GCPy is a Python-based toolkit containing useful functions for working specifically with the GEOS-Chem model of atmospheric chemistry and composition.
GCPy aims to build on the well-established scientific Python technical stack, leveraging tools like cartopy and xarray to simplify the task of working with model output and performing atmospheric chemistry analyses.
- Produce plots and tables from GEOS-Chem output using simple function calls.
- Generate the standard evaluation plots and tables from GEOS-Chem benchmark output.
- Obtain GEOS-Chem's horizontal/vertical grid information.
- Implement GCHP-specific regridding functionalities (e.g. cubed-sphere to lat-lon regridding).
- Provide example scripts for creating specific types of plots or analysis from GEOS-Chem output.
- General NetCDF file modification: (crop a domain, extract some variables):
- Use xarray instead.
- Also see our Working with netCDF data files wiki page.
- Statistical analysis:
- Use scipy/scikit-learn tools instead.
- Machine Learning:
- Use the standard machine learning utilities (pytorch, tensorflow, julia, etc.).