Artificial Intelligence and Machine Learning for Enhanced Representation of Processes and Extremes in Earth System Models

Informazioni relative al progetto

AI4PEX

ID dell’accordo di sovvenzione: 101137682

DOI

10.3030/101137682

Data della firma CE 24 Ottobre 2023

Data di avvio 1 Aprile 2024

Data di completamento 31 Marzo 2028

Finanziato da

• Climate, Energy and Mobility

Costo totale

Nessun dato

Contributo UE

€ 6 638 882,50

Coordinato da

MAX-PLANCK-GESELLSCHAFT ZUR FORDERUNG DER WISSENSCHAFTEN EV
Germany

CORDIS fornisce collegamenti ai risultati finali pubblici e alle pubblicazioni dei progetti ORIZZONTE.

I link ai risultati e alle pubblicazioni dei progetti del 7° PQ, così come i link ad alcuni tipi di risultati specifici come dataset e software, sono recuperati dinamicamente da .OpenAIRE .

Pubblicazioni

Peer reviewed articles (24)

Environmental Research Letters

Autori: Elizabeth A Barnes; Noah S Diffenbaugh; Sonia I Seneviratne
Pubblicato in: Environmental Research Letters, Numero 20 (1), 2024, ISSN 1748-9326
Editore: IOP Science
DOI: 10.3929/ETHZ-B-000712192

Sub-seasonal forest carbon dynamics lose persistence under extremes

Autori: Tristan K E Williams, Álvaro Moreno Martínez, Francesco Martinuzzi, Miguel D Mahecha, Gustau Camps-Valls
Pubblicato in: Environmental Research Letters, Numero 20, 2025, ISSN 1748-9326
Editore: IOP Publishing
DOI: 10.1088/1748-9326/ADE8FF

Scale‐Aware Parameterization of Cloud Fraction and Condensate for a Global Atmospheric Model Machine‐Learned From Coarse‐Grained Kilometer‐Scale Simulations

Autori: Cyril Morcrette, Tobias Cave, Helena Reid, Joana da Silva Rodrigues, Teo Deveney, Lisa Kreusser, Kwinten Van Weverberg, Chris Budd
Pubblicato in: Journal of Advances in Modeling Earth Systems, Numero 17, 2025, ISSN 1942-2466
Editore: American Geophysical Union (AGU)
DOI: 10.1029/2024MS004651

Early-twentieth-century cold bias in ocean surface temperature observations

Autori: Sippel, Sebastian; Kent, Elizabeth C.; Meinshausen, Nicolai; Chan, Duo; Kadow, Christopher; Neukom, Raphael; Fischer, Erich M.; Humphrey, Vincent; Rohde, Robert; de Vries, Iris; Knutti, Reto
Pubblicato in: Nature, Numero 635, 2024, ISSN 1476-4687
Editore: Springer Nature
DOI: 10.5194/EGUSPHERE-EGU25-6761

Distilling Machine Learning’s Added Value: Pareto Fronts in Atmospheric Applications

Autori: Tom Beucler, Arthur Grundner, Sara Shamekh, Peter Ukkonen, Matthew Chantry, Ryan Lagerquist
Pubblicato in: Artificial Intelligence for the Earth Systems, Numero 4, 2025, ISSN 2769-7525
Editore: American Meteorological Society
DOI: 10.1175/AIES-D-24-0078.1

Artificial intelligence for modeling and understanding extreme weather and climate events

Autori: Gustau Camps-Valls, Miguel-Ángel Fernández-Torres, Kai-Hendrik Cohrs, Adrian Höhl, Andrea Castelletti, Aytac Pacal, Claire Robin, Francesco Martinuzzi, Ioannis Papoutsis, Ioannis Prapas, Jorge Pérez-Aracil, Katja Weigel, Maria Gonzalez-Calabuig, Markus Reichstein, Martin Rabel, Matteo Giuliani, Miguel D. Mahecha, Oana-Iuliana Popescu, Oscar J. Pellicer-Valero, Said Ouala, Sancho Salcedo-Sanz, Sebastian Sippel, Spyros Kondylatos, Tamara Happé, Tristan Williams
Pubblicato in: Nature Communications, Numero 16, 2025, ISSN 2041-1723
Editore: Springer Science and Business Media LLC
DOI: 10.1038/S41467-025-56573-8

Combining climate models and observations to predict the time remaining until regional warming thresholds are reached

Autori: Elizabeth A Barnes, Noah S Diffenbaugh, Sonia I Seneviratne
Pubblicato in: Environmental Research Letters, Numero 20, 2025, ISSN 1748-9326
Editore: IOP Publishing
DOI: 10.1088/1748-9326/AD91CA

Simulating Atmospheric Processes in Earth System Models and Quantifying Uncertainties With Deep Learning Multi‐Member and Stochastic Parameterizations

Autori: Gunnar Behrens, Tom Beucler, Fernando Iglesias‐Suarez, Sungduk Yu, Pierre Gentine, Michael Pritchard, Mierk Schwabe, Veronika Eyring
Pubblicato in: Journal of Advances in Modeling Earth Systems, Numero 17, 2025, ISSN 1942-2466
Editore: American Geophysical Union (AGU)
DOI: 10.1029/2024MS004272

Analyzing climate scenarios using dynamic mode decomposition with control

Autori: Nathan Mankovich, Shahine Bouabid, Peer Nowack, Deborah Bassotto, Gustau Camps-Valls
Pubblicato in: Environmental Data Science, Numero 4, 2025, ISSN 2634-4602
Editore: Cambridge University Press (CUP)
DOI: 10.1017/EDS.2025.8

Enhanced Computational Complexity in Continuous-Depth Models: Neural Ordinary Differential Equations With Trainable Numerical Schemes

Autori: Said Ouala, Laurent Debreu, Bertrand Chapron, Fabrice Collard, Lucile Gaultier, Ronan Fablet
Pubblicato in: IEEE Transactions on Pattern Analysis and Machine Intelligence, 2025, ISSN 0162-8828
Editore: Institute of Electrical and Electronics Engineers (IEEE)
DOI: 10.1109/TPAMI.2025.3599629

Adjoint‐Based Online Learning of Two‐Layer Quasi‐Geostrophic Baroclinic Turbulence

Autori: F. E. Yan, H. Frezat, J. Le Sommer, J. Mak, K. Otness
Pubblicato in: Journal of Advances in Modeling Earth Systems, Numero 17, 2025, ISSN 1942-2466
Editore: American Geophysical Union (AGU)
DOI: 10.1029/2024MS004857

Either Or: Interactive Articles or Videos for Climate Science Communication

Autori: J. Poehls, M. Meuschke, N. Carvalhais, K. Lawonn
Pubblicato in: Computer Graphics Forum, Numero 44, 2025, ISSN 0167-7055
Editore: Wiley
DOI: 10.1111/CGF.70129

Improving vertical detail in simulated temperature and humidity data using machine learning

Autori: Joana D. da Silva Rodrigues, Cyril J. Morcrette
Pubblicato in: Atmospheric Science Letters, Numero 26, 2025, ISSN 1530-261X
Editore: Wiley
DOI: 10.1002/ASL.1288

Record-breaking extremes in a warming climate

Autori: Fischer, Erich; Bador, Margot; Huser, Raphaël; Kendon, Elizabeth; Robinson, Alexander; Sippel, Sebastian
Pubblicato in: Nature Reviews Earth & Environment, Numero 6 (7), 2025, ISSN 2662-138X
Editore: Springer Nature
DOI: 10.1038/S43017-025-00681-Y

Tuning the ICON-A 2.6.4 climate model with machine-learning-based emulators and history matching

Autori: P. Bonnet; L. Pastori; M. Schwabe; M. Giorgetta; F. Iglesias-Suarez; V. Eyring; V. Eyring
Pubblicato in: Geoscientific Model Development, Numero 18 (12), 2025, ISSN 1991-9603
Editore: EGU
DOI: 10.5194/GMD-18-3681-2025

Online calibration of deep learning sub-models for hybrid numerical modeling systems

Autori: Ouala, Said; Chapron, Bertrand; Collard, Fabrice; Gaultier, Lucile; Fablet, Ronan
Pubblicato in: Communications Physics, Numero 7, 2024, ISSN 2399-3650
Editore: Springer Nature
DOI: 10.48550/ARXIV.2311.10665

Advanced climate model evaluation with ESMValTool v2.11.0 using parallel, out-of-core, and distributed computing.

Autori: Schlund, M., Andela, B., Benke, J., Comer, R., Hassler, B., Hogan, E., Kalverla, P., Lauer, A., Little, B., Loosveldt Tomas, S., Nattino, F., Peglar, P., Predoi, V., Smeets, S., Worsley, S., Yeo, M., & Zimmermann, K.
Pubblicato in: Geoscientific Model Development, Numero 18, 2025, ISSN 1991-9603
Editore: EGU
DOI: 10.5194/GMD-2024-236

Online Learning of Entrainment Closures in a Hybrid Machine Learning Parameterization

Autori: Costa Christopoulos, Ignacio Lopez‐Gomez, Tom Beucler, Yair Cohen, Charles Kawczynski, Oliver R. A. Dunbar, Tapio Schneider
Pubblicato in: Journal of Advances in Modeling Earth Systems, Numero 16, 2025, ISSN 1942-2466
Editore: American Geophysical Union (AGU)
DOI: 10.1029/2024MS004485

Examining the Fidelity of Leith Subgrid Closures for Parameterizing Mesoscale Eddies in Idealized and Global (NEMO) Ocean Models

Autori: T. Wilder, T. Kuhlbrodt
Pubblicato in: Journal of Advances in Modeling Earth Systems, Numero 17, 2025, ISSN 1942-2466
Editore: American Geophysical Union (AGU)
DOI: 10.1029/2025MS004950

Estimating Information Theoretic Measures via Multidimensional Gaussianization

Autori: Valero Laparra, Juan Emmanuel Johnson, Gustau Camps-Valls, Raúl Santos-Rodríguez, Jesús Malo
Pubblicato in: IEEE Transactions on Pattern Analysis and Machine Intelligence, Numero 47, 2025, ISSN 0162-8828
Editore: Institute of Electrical and Electronics Engineers (IEEE)
DOI: 10.1109/TPAMI.2024.3495827

Calibration and uncertainty quantification for deep learning-based drought detection

Autori: Mengxue Zhang, Miguel-Ángel Fernández-Torres, Kai-Hendrik Cohrs, Gustau Camps-Valls
Pubblicato in: International Journal of Applied Earth Observation and Geoinformation, Numero 140, 2025, ISSN 1569-8432
Editore: Elsevier BV
DOI: 10.1016/J.JAG.2025.104563

Navigating the Noise: Bringing Clarity to ML Parameterization Design With O $\boldsymbol{\mathcal{O}}$(100) Ensembles

Autori: Jerry Lin, Sungduk Yu, Liran Peng, Tom Beucler, Eliot Wong‐Toi, Zeyuan Hu, Pierre Gentine, Margarita Geleta, Mike Pritchard
Pubblicato in: Journal of Advances in Modeling Earth Systems, Numero 17, 2025, ISSN 1942-2466
Editore: American Geophysical Union (AGU)
DOI: 10.1029/2024MS004551

Flash drought impacts on global ecosystems amplified by extreme heat

Autori: Lei Gu; Dominik L. Schumacher; Erich M. Fischer; Louise J. Slater; Jiabo Yin; Sebastian Sippel; Jie Chen; Pan Liu; Reto Knutti
Pubblicato in: Nature Geoscience, Numero 18, 2025, ISSN 1752-0908
Editore: Springer Nature
DOI: 10.3929/ETHZ-B-000739383

Neural Variational Data Assimilation with Uncertainty Quantification Using SPDE Priors

Autori: Beauchamp, Maxime; Fablet, Ronan; Benaichouche, Simon; Tandeo, Pierre; Desassis, Nicolas; Chapron, Bertrand
Pubblicato in: Artificial Intelligence for the Earth Systems, Numero 4 (3), 2025, ISSN 2769-7525
Editore: American Meteorological Society
DOI: 10.48550/ARXIV.2402.01855

Thesis and dissertations (1)

Classifying and Tracking of Mesoscale Cloud Patterns from Satellite Images using Machine Learning

Autori: Granberg, A., & Lundholm, V.
Pubblicato in: 2025
Editore: DiVA, Linköping University

Conference proceedings (1)

Towards Physically Consistent Deep Learning For Climate Model Parameterizations

Autori: Birgit Kühbacher, Fernando Iglesias-Suarez, Niki Kilbertus, Veronika Eyring
Pubblicato in: 2024 International Conference on Machine Learning and Applications (ICMLA), 2025
Editore: IEEE
DOI: 10.1109/ICMLA61862.2024.00044