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Inferring causation from time series in Earth system sciences

Author

Listed:
  • Jakob Runge

    (Institute of Data Science
    Imperial College)

  • Sebastian Bathiany

    (Helmholtz-Zentrum Geesthacht
    Wageningen University)

  • Erik Bollt

    (Clarkson University)

  • Gustau Camps-Valls

    (Universitat de València)

  • Dim Coumou

    (VU University Amsterdam
    Potsdam Institute for Climate Impact Research, Earth System Analysis)

  • Ethan Deyle

    (University of California, San Diego)

  • Clark Glymour

    (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

    (Universitat de València)

  • Egbert H. Nes

    (Wageningen University)

  • Jonas Peters

    (University of Copenhagen)

  • Rick Quax

    (University of Amsterdam
    University of Amsterdam)

  • Markus Reichstein

    (Max Planck Institute for Biogeochemistry)

  • Marten Scheffer

    (Wageningen University)

  • Bernhard Schölkopf

    (Max Planck Institute for Intelligent Systems)

  • Peter Spirtes

    (Carnegie Mellon University)

  • George Sugihara

    (University of California, San Diego)

  • Jie Sun

    (Clarkson University
    Clarkson University)

  • Kun Zhang

    (Carnegie Mellon University)

  • Jakob Zscheischler

    (Institute for Atmospheric and Climate Science, ETH Zurich
    University of Bern
    University of Bern)

Abstract

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.

Suggested Citation

  • 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. Nes & Jonas Peters, 2019. "Inferring causation from time series in Earth system sciences," Nature Communications, Nature, vol. 10(1), pages 1-13, December.
    • Handle: RePEc:nat:natcom:v:10:y:2019:i:1:d:10.1038_s41467-019-10105-3
    DOI: 10.1038/s41467-019-10105-3
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