Regridding Satellite and Model Data to DGGS Using the Pangeo Ecosystem

Regridding Satellite and Model Data to DGGS Using the Pangeo Ecosystem#

Welcome! This Jupyter Book presents a practical evaluation of different Python-based regridding tools for mapping geospatial datasets to Discrete Global Grid Systems (DGGS), particularly HEALPix and H3.

Objectives#

  • Understand the fundamentals of regridding and its role in comparing gridded data.

  • Explore offline, area-based regridding techniques.

  • Compare regridding tools available in the Pangeo ecosystem:

    • xesmf

    • uxarray

    • grid-weights

  • Evaluate their compatibility with DGGS such as HEALPix and H3.

Why DGGS?#

DGGS provide a hierarchical, equal-area tiling of the globe and are increasingly used in Earth observation and climate modeling. HEALPix, originally developed for astrophysics, offers excellent characteristics for global-scale geoscientific applications.

Structure of the Book#

This book is divided into the following sections:

Citation#

This work is developed by researchers at LOPS, CNES, and Development Seed [MDZ+25].

References#

[MDZ+25]

Justus Magin, Jean-Marc Delouis, Lionel Zawadski, Julien Petiton, Max Jones, and Tina Odaka. Regridding satellite and model data to dggs (healpix) using the pangeo ecosystem. March 2025. URL: http://dx.doi.org/10.5194/egusphere-egu25-18285, doi:10.5194/egusphere-egu25-18285.

Contents