UXarray: A Python package for the analysis of kilometer-scale atmosphere and ocean model outputs

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Authors: John Clyne, Hongyu chen, Orhan Eroglu, Robert Jacob, Rajeev Jain, Brian Medeiros, Paul Aaron Ullrich, Colin M. Zarzycki
Cited by: 0

Abstract

UXarray is a community-developed Python package that extends the widely used Xarray ecosystem with native support for horizontally unstructured meshes, eliminating the need for costly, problematic regridding prior to visualization and analysis. Designed to meet the growing demands of kilometer-scale climate and weather models, UXarray aims to become a preeminent tool for the analysis, visualization, and postprocessing of Earth system data on irregular grids. It has been used in practice across a wide range of high-resolution atmospheric and ocean models, including MPAS, CAM-SE, E3SM, FESOM2, IFS, and ICON.Recently, UXarray played a key role in the 2025 WCRP Digital Earth – Global Hackathon (DEGH), where over 600 researchers, spanning four continents, collaborated to explore km-scale outputs, contributed from 11 different modeling centers from around the world. The use of UXarray was essential to fulfilling hackathon objectives, such as promoting global collaboration, sharing best-practice in process-based analysis of km-scale simulations, developing practical km-scale analysis workflows, and facilitating model intercomparison.This presentation will highlight UXarray’s current capabilities—including visualization tools and foundational analysis operators—share insights from the DEGH experience, outline future development plans, and highlight ways that the community can engage to shape the package moving forward.

Fields of Study & Subjects

Computational Physics and Python Applications Meteorological Phenomena and Simulations Scientific Computing and Data Management

Publication details

Journal / source
EGU General Assembly Conference Abstracts
Publication date
14 March 2026
Language
EN