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Hacking Km-Scale Models: A Participative Model for Climate Information

  • Andrew Gettelman
  • , Pier Luigi Vidale
  • , Björn Stevens
  • , Florian Ziemen
  • , Zhe Feng
  • , Heike Konow
  • , Tobias Kölling
  • , Lukas Kluft
  • , John Clyne
  • , Julia Kukulies
  • , Brian Medeiros
  • , William K. Jones
  • , Sara Pasqualetto
  • , Yuting Wu
  • , Saskia Brose
  • , Lluis Fita
  • , Samuel Green
  • University of Reading
  • National Centre for Atmospheric Science
  • University of California at Los Angeles
  • Max Planck Institute for Meteorology
  • MPI Hamburg
  • National Center for Atmospheric Research
  • German Climate Computing Center
  • Helmholtz-Zentrum Hereon
  • Deutsches Klimarechenzentrum
  • Pacific Northwest National Laboratory
  • Karlsruhe Institute of Technology
  • University of Hamburg
  • Ludwig Maximilian University of Munich
  • University of California at Davis
  • University Corporation For Atmospheric Res
  • IEEE
  • University of Gothenburg
  • University of Oxford

Research output: Contribution to journalArticlepeer-review

Abstract

In May 2025 nearly 700 participants from all around the world coalesced at 10 regional nodes, and a few satellite nodes, to take part in a global hackathon of km-scale (horizontal grid spacing < 10 km) regional and global Earth System Models. Exciting science is emerging from these efforts, ranging across novel model analysis, new ways of integrating with satellite data, and emulation with machine learning. New technologies were trialed that enable the community to work in new and complementary ways to democratize access to global information at a local scale from a set of the world's highest-resolution climate models. The hackathon demonstrated how exascale data can be organized to be accessible to anyone. Fundamentally, the community could apply these techniques and technologies to move towards more participative models for co-production and delivery of diverse sources of climate information for climate scientists and citizens alike.
Original languageAmerican English
Article numberBAMS-D-25-0183.1
JournalBulletin of the American Meteorological Society (BAMS)
DOIs
StatePublished - Apr 28 2026

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