Nature Communications (Jun 2019)
Inferring causation from time series in Earth system sciences
- Jakob Runge,
- Sebastian Bathiany,
- Erik Bollt,
- Gustau Camps-Valls,
- Dim Coumou,
- Ethan Deyle,
- Clark Glymour,
- Marlene Kretschmer,
- Miguel D. Mahecha,
- Jordi Muñoz-Marí,
- Egbert H. van Nes,
- Jonas Peters,
- Rick Quax,
- Markus Reichstein,
- Marten Scheffer,
- Bernhard Schölkopf,
- Peter Spirtes,
- George Sugihara,
- Jie Sun,
- Kun Zhang,
- Jakob Zscheischler
Affiliations
- Jakob Runge
- German Aerospace Center, Institute of Data Science
- Sebastian Bathiany
- Climate Service Center Germany (GERICS), Helmholtz-Zentrum Geesthacht
- Erik Bollt
- Department of Mathematics, Clarkson Center for Complex Systems Science (C3S2), Clarkson University
- Gustau Camps-Valls
- Image Processing Laboratory, Universitat de València
- Dim Coumou
- Department of Water and Climate Risk, Institute for Environmental Studies (IVM), VU University Amsterdam
- Ethan Deyle
- Scripps Institution of Oceanography, University of California, San Diego
- Clark Glymour
- Department of Philosophy, Carnegie Mellon University
- Marlene Kretschmer
- Potsdam Institute for Climate Impact Research, Earth System Analysis
- Miguel D. Mahecha
- Max Planck Institute for Biogeochemistry
- Jordi Muñoz-Marí
- Image Processing Laboratory, Universitat de València
- Egbert H. van Nes
- Department of Environmental Sciences, Wageningen University
- Jonas Peters
- Department of Mathematical Sciences, University of Copenhagen
- Rick Quax
- Institute for Informatics, University of Amsterdam
- Markus Reichstein
- Max Planck Institute for Biogeochemistry
- Marten Scheffer
- Department of Environmental Sciences, Wageningen University
- Bernhard Schölkopf
- Max Planck Institute for Intelligent Systems
- Peter Spirtes
- Department of Philosophy, Carnegie Mellon University
- George Sugihara
- Scripps Institution of Oceanography, University of California, San Diego
- Jie Sun
- Department of Mathematics, Clarkson Center for Complex Systems Science (C3S2), Clarkson University
- Kun Zhang
- Department of Philosophy, Carnegie Mellon University
- Jakob Zscheischler
- Institute for Atmospheric and Climate Science, ETH Zurich
- DOI
- https://doi.org/10.1038/s41467-019-10105-3
- Journal volume & issue
-
Vol. 10,
no. 1
pp. 1 – 13
Abstract
Questions of causality are ubiquitous in Earth system sciences and beyond, yet correlation techniques still prevail. This Perspective provides an overview of causal inference methods, identifies promising applications and methodological challenges, and initiates a causality benchmark platform.
