xCDAT: A Python package for simplifying climate data analysis on structured grids

xCDAT: A Python package for simplifying climate data analysis on structured grids

• Tom Vo

• vo13@llnl.gov

Tom Vo, LLNL; Stephen Po-Chedley, LLNL; Jason Boutte, LLNL; Jill Zhang, LLNL; Jiwoo Lee, LLNL

Performance - Algorithms - Tools

E3SM

xCDAT is an extension of xarray for climate data analysis on structured grids. It serves as a modern successor to the Community Data Analysis Tools (CDAT) library. The goal of xCDAT is to provide generalizable features and utilities for streamlining climate data analysis. xCDAT's design philosophy focuses on reducing the overhead to accomplish certain tasks in xarray. xCDAT abstracts boilerplate logic with robust APIs, resulting in reusable, readable, and less-error prone analysis code that contributes to reproducible science. xCDAT prioritizes compatibility with CF-compliant datasets on structured grids (e.g., CMIP6). Key features include spatial averaging, temporal averaging, and regridding, which are all inspired by the CDAT library and leverage powerful packages in the xarray ecosystem such as xESMF and CF Xarray. The core team is driven to provide a maintainable and extensible package that serves the needs of the climate community in the long-term.

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Todo – add slides here

Please post any question, comments, and ideas in the xCDAT GitHub Discussions forum!