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Inferring causation from time series in Earth system sciences.

  • Runge J German Aerospace Center, Institute of Data Science, Mälzer Str. 3, 07745, Jena, Germany. jakob.runge@dlr.de.
  • Bathiany S Climate Service Center Germany (GERICS), Helmholtz-Zentrum Geesthacht, Fischertwiete 1, 20095, Hamburg, Germany.
  • Bollt E Department of Mathematics, Clarkson Center for Complex Systems Science (C3S2), Clarkson University, 8 Clarkson Ave., Potsdam, NY, 13699-5815, USA.
  • Camps-Valls G Image Processing Laboratory, Universitat de València, ES-46980, Paterna (València), Spain.
  • Coumou D Department of Water and Climate Risk, Institute for Environmental Studies (IVM), VU University Amsterdam, De Boelelaan 1087, 1081 HV, Amsterdam, The Netherlands.
  • Deyle E Scripps Institution of Oceanography, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA, 92093, USA.
  • Glymour C Department of Philosophy, Carnegie Mellon University, 5000 Forbes Ave, Pittsburgh, PA, 15213, USA.
  • Kretschmer M Potsdam Institute for Climate Impact Research, Earth System Analysis, Telegraphenberg A62, 14473, Potsdam, Germany.
  • Mahecha MD Max Planck Institute for Biogeochemistry, PO Box 100164, 07701, Jena, Germany.
  • Muñoz-Marí J Image Processing Laboratory, Universitat de València, ES-46980, Paterna (València), Spain.
  • van Nes EH Department of Environmental Sciences, Wageningen University, P.O. Box 47, NL-6700 AA, Wageningen, The Netherlands.
  • Peters J Department of Mathematical Sciences, University of Copenhagen, Universitetsparken 5, 2100, København, Denmark.
  • Quax R Institute for Informatics, University of Amsterdam, PO Box 94323, 1090 GH, Amsterdam, The Netherlands.
  • Reichstein M Max Planck Institute for Biogeochemistry, PO Box 100164, 07701, Jena, Germany.
  • Scheffer M Department of Environmental Sciences, Wageningen University, P.O. Box 47, NL-6700 AA, Wageningen, The Netherlands.
  • Schölkopf B Max Planck Institute for Intelligent Systems, Max Planck Ring 4, 72076, Tübingen, Germany.
  • Spirtes P Department of Philosophy, Carnegie Mellon University, 5000 Forbes Ave, Pittsburgh, PA, 15213, USA.
  • Sugihara G Scripps Institution of Oceanography, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA, 92093, USA.
  • Sun J Department of Mathematics, Clarkson Center for Complex Systems Science (C3S2), Clarkson University, 8 Clarkson Ave., Potsdam, NY, 13699-5815, USA.
  • Zhang K Department of Philosophy, Carnegie Mellon University, 5000 Forbes Ave, Pittsburgh, PA, 15213, USA.
  • Zscheischler J Institute for Atmospheric and Climate Science, ETH Zurich, Universitätstrasse 16, 8092, Zurich, Switzerland.
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  • 2019-06-16
Published in:
  • Nature communications. - 2019
General Biochemistry, Genetics and Molecular Biology
General Physics and Astronomy
General Chemistry
English The heart of the scientific enterprise is a rational effort to understand the causes behind the phenomena we observe. In large-scale complex dynamical systems such as the Earth system, real experiments are rarely feasible. However, a rapidly increasing amount of observational and simulated data opens up the use of novel data-driven causal methods beyond the commonly adopted correlation techniques. Here, we give an overview of causal inference frameworks and identify promising generic application cases common in Earth system sciences and beyond. We discuss challenges and initiate the benchmark platform causeme.net to close the gap between method users and developers.
Language
  • English
Open access status
gold
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Persistent URL
https://sonar.ch/global/documents/185431
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