Machine learning in TerraDT: from emulators to impact models for the cryosphere and land surface
This file covers all the presentations held on 17th September 2026, during the TerraDT webinar: "Machine learning in TerraDT: from emulators to impact models for the cryosphere and land surface". More details and the agenda are available on the website: https://terradt.eu/events/machine-learning-terradt-emulators-impact-models-cryosphere-and-land-surface
Authors
- Peter Dominik Dueben (ORCID: https://orcid.org/0000-0002-4610-3326)
- Stefano Materia (ORCID: https://orcid.org/0000-0001-5635-2847)
- N. Devaraju (ORCID: https://orcid.org/0000-0001-8471-3961)
- Marina Castaño (ORCID: https://orcid.org/0009-0007-6516-4320)
- Maria Grazia Giuffrida (ORCID: https://orcid.org/0000-0001-8655-0190)
- Amirpasha Mozaffari (ORCID: https://orcid.org/0000-0001-6719-0425)
- Benjamin Rodenberg (ORCID: https://orcid.org/0000-0002-3116-0133)
Institutions
- European Centre for Medium-Range Weather Forecasts (GB)
- Commissariat à l'Énergie Atomique et aux Énergies Alternatives (FR)
- Barcelona Supercomputing Center (ES)
- CEA Paris-Saclay - Etablissement de Saclay (FR)
- University of Oxford (GB)
- CEA Paris-Saclay (FR)
- CSC - IT Center for Science (Finland) (FI)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2026-11-06
- DOI
- https://doi.org/10.5281/zenodo.24014034
- Primary Topic
- Cryospheric studies and observations
- Type
- article
- Field-Weighted Citation Impact
- 0.00