xgcm: General Circulation Model Postprocessing with xarray ========================================================== **xgcm** is a python packge for working with the datasets produced by numerical `General Circulation Models `_ (GCMs) and similar gridded datasets that are amenable to `finite volume `_ analysis. In these datasets, different variables are located at different positions with respect to a volume or area element (e.g. cell center, cell face, etc.) xgcm solves the problem of how to interpolate and difference these variables from one position to another. xgcm consumes and produces xarray_ data structures, which are coordinate and metadata-rich representations of multidimensional array data. xarray is ideal for analyzing GCM data in many ways, providing convenient indexing and grouping, coordinate-aware data transformations, and (via dask_) parallel, out-of-core array computation. On top of this, xgcm adds an understanding of the finite volume `Arakawa Grids`_ commonly used in ocean and atmospheric models and differential and integral operators suited to these grids. xgcm was motivated by the rapid growth in the numerical resolution of ocean, atmosphere, and climate models. While highly parallel supercomputers can now easily generate tera- and petascale datasets, common post-processing workflows struggle with these volumes. Furthermore, we believe that a flexible, evolving, open-source, python-based framework for GCM analysis will enhance the productivity of the field as a whole, accelerating the rate of discovery in climate science. xgcm is part of the Pangeo_ initiative. .. _Pangeo: http://pangeo.io .. _dask: http://dask.pydata.org .. _xarray: http://xarray.pydata.org .. _Arakawa Grids: https://en.wikipedia.org/wiki/Arakawa_grids Contents -------- .. toctree:: :maxdepth: 1 installation grids grid_topology grid_metrics grid_ufuncs ufunc_examples boundary_conditions transform xgcm-examples/02_mitgcm xgcm-examples/01_eccov4 xgcm-examples/03_MOM6 xgcm-examples/04_nemo_idealized xgcm-examples/05_autogenerate whats-new contributor_guide api