Advanced spatio-temporal causal inference for climate research

Project Information

CausalEarth

Grant agreement ID: 948112

DOI

10.3030/948112

EC signature date 13 January 2021

Start date 1 February 2021

End date 31 July 2026

Funded under

• EXCELLENT SCIENCE - European Research Council (ERC)

Total cost

€ 1 499 631,00

EU contribution

€ 1 499 631,00

Coordinated by

UNIVERSITAET POTSDAM
Germany

CORDIS provides links to public deliverables and publications of HORIZON projects.

Links to deliverables and publications from FP7 projects, as well as links to some specific result types such as dataset and software, are dynamically retrieved from OpenAIRE .

Deliverables

Open Research Data Pilot (1)

Data Management Plan

Participation in the Open Research Data Pilot

Publications

Peer reviewed articles (8)

Causal inference for time series

Author(s): Runge Jakob, Gerhardus Andreas, Varando Gherardo, Eyring Veronika, Camps-Valls Gustau
Published in: Nature Reviews Earth \& Environment, Issue 10, 2023, Page(s) 1-19, ISSN 2041-1723
Publisher: Nature Publishing Group
DOI: 10.1038/s43017-023-00431-y

Clustering of causal graphs to explore drivers of river discharge

Author(s): Günther, W., Miersch, P., Ninad, U.,Runge, J.
Published in: Environmental Data Science, Issue Volume 2, 2023, Page(s) e25, ISSN 2634-4602
Publisher: Cambridge University Press
DOI: 10.1017/eds.2023.17

Modern causal inference approaches to investigate biodiversity-ecosystem functioning relationships

Author(s): Jakob Runge
Published in: nature communications, Issue volume 14, number 1, 2023, Page(s) 1917, ISSN 2041-1723
Publisher: Nature Publishing Group
DOI: 10.1038/s41467-023-37546-1

Causal model evaluation of Arctic-midlatitude teleconnections in CMIP6

Author(s): Evgenia Galytska; Katja Weigel; Dörthe Handorf; Ralf Jaiser; Raphael Harry Köhler; Jakob Runge; Veronika Eyring
Published in: Journal of Geophysical Research: Atmospheres, 2023, ISSN 2169-8996
Publisher: AGU
DOI: 10.1002/essoar.10512569.1

Stratocumulus adjustments to aerosol perturbations disentangled with a causal approach

Author(s): Emilie Fons; Jakob Runge; David Neubauer; Ulrike Lohmann
Published in: npj Climate and Atmospheric Science, 6 (1), 2023, ISSN 2397-3722
Publisher: Nature Springer
DOI: 10.1038/s41612-023-00452-w

Selecting robust features for machine-learning applications using multidata causal discovery

Author(s): Saranya Ganesh S.; Tom Beucler; Frederick Iat-Hin Tam; Milton S. Gomez; Jakob Runge; Andreas Gerhardus
Published in: Environmental Data Science, Issue 2, 2023, ISSN 2634-4602
Publisher: Cambridge University Press
DOI: 10.1017/eds.2023.21

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

Author(s): Xavier-Andoni Tibau; Christian Reimers; Andreas Gerhardus; Joachim Denzler; Veronika Eyring; Jakob Runge
Published in: Environmental Data Science, 2022, ISSN 2634-4602
Publisher: CUP
DOI: 10.1017/eds.2022.33

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

Author(s): Soufiane Karmouche, Evgenia Galytska, Jakob Runge, Gerald A. Meehl, Adam S. Phillips, Katja Weigel, and Veronika Eyring
Published in: Earth System Dynamics, Issue Volume 14, issue 2, 2023, Page(s) 309–344, ISSN 2190-4979
Publisher: Copernicus Gesellschaft mbH
DOI: 10.5194/esd-14-309-2023

Conference proceedings (6)

Increasing effect sizes of pairwise conditional independence tests between random vectors

Author(s): T Hochsprung, J Wahl, A Gerhardus, U Ninad, J Runge
Published in: Uncertainty in Artificial Intelligence, Issue Volume 216, 2023, Page(s) 879-889, ISSN 1525-3384
Publisher: MLResearchPress

Conditional Independence Testing with Heteroskedastic Data and Applications to Causal Discovery.

Author(s): Wiebke Günther, Urmi Ninad, jonas Wahl, Jakob Runge
Published in: Advances in Neural Information Processing Systems 35, Issue volume 35, 2023, Page(s) 16191-16202
Publisher: MIT Press

Vector causal inference between two groups of variables

Author(s): Wahl Jonas, Ninad Urmi, Runge Jakob
Published in: Proceedings of the AAAI Conference on Artificial Intelligence, Issue Volume 37,number 10, 2023, Page(s) 12305-12312, ISBN 978-1-57735-880-0
Publisher: AAAI Press
DOI: 10.1609/aaai.v37i10.26450

Causal discovery for time series from multiple datasets with latent contexts

Author(s): Wiebke Günther, Urmi Ninad, Jakob Runge
Published in: Uncertainty in Artificial Intelligence, Issue Volume 216, 2023, Page(s) 766-776, ISSN 1525-3384
Publisher: MLResearchPress

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

Author(s): XA Tibau, C Reimers, A Gerhardus, J Denzler, V Eyring, J Runge
Published in: Enviromental Data Science,Volume 1, Issue E12, 2022, Page(s) 1-29
Publisher: Cambridge University Press
DOI: 10.1017/eds.2022.11

Necessary and sufficient graphical conditions for optimal adjustment sets in causal graphical models with hidden variables

Author(s): Jakob Runge
Published in: Advances in Neural Information Processing Systems, Issue 34, 2021, Page(s) 1-41, ISBN 15762-15773
Publisher: Corell University