Understanding and Modelling the Earth System with Machine Learning

CORDIS oferuje możliwość skorzystania z odnośników do publicznie dostępnych publikacji i rezultatów projektów realizowanych w ramach programów ramowych HORYZONT.

Odnośniki do rezultatów i publikacji związanych z poszczególnymi projektami 7PR, a także odnośniki do niektórych konkretnych kategorii wyników, takich jak zbiory danych i oprogramowanie, są dynamicznie pobierane z systemu OpenAIRE .

Publikacje

Towards Causal Discovery for Earth System Sciences

Autorzy: Emiliano Diaz
Opublikowane w: 2023
Wydawca: Universitat de València

Consistent long-term observational datasets of soil moisture and vegetation reveal trends and variability in soil moisture, improve carbon cycle models, and constrain climate models.

Autorzy: Olya Skulovich
Opublikowane w: 2024
Wydawca: Columbia University

Causal discovery of Atlantic-Pacific interactions in observations and CMIP6 models

Autorzy: Karmouche, Soufiane
Opublikowane w: 2024
Wydawca: University of Bremen
DOI: 10.26092/elib/2833

Understanding and Modelling Convection with Machine Learning

Autorzy: Behrens, Gunnar
Opublikowane w: 2024
Wydawca: University of Bremen
DOI: 10.26092/elib/3050

A comparison of drought indices in CMIP6 climate projections

Autorzy: Lukas Ruhe
Opublikowane w: Master Thesis, 2022
Wydawca: University of Bremen, Germany

Detecting Activity of Tropical Cyclones with the Unsupervised Maximally Divergent Interval Algorithm

Autorzy: Simon Zitzmann
Opublikowane w: Master Thesis, 2020
Wydawca: LMU Munich

Data-driven cloud cover parameterizations for the ICON earth system model using deep learning and symbolic regression

Autorzy: Grundner, Arthur
Opublikowane w: Dissertation, 2024
Wydawca: University of Bremen
DOI: 10.26092/elib/2821

Machine-learning based observational cloud products for process-oriented climate model evaluation

Autorzy: Kaps, Arndt
Opublikowane w: 2024
Wydawca: University of Bremen
DOI: 10.26092/elib/2997

Understanding Land-Atmosphere Interactions Across Multiple Scales

Autorzy: Yu Huang
Opublikowane w: 2024
Wydawca: Columbia university

Estimating Information in Earth System Data with Machine Learning

Autorzy: Emmanuel J. Johnson
Opublikowane w: 2021
Wydawca: University of Valencia

Constraining uncertainties in multi-model projections of the future climate with observations

Autorzy: Manuel Schlund
Opublikowane w: Dissertation, 2021
Wydawca: University of Bremen
DOI: 10.26092/elib/941

Carbon system state determines warming potential of emissions

Autorzy: Alexander J. Winkler, Ranga Myneni, Christian Reimers, Markus Reichstein, Victor Brovkin
Opublikowane w: PLOS ONE, Numer 19, 2024, Strona(/y) e0306128, ISSN 1932-6203
Wydawca: Public Library of Science
DOI: 10.1371/journal.pone.0306128

Detecting extreme temperature events using Gaussian mixture models

Autorzy: Paçal, A., Hassler, B., Weigel, K., Kurnaz, M. L., Wehner, M. F., Eyring, V.
Opublikowane w: Journal of Geophysical Research: Atmospheres, Numer Volume 128; Numer 18; 22.09.2023, 2023, Strona(/y) e2023JD038906, ISSN 2169-897X
Wydawca: ADVANCING EARTH AND SPACE SCIENCES
DOI: 10.1029/2023jd038906

Regulation of the global carbon and water cycles through vegetation structural and physiological dynamics

Autorzy: Wantong Li, Gregory Duveiller, Sebastian Wieneke, Matthias Forkel, Pierre Gentine, Markus Reichstein, Shuli Niu, Mirco Migliavacca, Rene Orth
Opublikowane w: Environmental Research Letters, Numer 19, 2024, Strona(/y) 073008, ISSN 1748-9326
Wydawca: Institute of Physics Publishing
DOI: 10.1088/1748-9326/ad5858

Soil dryness matters to ecosystem photosynthesis when and where it does

Autorzy: Jiangong Liu, Qiren Wang, Weiwei Zhan, Xu Lian, Pierre Gentine
Opublikowane w: Nature water submitted, 2024, ISSN 1758-678X
Wydawca: Nature Publishing Group
DOI: 10.21203/rs.3.rs-5147541/v1

Deep Learning and Earth Observation to Support the Sustainable Development Goals

Autorzy: Persello, C., Wegner, J.D., Hänsch, R., Tuia, D., Ghamisi, P., Koeva, M., Camps-Valls, G.
Opublikowane w: IEEE Geoscience and Remote Sensing Magazine, 2022, Strona(/y) 2-30, ISSN 2168-6831
Wydawca: IEEE Geosciene and Remote Sensing Society
DOI: 10.1109/mgrs.2021.3136100

Characterizing clouds with the CCClim dataset, a machine learning cloud class climatology

Autorzy: Arndt Kaps, Axel Lauer, Rémi Kazeroni, Martin Stengel, Veronika Eyring
Opublikowane w: Earth System Science Data, Numer 16, 2024, Strona(/y) 3001-3016, ISSN 1866-3516
Wydawca: Copernicus GmbH
DOI: 10.5194/essd-16-3001-2024

Reliance on fossil fuels increases during extreme temperature events in the continental United States

Autorzy: Wenli Zhao, Biqing Zhu, Steven J. Davis, Philippe Ciais, Chaopeng Hong, Zhu Liu, Pierre Gentine
Opublikowane w: Communications Earth & Environment, Numer 4, 2023, ISSN 2662-4435
Wydawca: NA
DOI: 10.1038/s43247-023-01147-z

Structural learning of simple staged trees

Autorzy: Manuele Leonelli, Gherardo Varando
Opublikowane w: Data Mining and Knowledge Discovery, Numer 38, 2024, Strona(/y) 1520-1544, ISSN 1384-5810
Wydawca: Kluwer Academic Publishers
DOI: 10.1007/s10618-024-01007-0

Evaluation of native Earth system model output with ESMValTool v2.6.0

Autorzy: Manuel Schlund, Birgit Hassler, Axel Lauer, Bouwe Andela, Patrick Jöckel, Rémi Kazeroni, Saskia Loosveldt Tomas, Brian Medeiros, Valeriu Predoi, Stéphane Sénési, Jérôme Servonnat, Tobias Stacke, Javier Vegas-Regidor, Klaus Zimmermann, Veronika Eyring
Opublikowane w: Geoscientific Model Development, Numer 16, 2023, Strona(/y) 315-333, ISSN 1991-9603
Wydawca: Copernicus GmbH
DOI: 10.5194/gmd-16-315-2023

Pushing the frontiers in climate modelling and analysis with machine learning

Autorzy: Veronika Eyring, William D. Collins, Pierre Gentine, Elizabeth A. Barnes, Marcelo Barreiro, Tom Beucler, Marc Bocquet, Christopher S. Bretherton, Hannah M. Christensen, Katherine Dagon, David John Gagne, David Hall, Dorit Hammerling, Stephan Hoyer, Fernando Iglesias-Suarez, Ignacio Lopez-Gomez, Marie C. McGraw, Gerald A. Meehl, Maria J. Molina, Claire Monteleoni, Juliane Mueller, Michael S. Pritch
Opublikowane w: Nature Climate Change, Numer 14, 2024, Strona(/y) 916-928, ISSN 1758-678X
Wydawca: Nature Publishing Group
DOI: 10.1038/s41558-024-02095-y

Interpretable Multiscale Machine Learning‐Based Parameterizations of Convection for ICON

Autorzy: Helge Heuer, Mierk Schwabe, Pierre Gentine, Marco A. Giorgetta, Veronika Eyring
Opublikowane w: Journal of Advances in Modeling Earth Systems, Numer 16, 2024, ISSN 1942-2466
Wydawca: American Geophysical Union
DOI: 10.1029/2024ms004398

Monitoring and benchmarking Earth system model simulations with ESMValTool v2.12.0

Autorzy: Axel Lauer, Lisa Bock, Birgit Hassler, Patrick Jöckel, Lukas Ruhe, Manuel Schlund
Opublikowane w: Geoscientific Model Development, Numer 18, 2025, Strona(/y) 1169-1188, ISSN 1991-9603
Wydawca: Copernicus Publications
DOI: 10.5194/gmd-18-1169-2025

Inferring causal relations from observational long-term carbon and water fluxes records

Autorzy: Díaz, E. Adsura, J.E., Martínez, Á.M, Piles, M., Camps-Valls, G
Opublikowane w: Scientific Reports, Numer 12, 2022, Strona(/y) 1610, ISSN 2045-2322
Wydawca: Nature Publishing Group
DOI: 10.1038/s41598-022-05377-7

Constraining uncertainty in projected gross primary production with machine learning

Autorzy: M. Schlund, V. Eyring, G.-Camps-Valls, P. Friedlingstein, P. Gentine, & M. Reichstein
Opublikowane w: American Geophysical Union / Wiley Periodicals, 2020, ISSN 2576-604X
Wydawca: American Geophysical Union / Wiley Periodicals
DOI: 10.1029/2019jg005619

Evidence for widespread thermal acclimation of canopy photosynthesis

Autorzy: Jiangong Liu, Youngryel Ryu, Xiangzhong Luo, Benjamin Dechant, Benjamin Stocker, Trevor Keenan, Pierre Gentine, Xing Li, Bolun Li, Sandy Harrison, Iain Prentice
Opublikowane w: Nature Ecology - accepted, 2024, ISSN 1758-678X
Wydawca: Nature Publishing Group
DOI: 10.21203/rs.3.rs-4013319/v1

A hybrid generative adversarial network for weakly-supervised cloud detection in multispectral images

Autorzy: Jun Li, Zhaocong Wu, Qinghong Sheng, Bo Wang, Zhongwen Hu, Shaobo Zheng, Gustau Camps-Valls, Matthieu Molinier
Opublikowane w: Remote Sensing of Environment, Numer 280, 2022, Strona(/y) 113197, ISSN 0034-4257
Wydawca: Elsevier BV
DOI: 10.1016/j.rse.2022.113197

MetaFlux: Meta-learning global carbon fluxes from sparse spatiotemporal observations

Autorzy: Juan Nathaniel, Jiangong Liu, Pierre Gentine
Opublikowane w: Scientific Data, Numer 10, 2023, ISSN 2052-4463
Wydawca: NA
DOI: 10.1038/s41597-023-02349-y

Spatiotemporal upscaling of sparse air-sea pCO2 data via physics-informed transfer learning

Autorzy: Siyeon Kim, Juan Nathaniel, Zhewen Hou, Tian Zheng, Pierre Gentine
Opublikowane w: Scientific Data, Numer 11, 2024, ISSN 2052-4463
Wydawca: NA
DOI: 10.1038/s41597-024-03959-w

Hybrid modeling: Fusion of a deep approach and physics-based model for global hydrological modeling

Autorzy: Kraft, B., Jung, M., Körner, M., & Reichstein, M.
Opublikowane w: The International Archives of Photogrammetry, Remote Sensing and Spatial Information Science, Numer 21949034, 2020, ISSN 2194-9034
Wydawca: Copernicus Publications
DOI: 10.5194/isprs-archives-xliii-b2-2020-1537-2020

Satellite Analyses Unravel the Multi-Decadal Impact of Dam Management on Tropical Floodplain Vegetation

Autorzy: Luca Salerno, Álvaro Moreno-Martínez, Emma Izquierdo-Verdiguier, Nicholas Clinton, Annunziato Siviglia, and Carlo Camporeale
Opublikowane w: Frontiers in Environmental Science, Numer 2296665X, 2022, ISSN 2296-665X
Wydawca: Frontiers
DOI: 10.3389/fenvs.2022.871530

Pairwise causal discovery with support measure machines

Autorzy: Gherardo Varando, Salvador Catsis, Emiliano Diaz, Gustau Camps-Valls
Opublikowane w: Applied Soft Computing, Numer 150, 2024, Strona(/y) 111030, ISSN 1568-4946
Wydawca: Elsevier BV
DOI: 10.1016/j.asoc.2023.111030

Deep Learning With Noisy Labels for Spatiotemporal Drought Detection

Autorzy: Jordi Cortés-Andrés, Miguel-Ángel Fernández-Torres, Gustau Camps-Valls
Opublikowane w: IEEE Transactions on Geoscience and Remote Sensing, Numer 62, 2024, Strona(/y) 1-13, ISSN 0196-2892
Wydawca: Institute of Electrical and Electronics Engineers
DOI: 10.1109/tgrs.2024.3504340

Learning latent functions for causal discovery

Autorzy: E Diaz. JE Johnson, G Varando, G Camps-Valls
Opublikowane w: Machine Learning: Science and Technology, 2023, ISSN 2632-2153
Wydawca: IOP Science
DOI: 10.1088/2632-2153/ace151

Climate-invariant machine learning

Autorzy: Tom Beucler, Pierre Gentine, Janni Yuval, Ankitesh Gupta, Liran Peng, Jerry Lin, Sungduk Yu, Stephan Rasp, Fiaz Ahmed, Paul A. O’Gorman, J. David Neelin, Nicholas J. Lutsko, Michael Pritchard
Opublikowane w: Science Advances, Numer 10, 2024, ISSN 2375-2548
Wydawca: NA
DOI: 10.1126/sciadv.adj7250

Learning Atmospheric Boundary Layer Turbulence

Autorzy: Sara Shamekh, Pierre Gentine
Opublikowane w: JAMES in review, 2023, ISSN 1758-678X
Wydawca: Nature Publishing Group
DOI: 10.22541/essoar.168748456.60017486/v1

A spatiotemporal stochastic climate model for benchmarking causal discovery methods for teleconnections

Autorzy: Tibau, X., Reimers, C., Gerhardus, A., Denzler, J., Eyring, V., Runge, J.
Opublikowane w: Environmental Data Science, Numer 26344602, 2022, ISSN 2634-4602
Wydawca: Cambridge University Press
DOI: 10.1017/eds.2022.11

Generative networks for spatio-temporal gap filling of Sentinel-2 reflectances

Autorzy: Maria Gonzalez-Calabuig, Miguel-Ángel Fernández-Torres, Gustau Camps-Valls
Opublikowane w: ISPRS Journal of Photogrammetry and Remote Sensing, Numer 220, 2025, Strona(/y) 637-648, ISSN 0924-2716
Wydawca: Elsevier BV
DOI: 10.1016/j.isprsjprs.2025.01.016

Causal hybrid modeling with double machine learning—applications in carbon flux modeling

Autorzy: Kai-Hendrik Cohrs, Gherardo Varando, Nuno Carvalhais, Markus Reichstein, Gustau Camps-Valls
Opublikowane w: Machine Learning: Science and Technology, Numer 5, 2024, Strona(/y) 035021, ISSN 2632-2153
Wydawca: IOP Science
DOI: 10.1088/2632-2153/ad5a60

X-BASE: the first terrestrial carbon and water flux products from an extended data-driven scaling framework, FLUXCOM-X

Autorzy: Jacob A. Nelson, Sophia Walther, Fabian Gans, Basil Kraft, Ulrich Weber, Kimberly Novick, Nina Buchmann, Mirco Migliavacca, Georg Wohlfahrt, Ladislav Šigut, Andreas Ibrom, Dario Papale, Mathias Göckede, Gregory Duveiller, Alexander Knohl, Lukas Hörtnagl, Russell L. Scott, Jiří Dušek, Weijie Zhang, Zayd Mahmoud Hamdi, Markus Reichstein, Sergio Aranda-Barranco, Jonas Ardö, Maarten Op de Beeck
Opublikowane w: Biogeosciences, Numer 21, 2025, Strona(/y) 5079-5115, ISSN 1726-4189
Wydawca: Biogeosciences
DOI: 10.5194/bg-21-5079-2024

Causally‐Informed Deep Learning to Improve Climate Models and Projections

Autorzy: Fernando Iglesias‐Suarez, Pierre Gentine, Breixo Solino‐Fernandez, Tom Beucler, Michael Pritchard, Jakob Runge, Veronika Eyring
Opublikowane w: Journal of Geophysical Research: Atmospheres, Numer 129, 2024, ISSN 2169-897X
Wydawca: AGU
DOI: 10.1029/2023jd039202

Quantifying uncertainty in high resolution biophysical variable retrieval maps

Autorzy: Laura Martínez-Ferrer, Álvaro Moreno-Martínez, Manuel Campos-Taberner, Francisco Javier García-Haro, Jordi Munoz-Marí, Steven W. Running, John Kimball, Nicholas Clinton, Gustau Camps-Valls
Opublikowane w: Remote Sensing of Environment (RSE), 2022, ISSN 0034-4257
Wydawca: Elsevier BV

Assessing and improving the transferability of current global spatial prediction models.

Autorzy: Ludwig, Marvin and Moreno-Martinez, Alvaro and Hölzel, Norbert and Pebesma, Edzer and Meyer, Hanna
Opublikowane w: Global Ecology and Biogeography, 2023, ISSN 1466-822X
Wydawca: Blackwell Publishing Inc.
DOI: 10.1111/geb.13635

Role of locality, fidelity and symmetry regularization in learning explainable representations

Autorzy: Michele Ronco, Gustau Camps-Valls
Opublikowane w: Neurocomputing, Numer 562, 2023, Strona(/y) 126884, ISSN 0925-2312
Wydawca: Elsevier BV
DOI: 10.1016/j.neucom.2023.126884

Reflections and projections on a decade of climate science

Autorzy: V. Eyring, V. Mishra, G. Griffith, L. Chen, T. F. Keenan, M. R. Turetsky, S. Brown, F. Jotzo, F. C. Moore, and S. van der Linden
Opublikowane w: Nature Publishing Group / Springer Nature, 2021, ISSN 1758-6798
Wydawca: Nature Publishing Group / Springer Nature
DOI: 10.1038/s41558-021-01020-x

Causal inference for time series

Autorzy: J., Runge, A., Gerhardus, G., Varando, V., Eyring, G., Camps-Valls
Opublikowane w: nature reviews earth & environment, Numer Volume 4; 07.2023, 2023, Strona(/y) 487-505, ISSN 2662-138X
Wydawca: Springer Nature
DOI: 10.1038/s43017-023-00431-y

Within-season crop monitoring at continental scale utilizing new gap-filled Landsat temporal series

Autorzy: C. Rajadel-Lambistos, E. Izquierdo-Verdiguier, A. Moreno-Martínez, M. P. Maneta, S. Begueria, J. S. Kimball, N. Clinton, C. Atzberger, G. Camps-Valls, S.W. Running
Opublikowane w: International Journal of Digital Earth, Numer 17, 2025, ISSN 1753-8947
Wydawca: Taylor & Francis
DOI: 10.1080/17538947.2024.2359577

Collaboration between artificial intelligence and Earth science communities for mutual benefit

Autorzy: Min Chen, Zhen Qian, Niklas Boers, Felix Creutzig, Gustau Camps-Valls, Klaus Hubacek, Christophe Claramunt, John P. Wilson, Stefano Nativi, Anthony J. Jakeman, R. Dietmar Müller, Michael Batty, Chenghu Zhou, Fahu Chen, Qiao Wang, Fan Zhang, C. Michael Barton, Josef Strobl, Michael Meadows, Carlo Ratti, Philipp Hess, Qingsong Xu, Zhixin Zhang, Qiushi Gu, A-Xing Zhu, Hui Lin, Linwang Yuan, Guonian
Opublikowane w: Nature Geoscience, Numer 17, 2024, Strona(/y) 949-952, ISSN 1752-0894
Wydawca: Nature Publishing Group
DOI: 10.1038/s41561-024-01550-x

Converging Findings of Climate Models and Satellite Observations on the Positive Impact of European Forests on Cloud Cover

Autorzy: Luca Caporaso, Gregory Duveiller, Graziano Giuliani, Filippo Giorgi, Martin Stengel, Emanuele Massaro, Matteo Piccardo, Alessandro Cescatti
Opublikowane w: Journal of Geophysical Research: Atmospheres, Numer 129, 2024, ISSN 2169-897X
Wydawca: Wiley Online Library
DOI: 10.1029/2023jd039235

Changing effects of external forcing on Atlantic–Pacific interactions

Autorzy: Soufiane Karmouche, Evgenia Galytska, Gerald A. Meehl, Jakob Runge, Katja Weigel, Veronika Eyring
Opublikowane w: Earth System Dynamics, Numer 15, 2024, Strona(/y) 689-715, ISSN 2190-4987
Wydawca: Copernicus GmbH
DOI: 10.5194/esd-15-689-2024

Physics-aware nonparametric regression models for Earth data analysis

Autorzy: Jordi Cortés-Andrés; Gustau Camps-Valls; Sebastian Sippel; Enikő Székely; Dino Sejdinovic; Emiliano Diaz; Adrián Pérez-Suay; Zhu Li; Miguel Mahecha; Markus Reichstein
Opublikowane w: Environmental Research Letters, 17 (5), Numer 17489326, 2022, ISSN 1748-9326
Wydawca: Institute of Physics Publishing
DOI: 10.3929/ethz-b-000546957

Identifying compound weather drivers of forest biomass loss with generative deep learning

Autorzy: Mohit Anand, Friedrich J. Bohn, Gustau Camps-Valls, Rico Fischer, Andreas Huth, Lily-belle Sweet, Jakob Zscheischler
Opublikowane w: Environmental Data Science, Numer 3, 2024, ISSN 2634-4602
Wydawca: Cambridge Press
DOI: 10.1017/eds.2024.2

Quantifying uncertainty in high resolution biophysical variable retrieval with machine learning

Autorzy: Laura Martínez-Ferrer, Álvaro Moreno-Martínez, Manuel Campos-Taberner, Francisco Javier García-Haro, Jordi Muñoz-Marí, Steven W. Running, John Kimball, Nicholas Clinton, Gustau Camps-Valls
Opublikowane w: Remote Sensing of Environment, Numer 280, 2022, Strona(/y) 113199, ISSN 0034-4257
Wydawca: Elsevier BV
DOI: 10.1016/j.rse.2022.113199

Contrasting drought legacy effects on gross primary productivity in a mixed versus pure beech forest

Autorzy: Yu, X. and Orth, R. and Reichstein, M. and Bahn, M. and Klosterhalfen, A. and Knohl, A. and Koebsch, F. and Migliavacca, M. and Mund, M. and Nelson, J. A. and Stocker, B. D. and Walther, S. and Bastos, A.
Opublikowane w: Biogeosciences, Numer 17264189, 2022, ISSN 1726-4189
Wydawca: Copernicus Publications
DOI: 10.5194/bg-19-4315-2022

ClimateBench v1.0: A Benchmark for Data-Driven Climate Projections

Autorzy: Watson-Parris, D., Rao, Y., Olivié, D., Seland, Ø., Nowack, P., Camps-Valls, G., Stier, P., Bouabid, S., Dewey, M., Fons, E., Gonzalez, J., Harder, P., Jeggle, K., Lenhardt, J., Manshausen, P., Novitasari, M., Ricard, L., Roesch, C.
Opublikowane w: Journal of Advances in Modeling Earth Systems, Numer 14 (10) :e2021MS002954, 2022, ISSN 1942-2466
Wydawca: American Geophysical Union

Biogeophysical Radiative Forcings of Large‐Scale Afforestation in Europe Are Highly Localized and Dominated by Surface Albedo Change

Autorzy: Ryan M. Bright, Luca Caporaso, Gregory Duveiller, Matteo Piccardo, Alessandro Cescatti
Opublikowane w: Geophysical Research Letters, Numer 52, 2025, ISSN 0094-8276
Wydawca: American Geophysical Union
DOI: 10.1029/2024gl112739

ClimateBench v1.0: A Benchmark for Data‐Driven Climate Projections

Autorzy: D. Watson‐Parris, Y. Rao, D. Olivié, Ø. Seland, P. Nowack, G. Camps‐Valls, P. Stier, S. Bouabid, M. Dewey, E. Fons, J. Gonzalez, P. Harder, K. Jeggle, J. Lenhardt, P. Manshausen, M. Novitasari, L. Ricard, C. Roesch
Opublikowane w: Journal of Advances in Modeling Earth Systems, Numer 14, 2023, ISSN 1942-2466
Wydawca: American Geophysical Union
DOI: 10.1029/2021ms002954

The AIDE Toolbox: Artificial intelligence for disentangling extreme events [Software and Data Sets]

Autorzy: Maria Gonzalez-Calabuig, Jordi Cortés-Andrés, Tristan Keith Ellis Williams, Mengxue Zhang, Oscar Jose Pellicer-Valero, Miguel-Ángel Fernández-Torres, Gustau Camps-Valls
Opublikowane w: IEEE Geoscience and Remote Sensing Magazine, Numer 12, 2024, Strona(/y) 113-118, ISSN 2168-6831
Wydawca: IEEE Geosciene and Remote Sensing Society
DOI: 10.1109/mgrs.2024.3382544

Discovering causal relations and equations from data

Autorzy: Gustau Camps-Valls, Andreas Gerhardus, Urmi Ninad, Gherardo Varando, Georg Martius, Emili Balaguer-Ballester, Ricardo Vinuesa, Emiliano Diaz, Laure Zanna, Jakob Runge
Opublikowane w: Physics Reports, Numer 1044, 2024, Strona(/y) 1-68, ISSN 0370-1573
Wydawca: Elsevier BV
DOI: 10.1016/j.physrep.2023.10.005

Soil moisture–atmosphere feedback dominates land carbon uptake variability

Autorzy: Humphrey, V., Berg, A., Ciais, P., Gentine, P., Jung, M., Reichstein, M., Seneviratne, S.I. and Frankenberg, C.
Opublikowane w: Nature, Numer 14764687, 2021, ISSN 1476-4687
Wydawca: Springer Nature
DOI: 10.1038/s41586-021-03325-5

AI-empowered next-generation multiscale climate modelling for mitigation and adaptation

Autorzy: Veronika Eyring, Pierre Gentine, Gustau Camps-Valls, David M. Lawrence, Markus Reichstein
Opublikowane w: Nature Geoscience, Numer 17, 2024, Strona(/y) 963-971, ISSN 1752-0894
Wydawca: Nature Publishing Group
DOI: 10.1038/s41561-024-01527-w

Groundwater rivals aridity in determining global photosynthesis

Autorzy: Francesco Giardina, Sonia I. Seneviratne, Jiangong Liu, Benjamin D. Stocker, Pierre Gentine
Opublikowane w: Nature Geo submitted, 2024, ISSN 1758-678X
Wydawca: Nature Publishing Group
DOI: 10.21203/rs.3.rs-3793488/v1

Data‐Driven Equation Discovery of a Cloud Cover Parameterization

Autorzy: Arthur Grundner, Tom Beucler, Pierre Gentine, Veronika Eyring
Opublikowane w: Journal of Advances in Modeling Earth Systems, Numer 16, 2024, ISSN 1942-2466
Wydawca: American Geophysical Union
DOI: 10.1029/2023ms003763

Analyzing climate scenarios using dynamic mode decomposition with control

Autorzy: Nathan Mankovich, Shahine Bouabid, Peer Nowack, Deborah Bassotto, Gustau Camps-Valls
Opublikowane w: Environmental Data Science, Numer 4, 2025, ISSN 2634-4602
Wydawca: Cambridge Press
DOI: 10.1017/eds.2025.8

Causal discovery reveals complex patterns of drought-induced displacement

Autorzy: Jose María Tárraga, Eva Sevillano-Marco, Jordi Muñoz-Marí, María Piles, Vasileios Sitokonstantinou, Michele Ronco, María Teresa Miranda, Jordi Cerdà, Gustau Camps-Valls
Opublikowane w: iScience, Numer 27, 2025, Strona(/y) 110628, ISSN 2589-0042
Wydawca: Elsevier
DOI: 10.1016/j.isci.2024.110628

Invertible Neural Networks for Probabilistic Aerosol Optical Depth Retrieval

Autorzy: Paolo Pelucchi, Jorge Vicent Servera, Philip Stier, Gustau Camps-Valls
Opublikowane w: IEEE Transactions on Geoscience and Remote Sensing, Numer 63, 2025, Strona(/y) 1-13, ISSN 0196-2892
Wydawca: Institute of Electrical and Electronics Engineers
DOI: 10.1109/tgrs.2025.3540173

Implicit learning of convective organization explains precipitation stochasticity

Autorzy: Sara Shamekh, Kara D. Lamb, Yu Huang, Pierre Gentine
Opublikowane w: Proceedings of the National Academy of Sciences, Numer 120, 2023, ISSN 0027-8424
Wydawca: National Academy of Sciences
DOI: 10.1073/pnas.2216158120

Satellite remote sensing reveals the footprint of biodiversity on multiple ecosystem functions across the NEON eddy covariance network

Autorzy: Ulisse Gomarasca, Gregory Duveiller, Javier Pacheco-Labrador, Guido Ceccherini, Alessandro Cescatti, Marco Girardello, Jacob A Nelson, Markus Reichstein, Christian Wirth, Mirco Migliavacca
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Estimating the CO<sub>2</sub> Fertilization Effect on Extratropical Forest Productivity From Flux‐Tower Observations

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Towards a Collective Agenda on AI for Earth Science Data Analysis

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Gaussianizing the Earth: Multidimensional Information Measures for Earth Data Analysis

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Exploring Optimal Complexity for Water Stress Representation in Terrestrial Carbon Models: A Hybrid-Machine Learning Model Approach

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Hybrid modeling of evapotranspiration: inferring stomatal and aerodynamic resistances using combined physics-based and machine learning

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Retrieval of Physical Parameters With Deep Structured Kernel Regression

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Emergence of the physiological effects of elevated CO2 on land–atmosphere exchange of carbon and water

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Constraining biospheric carbon dioxide fluxes by combined top-down and bottom-up approaches

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Regime-oriented causal model evaluation of Atlantic-Pacific teleconnections in CMIP6

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Non-Linear Dimensionality Reduction With a Variational Encoder Decoder to Understand Convective Processes in Climate Models

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Evaluating causal Arctic-midlatitude teleconnections in CMIP6

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Enhanced global carbon cycle sensitivity to tropical temperature linked to internal climate variability

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DeepPhenoMem V1.0: deep learning modelling of canopy greenness dynamics accounting for multi-variate meteorological memory effects on vegetation phenology

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Multioutput Feature Selection for Emulation and Sensitivity Analysis

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Estimating Information Theoretic Measures via Multidimensional Gaussianization

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Large language models for causal hypothesis generation in science

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Differentiable Land Model Retrieves Global Environmental Controls of Ecological Parameters

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Inference over radiative transfer models using variational and expectation maximization methods

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Integration of a Deep‐Learning‐Based Fire Model Into a Global Land Surface Model

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A Data-Driven Approach to Partitioning Net Ecosystem Exchange using a Deep State Space Model

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Bringing it all together: science priorities for improved understanding of Earth system change and to support international climate policy

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Leaf-level coordination principles propagate to the ecosystem scale.

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Domain knowledge-driven variational recurrent networks for drought monitoring

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Getting the leaves right matters for estimating temperature extremes

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Emulation of Forward Modeled Top-of-Atmosphere MODIS-Based Spectral Channels Using Machine Learning

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Soil and vegetation water content identify the main terrestrial ecosystem changes

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Artificial intelligence for modeling and understanding extreme weather and climate events

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Multifidelity Gaussian Process Emulation for Atmospheric Radiative Transfer Models

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The R Package stagedtrees for Structural Learning of Stratified Staged Trees

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A Scalable Unsupervised Feature Selection With Orthogonal Graph Representation for Hyperspectral Images

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Machine learning-based parametrizations for the ICON model

Autorzy: Fernando Iglesias-Suarez, Arthur Grundner, Gunnar Behrens, Tom Beucler, Pierre Gentine, Marco Giorgetta, Michael Pritchard, and Veronika Eyring
Opublikowane w: AGU (American Geophysical Union) Fall Meeting 2021, 2021
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Simulating Atmospheric Processes in ESMs and Quantifying Uncertainties with Deep Learning Multi-Member and Stochastic Parameterizations

Autorzy: Behrens, Gunnar und Beucler, Tom und Iglesias-Suarez, Fernando und Yu, Sungduk und Gentine, Pierre und Pritchard, Michael und Schwabe, Mierk und Eyring, Veronika
Opublikowane w: Oxford Workshop on Model Uncertainty, 2024
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Machine learning-based parametrizations for the ICON model

Autorzy: Arthur Grundner, Fernando Iglesias-Suarez, Veronika Eyring, Pierre Gentine, Tom Beucler, and Marco Giorgetta
Opublikowane w: 3rd NOAA Workshop on Leveraging AI in Environmental Sciences, 2021
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Non-Linear Dimensionality Reduction With a Variational Encoder Decoder (VED) to Understand Convective Processes in Climate Models

Autorzy: Behrens, Gunnar und Beucler, Tom und Gentine, Pierre und Iglesias-Suarez, Fernando und Pritchard, Michael und Eyring, Veronika
Opublikowane w: American Geophysical Union Fall Meeting 2022, 2022
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Understanding Climate Impacts on Vegetation with Gaussian Processes in Granger Causality

Autorzy: M Morata, D Bueso, M Piles, G Camps-Valls
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Carbon fluxes estimation with aleatoric and epistemic uncertainties at high spatial resolution over large areas

Autorzy: Laura Martínez-Ferrer, Álvaro Moreno-Martínez, John S. Kimball, Steven W. Running, Nicholas Clinton, and Gustau Camps-Valls
Opublikowane w: EGU General Assembly 2022, 2022
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Causally-informed neural nets to improve convection in climate models

Autorzy: F. Iglesias-Suarez, V. Eyring, P. Gentine, T. Beucler, M. Pritchard, J. Runge, and B. Solino-Fernandez
Opublikowane w: 2nd ELLIS workshop on Machine Learning for Earth and Climate sciences, 2022
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Large Scale Masked Autoencoding for Reducing Label Requirements on SAR Data

Autorzy: Allen, M., Dorr, F., Gallego-Mejia, J.A., Martínez-Ferrer, L., Jungbluth, A., Kalaitzis, F., Ramos-Pollán, R.
Opublikowane w: NeurIPS 2023 - Workshop on Tackling Climate Change with Machine Learning., 2023
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On the Generalization of Agricultural Drought Classification from Climate Data

Autorzy: J. Gottfriedsen, M. Berrendorf, P. Gentine, B. Hassler, M. Reichstein, K. Weigel, V. Eyring
Opublikowane w: NeurIPS, 2021, ISSN 2331-8422
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Machine learning-based parameterizations for the ICON model

Autorzy: Arthur Grundner, Fernando Iglesias-Suarez, Tom Beucler, Pierre Gentine, Marco Giorgetta, and Veronika Eyring
Opublikowane w: ICCARUS, 2022
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Causally-informed neural nets to improve subgrid processes in climate models

Autorzy: F. Iglesias-Suarez, V. Eyring, P. Gentine, T. Beucler, M. Pritchard, J. Runge, and B. Solino-Fernandez
Opublikowane w: II ELLIS Doctoral Symposium 2022, 2022
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Interpretable multiscale Machine Learning-Based Parameterizations of Convection for ICON

Autorzy: Helge Heuer, Mierk Schwabe, Pierre Gentine, Marco A. Giorgetta, Veronika Eyring
Opublikowane w: EGU General Assembly 2024, 2024
Wydawca: EGU
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Physics-Aware Machine Learning For Geosciences And Remote Sensing

Autorzy: G Camps-Valls, DH Svendsen, J Cortés, A Moreno-Martínez, A Pérez-Suay, J Adsuara, I Martin, M Piles, J Muñoz-Marí, L Martino
Opublikowane w: IGARSS 2021 - 2021 IEEE International Geoscience and Remote Sensing Symposium, Brussels, Belgium 2021, 2021, ISBN 978-1-6654-0369-6
Wydawca: IEEE
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Bootstrap aggregation and confidence measures to improve time series causal discovery

Autorzy: Kevin Debeire; Andreas Gerhardus; Jakob Runge; Veronika Eyring
Opublikowane w: Proceedings of Machine Learning Research, Numer 236, 2024
Wydawca: PMLR

Location-Aware Convolutional Encoder-Decoder for Drought Detection in Europe

Autorzy: J. Cortés-Andrés, M.Á. Fernández-Torres, G. Camps-Valls
Opublikowane w: AGU 2021, 2021
Wydawca: AGU 2021

Upscaling plant traits to ecosystem level: blending local biodiversity, global traits databases, and remote sensing data.

Autorzy: Álvaro Moreno-Martínez, Jose E Adsuara, Jordi Muñoz-Marí, Emma Izquierdo-Verdiguier, Jens Katge, Nuno Carvalhais, Markus Reichstein, Steven W Running, Gustau Camps-Valls
Opublikowane w: EGU General Assembly 2021, 2021
Wydawca: EGU

M3LEO: A Multi-Modal, Multi-Label Earth Observation Dataset Integrating Interferometric SAR and Multispectral Data.

Autorzy: Allen, M., Dorr, F., Gallego-Mejia, J.A., Martínez-Ferrer, L., Jungbluth, A., Kalaitzis, F., Ramos-Pollán, R.
Opublikowane w: Part of Advances in Neural Information Processing Systems Datasets and Benchmarks Track 37 (NeurIPS 2024) (pp. 104694-104723), 2024
Wydawca: NeuIPS

Learning Granger Causal Feature Representations

Autorzy: G Varando, MA Fernández-Torres, G Camps-Valls
Opublikowane w: ICML 2021 - International Conference on Machine Learning - Workshop on Tackling Climate Change with Machine Learning, 2021
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Fewshot learning on global multimodal embeddings for earth observation tasks,

Autorzy: Allen, M., Dorr, F., Gallego-Mejia, J.A., Martínez-Ferrer, L., Jungbluth, A., Kalaitzis, F., Ramos-Pollán, R
Opublikowane w: NeurIPS 2023 - R0-FoMo: Workshop on Robustness of Few-shot and Zero-shot Learning in Foundation Models, 2023
Wydawca: NeurIPS

Towards Inference in Hybrid Earth System Models

Autorzy: Kai-Hendrik Cohrs
Opublikowane w: AAAI 2024 Bridge on Knowledge-Guided Machine Learning, Numer Invited talk, 2024
Wydawca: AAAI

ClimSim: A large multi-scale dataset for hybrid physics-ML climate emulation

Autorzy: Sungduk Yu, Zeyuan Hu, Akshay Subramaniam, Walter Hannah, Liran Peng, Jerry Lin, Mohamed Aziz Bhouri, Ritwik Gupta, Björn Lütjens, Justus C. Will, Gunnar Behrens, Julius J. M. Busecke, Nora Loose, Charles I. Stern, Tom Beucler, Bryce Harrop, Helge Heuer, Benjamin R. Hillman, Andrea Jenney, Nana Liu, Alistair White, Tian Zheng, Zhiming Kuang, Fiaz Ahmed, Elizabeth Barnes, Noah D. Brenowitz, Chris
Opublikowane w: 37th Conference on Neural Information Processing Systems, NeurIPS 2023, 2023
Wydawca: NeurIPS
DOI: 10.48550/arxiv.2306.08754

Context-Specific Causal Discovery for Categorical Data Using Staged Trees

Autorzy: Leonelli, M., Varando, G.
Opublikowane w: Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR, 206: 8871–8888, 2023
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Anomaly Attribution of Multivariate Time Series using Counterfactual Reasoning

Autorzy: Trifunov, V., T., Shadaydeh, M., Barz, B., and Denzler, J. A.
Opublikowane w: ICMLA, 2021
Wydawca: IEEE
DOI: 10.1109/icmla52953.2021.00033

Time Series Causal Link Estimation under Hidden Confounding using Knockoff Interventions

Autorzy: Violeta-Teodora Trifunov, Maha Shadaydeh, Joachim Denzler
Opublikowane w: A causal view on dynamical systems, NeurIPS 2022 workshop, 2022
Wydawca: NeurIPS

Causal model evaluation

Autorzy: Katja Weigel, Kevin Debeire, Evgenia Galytska, Soufiane Karmouche, Jakob Runge, and Veronika Eyring
Opublikowane w: Exploring the Frontiers in Earth System Modeling with Machine Learning and Big Data, 2022
Wydawca: AGCI

A two-stage machine learning framework using global satellite data of cloud classes for process-oriented model evaluation

Autorzy: Kaps, A., Lauer, A., Camps-Valls,G., Gentine, P., Gómez-Chova,L., Eyring, V.
Opublikowane w: Living Planet Symposium 2022, 2022
Wydawca: EESA

Learning Granger Causal Feature Representations

Autorzy: G. Varando, M.Á. Fernández-Torres, G. Camps-Valls
Opublikowane w: AGU (American Geophysical Union) Fall Meeting 2021, 2022
Wydawca: AGU

Causally-informed neural nets to improve subgrid processes in climate models

Autorzy: F. Iglesias-Suarez, V. Eyring, P. Gentine, T. Beucler, M. Pritchard, J. Runge, and B. Solino-Fernandez
Opublikowane w: Exploring the Frontiers in Earth System Modeling with Machine Learning and Big Data, 2022
Wydawca: AGCI

Graphs in State-Space Models for Granger Causality in Climate Science

Autorzy: Elvira, V., Chouzenoux, É., Cerdà-Bautista, J., Camps-Valls, G.
Opublikowane w: CausalStats23: When Causal Inference Meets Statistical Analysis, 2023
Wydawca: CNRS

Development of a Machine Learning Based Parameterization of Convection for ICON

Autorzy: H. Heuer, M. Schwabe, P. Gentine, V. Eyring
Opublikowane w: Atmospheric Physics: Experiment meets Modelling, 2022
Wydawca: Bad Honnef Physics School

Identifying the Causes of Pyrocumulonimbus (PyroCb)

Autorzy: Díaz Salas-Porras, E., Tazi, K., Braude, A., Okoh, D., Lamb, K.D., Watson-Parris, D., Harder, P., Meinert, N.
Opublikowane w: NeurIPS 2022 Workshop - Causality for Real-world Impact, 2022
Wydawca: Neurips

Long-time record andcontinuous high resolution gross primary productivity estimates at continental scales.

Autorzy: Alvaro Moreno, Laura Martínez-Ferrer, John Kimball, Martin Jung, Markus Reichstein, Steven W Running, Nicholas Clinton and Gustau Camps-Valls
Opublikowane w: AGU (American Geophysical Union) Fall Meeting 2021, 2021
Wydawca: AGU

Machine Learning-Based Parameterizations of Convection for ICON

Autorzy: Heuer, Helge Gustav Helmut; Schwabe, Mierk; Gentine, Pierre; Giorgetta, Marco A.; Eyring, Veronika
Opublikowane w: AGU Fall Meeting 2023, 2023
Wydawca: AGU

Investigation on the biophysical and biogeochemical responses of ecosystem conductance to water stress using eddy-covariance data

Autorzy: Han J., Zhan W., Gentine P.
Opublikowane w: American Geophysical Union Fall 2021, 2021
Wydawca: AGU

Machine learning-based parametrizations for ICON and evaluation with satellite data using the ESMValTool

Autorzy: Fernando Iglesias-Suarez, Arthur Grundner, Manuel Schlund, Mierk Schwabe, Tom Beucler, Pierre Gentine, Marco A. Giorgetta, and Veronika Eyring
Opublikowane w: Living Planet Symposium 2022, 2022
Wydawca: EESA

Recent Trends, Challenges and Limitations of Explainable AI in Remote Sensing

Autorzy: Höhl, A., Obadic, I., Fernández-Torres, M. Á., Oliveira, D., & Zhu, X. X.
Opublikowane w: . In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 8199-8205)., 2024
Wydawca: CVF

Exploring Generalisability of Self-Distillation with No Labels for SAR-Based Vegetation Prediction

Autorzy: Martínez-Ferrer, L., Jungbluth, A., Gallego-Mejia, J.A., Allen, M., Dorr, F., Kalaitzis, F., Ramos-Pollán, R.
Opublikowane w: NeurIPS 2023 - Workshop on Distribution Shifts: New Frontiers with Foundation Models, 2023
Wydawca: Neurips

Semiparametric Inference and Equation Discovery with the Bayesian Machine Scientist

Autorzy: Cohrs, K-H. and Varando, G. and Guimerà, R. and Sales-Pardo, M. and Camps-Valls, G
Opublikowane w: AI for Differential Equations in Science Workshop in ICLR 2024, 2024
Wydawca: ICLR

Double Machine Learning for Earth and Climate Sciences

Autorzy: Kai Hendrik Cohrs, Gherardo Varando, Nuno Carvalhais, Markus Reichstein, Gustau Camps-Valls
Opublikowane w: Nordic Probabilistic AI Summer School 2022, 2022
Wydawca: Nordic Probabilistic AI Summer School 2022

Exploiting Spatial and Temporal Information with ConvLSTM Networks for Cloud Detection over Landmarks

Autorzy: D. López-Puigdollers, A. Pérez-Suay, G. Mateo-García, L. Gómez-Chova
Opublikowane w: Living Planet Symposium 2022, 2022
Wydawca: Living Planet Symposium 2022 - ESA

Towards Physically Consistent Deep Learning For Climate Model Parameterizations

Autorzy: Birgit Kühbacher; Fernando Iglesias-Suarez; Niki Kilbertus; Veronika Eyring
Opublikowane w: ICMLA 2024, 2024
Wydawca: ICMLA
DOI: 10.48550/arxiv.2406.03920

Analyzing Climate Scenarios Using Dynamic Mode Decomposition With Control

Autorzy: Mankovich M., Bouabid S. and Camps-Valls G.
Opublikowane w: Dynamics, Data and Deep Learning workshop, Bristol, UK 2024, 2024
Wydawca: Bristol

Physics-informed Machine Learning-Based Cloud Microphysics Parameterization for Earth System Models

Autorzy: Sarauer, E.; Schwabe, M.; Lauer, A.; Stier, P.; Weiss, P.; Eyring, V.
Opublikowane w: Tackling Climate Change with Machine Learning workshop at ICLR 2024, 2024
Wydawca: ICLR

Characterizing the Earth complex dynamical system through spectral decomposition of kernel transfer operators

Autorzy: J. Adsuara, G. Varando, A. Pérez-Suay, K. Cohrs, E. Díaz, D. Bueso, G. Camps-Valls
Opublikowane w: Living Planet Symposium 2022, 2022
Wydawca: ESA

Development of a Machine Learning Based Parameterization of Convection for ICON

Autorzy: H. Heuer, M. Schwabe, P. Gentine, V. Eyring
Opublikowane w: Summer School on Land-Atmosphere Interaction Processes and Convection, 2022
Wydawca: CHESS

The Kernelized Taylor Diagram

Autorzy: Kristoffer Wickstrøm, Juan Emmanuel Johnson, Sigurd Løkse, Gustau Camps-Valls, Karl Øyvind Mikalsen, Michael Kampffmeyer, and Robert Jenssen
Opublikowane w: Symposium of the Norwegian AI Society, 31 May-1 June 2022, Oslo, Norway 2022, 2022
Wydawca: Norwegian AI Society

Recent Advances in Deep Learning for Spatio-Temporal Drought Monitoring, Forecasting and Model Understanding

Autorzy: J. Cortés-Andrés, M.Á. Fernández-Torres, G. Camps-Valls
Opublikowane w: EGU 2021, 2021
Wydawca: EGU

Learning Causal Representations with Granger PCA

Autorzy: Varando, G., Fernández-Torres, M.Á., Muñoz-Marí, J., Camps-Valls, G.
Opublikowane w: Causal Representation Learning Workshop @ UAI'22,, 2022
Wydawca: UAI

Interpretable AI – two examples

Autorzy: M. Schwabe, G. Behrens, T. Beucler, F. Iglesias-Suarez, P. Gentine, M. Giorgetta, A. Grundner, M. Pritchard, V. Eyring
Opublikowane w: 2nd ELLIS workshop on Machine Learning for Earth and Climate sciences, 2022
Wydawca: ELLIS

Causal discovery on climate models data

Autorzy: Kevin Debeire, Jakob Runge, and Veronika Eyring
Opublikowane w: ML for Earth System Modelling and Analytics workshop 2021, 2021
Wydawca: ML for Earth System Modelling and Analytics workshop

Causal evaluation of Arctic-midlatitude processes in CMIP6 model simulations

Autorzy: Evgenia Galytska, Katja Weigel, Jakob Runge, Dörthe Handorf, Ralf Jaiser, Raphael Köhler, and Veronika Eyring
Opublikowane w: EGU General Assembly 2022, 2022
Wydawca: EGU
DOI: 10.5194/egusphere-egu22-870

Intercomparing Global Foliar Trait and Canopy Height Maps: Upscaling Approaches and Spatial Patterns

Autorzy: Benjamin Dechant, Ryan Pavlick, Jens Kattge, Fabian D Schneider, Ethan E Butler, Alvaro Moreno
Opublikowane w: AGU (American Geophysical Union) Fall Meeting 2021, 2021
Wydawca: AGU (American Geophysical Union) Fall Meeting 2021

Learning Causal Representations with Granger PCA

Autorzy: G. Varando, M.Á. Fernández-Torres, J. Muñoz-Marí, G. Camps-Valls
Opublikowane w: Causal Representation Learning workshop at the 38th Conference on Uncertainty in Artificial Intelligence (UAI CRL 2022), 2022
Wydawca: UAI

Proof-of-concept: Using ChatGPT to Translate and Modernize an Earth System Model from Fortran to Python/JAX

Autorzy: Anthony Zhou, Linnia Hawkins, Pierre Gentine
Opublikowane w: NeurIPS, 2024
Wydawca: NeurIPS

Epistemic and aleatoric uncertainty maps in high resolution biophysical parameter retrieval

Autorzy: Laura Martínez-Ferrer, Álvaro Moreno-Martínez, Jordi Muñoz-Marí,Emma Izquierdo-Verdiguier, Manuel Campos-Taberner, Javier García-Haro, MarcoManeta, Nathaniel Robinson, Nicholas Clinton, John Kimball, Steven W. Running, andGustau Camps-Valls
Opublikowane w: EGU General Assembly 2021, 2021
Wydawca: EGU General Assembly 2021

A two-stage machine learning framework using global satellite data of cloud classes for process-oriented model evaluation

Autorzy: Kaps, A., Lauer, A., Camps-Valls,G., Gentine, P., Gómez-Chova,L., Eyring, V.
Opublikowane w: EGU General Assembly 2022, 2022
Wydawca: EGU
DOI: 10.5194/egusphere-egu22-676

Carbon fluxes estimation at scale: long-term, continuous, high spatial resolution with uncertainties at continental scales

Autorzy: Laura Martínez-Ferrer, Alvaro Moreno‑Martínez, John S. Kimball, Steven W. Running, Nicholas Clinton, Gustau Camps-Valls
Opublikowane w: Living Planet Symposium 2022, 2022
Wydawca: Living Planet Symposium 2022

Machine learning for improved understanding and projections of climate change

Autorzy: Schwabe, Mierk; Eyring, Veronika
Opublikowane w: TRR 165/181 Conference, 2023
Wydawca: TRR 165/181 Conference

Large Language Models for Constrained-Based Causal Discovery.

Autorzy: Cohrs, K., Diaz, E., Sitokonstantinou, V., Varando G. and Camps-Valls, G.
Opublikowane w: AAAI 2024 Workshop on 'Are Large Language Models Simply Causal Parrots?, 2024
Wydawca: AAAI

Comparing Data-Driven and Mechanistic Models for Predicting Phenology in Deciduous Broadleaf Forests

Autorzy: Reimers, C.; Hafezi Rachti, D.; Liu, G.; Winkler, A.
Opublikowane w: arXiv, Numer 9, 2023
Wydawca: NeurIPS 2023 Workshop on Tackling Climate Change with Machine Learning
DOI: 10.48550/arxiv.2401.03960

Learning ENSO-related Principal Modes of Vegetation via a Granger-Causal Variational Autoencoder

Autorzy: G. Varando, M.Á. Fernández-Torres, G. Camps-Valls
Opublikowane w: EGU 2022, 2022
Wydawca: EGU

Highly Efficient Structural Learning of Sparse Staged Trees

Autorzy: M. Leonelli, G. Varando
Opublikowane w: The 11th International Conference on Probabilistic Graphical Models, 2022
Wydawca: PMLR press

Machine learning based gravity wave parametrizations for ICON

Autorzy: Schwabe, M., Grundner, A., Gentine, P., Giorgetta, M. A., Rapp, M., Eyring, V.
Opublikowane w: SPARC Gravity Wave Symposium 2022, 2022
Wydawca: SPARC

Spatio-Temporal Gaussianization Flows for Extreme Event Detection

Autorzy: M.Á. Fernández-Torres, J.E. Johnson, M. Piles, G. Camps-Valls
Opublikowane w: EGU, 2021
Wydawca: EGU

Deep learning based cloud cover parameterization for ICON

Autorzy: Grundner, A., Beucler, T., Gentine, P., Iglesias-Suarez, F., Giorgetta, M. A., Eyring, V.
Opublikowane w: Journal of Advances in Modeling Earth Systems, Numer Volume 14; Numer 12; 14.12.2022, 2021, Strona(/y) e2021MS002959, ISSN 1942-2466
Wydawca: American Geophysical Union
DOI: 10.1029/2021ms002959

Causal model evaluation of Arctic-midlatitude teleconnections in CMIP6

Autorzy: E. Galytska, K. Weigel, D. Handorf, R. Jaiser, R.H. Köhler, J. Runge, and V. Eyring
Opublikowane w: Earth and Space Science Open Archive, Numer 23335084, 2022, ISSN 2333-5084
Wydawca: Earth and Space Science Open Archive
DOI: 10.1002/essoar.10512569.1

Climate-Invariant Machine Learning

Autorzy: Beucler, T., Pritchard, M., Yuval, J., Gupta, A., Peng, L., Rasp, S., Ahmed, F., O'Gorman, P.A., Neelin, J.D., Lutsko, N.J. and Gentine, P.
Opublikowane w: arXiv, Numer 23318422, 2021, ISSN 2331-8422
Wydawca: arXiv
DOI: 10.48550/arxiv.2112.08440

Integrating Domain Knowledge in Data-Driven Earth Observation With Process Convolutions

Autorzy: Svendsen, D. H., Piles, M., Muñoz-Marí, J., Luengo, D., Martino, L, Camps-Valls G.
Opublikowane w: IEEE Transactions on Geoscience and Remote Sensing, Numer 60, 2022, Strona(/y) 1-15, ISSN 0196-2892
Wydawca: Institute of Electrical and Electronics Engineers
DOI: 10.1109/tgrs.2021.3059550

Bringing it all together: Science and modelling priorities to support international climate policy

Autorzy: Colin Gareth Jones, Fanny Adloff, Ben Booth, Peter Cox, Veronika Eyring, Pierre Friedlingstein, Katja Frieler, Helene Hewitt, Hazel Jeffery, Sylvie Joussaume, Torben Koenigk, Bryan N. Lawrence, Eleanor O'Rourke, Malcolm Roberts, Benjamin Sanderson, Roland Séférian, Samuel Somot, Pier-Luigi Vidale, Detlef van Vuuren, Mario Acosta, Mats Bentsen, Raffaele Bernardello, Richard Betts, Ed Blockley, Ju
Opublikowane w: EGUsphere, 2024, ISSN 2190-4987
Wydawca: Copernicus GmbH
DOI: 10.5194/egusphere-2024-453

Machine-Learned Cloud Classes From Satellite Datafor Process-Oriented Climate Model Evaluation

Autorzy: Kaps, A., Lauer, A., Camps-Valls, G., Gentine, P., Gómez-Chova, L., Eyring, V.
Opublikowane w: TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, Numer Volume 61; 31.01.2023, 2022, ISSN 2331-8422
Wydawca: IEEE
DOI: 10.1109/tgrs.2023.3237008

Two for one: Partitioning CO2 fluxes and understanding the relationship between solar-induced chlorophyll fluorescence and gross primary productivity using machine learning

Autorzy: Weiwei Zhan, Xi Yang, Youngryel Ryu, Benjamin Dechant, Yu Huang, Yves Goulas, Minseok Kang, Pierre Gentine
Opublikowane w: Agricultural and Forest Meteorology, Numer 321, 2023, Strona(/y) 108980, ISSN 0168-1923
Wydawca: Elsevier BV
DOI: 10.1016/j.agrformet.2022.108980

Evaluation of Native Earth System Model Output with ESMValTool v2.6.0

Autorzy: M., Schlund, B., Hassler, A., Lauer, B., Andela, P., Jöckel, R., Kazeroni, S. L., Tomas, B., Medeiros, V., Predoi, S., Sénési, J., Servonnat, T., Stacke, J., Vegas-Regidor, K., Zimmermann, V., Eyring
Opublikowane w: Geoscientific Model Development Discussions, Numer Volume 16; 11.01.2023, 2022, Strona(/y) 315-333, ISSN 1991-962X
Wydawca: Geoscientific Model Development Discussions
DOI: 10.5194/gmd-2022-205

Physics-aware Machine Learning for Earth Observation

Autorzy: Camps-Valls, G.
Opublikowane w: NeurIPS 2022 - Workshop on Tackling Climate Change with Machine Learning, Numer Keynote talk, 2022
Wydawca: Neurips

Learning Causal Representations with Granger Rotated PCA

Autorzy: Gherardo Varando
Opublikowane w: 16th International Conference of the ERCIM WG on Computational and Methodological Statistics, Numer Invited talk, 2023
Wydawca: CMS

Intercomparison of global foliar trait maps reveals fundamental differences and limitations of upscaling approaches.

Autorzy: Benjamin Dechant , Jens Kattge, Ryan Pavlick, Fabian Schneider, Francesco Sabatini, Alvaro Moreno-Martinez, Ethan Butler, Peter van Bodegom, Helena Vallicrosa, Teja Kattenborn, Coline Boonman, Nima Madani, Ian Wright, Ning Dong, Hannes Feilhauer, Josep Penuelas, Jordi Sardans, Jesus Aguirre-Gutierrez, Peter Reich, Pedro Leitao, Jeannine Cavender-Bares, Isla H. Myers-Smith , Sandra Duran, Holly Cro
Opublikowane w: 2023
Wydawca: EarthArchiv

Geological carbon cycle constraints on the terrestrial hydrological response to higher atmospheric CO2.

Autorzy: Rugenstein, J.K.C., Winkler, A.J.
Opublikowane w: ESSOAR, 2022
Wydawca: ESSOAR
DOI: 10.1002/essoar.10512683.1

Emergence of the physiological effects of elevated CO2 on land-atmosphere exchange of carbon and water

Autorzy: Chunhui Zhan, René Orth, Mirco Migliavacca, Sönke Zaehle, Markus Reichstein, Jan Engel, Anja Rammig, Alexander J. Winkler
Opublikowane w: Earth and Space Science Open Archive, 2022
Wydawca: Earth and Space Science Open Archive
DOI: 10.1002/essoar.10510955.1

The biogeophysical effects of idealized land cover and land management changes in Earth System Models

Autorzy: Steven Johan De Hertog, Felix Havermann, Inne Vanderkelen, Suqi Guo, Fei Luo, Iris Manola, Dim Coumou, Edouard Léopold Davin, Gregory Duveiller, Quentin Lejeune, Julia Pongratz, Carl-Friedrich Schleussner, Sonia Isabelle Seneviratne, Wim Thiery
Opublikowane w: Earth System Dynamcis Discussions, 2022
Wydawca: Copernicus GmbH
DOI: 10.5194/esd-2022-5

Better Better — machine learning for improved climate models and projections

Autorzy: Eyring V. and Gentine P.
Opublikowane w: 2021
Wydawca: UN

Interannual global carbon cycle variations linked to atmospheric circulation variability

Autorzy: Na Li, Sebastian Sippel, Alexander J. Winkler, Miguel D. Mahecha, Markus Reichstein, Ana Bastos
Opublikowane w: Earth System Dynamics Discussion, 2022
Wydawca: Copernicus GmbH
DOI: 10.5194/egusphere-2022-96

Extreme Event Monitoring, Everywhere, All at Once: Challenges and Strategies

Autorzy: Fernández-Torres, M.A.
Opublikowane w: ICS Theoretical Astrophysics & Computational Science Seminar, Universität Zürich, Zurich, Switzerland, Numer Invited talk, 2023
Wydawca: ETH

Generative Adversarial Networks in the Geosciences

Autorzy: Mateo-Garc\'\ia, Gonzalo and Laparra, Valero and Requena-Mesa, Christian and G\'omez-Chova, Luis
Opublikowane w: Deep learning for the Earth Sciences: A comprehensive approach to remote sensing, climate science and geosciences. Wiley & Sons 2021, 2021
Wydawca: Wiley and sons

Combining system modeling and machine learning into hybrid ecosystem modeling. Science-guided Machine Learning: Emerging Trends in Combining Scientific Knowledge with Data-driven Methods, Data Mining and Knowledge Discovery Series. CRC Press 2021

Autorzy: Reichstein, M. and Ahrens, B. and Kraft, B. and Camps-Valls, G. and Carvalhais, N. and Gans, F. and Gentine, P. and Winkler, A.J.
Opublikowane w: 2022
Wydawca: Chapman and Hall/CRC
DOI: 10.1201/9781003143376

Perspective on Deep Learning for Earth Sciences

Autorzy: Gustau Camps-Valls
Opublikowane w: Generalization with Deep Learning, 2021, ISSN 1013-2511
Wydawca: World Scientific
DOI: 10.1142/9789811218842_0007

Spatio-temporal Autoencoders in Weather and Climate Research

Autorzy: Xavier-Andoni Tibau, Christian Reimers, Christian Requena-Mesa, and Jakob Runge
Opublikowane w: 2021, ISBN 9781119646181
Wydawca: John Wiley & Sons, Ltd
DOI: 10.1002/9781119646181.ch13

Deep Learning for the Parametrization of Subgrid Processes in Climate Models

Autorzy: P. Gentine, V. Eyring and T. Beucler
Opublikowane w: Chapter 21 In Book: Deep Learning for the Earth Sciences, Eds G. Camps-Valls, D. Tuia, X. X. Zhu, M. Reichstein, 2021
Wydawca: John Wiley & Sons Ltd
DOI: 10.1002/9781119646181.ch21

Learning Unsupervised Feature Representations of Remote Sensing Data with Sparse Convolutional Networks

Autorzy: Adsuara, Jose E and Campos-Taberner, Manuel and Garc\'\ia-Haro, Javier and Gatta, Carlo and Romero, Adriana and Camps-Valls, Gustau
Opublikowane w: Deep learning for the Earth Sciences: A comprehensive approach to remote sensing, climate science and geosciences. Wiley & Sons 2021, 2021
Wydawca: Wiley and sons

Introduction to Deep Learning for the Earth Sciences

Autorzy: Gustau Camps-Valls, Xiao Xiang Zhu, Devis Tuia, and Markus Reichstein
Opublikowane w: Deep learning for the Earth Sciences: A comprehensive approach to remote sensing, climate science and geosciences. Wiley & Sons 2021, 2021
Wydawca: Wiley and sons

Outloook to Deep Learning for the Earth Sciences

Autorzy: Markus Reichstein, Gustau Camps-Valls, Devis Tuia, and Xiao Xiang Zhu
Opublikowane w: Deep learning for the Earth Sciences: A comprehensive approach to remote sensing, climate science and geosciences. Wiley & Sons 2021, 2021
Wydawca: Wiley and sons
DOI: 10.1002/9781119646181.ch23

Emulating Ecological Memory with Recurrent Neural Networks

Autorzy: Basil Kraft, Simon Besnard, and Sujan Koirala
Opublikowane w: 2021
Wydawca: Wiley Online Library
DOI: 10.1002/9781119646181.ch18

Deep learning for the Earth Sciences: A comprehensive approach to remote sensing, climate science and geosciences

Autorzy: Gustau Camps-Valls, Devis Tuia, Xiao Xiang Zhu, Markus Reichstein
Opublikowane w: Deep learning for the Earth Sciences: A comprehensive approach to remote sensing, climate science and geosciences, 2021, ISBN 9781119646181
Wydawca: Wiley and sons
DOI: 10.1002/9781119646181

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