Earthkit: Open-source tools for seamless earth science workflows

Working with meteorological and climatological datasets often means grappling with a patchwork of file formats, incompatible data structures, and complex APIs before any real analysis can begin. Earthkit is an open-source ecosystem of Python-based tools designed to remove these obstacles, offering high-level, concise APIs that let researchers and operational users focus on their science rather than getting bogged down in the details of software.

Led by ECMWF, earthkit builds on decades of experience developing operational meteorological software to provide a modern, accessible Python toolkit. It integrates seamlessly with essential data science packages like xarray, pandas, and geopandas, bridging the gap between specialised meteorological capabilities and the tools data scientists already use.

Earthkit provides a consistent interface for accessing data from a wide range of sources - from local files and URLs to in-memory streams and remote web services - and across diverse formats including GRIB, netCDF, Zarr, and GeoTIFF, without requiring users to master the intricacies of each. Earthkit also brings capabilities to the open-source ecosystem that have previously been hard to find, including regridding across complex grid types such as HEALPix, Reduced Gaussian, ORCA, and ICON, as well as meteorological and hydrological algorithms, with GPU acceleration for computationally intensive operations.

This presentation introduces the earthkit ecosystem and demonstrates through practical examples how its components work together to support reproducible, format-agnostic, end-to-end workflows - from data retrieval and analysis through to publication-quality visualisation. Earthkit is designed for anyone who works with weather and climate data, and aims to make modern earth science data more accessible, interoperable, and actionable.