><span>branch_time_in_parent :</span></dt><dd>0.0</dd><dt><span>contact :</span></dt><dd>contact.cmip@meteo.fr</dd><dt><span>creation_date :</span></dt><dd>2018-06-10T22:12:36Z</dd><dt><span>data_specs_version :</span></dt><dd>01.00.21</dd><dt><span>description :</span></dt><dd>CMIP6 historical</dd><dt><span>dr2xml_md5sum :</span></dt><dd>789c0010d555326fb79e73c3e20c5d0e</dd><dt><span>dr2xml_version :</span></dt><dd>1.9</dd><dt><span>experiment :</span></dt><dd>all-forcing simulation of the recent past</dd><dt><span>experiment_id :</span></dt><dd>historical</dd><dt><span>external_variables :</span></dt><dd>areacello volcello</dd><dt><span>forcing_index :</span></dt><dd>2</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>further_info_url :</span></dt><dd>https://furtherinfo.es-doc.org/CMIP6.CNRM-CERFACS.CNRM-ESM2-1.historical.none.r1i1p1f2</dd><dt><span>grid :</span></dt><dd>native ocean tri-polar grid with 105 k ocean cells</dd><dt><span>grid_label :</span></dt><dd>gn</dd><dt><span>history :</span></dt><dd>none</dd><dt><span>initialization_index :</span></dt><dd>1</dd><dt><span>institution :</span></dt><dd>CNRM (Centre National de Recherches Meteorologiques, Toulouse 31057, France), CERFACS (Centre Europeen de Recherche et de Formation Avancee en Calcul Scientifique, Toulouse 31057, France)</dd><dt><span>institution_id :</span></dt><dd>CNRM-CERFACS</dd><dt><span>license :</span></dt><dd>CMIP6 model data produced by CNRM-CERFACS is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (https://creativecommons.org/licenses). Consult https://pcmdi.llnl.gov/CMIP6/TermsOfUse for terms of use governing CMIP6 output, including citation requirements and proper acknowledgment. Further information about this data, including some limitations, can be found via the further_info_url (recorded as a global attribute in this file) and at http://www.umr-cnrm.fr/cmip6/. The data producers and data providers make no warranty, either express or implied, including, but not limited to, warranties of merchantability and fitness for a particular purpose. All liabilities arising from the supply of the information (including any liability arising in negligence) are excluded to the fullest extent permitted by law.</dd><dt><span>mip_era :</span></dt><dd>CMIP6</dd><dt><span>nemo_gelato_commit :</span></dt><dd>49095b3accd5d4c_6524fe19b00467a</dd><dt><span>nominal_resolution :</span></dt><dd>100 km</dd><dt><span>parent_activity_id :</span></dt><dd>CMIP</dd><dt><span>parent_experiment_id :</span></dt><dd>piControl</dd><dt><span>parent_mip_era :</span></dt><dd>CMIP6</dd><dt><span>parent_source_id :</span></dt><dd>CNRM-ESM2-1</dd><dt><span>parent_time_units :</span></dt><dd>days since 1850-01-01 00:00:00</dd><dt><span>parent_variant_label :</span></dt><dd>r1i1p1f2</dd><dt><span>physics_index :</span></dt><dd>1</dd><dt><span>product :</span></dt><dd>model-output</dd><dt><span>realization_index :</span></dt><dd>1</dd><dt><span>realm :</span></dt><dd>ocean</dd><dt><span>references :</span></dt><dd>http://www.umr-cnrm.fr/cmip6/references</dd><dt><span>source :</span></dt><dd>CNRM-ESM2-1 (2017):  aerosol: TACTIC_v2 atmos: Arpege 6.3 (T127; Gaussian Reduced with 24572 grid points in total distributed over 128 latitude circles (with 256 grid points per latitude circle between 30degN and 30degS reducing to 20 grid points per latitude circle at 88.9degN and 88.9degS); 91 levels; top level 78.4 km) atmosChem: REPROBUS-C_v2 land: Surfex 8.0c ocean: Nemo 3.6 (eORCA1, tripolar primarily 1deg; 362 x 294 longitude/latitude; 75 levels; top grid cell 0-1 m) ocnBgchem: Pisces 2.s seaIce: Gelato 6.1</dd><dt><span>source_id :</span></dt><dd>CNRM-ESM2-1</dd><dt><span>source_type :</span></dt><dd>AOGCM BGC AER CHEM</dd><dt><span>sub_experiment :</span></dt><dd>none</dd><dt><span>sub_experiment_id :</span></dt><dd>none</dd><dt><span>table_id :</span></dt><dd>Omon</dd><dt><span>title :</span></dt><dd>CNRM-ESM2-1 model output prepared for CMIP6 / CMIP historical</dd><dt><span>tracking_id :</span></dt><dd>hdl:21.14100/9c34b796-c31d-4c1f-be90-21d032267f6e\n",
       "hdl:21.14100/e6ff74ce-1ace-4151-abf2-3e25386a8449\n",
       "hdl:21.14100/3e3933f8-8edb-4296-928b-a84a5ba62ed3\n",
       "hdl:21.14100/a55236c8-6a3e-4a77-97d4-48c7336aa825\n",
       "hdl:21.14100/7031a63f-4d30-4672-8ab6-f516f604ee41\n",
       "hdl:21.14100/72029dae-43de-4097-abae-b24a749387b2\n",
       "hdl:21.14100/f8a5f02d-55c6-4c6a-a37f-9e01c3b68989</dd><dt><span>variable_id :</span></dt><dd>thetao</dd><dt><span>variant_label :</span></dt><dd>r1i1p1f2</dd><dt><span>xios_commit :</span></dt><dd>1442-shuffle</dd><dt><span>status :</span></dt><dd>2019-11-05;created;by nhn2@columbia.edu</dd><dt><span>netcdf_tracking_ids :</span></dt><dd>hdl:21.14100/9c34b796-c31d-4c1f-be90-21d032267f6e\n",
       "hdl:21.14100/e6ff74ce-1ace-4151-abf2-3e25386a8449\n",
       "hdl:21.14100/3e3933f8-8edb-4296-928b-a84a5ba62ed3\n",
       "hdl:21.14100/a55236c8-6a3e-4a77-97d4-48c7336aa825\n",
       "hdl:21.14100/7031a63f-4d30-4672-8ab6-f516f604ee41\n",
       "hdl:21.14100/72029dae-43de-4097-abae-b24a749387b2\n",
       "hdl:21.14100/f8a5f02d-55c6-4c6a-a37f-9e01c3b68989</dd><dt><span>version_id :</span></dt><dd>v20181206</dd><dt><span>intake_esm_varname :</span></dt><dd>None</dd><dt><span>intake_esm_dataset_key :</span></dt><dd>CMIP.CNRM-CERFACS.CNRM-ESM2-1.historical.r1i1p1f2.Omon.thetao.gn.gs://cmip6/CMIP6/CMIP/CNRM-CERFACS/CNRM-ESM2-1/historical/r1i1p1f2/Omon/thetao/gn/v20181206/.nan.20181206</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:       (y: 294, x: 362, nvertex: 4, lev: 75, axis_nbounds: 2,\n",
       "                   time: 1980, y_c: 294)\n",
       "Coordinates: (12/13)\n",
       "    bounds_lat    (y, x, nvertex) float64 dask.array<chunksize=(294, 362, 4), meta=np.ndarray>\n",
       "    bounds_lon    (y, x, nvertex) float64 dask.array<chunksize=(294, 362, 4), meta=np.ndarray>\n",
       "    lat           (y, x) float64 dask.array<chunksize=(294, 362), meta=np.ndarray>\n",
       "  * lev           (lev) float64 0.5058 1.556 2.668 ... 5.698e+03 5.902e+03\n",
       "    lev_bounds    (lev, axis_nbounds) float64 dask.array<chunksize=(75, 2), meta=np.ndarray>\n",
       "    lon           (y, x) float64 dask.array<chunksize=(294, 362), meta=np.ndarray>\n",
       "    ...            ...\n",
       "    time_bounds   (time, axis_nbounds) object dask.array<chunksize=(1980, 2), meta=np.ndarray>\n",
       "    bounds_lat_v  (y_c, x, nvertex) float64 dask.array<chunksize=(294, 362, 4), meta=np.ndarray>\n",
       "    bounds_lon_v  (y_c, x, nvertex) float64 dask.array<chunksize=(294, 362, 4), meta=np.ndarray>\n",
       "    lat_v         (y_c, x) float64 dask.array<chunksize=(294, 362), meta=np.ndarray>\n",
       "    lon_v         (y_c, x) float64 dask.array<chunksize=(294, 362), meta=np.ndarray>\n",
       "    areacello     (y, x) float32 dask.array<chunksize=(294, 362), meta=np.ndarray>\n",
       "Dimensions without coordinates: y, x, nvertex, axis_nbounds, y_c\n",
       "Data variables:\n",
       "    thetao        (time, lev, y, x) float32 dask.array<chunksize=(4, 75, 294, 362), meta=np.ndarray>\n",
       "    so            (time, lev, y, x) float32 dask.array<chunksize=(5, 75, 294, 362), meta=np.ndarray>\n",
       "    vo            (time, lev, y_c, x) float32 dask.array<chunksize=(3, 75, 294, 362), meta=np.ndarray>\n",
       "Attributes: (12/57)\n",
       "    CMIP6_CV_version:        cv=6.2.3.0-7-g2019642\n",
       "    Conventions:             CF-1.7 CMIP-6.2\n",
       "    EXPID:                   CNRM-ESM2-1_historical_r1i1p1f2\n",
       "    activity_id:             CMIP\n",
       "    arpege_minor_version:    6.3.2\n",
       "    branch_method:           standard\n",
       "    ...                      ...\n",
       "    xios_commit:             1442-shuffle\n",
       "    status:                  2019-11-05;created;by nhn2@columbia.edu\n",
       "    netcdf_tracking_ids:     hdl:21.14100/9c34b796-c31d-4c1f-be90-21d032267f6...\n",
       "    version_id:              v20181206\n",
       "    intake_esm_varname:      None\n",
       "    intake_esm_dataset_key:  CMIP.CNRM-CERFACS.CNRM-ESM2-1.historical.r1i1p1f..."
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "thetao = ddict['CMIP.CNRM-CERFACS.CNRM-ESM2-1.historical.r1i1p1f2.Omon.thetao.gn.gs://cmip6/CMIP6/CMIP/CNRM-CERFACS/CNRM-ESM2-1/historical/r1i1p1f2/Omon/thetao/gn/v20181206/.nan.20181206']\n",
    "so = ddict['CMIP.CNRM-CERFACS.CNRM-ESM2-1.historical.r1i1p1f2.Omon.so.gn.gs://cmip6/CMIP6/CMIP/CNRM-CERFACS/CNRM-ESM2-1/historical/r1i1p1f2/Omon/so/gn/v20181206/.nan.20181206']\n",
    "vo = ddict['CMIP.CNRM-CERFACS.CNRM-ESM2-1.historical.r1i1p1f2.Omon.vo.gn.gs://cmip6/CMIP6/CMIP/CNRM-CERFACS/CNRM-ESM2-1/historical/r1i1p1f2/Omon/vo/gn/v20181206/.nan.20181206']\n",
    "areacello = ddict['CMIP.CNRM-CERFACS.CNRM-ESM2-1.historical.r1i1p1f2.Ofx.areacello.gn.gs://cmip6/CMIP6/CMIP/CNRM-CERFACS/CNRM-ESM2-1/historical/r1i1p1f2/Ofx/areacello/gn/v20181206/.nan.20181206'].areacello\n",
    "\n",
    "vo = vo.rename({'y':'y_c', 'lon':'lon_v', 'lat':'lat_v', 'bounds_lon':'bounds_lon_v', 'bounds_lat':'bounds_lat_v'})\n",
    "\n",
    "ds = xr.merge([thetao,so,vo], compat='override')\n",
    "ds = ds.assign_coords(areacello=areacello.fillna(0))\n",
    "ds"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The grid is missing an `outer` coordinate for the Z axis, so we will construct one.\n",
    "This will be needed for conservative interpolation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "import cf_xarray\n",
    "level_outer_data = cf_xarray.bounds_to_vertices(ds.lev_bounds, 'axis_nbounds').load().data\n",
    "\n",
    "ds = ds.assign_coords({'level_outer': level_outer_data})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Linear Interpolation\n",
    "\n",
    "#### Depth to Depth\n",
    "To illustrate linear interpolation, we will first interpolate salinity onto a uniformly spaced vertical grid. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<xgcm.Grid>\n",
       "Z Axis (not periodic, boundary=None):\n",
       "  * center   lev"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grid = Grid(ds, coords={'Z': {'center': 'lev'},\n",
    "                        },\n",
    "                periodic=False\n",
    "            )\n",
    "grid"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
       "<defs>\n",
       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
       "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
       "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
       "</symbol>\n",
       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
       "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
       "<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "</symbol>\n",
       "</defs>\n",
       "</svg>\n",
       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
       " *\n",
       " */\n",
       "\n",
       ":root {\n",
       "  --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
       "  --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
       "  --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
       "  --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
       "  --xr-background-color: var(--jp-layout-color0, white);\n",
       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
       "}\n",
       "\n",
       "html[theme=dark],\n",
       "body.vscode-dark {\n",
       "  --xr-font-color0: rgba(255, 255, 255, 1);\n",
       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
       "  --xr-border-color: #1F1F1F;\n",
       "  --xr-disabled-color: #515151;\n",
       "  --xr-background-color: #111111;\n",
       "  --xr-background-color-row-even: #111111;\n",
       "  --xr-background-color-row-odd: #313131;\n",
       "}\n",
       "\n",
       ".xr-wrap {\n",
       "  display: block !important;\n",
       "  min-width: 300px;\n",
       "  max-width: 700px;\n",
       "}\n",
       "\n",
       ".xr-text-repr-fallback {\n",
       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-header {\n",
       "  padding-top: 6px;\n",
       "  padding-bottom: 6px;\n",
       "  margin-bottom: 4px;\n",
       "  border-bottom: solid 1px var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-header > div,\n",
       ".xr-header > ul {\n",
       "  display: inline;\n",
       "  margin-top: 0;\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-obj-type,\n",
       ".xr-array-name {\n",
       "  margin-left: 2px;\n",
       "  margin-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-obj-type {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-sections {\n",
       "  padding-left: 0 !important;\n",
       "  display: grid;\n",
       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: '►';\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;so&#x27; (time: 1980, y: 294, x: 362, lev: 10)&gt;\n",
       "dask.array&lt;transpose, shape=(1980, 294, 362, 10), dtype=float32, chunksize=(5, 294, 362, 10), chunktype=numpy.ndarray&gt;\n",
       "Coordinates:\n",
       "    lat        (y, x) float64 dask.array&lt;chunksize=(294, 362), meta=np.ndarray&gt;\n",
       "    lon        (y, x) float64 dask.array&lt;chunksize=(294, 362), meta=np.ndarray&gt;\n",
       "  * time       (time) object 1850-01-16 12:00:00 ... 2014-12-16 12:00:00\n",
       "    areacello  (y, x) float32 dask.array&lt;chunksize=(294, 362), meta=np.ndarray&gt;\n",
       "  * lev        (lev) int64 0 50 100 150 200 250 300 350 400 450\n",
       "Dimensions without coordinates: y, x</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'so'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 1980</li><li><span>y</span>: 294</li><li><span>x</span>: 362</li><li><span class='xr-has-index'>lev</span>: 10</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-175447dc-974a-43bf-af0d-c905c08b6cc8' class='xr-array-in' type='checkbox' checked><label for='section-175447dc-974a-43bf-af0d-c905c08b6cc8' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>dask.array&lt;chunksize=(5, 294, 362, 10), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table>\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 7.85 GiB </td>\n",
       "                        <td> 20.30 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (1980, 294, 362, 10) </td>\n",
       "                        <td> (5, 294, 362, 10) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 1983 Tasks </td>\n",
       "                        <td> 396 Chunks </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> float32 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"479\" height=\"115\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"25\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"3\" y1=\"0\" x2=\"3\" y2=\"25\" />\n",
       "  <line x1=\"7\" y1=\"0\" x2=\"7\" y2=\"25\" />\n",
       "  <line x1=\"11\" y1=\"0\" x2=\"11\" y2=\"25\" />\n",
       "  <line x1=\"14\" y1=\"0\" x2=\"14\" y2=\"25\" />\n",
       "  <line x1=\"18\" y1=\"0\" x2=\"18\" y2=\"25\" />\n",
       "  <line x1=\"22\" y1=\"0\" x2=\"22\" y2=\"25\" />\n",
       "  <line x1=\"26\" y1=\"0\" x2=\"26\" y2=\"25\" />\n",
       "  <line x1=\"30\" y1=\"0\" x2=\"30\" y2=\"25\" />\n",
       "  <line x1=\"33\" y1=\"0\" x2=\"33\" y2=\"25\" />\n",
       "  <line x1=\"37\" y1=\"0\" x2=\"37\" y2=\"25\" />\n",
       "  <line x1=\"41\" y1=\"0\" x2=\"41\" y2=\"25\" />\n",
       "  <line x1=\"44\" y1=\"0\" x2=\"44\" y2=\"25\" />\n",
       "  <line x1=\"48\" y1=\"0\" x2=\"48\" y2=\"25\" />\n",
       "  <line x1=\"52\" y1=\"0\" x2=\"52\" y2=\"25\" />\n",
       "  <line x1=\"56\" y1=\"0\" x2=\"56\" y2=\"25\" />\n",
       "  <line x1=\"60\" y1=\"0\" x2=\"60\" y2=\"25\" />\n",
       "  <line x1=\"63\" y1=\"0\" x2=\"63\" y2=\"25\" />\n",
       "  <line x1=\"67\" y1=\"0\" x2=\"67\" y2=\"25\" />\n",
       "  <line x1=\"71\" y1=\"0\" x2=\"71\" y2=\"25\" />\n",
       "  <line x1=\"74\" y1=\"0\" x2=\"74\" y2=\"25\" />\n",
       "  <line x1=\"78\" y1=\"0\" x2=\"78\" y2=\"25\" />\n",
       "  <line x1=\"82\" y1=\"0\" x2=\"82\" y2=\"25\" />\n",
       "  <line x1=\"86\" y1=\"0\" x2=\"86\" y2=\"25\" />\n",
       "  <line x1=\"90\" y1=\"0\" x2=\"90\" y2=\"25\" />\n",
       "  <line x1=\"93\" y1=\"0\" x2=\"93\" y2=\"25\" />\n",
       "  <line x1=\"97\" y1=\"0\" x2=\"97\" y2=\"25\" />\n",
       "  <line x1=\"101\" y1=\"0\" x2=\"101\" y2=\"25\" />\n",
       "  <line x1=\"104\" y1=\"0\" x2=\"104\" y2=\"25\" />\n",
       "  <line x1=\"108\" y1=\"0\" x2=\"108\" y2=\"25\" />\n",
       "  <line x1=\"112\" y1=\"0\" x2=\"112\" y2=\"25\" />\n",
       "  <line x1=\"116\" y1=\"0\" x2=\"116\" y2=\"25\" />\n",
       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,25.412616514582485 0.0,25.412616514582485\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"60.000000\" y=\"45.412617\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >1980</text>\n",
       "  <text x=\"140.000000\" y=\"12.706308\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,140.000000,12.706308)\">1</text>\n",
       "\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"190\" y1=\"0\" x2=\"213\" y2=\"23\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"190\" y1=\"41\" x2=\"213\" y2=\"65\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"190\" y1=\"0\" x2=\"190\" y2=\"41\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"213\" y1=\"23\" x2=\"213\" y2=\"65\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"190.0,0.0 213.91602936102825,23.91602936102826 213.91602936102825,65.53787035906035 190.0,41.62184099803209\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"190\" y1=\"0\" x2=\"215\" y2=\"0\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"213\" y1=\"23\" x2=\"239\" y2=\"23\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"190\" y1=\"0\" x2=\"213\" y2=\"23\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"215\" y1=\"0\" x2=\"239\" y2=\"23\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"190.0,0.0 215.41261651458248,0.0 239.32864587561073,23.91602936102826 213.91602936102825,23.91602936102826\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"213\" y1=\"23\" x2=\"239\" y2=\"23\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"213\" y1=\"65\" x2=\"239\" y2=\"65\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"213\" y1=\"23\" x2=\"213\" y2=\"65\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"239\" y1=\"23\" x2=\"239\" y2=\"65\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"213.91602936102825,23.91602936102826 239.32864587561073,23.91602936102826 239.32864587561073,65.53787035906035 213.91602936102825,65.53787035906035\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"226.622338\" y=\"85.537870\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >10</text>\n",
       "  <text x=\"259.328646\" y=\"44.726950\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,259.328646,44.726950)\">362</text>\n",
       "  <text x=\"191.958015\" y=\"73.579856\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,191.958015,73.579856)\">294</text>\n",
       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></div></li><li class='xr-section-item'><input id='section-d4ff4623-dbbf-48ad-aca5-31b98faeec85' class='xr-section-summary-in' type='checkbox'  checked><label for='section-d4ff4623-dbbf-48ad-aca5-31b98faeec85' class='xr-section-summary' >Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(294, 362), meta=np.ndarray&gt;</div><input id='attrs-b15dfe3f-6b28-4a35-92ea-693bcdcf4ce3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b15dfe3f-6b28-4a35-92ea-693bcdcf4ce3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-90412a02-ffd0-41f4-9a0c-35cc165bee79' class='xr-var-data-in' type='checkbox'><label for='data-90412a02-ffd0-41f4-9a0c-35cc165bee79' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table>\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 831.47 kiB </td>\n",
       "                        <td> 831.47 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (294, 362) </td>\n",
       "                        <td> (294, 362) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 2 Tasks </td>\n",
       "                        <td> 1 Chunks </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> float64 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"170\" height=\"147\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"0\" y1=\"97\" x2=\"120\" y2=\"97\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"97\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"97\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,97.4585635359116 0.0,97.4585635359116\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"60.000000\" y=\"117.458564\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >362</text>\n",
       "  <text x=\"140.000000\" y=\"48.729282\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,48.729282)\">294</text>\n",
       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(294, 362), meta=np.ndarray&gt;</div><input id='attrs-d719b20b-05b3-4854-ad8d-0868484de192' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d719b20b-05b3-4854-ad8d-0868484de192' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e59d2b6c-d085-4c5a-bfd6-e9b2c6281685' class='xr-var-data-in' type='checkbox'><label for='data-e59d2b6c-d085-4c5a-bfd6-e9b2c6281685' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table>\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 831.47 kiB </td>\n",
       "                        <td> 831.47 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (294, 362) </td>\n",
       "                        <td> (294, 362) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 2 Tasks </td>\n",
       "                        <td> 1 Chunks </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> float64 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"170\" height=\"147\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"0\" y1=\"97\" x2=\"120\" y2=\"97\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"97\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"97\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,97.4585635359116 0.0,97.4585635359116\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"60.000000\" y=\"117.458564\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >362</text>\n",
       "  <text x=\"140.000000\" y=\"48.729282\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,48.729282)\">294</text>\n",
       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>1850-01-16 12:00:00 ... 2014-12-...</div><input id='attrs-8ffec251-d061-4e60-9fc8-6f99cbb8ea0b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8ffec251-d061-4e60-9fc8-6f99cbb8ea0b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6c00d67e-b727-4f1c-8fe3-47e9c227faa6' class='xr-var-data-in' type='checkbox'><label for='data-6c00d67e-b727-4f1c-8fe3-47e9c227faa6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeGregorian(1850, 1, 16, 12, 0, 0, 0, has_year_zero=False),\n",
       "       cftime.DatetimeGregorian(1850, 2, 15, 0, 0, 0, 0, has_year_zero=False),\n",
       "       cftime.DatetimeGregorian(1850, 3, 16, 12, 0, 0, 0, has_year_zero=False),\n",
       "       ...,\n",
       "       cftime.DatetimeGregorian(2014, 10, 16, 12, 0, 0, 0, has_year_zero=False),\n",
       "       cftime.DatetimeGregorian(2014, 11, 16, 0, 0, 0, 0, has_year_zero=False),\n",
       "       cftime.DatetimeGregorian(2014, 12, 16, 12, 0, 0, 0, has_year_zero=False)],\n",
       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>areacello</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(294, 362), meta=np.ndarray&gt;</div><input id='attrs-6b98471a-509d-415d-81c7-5565eb6f2022' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6b98471a-509d-415d-81c7-5565eb6f2022' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-53da1e9c-84e6-4943-980e-649d429d7775' class='xr-var-data-in' type='checkbox'><label for='data-53da1e9c-84e6-4943-980e-649d429d7775' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table>\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 415.73 kiB </td>\n",
       "                        <td> 415.73 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (294, 362) </td>\n",
       "                        <td> (294, 362) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 5 Tasks </td>\n",
       "                        <td> 1 Chunks </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> float32 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"170\" height=\"147\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"0\" y1=\"97\" x2=\"120\" y2=\"97\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"97\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"97\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,97.4585635359116 0.0,97.4585635359116\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"60.000000\" y=\"117.458564\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >362</text>\n",
       "  <text x=\"140.000000\" y=\"48.729282\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,48.729282)\">294</text>\n",
       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lev</span></div><div class='xr-var-dims'>(lev)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 50 100 150 ... 300 350 400 450</div><input id='attrs-22bd578d-1b24-45fe-88a2-6e59ce9df533' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-22bd578d-1b24-45fe-88a2-6e59ce9df533' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c2f9d89d-dc6a-422a-8176-9529c4f75dca' class='xr-var-data-in' type='checkbox'><label for='data-c2f9d89d-dc6a-422a-8176-9529c4f75dca' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([  0,  50, 100, 150, 200, 250, 300, 350, 400, 450])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-0f4c298d-ab8b-4b3b-b1a9-fd7cf646aa9a' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-0f4c298d-ab8b-4b3b-b1a9-fd7cf646aa9a' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'so' (time: 1980, y: 294, x: 362, lev: 10)>\n",
       "dask.array<transpose, shape=(1980, 294, 362, 10), dtype=float32, chunksize=(5, 294, 362, 10), chunktype=numpy.ndarray>\n",
       "Coordinates:\n",
       "    lat        (y, x) float64 dask.array<chunksize=(294, 362), meta=np.ndarray>\n",
       "    lon        (y, x) float64 dask.array<chunksize=(294, 362), meta=np.ndarray>\n",
       "  * time       (time) object 1850-01-16 12:00:00 ... 2014-12-16 12:00:00\n",
       "    areacello  (y, x) float32 dask.array<chunksize=(294, 362), meta=np.ndarray>\n",
       "  * lev        (lev) int64 0 50 100 150 200 250 300 350 400 450\n",
       "Dimensions without coordinates: y, x"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "target_depth_levels = np.arange(0,500,50)\n",
    "salt_on_depth = grid.transform(ds.so, 'Z', target_depth_levels, target_data=None, method='linear')\n",
    "salt_on_depth"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note that the computation is lazy. (No data has been downloaded or computed yet.)\n",
    "We can trigger computation by plotting something."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x7fc8587b8550>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "salt_on_depth.isel(time=0).sel(lev=50).plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Depth to Potential Temperature\n",
    "We can also interpolate salinity onto temperature surface through linear interpolation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
       "<defs>\n",
       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
       "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
       "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
       "</symbol>\n",
       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
       "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
       "<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "</symbol>\n",
       "</defs>\n",
       "</svg>\n",
       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
       " *\n",
       " */\n",
       "\n",
       ":root {\n",
       "  --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
       "  --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
       "  --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
       "  --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
       "  --xr-background-color: var(--jp-layout-color0, white);\n",
       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
       "}\n",
       "\n",
       "html[theme=dark],\n",
       "body.vscode-dark {\n",
       "  --xr-font-color0: rgba(255, 255, 255, 1);\n",
       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
       "  --xr-border-color: #1F1F1F;\n",
       "  --xr-disabled-color: #515151;\n",
       "  --xr-background-color: #111111;\n",
       "  --xr-background-color-row-even: #111111;\n",
       "  --xr-background-color-row-odd: #313131;\n",
       "}\n",
       "\n",
       ".xr-wrap {\n",
       "  display: block !important;\n",
       "  min-width: 300px;\n",
       "  max-width: 700px;\n",
       "}\n",
       "\n",
       ".xr-text-repr-fallback {\n",
       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-header {\n",
       "  padding-top: 6px;\n",
       "  padding-bottom: 6px;\n",
       "  margin-bottom: 4px;\n",
       "  border-bottom: solid 1px var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-header > div,\n",
       ".xr-header > ul {\n",
       "  display: inline;\n",
       "  margin-top: 0;\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-obj-type,\n",
       ".xr-array-name {\n",
       "  margin-left: 2px;\n",
       "  margin-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-obj-type {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-sections {\n",
       "  padding-left: 0 !important;\n",
       "  display: grid;\n",
       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: '►';\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;so&#x27; (time: 1980, y: 294, x: 362, thetao: 38)&gt;\n",
       "dask.array&lt;transpose, shape=(1980, 294, 362, 38), dtype=float32, chunksize=(4, 294, 362, 38), chunktype=numpy.ndarray&gt;\n",
       "Coordinates:\n",
       "    lat        (y, x) float64 dask.array&lt;chunksize=(294, 362), meta=np.ndarray&gt;\n",
       "    lon        (y, x) float64 dask.array&lt;chunksize=(294, 362), meta=np.ndarray&gt;\n",
       "  * time       (time) object 1850-01-16 12:00:00 ... 2014-12-16 12:00:00\n",
       "    areacello  (y, x) float32 dask.array&lt;chunksize=(294, 362), meta=np.ndarray&gt;\n",
       "  * thetao     (thetao) int64 -2 -1 0 1 2 3 4 5 6 ... 27 28 29 30 31 32 33 34 35\n",
       "Dimensions without coordinates: y, x</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'so'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 1980</li><li><span>y</span>: 294</li><li><span>x</span>: 362</li><li><span class='xr-has-index'>thetao</span>: 38</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-a36d2f47-daa9-430b-a153-6c8f71559f8a' class='xr-array-in' type='checkbox' checked><label for='section-a36d2f47-daa9-430b-a153-6c8f71559f8a' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>dask.array&lt;chunksize=(4, 294, 362, 38), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table>\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 29.83 GiB </td>\n",
       "                        <td> 61.71 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (1980, 294, 362, 38) </td>\n",
       "                        <td> (4, 294, 362, 38) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 7131 Tasks </td>\n",
       "                        <td> 792 Chunks </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> float32 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"482\" height=\"115\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"25\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"3\" y1=\"0\" x2=\"3\" y2=\"25\" />\n",
       "  <line x1=\"7\" y1=\"0\" x2=\"7\" y2=\"25\" />\n",
       "  <line x1=\"11\" y1=\"0\" x2=\"11\" y2=\"25\" />\n",
       "  <line x1=\"15\" y1=\"0\" x2=\"15\" y2=\"25\" />\n",
       "  <line x1=\"18\" y1=\"0\" x2=\"18\" y2=\"25\" />\n",
       "  <line x1=\"22\" y1=\"0\" x2=\"22\" y2=\"25\" />\n",
       "  <line x1=\"26\" y1=\"0\" x2=\"26\" y2=\"25\" />\n",
       "  <line x1=\"30\" y1=\"0\" x2=\"30\" y2=\"25\" />\n",
       "  <line x1=\"33\" y1=\"0\" x2=\"33\" y2=\"25\" />\n",
       "  <line x1=\"37\" y1=\"0\" x2=\"37\" y2=\"25\" />\n",
       "  <line x1=\"41\" y1=\"0\" x2=\"41\" y2=\"25\" />\n",
       "  <line x1=\"45\" y1=\"0\" x2=\"45\" y2=\"25\" />\n",
       "  <line x1=\"48\" y1=\"0\" x2=\"48\" y2=\"25\" />\n",
       "  <line x1=\"52\" y1=\"0\" x2=\"52\" y2=\"25\" />\n",
       "  <line x1=\"56\" y1=\"0\" x2=\"56\" y2=\"25\" />\n",
       "  <line x1=\"60\" y1=\"0\" x2=\"60\" y2=\"25\" />\n",
       "  <line x1=\"63\" y1=\"0\" x2=\"63\" y2=\"25\" />\n",
       "  <line x1=\"67\" y1=\"0\" x2=\"67\" y2=\"25\" />\n",
       "  <line x1=\"71\" y1=\"0\" x2=\"71\" y2=\"25\" />\n",
       "  <line x1=\"74\" y1=\"0\" x2=\"74\" y2=\"25\" />\n",
       "  <line x1=\"78\" y1=\"0\" x2=\"78\" y2=\"25\" />\n",
       "  <line x1=\"82\" y1=\"0\" x2=\"82\" y2=\"25\" />\n",
       "  <line x1=\"86\" y1=\"0\" x2=\"86\" y2=\"25\" />\n",
       "  <line x1=\"90\" y1=\"0\" x2=\"90\" y2=\"25\" />\n",
       "  <line x1=\"93\" y1=\"0\" x2=\"93\" y2=\"25\" />\n",
       "  <line x1=\"97\" y1=\"0\" x2=\"97\" y2=\"25\" />\n",
       "  <line x1=\"101\" y1=\"0\" x2=\"101\" y2=\"25\" />\n",
       "  <line x1=\"104\" y1=\"0\" x2=\"104\" y2=\"25\" />\n",
       "  <line x1=\"108\" y1=\"0\" x2=\"108\" y2=\"25\" />\n",
       "  <line x1=\"112\" y1=\"0\" x2=\"112\" y2=\"25\" />\n",
       "  <line x1=\"116\" y1=\"0\" x2=\"116\" y2=\"25\" />\n",
       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,25.412616514582485 0.0,25.412616514582485\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"60.000000\" y=\"45.412617\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >1980</text>\n",
       "  <text x=\"140.000000\" y=\"12.706308\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,140.000000,12.706308)\">1</text>\n",
       "\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"190\" y1=\"0\" x2=\"213\" y2=\"23\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"190\" y1=\"41\" x2=\"213\" y2=\"65\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"190\" y1=\"0\" x2=\"190\" y2=\"41\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"213\" y1=\"23\" x2=\"213\" y2=\"65\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"190.0,0.0 213.91602936102825,23.91602936102826 213.91602936102825,65.53787035906035 190.0,41.62184099803209\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"190\" y1=\"0\" x2=\"218\" y2=\"0\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"213\" y1=\"23\" x2=\"242\" y2=\"23\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"190\" y1=\"0\" x2=\"213\" y2=\"23\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"218\" y1=\"0\" x2=\"242\" y2=\"23\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"190.0,0.0 218.79944599206226,0.0 242.7154753530905,23.91602936102826 213.91602936102825,23.91602936102826\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"213\" y1=\"23\" x2=\"242\" y2=\"23\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"213\" y1=\"65\" x2=\"242\" y2=\"65\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"213\" y1=\"23\" x2=\"213\" y2=\"65\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"242\" y1=\"23\" x2=\"242\" y2=\"65\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"213.91602936102825,23.91602936102826 242.7154753530905,23.91602936102826 242.7154753530905,65.53787035906035 213.91602936102825,65.53787035906035\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"228.315752\" y=\"85.537870\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >38</text>\n",
       "  <text x=\"262.715475\" y=\"44.726950\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,262.715475,44.726950)\">362</text>\n",
       "  <text x=\"191.958015\" y=\"73.579856\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,191.958015,73.579856)\">294</text>\n",
       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></div></li><li class='xr-section-item'><input id='section-c9e1a54b-e6c1-4507-8ef3-39c84f5ebe0a' class='xr-section-summary-in' type='checkbox'  checked><label for='section-c9e1a54b-e6c1-4507-8ef3-39c84f5ebe0a' class='xr-section-summary' >Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(294, 362), meta=np.ndarray&gt;</div><input id='attrs-749ad2c8-a0d6-446a-a4a2-46ef0cef352b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-749ad2c8-a0d6-446a-a4a2-46ef0cef352b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-14f0184b-e929-476a-9db8-a11f6a23c281' class='xr-var-data-in' type='checkbox'><label for='data-14f0184b-e929-476a-9db8-a11f6a23c281' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table>\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 831.47 kiB </td>\n",
       "                        <td> 831.47 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (294, 362) </td>\n",
       "                        <td> (294, 362) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 2 Tasks </td>\n",
       "                        <td> 1 Chunks </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> float64 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"170\" height=\"147\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"0\" y1=\"97\" x2=\"120\" y2=\"97\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"97\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"97\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,97.4585635359116 0.0,97.4585635359116\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"60.000000\" y=\"117.458564\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >362</text>\n",
       "  <text x=\"140.000000\" y=\"48.729282\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,48.729282)\">294</text>\n",
       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(294, 362), meta=np.ndarray&gt;</div><input id='attrs-d5d91606-a30d-4855-9699-9ff20664698e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d5d91606-a30d-4855-9699-9ff20664698e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-046726ed-de6e-4d50-a9d0-542f85e554fd' class='xr-var-data-in' type='checkbox'><label for='data-046726ed-de6e-4d50-a9d0-542f85e554fd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table>\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 831.47 kiB </td>\n",
       "                        <td> 831.47 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (294, 362) </td>\n",
       "                        <td> (294, 362) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 2 Tasks </td>\n",
       "                        <td> 1 Chunks </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> float64 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"170\" height=\"147\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"0\" y1=\"97\" x2=\"120\" y2=\"97\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"97\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"97\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,97.4585635359116 0.0,97.4585635359116\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"60.000000\" y=\"117.458564\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >362</text>\n",
       "  <text x=\"140.000000\" y=\"48.729282\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,48.729282)\">294</text>\n",
       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>1850-01-16 12:00:00 ... 2014-12-...</div><input id='attrs-10e7d56b-d53e-45d5-93ae-f0c28180b18c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-10e7d56b-d53e-45d5-93ae-f0c28180b18c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1abd5920-2c3c-4b62-a845-df8ef094fc09' class='xr-var-data-in' type='checkbox'><label for='data-1abd5920-2c3c-4b62-a845-df8ef094fc09' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeGregorian(1850, 1, 16, 12, 0, 0, 0, has_year_zero=False),\n",
       "       cftime.DatetimeGregorian(1850, 2, 15, 0, 0, 0, 0, has_year_zero=False),\n",
       "       cftime.DatetimeGregorian(1850, 3, 16, 12, 0, 0, 0, has_year_zero=False),\n",
       "       ...,\n",
       "       cftime.DatetimeGregorian(2014, 10, 16, 12, 0, 0, 0, has_year_zero=False),\n",
       "       cftime.DatetimeGregorian(2014, 11, 16, 0, 0, 0, 0, has_year_zero=False),\n",
       "       cftime.DatetimeGregorian(2014, 12, 16, 12, 0, 0, 0, has_year_zero=False)],\n",
       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>areacello</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(294, 362), meta=np.ndarray&gt;</div><input id='attrs-2e5c8f0a-8e0d-4de7-a014-b1c5279ccd88' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2e5c8f0a-8e0d-4de7-a014-b1c5279ccd88' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-187fa602-690f-40ca-a015-ad03ad081d50' class='xr-var-data-in' type='checkbox'><label for='data-187fa602-690f-40ca-a015-ad03ad081d50' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table>\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 415.73 kiB </td>\n",
       "                        <td> 415.73 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (294, 362) </td>\n",
       "                        <td> (294, 362) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 5 Tasks </td>\n",
       "                        <td> 1 Chunks </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> float32 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"170\" height=\"147\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"0\" y1=\"97\" x2=\"120\" y2=\"97\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"97\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"97\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,97.4585635359116 0.0,97.4585635359116\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"60.000000\" y=\"117.458564\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >362</text>\n",
       "  <text x=\"140.000000\" y=\"48.729282\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,48.729282)\">294</text>\n",
       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>thetao</span></div><div class='xr-var-dims'>(thetao)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>-2 -1 0 1 2 3 ... 30 31 32 33 34 35</div><input id='attrs-6878b63c-3791-4256-9c11-f9cedd730056' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6878b63c-3791-4256-9c11-f9cedd730056' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ba07467e-cd24-4e7a-a1c2-64721062587b' class='xr-var-data-in' type='checkbox'><label for='data-ba07467e-cd24-4e7a-a1c2-64721062587b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-2, -1,  0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15,\n",
       "       16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33,\n",
       "       34, 35])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-98d6887f-9f33-478f-827a-110faf52764a' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-98d6887f-9f33-478f-827a-110faf52764a' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'so' (time: 1980, y: 294, x: 362, thetao: 38)>\n",
       "dask.array<transpose, shape=(1980, 294, 362, 38), dtype=float32, chunksize=(4, 294, 362, 38), chunktype=numpy.ndarray>\n",
       "Coordinates:\n",
       "    lat        (y, x) float64 dask.array<chunksize=(294, 362), meta=np.ndarray>\n",
       "    lon        (y, x) float64 dask.array<chunksize=(294, 362), meta=np.ndarray>\n",
       "  * time       (time) object 1850-01-16 12:00:00 ... 2014-12-16 12:00:00\n",
       "    areacello  (y, x) float32 dask.array<chunksize=(294, 362), meta=np.ndarray>\n",
       "  * thetao     (thetao) int64 -2 -1 0 1 2 3 4 5 6 ... 27 28 29 30 31 32 33 34 35\n",
       "Dimensions without coordinates: y, x"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "target_theta_levels = np.arange(-2, 36)\n",
    "salt_on_theta = grid.transform(ds.so, 'Z', target_theta_levels, target_data=ds.thetao, method='linear')\n",
    "salt_on_theta"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/jthielen/miniconda3/envs/test_env_xgcm/lib/python3.10/site-packages/numba/np/ufunc/gufunc.py:170: RuntimeWarning: invalid value encountered in _interp_1d_linear\n",
      "  return self.ufunc(*args, **kwargs)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x7fc85a7b3760>"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "salt_on_theta.isel(time=0).sel(thetao=20).plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/jthielen/miniconda3/envs/test_env_xgcm/lib/python3.10/site-packages/numba/np/ufunc/gufunc.py:170: RuntimeWarning: invalid value encountered in _interp_1d_linear\n",
      "  return self.ufunc(*args, **kwargs)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x7fc85a40d1e0>"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "salt_on_theta.isel(time=0).mean(dim='x').plot(x='y')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Conservative Interpolation\n",
    "\n",
    "To do conservative interpolation, we will attempt to calculate the meridional overturning in temperature space.\n",
    "Note that this is not a perfectly precise calculation.\n",
    "However, it's sufficient to illustrate the basic principles of the calculation."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Create another grid object for conservative interpolation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "ename": "ValueError",
     "evalue": "Could not find dimension `x_c` (for the `right` position on axis `X`) in input dataset.",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "Input \u001b[0;32mIn [27]\u001b[0m, in \u001b[0;36m<cell line: 1>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0m grid \u001b[38;5;241m=\u001b[39m \u001b[43mGrid\u001b[49m\u001b[43m(\u001b[49m\u001b[43mds\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcoords\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m{\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mZ\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43m{\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mcenter\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mlev\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mouter\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mlevel_outer\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m}\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m      2\u001b[0m \u001b[43m                        \u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mX\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43m{\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mcenter\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mx\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mright\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mx_c\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m}\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m      3\u001b[0m \u001b[43m                        \u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mY\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43m{\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mcenter\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43my\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mright\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43my_c\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m}\u001b[49m\n\u001b[1;32m      4\u001b[0m \u001b[43m                        \u001b[49m\u001b[43m}\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m      5\u001b[0m \u001b[43m            \u001b[49m\u001b[43mperiodic\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mFalse\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[1;32m      6\u001b[0m \u001b[43m            \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m      7\u001b[0m grid\n",
      "File \u001b[0;32m~/develop/xgcm/xgcm/grid.py:1271\u001b[0m, in \u001b[0;36mGrid.__init__\u001b[0;34m(self, ds, check_dims, periodic, default_shifts, face_connections, coords, metrics, boundary, fill_value)\u001b[0m\n\u001b[1;32m   1269\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m pos, dim \u001b[38;5;129;01min\u001b[39;00m positions\u001b[38;5;241m.\u001b[39mitems():\n\u001b[1;32m   1270\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m (dim \u001b[38;5;129;01min\u001b[39;00m ds\u001b[38;5;241m.\u001b[39mvariables \u001b[38;5;129;01mor\u001b[39;00m dim \u001b[38;5;129;01min\u001b[39;00m ds\u001b[38;5;241m.\u001b[39mdims):\n\u001b[0;32m-> 1271\u001b[0m         \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\n\u001b[1;32m   1272\u001b[0m             \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mCould not find dimension `\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mdim\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m` (for the `\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mpos\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m` position on axis `\u001b[39m\u001b[38;5;132;01m{\u001b[39;00maxis\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m`) in input dataset.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m   1273\u001b[0m         )\n\u001b[1;32m   1274\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m dim \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;129;01min\u001b[39;00m ds\u001b[38;5;241m.\u001b[39mdims:\n\u001b[1;32m   1275\u001b[0m         \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\n\u001b[1;32m   1276\u001b[0m             \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mInput `\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mdim\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m` (for the `\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mpos\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m` position on axis `\u001b[39m\u001b[38;5;132;01m{\u001b[39;00maxis\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m`) is not a dimension in the input datasets `ds`.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m   1277\u001b[0m         )\n",
      "\u001b[0;31mValueError\u001b[0m: Could not find dimension `x_c` (for the `right` position on axis `X`) in input dataset."
     ]
    }
   ],
   "source": [
    "grid = Grid(ds, coords={'Z': {'center': 'lev', 'outer': 'level_outer'},\n",
    "                        'X': {'center': 'x', 'right': 'x_c'},\n",
    "                        'Y': {'center': 'y', 'right': 'y_c'}\n",
    "                        },\n",
    "            periodic=False,\n",
    "            )\n",
    "grid"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To use conservative interpolation, we have to go from an intensive quantity (velocity) to an extensive one (velocity times cell thickness).\n",
    "We fill any missing values with 0, since they don't contribute to the transport."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "thickness = grid.diff(ds.level_outer, 'Z')\n",
    "v_transport =  ds.vo * thickness\n",
    "v_transport = v_transport.fillna(0.).rename('v_transport')\n",
    "v_transport"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We also need to interpolate `theta` or thetao, our target data for interpolation, to the same horizontal position as `v_transport`. This means moving from cell center to cell corner.\n",
    "This step introduces some considerable errors, particularly near the boundaries of bathymetry.\n",
    "(Xgcm currently has no special treatment for internal boundary conditions--see issue [222](https://github.com/xgcm/xgcm/issues/240).)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "ds['theta'] = grid.interp(ds.thetao, ['Y'], boundary='extend')\n",
    "ds.theta"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can transform `v_transport` to temperature space (`target_theta_levels`)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "v_transport_theta = grid.transform(v_transport, 'Z', target_theta_levels,\n",
    "                                   target_data=ds.theta, method='conservative')\n",
    "v_transport_theta"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Notice that this produced a warning. The `conservative` transformation method natively needs `target_data` to be provided on the cell bounds (here `level_outer`).\n",
    "Since transforming onto tracer coordinates is a very common scenario, xgcm uses linear interpolation to infer the values on the `outer` axis position.\n",
    "\n",
    "To demonstrate how to provide `target_data` on the outer grid position, we reproduce the steps xgcm executes internally:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "theta_outer = grid.interp(ds.theta,['Z'], boundary='extend')\n",
    "# the data cannot be chunked along the transformation axis\n",
    "theta_outer = theta_outer.chunk({'level_outer': -1}).rename('theta')\n",
    "theta_outer"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "When we apply the transformation we can see that the results in this case are equivalent:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "v_transport_theta_manual = grid.transform(v_transport, 'Z', target_theta_levels,\n",
    "                                   target_data=theta_outer, method='conservative')\n",
    "\n",
    "# Warning: this step takes a long time to compute. We will only compare the first time value\n",
    "xr.testing.assert_allclose(v_transport_theta_manual.isel(time=0), v_transport_theta.isel(time=0))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now  we verify visually that the vertically integrated transport is conserved under this transformation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "v_transport.isel(time=0).sum(dim='lev').plot(robust=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "v_transport_theta.isel(time=0).sum(dim='theta').plot(robust=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Finally, we attempt to plot a crude meridional overturning streamfunction for a single timestep."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "dx = 110e3 * np.cos(np.deg2rad(ds.lat_v))\n",
    "(v_transport_theta.isel(time=0) * dx).sum(dim='x').cumsum(dim='theta').plot.contourf(x='y_c', levels=31)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Logarithmic Interpolation\n",
    "\n",
    "As noted previously, logarithmic interpolation is most often used to interpolate data from atmospheric models with a non-isobaric vertical coordinate (such as sigma or hybrid sigma) to isobaric levels suitable for analysis.  And so, in place of the previous 4D ocean dataset, let's generate a synthetic 3D atmospheric dataset (loosely based on the Sanders 1971 Analytic Model) to use to explore logarithmic interpolation:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
       "<defs>\n",
       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
       "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
       "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
       "</symbol>\n",
       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
       "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
       "<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "</symbol>\n",
       "</defs>\n",
       "</svg>\n",
       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
       " *\n",
       " */\n",
       "\n",
       ":root {\n",
       "  --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
       "  --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
       "  --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
       "  --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
       "  --xr-background-color: var(--jp-layout-color0, white);\n",
       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
       "}\n",
       "\n",
       "html[theme=dark],\n",
       "body.vscode-dark {\n",
       "  --xr-font-color0: rgba(255, 255, 255, 1);\n",
       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
       "  --xr-border-color: #1F1F1F;\n",
       "  --xr-disabled-color: #515151;\n",
       "  --xr-background-color: #111111;\n",
       "  --xr-background-color-row-even: #111111;\n",
       "  --xr-background-color-row-odd: #313131;\n",
       "}\n",
       "\n",
       ".xr-wrap {\n",
       "  display: block !important;\n",
       "  min-width: 300px;\n",
       "  max-width: 700px;\n",
       "}\n",
       "\n",
       ".xr-text-repr-fallback {\n",
       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-header {\n",
       "  padding-top: 6px;\n",
       "  padding-bottom: 6px;\n",
       "  margin-bottom: 4px;\n",
       "  border-bottom: solid 1px var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-header > div,\n",
       ".xr-header > ul {\n",
       "  display: inline;\n",
       "  margin-top: 0;\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-obj-type,\n",
       ".xr-array-name {\n",
       "  margin-left: 2px;\n",
       "  margin-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-obj-type {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-sections {\n",
       "  padding-left: 0 !important;\n",
       "  display: grid;\n",
       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: '►';\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:       (y: 150, x: 250, sigma: 30)\n",
       "Coordinates:\n",
       "  * y             (y) float64 0.0 1.208e+04 2.416e+04 ... 1.788e+06 1.8e+06\n",
       "  * x             (x) float64 -1.5e+06 -1.488e+06 ... 1.488e+06 1.5e+06\n",
       "  * sigma         (sigma) float64 1.0 0.9655 0.931 ... 0.06897 0.03448 0.0\n",
       "Data variables:\n",
       "    temperature   (y, x, sigma) float64 305.5 302.2 298.9 ... 215.3 214.1 212.2\n",
       "    geopotential  (y, x, sigma) float64 1.146e+04 1.452e+04 ... 3.418e+05\n",
       "    pressure      (y, x, sigma) float64 8.728e+04 8.444e+04 ... 8.238e+03 5e+03</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-a500e483-b36b-4825-ba55-a3282b14ef16' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-a500e483-b36b-4825-ba55-a3282b14ef16' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>y</span>: 150</li><li><span class='xr-has-index'>x</span>: 250</li><li><span class='xr-has-index'>sigma</span>: 30</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-9f21ac19-ab35-43b8-abd1-0a969bae802a' class='xr-section-summary-in' type='checkbox'  checked><label for='section-9f21ac19-ab35-43b8-abd1-0a969bae802a' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 1.208e+04 ... 1.788e+06 1.8e+06</div><input id='attrs-7914511e-2b7d-461d-b62c-719b52eb0c3b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7914511e-2b7d-461d-b62c-719b52eb0c3b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3eefd86d-5e72-4409-873b-65438c6791af' class='xr-var-data-in' type='checkbox'><label for='data-3eefd86d-5e72-4409-873b-65438c6791af' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([      0.      ,   12080.536913,   24161.073826,   36241.610738,\n",
       "         48322.147651,   60402.684564,   72483.221477,   84563.758389,\n",
       "         96644.295302,  108724.832215,  120805.369128,  132885.90604 ,\n",
       "        144966.442953,  157046.979866,  169127.516779,  181208.053691,\n",
       "        193288.590604,  205369.127517,  217449.66443 ,  229530.201342,\n",
       "        241610.738255,  253691.275168,  265771.812081,  277852.348993,\n",
       "        289932.885906,  302013.422819,  314093.959732,  326174.496644,\n",
       "        338255.033557,  350335.57047 ,  362416.107383,  374496.644295,\n",
       "        386577.181208,  398657.718121,  410738.255034,  422818.791946,\n",
       "        434899.328859,  446979.865772,  459060.402685,  471140.939597,\n",
       "        483221.47651 ,  495302.013423,  507382.550336,  519463.087248,\n",
       "        531543.624161,  543624.161074,  555704.697987,  567785.234899,\n",
       "        579865.771812,  591946.308725,  604026.845638,  616107.38255 ,\n",
       "        628187.919463,  640268.456376,  652348.993289,  664429.530201,\n",
       "        676510.067114,  688590.604027,  700671.14094 ,  712751.677852,\n",
       "        724832.214765,  736912.751678,  748993.288591,  761073.825503,\n",
       "        773154.362416,  785234.899329,  797315.436242,  809395.973154,\n",
       "        821476.510067,  833557.04698 ,  845637.583893,  857718.120805,\n",
       "        869798.657718,  881879.194631,  893959.731544,  906040.268456,\n",
       "        918120.805369,  930201.342282,  942281.879195,  954362.416107,\n",
       "        966442.95302 ,  978523.489933,  990604.026846, 1002684.563758,\n",
       "       1014765.100671, 1026845.637584, 1038926.174497, 1051006.711409,\n",
       "       1063087.248322, 1075167.785235, 1087248.322148, 1099328.85906 ,\n",
       "       1111409.395973, 1123489.932886, 1135570.469799, 1147651.006711,\n",
       "       1159731.543624, 1171812.080537, 1183892.61745 , 1195973.154362,\n",
       "       1208053.691275, 1220134.228188, 1232214.765101, 1244295.302013,\n",
       "       1256375.838926, 1268456.375839, 1280536.912752, 1292617.449664,\n",
       "       1304697.986577, 1316778.52349 , 1328859.060403, 1340939.597315,\n",
       "       1353020.134228, 1365100.671141, 1377181.208054, 1389261.744966,\n",
       "       1401342.281879, 1413422.818792, 1425503.355705, 1437583.892617,\n",
       "       1449664.42953 , 1461744.966443, 1473825.503356, 1485906.040268,\n",
       "       1497986.577181, 1510067.114094, 1522147.651007, 1534228.187919,\n",
       "       1546308.724832, 1558389.261745, 1570469.798658, 1582550.33557 ,\n",
       "       1594630.872483, 1606711.409396, 1618791.946309, 1630872.483221,\n",
       "       1642953.020134, 1655033.557047, 1667114.09396 , 1679194.630872,\n",
       "       1691275.167785, 1703355.704698, 1715436.241611, 1727516.778523,\n",
       "       1739597.315436, 1751677.852349, 1763758.389262, 1775838.926174,\n",
       "       1787919.463087, 1800000.      ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-1.5e+06 -1.488e+06 ... 1.5e+06</div><input id='attrs-5410777c-86d9-4f46-8147-eec1089eb8e1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5410777c-86d9-4f46-8147-eec1089eb8e1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2baedff4-0bb7-49e6-ad4f-0eeb4a0ee0b0' class='xr-var-data-in' type='checkbox'><label for='data-2baedff4-0bb7-49e6-ad4f-0eeb4a0ee0b0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-1500000.      , -1487951.807229, -1475903.614458, ...,  1475903.614458,\n",
       "        1487951.807229,  1500000.      ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>sigma</span></div><div class='xr-var-dims'>(sigma)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.0 0.9655 0.931 ... 0.03448 0.0</div><input id='attrs-f389fb3c-6475-45c5-8eb0-578eb5624eef' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f389fb3c-6475-45c5-8eb0-578eb5624eef' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6809849d-6440-45fb-b4b6-f6d3d12a169b' class='xr-var-data-in' type='checkbox'><label for='data-6809849d-6440-45fb-b4b6-f6d3d12a169b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1.      , 0.965517, 0.931034, 0.896552, 0.862069, 0.827586, 0.793103,\n",
       "       0.758621, 0.724138, 0.689655, 0.655172, 0.62069 , 0.586207, 0.551724,\n",
       "       0.517241, 0.482759, 0.448276, 0.413793, 0.37931 , 0.344828, 0.310345,\n",
       "       0.275862, 0.241379, 0.206897, 0.172414, 0.137931, 0.103448, 0.068966,\n",
       "       0.034483, 0.      ])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-7e4f01fd-f274-4e38-9f7e-1cca17a05eb7' class='xr-section-summary-in' type='checkbox'  checked><label for='section-7e4f01fd-f274-4e38-9f7e-1cca17a05eb7' class='xr-section-summary' >Data variables: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>temperature</span></div><div class='xr-var-dims'>(y, x, sigma)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>305.5 302.2 298.9 ... 214.1 212.2</div><input id='attrs-da6c1fca-56ca-432d-9c80-e39bd9111719' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-da6c1fca-56ca-432d-9c80-e39bd9111719' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-891b7a89-e369-4517-9a3c-c1e8783fb49f' class='xr-var-data-in' type='checkbox'><label for='data-891b7a89-e369-4517-9a3c-c1e8783fb49f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[305.49123009, 302.19569012, 298.90423051, ..., 241.65188259,\n",
       "         242.72995545, 244.33361423],\n",
       "        [305.49580349, 302.20021263, 298.90869992, ..., 241.65128288,\n",
       "         242.72786361, 244.32857962],\n",
       "        [305.49681135, 302.20109377, 298.90944956, ..., 241.64231743,\n",
       "         242.71670887, 244.31347899],\n",
       "        ...,\n",
       "        [304.95927571, 301.66458149, 298.37403211, ..., 241.32987889,\n",
       "         242.50115771, 244.31347899],\n",
       "        [304.96389752, 301.66931839, 298.37888806, ..., 241.34200166,\n",
       "         242.51445753, 244.32857962],\n",
       "        [304.96538598, 301.67084531, 298.38045477, ..., 241.346012  ,\n",
       "         242.51886976, 244.33361423]],\n",
       "\n",
       "       [[305.44188207, 302.14526217, 298.85268567, ..., 241.53376782,\n",
       "         242.60169126, 244.19054582],\n",
       "        [305.44639823, 302.14972754, 298.85709808, ..., 241.5331358 ,\n",
       "         242.59957745, 244.18551138],\n",
       "        [305.44734927, 302.15055199, 298.85779116, ..., 241.52413856,\n",
       "         242.5884012 , 244.17041129],\n",
       "...\n",
       "        [294.88053902, 291.34362661, 287.80251302, ..., 215.55693741,\n",
       "         214.30393625, 212.45393151],\n",
       "        [294.88216839, 291.34529231, 287.80421631, ..., 215.56088955,\n",
       "         214.30823432, 212.45873669],\n",
       "        [294.88276485, 291.34590079, 287.80483721, ..., 215.56223885,\n",
       "         214.30968935, 212.46033875]],\n",
       "\n",
       "       [[294.25349055, 290.71563687, 287.17358684, ..., 215.03081378,\n",
       "         213.85584025, 212.1913367 ],\n",
       "        [294.24641956, 290.70856772, 287.16652006, ..., 215.02587554,\n",
       "         213.85196477, 212.1897749 ],\n",
       "        [294.23832217, 290.70044851, 287.15837877, ..., 215.01839033,\n",
       "         213.84531158, 212.1850905 ],\n",
       "        ...,\n",
       "        [294.79421775, 291.25526371, 287.71203823, ..., 215.33869856,\n",
       "         214.06547028, 212.1850905 ],\n",
       "        [294.79581018, 291.25689155, 287.71370269, ..., 215.34255374,\n",
       "         214.06966197, 212.1897749 ],\n",
       "        [294.7963952 , 291.25748829, 287.71431154, ..., 215.34387123,\n",
       "         214.07108189, 212.1913367 ]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>geopotential</span></div><div class='xr-var-dims'>(y, x, sigma)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.146e+04 1.452e+04 ... 3.418e+05</div><input id='attrs-3154891d-90a4-40b0-938a-86e97bec0329' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3154891d-90a4-40b0-938a-86e97bec0329' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8b6f83d5-7cf0-4369-a3d2-bd58847ecdba' class='xr-var-data-in' type='checkbox'><label for='data-8b6f83d5-7cf0-4369-a3d2-bd58847ecdba' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[1.14600535e+04, 1.45203435e+04, 1.76575387e+04, ...,\n",
       "         2.04421342e+05, 2.50768611e+05, 3.90580209e+05],\n",
       "        [1.15972780e+04, 1.46576138e+04, 1.77948559e+04, ...,\n",
       "         2.04560259e+05, 2.50907271e+05, 3.90716823e+05],\n",
       "        [1.17327389e+04, 1.47930842e+04, 1.79303348e+04, ...,\n",
       "         2.04692692e+05, 2.51037778e+05, 3.90839794e+05],\n",
       "        ...,\n",
       "        [3.20252275e+01, 3.08696169e+03, 6.21861776e+03, ...,\n",
       "         1.92645735e+05, 2.38940301e+05, 3.78680443e+05],\n",
       "        [3.01660906e+01, 3.08514968e+03, 6.21685582e+03, ...,\n",
       "         1.92650487e+05, 2.38947486e+05, 3.78695780e+05],\n",
       "        [2.84066326e+01, 3.08340541e+03, 6.21512769e+03, ...,\n",
       "         1.92650898e+05, 2.38948703e+05, 3.78699708e+05]],\n",
       "\n",
       "       [[1.14600535e+04, 1.45198411e+04, 1.76565040e+04, ...,\n",
       "         2.04355113e+05, 2.50678808e+05, 3.90412519e+05],\n",
       "        [1.15972780e+04, 1.46571108e+04, 1.77938200e+04, ...,\n",
       "         2.04493994e+05, 2.50817425e+05, 3.90549085e+05],\n",
       "        [1.17327389e+04, 1.47925806e+04, 1.79292978e+04, ...,\n",
       "         2.04626391e+05, 2.50947892e+05, 3.90672009e+05],\n",
       "...\n",
       "        [3.20252275e+01, 2.98422956e+03, 6.00684591e+03, ...,\n",
       "         1.78484011e+05, 2.19614532e+05, 3.42115378e+05],\n",
       "        [3.01660906e+01, 2.98238701e+03, 6.00502095e+03, ...,\n",
       "         1.78484358e+05, 2.19615669e+05, 3.42119128e+05],\n",
       "        [2.84066326e+01, 2.98063362e+03, 6.00327398e+03, ...,\n",
       "         1.78483369e+05, 2.19614948e+05, 3.42119285e+05]],\n",
       "\n",
       "       [[1.14600535e+04, 1.44059375e+04, 1.74219939e+04, ...,\n",
       "         1.89445841e+05, 2.30483146e+05, 3.52779988e+05],\n",
       "        [1.15972780e+04, 1.45430908e+04, 1.75590734e+04, ...,\n",
       "         1.89578190e+05, 2.30614652e+05, 3.52909933e+05],\n",
       "        [1.17327389e+04, 1.46784700e+04, 1.76943678e+04, ...,\n",
       "         1.89707364e+05, 2.30742472e+05, 3.53034499e+05],\n",
       "        ...,\n",
       "        [3.20252275e+01, 2.98334985e+03, 6.00503284e+03, ...,\n",
       "         1.78363682e+05, 2.19450505e+05, 3.41805728e+05],\n",
       "        [3.01660906e+01, 2.98150693e+03, 6.00320710e+03, ...,\n",
       "         1.78363977e+05, 2.19451569e+05, 3.41809341e+05],\n",
       "        [2.84066326e+01, 2.97975343e+03, 6.00145988e+03, ...,\n",
       "         1.78362971e+05, 2.19450825e+05, 3.41809452e+05]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pressure</span></div><div class='xr-var-dims'>(y, x, sigma)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>8.728e+04 8.444e+04 ... 5e+03</div><input id='attrs-f6fe5884-4083-46c6-8528-da41b413d305' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f6fe5884-4083-46c6-8528-da41b413d305' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ffd4bcb3-4057-4a93-a4f9-dcf18631a4c6' class='xr-var-data-in' type='checkbox'><label for='data-ffd4bcb3-4057-4a93-a4f9-dcf18631a4c6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[ 87277.73323609,  84440.57002105,  81603.40680602, ...,\n",
       "          10674.32643008,   7837.16321504,   5000.        ],\n",
       "        [ 87124.98439728,  84293.08838358,  81461.19236988, ...,\n",
       "          10663.7920274 ,   7831.8960137 ,   5000.        ],\n",
       "        [ 86973.90920732,  84147.22268293,  81320.53615854, ...,\n",
       "          10653.37304878,   7826.68652439,   5000.        ],\n",
       "        ...,\n",
       "        [100957.52078754,  97648.64076038,  94339.76073322, ...,\n",
       "          11617.76005431,   8308.88002716,   5000.        ],\n",
       "        [100960.866917  ,  97651.87150607,  94342.87609514, ...,\n",
       "          11617.99082186,   8308.99541093,   5000.        ],\n",
       "        [100963.44864026,  97654.36420439,  94345.27976852, ...,\n",
       "          11618.16887174,   8309.08443587,   5000.        ]],\n",
       "\n",
       "       [[ 87269.70716152,  84432.82070768,  81595.93425383, ...,\n",
       "          10673.77290769,   7836.88645385,   5000.        ],\n",
       "        [ 87116.97235401,  84285.35261766,  81453.73288132, ...,\n",
       "          10663.23947269,   7831.61973635,   5000.        ],\n",
       "        [ 86965.91101054,  84139.50028604,  81313.08956154, ...,\n",
       "          10652.821449  ,   7826.4107245 ,   5000.        ],\n",
       "...\n",
       "        [ 98908.06832214,  95669.85906965,  92431.64981717, ...,\n",
       "          11476.41850498,   8238.20925249,   5000.        ],\n",
       "        [ 98910.71514152,  95672.4146194 ,  92434.11409728, ...,\n",
       "          11476.60104424,   8238.30052212,   5000.        ],\n",
       "        [ 98913.03393082,  95674.65345044,  92436.27297007, ...,\n",
       "          11476.76096075,   8238.38048037,   5000.        ]],\n",
       "\n",
       "       [[ 85490.34737605,  82714.81815618,  79939.28893632, ...,\n",
       "          10551.05843973,   7775.52921986,   5000.        ],\n",
       "        [ 85340.91052972,  82570.53430455,  79800.15807939, ...,\n",
       "          10540.75245033,   7770.37622516,   5000.        ],\n",
       "        [ 85193.47928229,  82428.18689324,  79662.8945042 , ...,\n",
       "          10530.58477809,   7765.29238904,   5000.        ],\n",
       "        ...,\n",
       "        [ 98890.83443521,  95653.21945469,  92415.60447416, ...,\n",
       "          11475.22996105,   8237.61498052,   5000.        ],\n",
       "        [ 98893.47321175,  95655.76723893,  92418.06126611, ...,\n",
       "          11475.41194564,   8237.70597282,   5000.        ],\n",
       "        [ 98895.78906903,  95658.00323907,  92420.2174091 , ...,\n",
       "          11475.57165993,   8237.78582997,   5000.        ]]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-ed3de60c-5728-41ad-bd75-18b61994e006' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-ed3de60c-5728-41ad-bd75-18b61994e006' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:       (y: 150, x: 250, sigma: 30)\n",
       "Coordinates:\n",
       "  * y             (y) float64 0.0 1.208e+04 2.416e+04 ... 1.788e+06 1.8e+06\n",
       "  * x             (x) float64 -1.5e+06 -1.488e+06 ... 1.488e+06 1.5e+06\n",
       "  * sigma         (sigma) float64 1.0 0.9655 0.931 ... 0.06897 0.03448 0.0\n",
       "Data variables:\n",
       "    temperature   (y, x, sigma) float64 305.5 302.2 298.9 ... 215.3 214.1 212.2\n",
       "    geopotential  (y, x, sigma) float64 1.146e+04 1.452e+04 ... 3.418e+05\n",
       "    pressure      (y, x, sigma) float64 8.728e+04 8.444e+04 ... 8.238e+03 5e+03"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def generate_analytic_model(\n",
    "    nx=250,\n",
    "    ny=150,\n",
    "    nsigma=30,\n",
    "    L=3e6,\n",
    "    y_max=1.8e6,\n",
    "    y_scale_factor=0.333,\n",
    "    alpha=0.722,\n",
    "    terrain_rise=1.5e3,\n",
    "    pressure_variability=1e3,\n",
    "    pressure_sea_level_mean=1e5,\n",
    "    pressure_top=5e3,\n",
    "    scale_height=8e3,\n",
    "    temperature_variability=5,\n",
    "    temperature_mean_surface=300,\n",
    "    temperature_mean_tropopause=228.5,\n",
    "    a=1.12e-5,\n",
    "    b=2.3e-3,\n",
    "    k=20\n",
    "):\n",
    "    \"\"\"Generate sythetic data for an atmospheric trough over a Gaussian terrain.\n",
    "    \n",
    "    Parameters\n",
    "    ----------\n",
    "    nx : int\n",
    "        Count of grid points in x direction\n",
    "    ny : int\n",
    "        Count of grid points in y direction\n",
    "    nsigma : int\n",
    "        Count of vertical sigma coordinate levels\n",
    "    L : float\n",
    "        Zonal wavelength of trough [meters]\n",
    "    y_max : float\n",
    "        Meridional extent of domain [meters]\n",
    "    alpha : float\n",
    "        Vertical control parameter for tropopause location [dimensionless]\n",
    "    terrain_rise : float\n",
    "        Max height of the terrain [meters]\n",
    "    pressure_variability : float\n",
    "        Wave amplitude of sea-level pressure field [Pa]\n",
    "    pressure_sea_level_mean : float\n",
    "        Domain average of sea-level pressure field [Pa]\n",
    "    pressure_top : float\n",
    "        Uniform pressure at top of domain [Pa]\n",
    "    scale_height : float\n",
    "        Control parameter for conversion of sea-level pressure to surface pressure [meters]\n",
    "    temperature_variability : float\n",
    "        Wave amplitude of temperature perturbation field [K]\n",
    "    temperature_mean_surface : float\n",
    "        Horizontal mean of temperature at ground level [K]\n",
    "    temperature_mean_tropopause : float\n",
    "        Horizontal mean of temperature at model top [K]\n",
    "    a : float\n",
    "        Meridional control parameter for temperature field shape [K / m]\n",
    "    b : float\n",
    "        Meridional control parameter for temperature field shape [Pa / m]\n",
    "    k : float\n",
    "        Vertical control parameter for mean temperature profile sharpness in vertical\n",
    "    \n",
    "    \"\"\"\n",
    "    # Constants\n",
    "    R = 287.05\n",
    "    g = 9.81\n",
    "\n",
    "    # Define coordinates (and broadcasted versions)\n",
    "    x = np.linspace(-L / 2, L / 2, nx)\n",
    "    y = np.linspace(0, y_max, ny)\n",
    "    sigma = np.linspace(1, 0, nsigma)\n",
    "\n",
    "    x_2d, y_2d = np.meshgrid(x, y)\n",
    "    x_3d, y_3d, sigma_3d = np.meshgrid(x, y, sigma)\n",
    "    \n",
    "    # Sea-level pressure (2D) as a trough shape\n",
    "    pressure_sea_level = (\n",
    "        pressure_sea_level_mean\n",
    "        - b * y_2d * y_scale_factor\n",
    "        - pressure_variability * np.cos(2 * np.pi / L * x_2d) * np.cos(2 * np.pi / L * y_2d * y_scale_factor)\n",
    "    )\n",
    "    \n",
    "    # Terrain height as an offset Gaussian shape (uniform in meridional direction)\n",
    "    geopotential_height_surface = np.exp(-((x_2d + L / 3) / (L / 3))**2) * terrain_rise\n",
    "    \n",
    "    # Surface pressure (2D) from sea-level pressure and terrain height\n",
    "    pressure_surface = pressure_sea_level * np.exp(\n",
    "        -geopotential_height_surface / scale_height\n",
    "    )\n",
    "    \n",
    "    # Pressure (3D) from definition of sigma coordinate\n",
    "    pressure = sigma_3d * (pressure_surface - pressure_top)[..., None] + pressure_top\n",
    "    \n",
    "    # Trough component of temperature\n",
    "    temperature_pertubation = (\n",
    "        -(1 + alpha * np.log(pressure_sea_level_mean / pressure))\n",
    "        * (\n",
    "            a * y_3d * y_scale_factor\n",
    "            + temperature_variability * np.cos(2 * np.pi / L * x_3d) * np.cos(2 * np.pi / L * y_3d * y_scale_factor)\n",
    "        )\n",
    "    )\n",
    "    \n",
    "    # Vertical component of temperature\n",
    "    temperature_mean = (\n",
    "        temperature_mean_tropopause\n",
    "        + (\n",
    "            np.log(1 + np.exp(k * (sigma + alpha - 1)))\n",
    "            / np.log(1 + np.exp(k * alpha))\n",
    "        ) * (temperature_mean_surface - temperature_mean_tropopause)\n",
    "    )\n",
    "    \n",
    "    # Combine and calcuate temperature and geopotential 3D\n",
    "    temperature = temperature_mean[None, None] + temperature_pertubation\n",
    "    geopotential = g * geopotential_height_surface[..., None] - np.concatenate(\n",
    "        (\n",
    "            np.zeros_like(x_2d)[..., None],\n",
    "            np.cumsum(\n",
    "                (\n",
    "                    R\n",
    "                    * (temperature[..., :-1] + temperature[..., 1:])\n",
    "                    / (sigma_3d[..., :-1] + sigma_3d[..., 1:])\n",
    "                    * np.diff(sigma_3d, axis=-1)\n",
    "                ),\n",
    "                axis=-1\n",
    "            )\n",
    "        ),\n",
    "        axis=-1\n",
    "    )\n",
    "    \n",
    "    # Return dataset!\n",
    "    return xr.Dataset(\n",
    "        {\n",
    "            'temperature': (('y', 'x', 'sigma'), temperature),\n",
    "            'geopotential': (('y', 'x', 'sigma'), geopotential),\n",
    "            'pressure': (('y', 'x', 'sigma'), pressure),\n",
    "        },\n",
    "        {\n",
    "            'y': y,\n",
    "            'x': x,\n",
    "            'sigma': sigma\n",
    "        }\n",
    "    ), {\n",
    "        'p_init': pressure_sea_level,\n",
    "        't_init': temperature_pertubation[..., 0]\n",
    "    }\n",
    "\n",
    "ds, stuff = generate_analytic_model()\n",
    "\n",
    "ds"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This synthetic model gives a low-pressure trough centered in the domain, with a sloping terrain in the zonal direction. Here is what that terrain (surface geopotential height) looks like:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fc85a69d4b0>]"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "(ds['geopotential'] / 9.81).rename('geopotential_height').sel(sigma=1, y=0).plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If we were to inspect a given vertical level of these data, it would be difficult to interpret due to the terrain-following nature of the sigma coordinate:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.contour.QuadContourSet at 0x7fc854a50df0>"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ds['geopotential'].isel(sigma=15).plot.contourf()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "And so, let's interpolate to some common meteorological upper-air levels (750 hPa, 500 hPa, and 300 hPa) for plotting and analysis: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
       "<defs>\n",
       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
       "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
       "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
       "</symbol>\n",
       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
       "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
       "<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "</symbol>\n",
       "</defs>\n",
       "</svg>\n",
       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
       " *\n",
       " */\n",
       "\n",
       ":root {\n",
       "  --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
       "  --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
       "  --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
       "  --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
       "  --xr-background-color: var(--jp-layout-color0, white);\n",
       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
       "}\n",
       "\n",
       "html[theme=dark],\n",
       "body.vscode-dark {\n",
       "  --xr-font-color0: rgba(255, 255, 255, 1);\n",
       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
       "  --xr-border-color: #1F1F1F;\n",
       "  --xr-disabled-color: #515151;\n",
       "  --xr-background-color: #111111;\n",
       "  --xr-background-color-row-even: #111111;\n",
       "  --xr-background-color-row-odd: #313131;\n",
       "}\n",
       "\n",
       ".xr-wrap {\n",
       "  display: block !important;\n",
       "  min-width: 300px;\n",
       "  max-width: 700px;\n",
       "}\n",
       "\n",
       ".xr-text-repr-fallback {\n",
       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-header {\n",
       "  padding-top: 6px;\n",
       "  padding-bottom: 6px;\n",
       "  margin-bottom: 4px;\n",
       "  border-bottom: solid 1px var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-header > div,\n",
       ".xr-header > ul {\n",
       "  display: inline;\n",
       "  margin-top: 0;\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-obj-type,\n",
       ".xr-array-name {\n",
       "  margin-left: 2px;\n",
       "  margin-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-obj-type {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-sections {\n",
       "  padding-left: 0 !important;\n",
       "  display: grid;\n",
       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: '►';\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:       (y: 150, x: 250, pressure: 3)\n",
       "Coordinates:\n",
       "  * y             (y) float64 0.0 1.208e+04 2.416e+04 ... 1.788e+06 1.8e+06\n",
       "  * x             (x) float64 -1.5e+06 -1.488e+06 ... 1.488e+06 1.5e+06\n",
       "  * pressure      (pressure) float64 7.5e+04 5e+04 3e+04\n",
       "Data variables:\n",
       "    geopotential  (y, x, pressure) float64 2.529e+04 6.027e+04 ... 9.459e+04\n",
       "    temperature   (y, x, pressure) float64 291.3 262.7 242.8 ... 240.8 221.8</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-a81f0c01-2614-466e-8bfd-384837cf05ed' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-a81f0c01-2614-466e-8bfd-384837cf05ed' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>y</span>: 150</li><li><span class='xr-has-index'>x</span>: 250</li><li><span class='xr-has-index'>pressure</span>: 3</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-8a50f5fe-2a9e-44f2-9c44-b05b5c0407bf' class='xr-section-summary-in' type='checkbox'  checked><label for='section-8a50f5fe-2a9e-44f2-9c44-b05b5c0407bf' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 1.208e+04 ... 1.788e+06 1.8e+06</div><input id='attrs-e3566995-a0d9-47d6-8a31-a830c2de2a57' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e3566995-a0d9-47d6-8a31-a830c2de2a57' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-55c4922e-b46f-4fb8-b0ad-529a662d25aa' class='xr-var-data-in' type='checkbox'><label for='data-55c4922e-b46f-4fb8-b0ad-529a662d25aa' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([      0.      ,   12080.536913,   24161.073826,   36241.610738,\n",
       "         48322.147651,   60402.684564,   72483.221477,   84563.758389,\n",
       "         96644.295302,  108724.832215,  120805.369128,  132885.90604 ,\n",
       "        144966.442953,  157046.979866,  169127.516779,  181208.053691,\n",
       "        193288.590604,  205369.127517,  217449.66443 ,  229530.201342,\n",
       "        241610.738255,  253691.275168,  265771.812081,  277852.348993,\n",
       "        289932.885906,  302013.422819,  314093.959732,  326174.496644,\n",
       "        338255.033557,  350335.57047 ,  362416.107383,  374496.644295,\n",
       "        386577.181208,  398657.718121,  410738.255034,  422818.791946,\n",
       "        434899.328859,  446979.865772,  459060.402685,  471140.939597,\n",
       "        483221.47651 ,  495302.013423,  507382.550336,  519463.087248,\n",
       "        531543.624161,  543624.161074,  555704.697987,  567785.234899,\n",
       "        579865.771812,  591946.308725,  604026.845638,  616107.38255 ,\n",
       "        628187.919463,  640268.456376,  652348.993289,  664429.530201,\n",
       "        676510.067114,  688590.604027,  700671.14094 ,  712751.677852,\n",
       "        724832.214765,  736912.751678,  748993.288591,  761073.825503,\n",
       "        773154.362416,  785234.899329,  797315.436242,  809395.973154,\n",
       "        821476.510067,  833557.04698 ,  845637.583893,  857718.120805,\n",
       "        869798.657718,  881879.194631,  893959.731544,  906040.268456,\n",
       "        918120.805369,  930201.342282,  942281.879195,  954362.416107,\n",
       "        966442.95302 ,  978523.489933,  990604.026846, 1002684.563758,\n",
       "       1014765.100671, 1026845.637584, 1038926.174497, 1051006.711409,\n",
       "       1063087.248322, 1075167.785235, 1087248.322148, 1099328.85906 ,\n",
       "       1111409.395973, 1123489.932886, 1135570.469799, 1147651.006711,\n",
       "       1159731.543624, 1171812.080537, 1183892.61745 , 1195973.154362,\n",
       "       1208053.691275, 1220134.228188, 1232214.765101, 1244295.302013,\n",
       "       1256375.838926, 1268456.375839, 1280536.912752, 1292617.449664,\n",
       "       1304697.986577, 1316778.52349 , 1328859.060403, 1340939.597315,\n",
       "       1353020.134228, 1365100.671141, 1377181.208054, 1389261.744966,\n",
       "       1401342.281879, 1413422.818792, 1425503.355705, 1437583.892617,\n",
       "       1449664.42953 , 1461744.966443, 1473825.503356, 1485906.040268,\n",
       "       1497986.577181, 1510067.114094, 1522147.651007, 1534228.187919,\n",
       "       1546308.724832, 1558389.261745, 1570469.798658, 1582550.33557 ,\n",
       "       1594630.872483, 1606711.409396, 1618791.946309, 1630872.483221,\n",
       "       1642953.020134, 1655033.557047, 1667114.09396 , 1679194.630872,\n",
       "       1691275.167785, 1703355.704698, 1715436.241611, 1727516.778523,\n",
       "       1739597.315436, 1751677.852349, 1763758.389262, 1775838.926174,\n",
       "       1787919.463087, 1800000.      ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-1.5e+06 -1.488e+06 ... 1.5e+06</div><input id='attrs-af445cda-8308-4aa2-b6fa-88b18ccb2555' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-af445cda-8308-4aa2-b6fa-88b18ccb2555' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-81f3f265-f69a-4ff8-a800-0c928324ae50' class='xr-var-data-in' type='checkbox'><label for='data-81f3f265-f69a-4ff8-a800-0c928324ae50' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-1500000.      , -1487951.807229, -1475903.614458, ...,  1475903.614458,\n",
       "        1487951.807229,  1500000.      ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>pressure</span></div><div class='xr-var-dims'>(pressure)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>7.5e+04 5e+04 3e+04</div><input id='attrs-f7b0a8b0-dc04-4020-b5c2-60a20fe7fc3c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f7b0a8b0-dc04-4020-b5c2-60a20fe7fc3c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c6cd1868-f096-4d49-b24d-8f4e22a2caf1' class='xr-var-data-in' type='checkbox'><label for='data-c6cd1868-f096-4d49-b24d-8f4e22a2caf1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([75000., 50000., 30000.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-49529ecd-3cf5-441e-be1f-2b9840de6f44' class='xr-section-summary-in' type='checkbox'  checked><label for='section-49529ecd-3cf5-441e-be1f-2b9840de6f44' class='xr-section-summary' >Data variables: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>geopotential</span></div><div class='xr-var-dims'>(y, x, pressure)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.529e+04 6.027e+04 ... 9.459e+04</div><input id='attrs-4ebce9d3-6517-4d5d-a18d-486e89f4150f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4ebce9d3-6517-4d5d-a18d-486e89f4150f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-274fa33f-4c8b-49ce-b6ab-14aceb5fe95a' class='xr-var-data-in' type='checkbox'><label for='data-274fa33f-4c8b-49ce-b6ab-14aceb5fe95a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[ 25287.83676273,  60269.40608511, 102606.3143656 ],\n",
       "        [ 25270.14491781,  60267.55577153, 102614.86483933],\n",
       "        [ 25251.91182001,  60264.46296755, 102621.15250807],\n",
       "        ...,\n",
       "        [ 26410.20506226,  60157.23776212, 101657.13023413],\n",
       "        [ 26411.61399329,  60159.20026952, 101660.29089329],\n",
       "        [ 26412.16747767,  60159.82125901, 101661.24049674]],\n",
       "\n",
       "       [[ 25277.2894549 ,  60251.9328587 , 102576.53375009],\n",
       "        [ 25259.62206473,  60250.10702578, 102585.10831535],\n",
       "        [ 25241.41333033,  60247.03863595, 102591.42005169],\n",
       "        ...,\n",
       "        [ 26397.95006478,  60137.94806826, 101625.40547668],\n",
       "        [ 26399.35848713,  60139.91002913, 101628.56555178],\n",
       "        [ 26399.91162376,  60140.53065735, 101629.5147873 ]],\n",
       "\n",
       "       [[ 25266.66299891,  60234.3260638 , 102546.52292979],\n",
       "        [ 25249.02028812,  60232.52495387, 102555.12185708],\n",
       "        [ 25230.83619202,  60229.48130557, 102561.45807817],\n",
       "        ...,\n",
       "...\n",
       "        ...,\n",
       "        [ 23760.11049494,  55954.73766707,  94708.12010479],\n",
       "        [ 23760.5827102 ,  55955.260656  ,  94708.95794593],\n",
       "        [ 23760.78318779,  55955.36076844,  94709.09338721]],\n",
       "\n",
       "       [[ 22995.81352946,  56434.38393864,  96037.52032452],\n",
       "        [ 22982.48001333,  56437.4772376 ,  96053.15699085],\n",
       "        [ 22969.0674971 ,  56440.12072135,  96067.89902699],\n",
       "        ...,\n",
       "        [ 23738.0025745 ,  55919.45215389,  94649.49172875],\n",
       "        [ 23738.46426402,  55919.95868659,  94650.30265163],\n",
       "        [ 23738.66087487,  55920.05295276,  94650.42876817]],\n",
       "\n",
       "       [[ 22976.85430342,  56402.45485677,  95982.66571965],\n",
       "        [ 22963.57101275,  56405.5996659 ,  95998.35491335],\n",
       "        [ 22950.21388009,  56408.30371983,  96013.16543872],\n",
       "        ...,\n",
       "        [ 23715.87188693,  55884.12669425,  94590.79241342],\n",
       "        [ 23716.32302722,  55884.61673075,  94591.57634846],\n",
       "        [ 23716.51576283,  55884.70513665,  94591.69311637]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temperature</span></div><div class='xr-var-dims'>(y, x, pressure)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>291.3 262.7 242.8 ... 240.8 221.8</div><input id='attrs-e3dca6b7-4563-4615-a4ee-7b7a2e9345ac' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e3dca6b7-4563-4615-a4ee-7b7a2e9345ac' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9854966b-7c21-490c-a39b-f369be1f0926' class='xr-var-data-in' type='checkbox'><label for='data-9854966b-7c21-490c-a39b-f369be1f0926' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[291.27521451, 262.66950882, 242.77958028],\n",
       "        [291.42881863, 262.76509415, 242.80774249],\n",
       "        [291.57717925, 262.85502899, 242.82968173],\n",
       "        ...,\n",
       "        [279.2524916 , 255.043627  , 240.56558187],\n",
       "        [279.25570078, 255.04922016, 240.57414443],\n",
       "        [279.25565056, 255.0503969 , 240.57684069]],\n",
       "\n",
       "       [[291.22875063, 262.60678176, 242.69666201],\n",
       "        [291.38235673, 262.70236873, 242.72482504],\n",
       "        [291.53071948, 262.79230539, 242.74676531],\n",
       "        ...,\n",
       "        [279.20495804, 254.98011489, 240.48203364],\n",
       "        [279.20816695, 254.98570774, 240.49059587],\n",
       "        [279.20811662, 254.98688438, 240.49329202]],\n",
       "\n",
       "       [[291.18192136, 262.54356203, 242.61309297],\n",
       "        [291.33552957, 262.63915081, 242.64125704],\n",
       "        [291.48389483, 262.72908977, 242.66319897],\n",
       "        ...,\n",
       "...\n",
       "        ...,\n",
       "        [268.76060606, 241.02228804, 222.11796104],\n",
       "        [268.76041146, 241.02334894, 222.12057768],\n",
       "        [268.75922362, 241.02301235, 222.12129079]],\n",
       "\n",
       "       [[280.95631955, 248.74066244, 224.31232276],\n",
       "        [281.11739619, 248.84408999, 224.35483975],\n",
       "        [281.27539884, 248.94481137, 224.3949731 ],\n",
       "        ...,\n",
       "        [268.67154604, 240.90319391, 221.96119698],\n",
       "        [268.67131132, 240.90420127, 221.96374326],\n",
       "        [268.67011007, 240.90384681, 221.96443291]],\n",
       "\n",
       "       [[280.86971777, 248.62343285, 224.15767476],\n",
       "        [281.03081114, 248.72688099, 224.20021661],\n",
       "        [281.1888565 , 248.82765808, 224.24042113],\n",
       "        ...,\n",
       "        [268.58237005, 240.78394305, 221.80422498],\n",
       "        [268.5820951 , 240.78489672, 221.80670071],\n",
       "        [268.58088042, 240.78452434, 221.80736683]]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-e10f4be0-1b98-4e74-9ee5-3b7412e17da2' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-e10f4be0-1b98-4e74-9ee5-3b7412e17da2' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:       (y: 150, x: 250, pressure: 3)\n",
       "Coordinates:\n",
       "  * y             (y) float64 0.0 1.208e+04 2.416e+04 ... 1.788e+06 1.8e+06\n",
       "  * x             (x) float64 -1.5e+06 -1.488e+06 ... 1.488e+06 1.5e+06\n",
       "  * pressure      (pressure) float64 7.5e+04 5e+04 3e+04\n",
       "Data variables:\n",
       "    geopotential  (y, x, pressure) float64 2.529e+04 6.027e+04 ... 9.459e+04\n",
       "    temperature   (y, x, pressure) float64 291.3 262.7 242.8 ... 240.8 221.8"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grid = Grid(\n",
    "    ds,\n",
    "    coords={\n",
    "        'X': {'center': 'x'},\n",
    "        'Y': {'center': 'y'},\n",
    "        'Z': {'center': 'sigma'}\n",
    "    },\n",
    "    periodic=False\n",
    ")\n",
    "\n",
    "isobaric_levels = np.array([7.5e4, 5.0e4, 3.0e4]) \n",
    "\n",
    "geopotential_isobaric = grid.transform(\n",
    "    ds['geopotential'],\n",
    "    'Z',\n",
    "    isobaric_levels,\n",
    "    target_data=ds['pressure'],\n",
    "    method='log'\n",
    ")\n",
    "temperature_isobaric = grid.transform(\n",
    "    ds['temperature'],\n",
    "    'Z',\n",
    "    isobaric_levels,\n",
    "    target_data=ds['pressure'],\n",
    "    method='log'\n",
    ")\n",
    "\n",
    "ds_isobaric = xr.merge([geopotential_isobaric, temperature_isobaric])\n",
    "\n",
    "ds_isobaric"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "An additional benefit of now having our data in isobaric coordinates is that the form of kinematics and dynamics formulas are more straightforward compared to non-isobaric forms. To demonstrate this, let's plot the 300 hPa Temperature and Geostrophic Wind:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Add inner coords for derivatives\n",
    "ds_isobaric.coords['x_inner'] = (ds_isobaric['x'].values[:-1] + ds_isobaric['x'].values[1:]) / 2\n",
    "ds_isobaric.coords['y_inner'] = (ds_isobaric['y'].values[:-1] + ds_isobaric['y'].values[1:]) / 2\n",
    "\n",
    "# Create new grid\n",
    "grid_isobaric = Grid(\n",
    "    ds_isobaric,\n",
    "    coords={\n",
    "        'X': {'center': 'x', 'inner': 'x_inner'},\n",
    "        'Y': {'center': 'y', 'inner': 'y_inner'},\n",
    "        'Z': {'center': 'pressure'}\n",
    "    },\n",
    "    periodic=False\n",
    ")\n",
    "\n",
    "# Calculate geostrophic wind components (without metrics)\n",
    "f = 1.2e-4  # f-plane approximation of Coriolis force\n",
    "u_wind = grid_isobaric.interp(\n",
    "    -grid_isobaric.diff(ds_isobaric['geopotential'], 'Y', to='inner') / grid_isobaric.diff(ds_isobaric['y'], 'Y', to='inner') / f,\n",
    "    to='inner',\n",
    "    axis='X'\n",
    ")\n",
    "v_wind = grid_isobaric.interp(\n",
    "    grid_isobaric.diff(ds_isobaric['geopotential'], 'X', to='inner') / grid_isobaric.diff(ds_isobaric['x'], 'X', to='inner') / f,\n",
    "    to='inner',\n",
    "    axis='Y'\n",
    ")\n",
    "\n",
    "# Plot\n",
    "level = 3.0e4\n",
    "fig, ax = plt.subplots(1, 1, figsize=[8,5])\n",
    "ds_isobaric['temperature'].sel(pressure=level).plot.contourf(ax=ax, alpha=0.3)\n",
    "ds_isobaric['geopotential'].sel(pressure=level).plot.contour(ax=ax, colors='k')\n",
    "barb_reduce = slice(10, -10, 25)\n",
    "ax.barbs(\n",
    "    u_wind.x_inner.values[barb_reduce],\n",
    "    u_wind.y_inner.values[barb_reduce],\n",
    "    u_wind.sel(pressure=level).values[barb_reduce, barb_reduce],\n",
    "    v_wind.sel(pressure=level).values[barb_reduce, barb_reduce]\n",
    ")\n",
    "ax.set_aspect('equal')\n",
    "\n",
    "plt.show();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Performance\n",
    "By default xgcm performs some simple checks when using `method='linear'`. \n",
    "It checks if the last value of the data is larger than the first, and if not, the data is flipped.This ensures that monotonically decreasing variables, like temperature are interpolated correctly. These checks have a performance penalty (~30% in some preliminary tests).\n",
    "\n",
    "If you have manually flipped your data and ensured that its monotonically increasing, you can switch the checks off to get even better performance.\n",
    "```python\n",
    "grid.transform(..., method='linear', bypass_checks=True)\n",
    "```"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.4"
  },
  "metadata": {
   "interpreter": {
    "hash": "0eebbd7d82d008a55ff9d28d9bdb7fecf01212b8a08de283d5d120546780e509"
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}