Analyzing Granger Causality in Climate Data with Time Series Classification Methods

  • Christina PapagiannopoulouEmail author
  • Stijn Decubber
  • Diego G. Miralles
  • Matthias Demuzere
  • Niko E. C. Verhoest
  • Willem Waegeman
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10536)


Attribution studies in climate science aim for scientifically ascertaining the influence of climatic variations on natural or anthropogenic factors. Many of those studies adopt the concept of Granger causality to infer statistical cause-effect relationships, while utilizing traditional autoregressive models. In this article, we investigate the potential of state-of-the-art time series classification techniques to enhance causal inference in climate science. We conduct a comparative experimental study of different types of algorithms on a large test suite that comprises a unique collection of datasets from the area of climate-vegetation dynamics. The results indicate that specialized time series classification methods are able to improve existing inference procedures. Substantial differences are observed among the methods that were tested.


Climate science Attribution studies Causal inference Granger causality Time series classification 



This work is funded by the Belgian Science Policy Office (BELSPO) in the framework of the STEREO III programme, project SAT-EX (SR/00/306). D. G. Miralles acknowledges support from the European Research Council (ERC) under grant agreement n\(^{\circ }\) 715254 (DRY-2-DRY). The data used in this manuscript can be accessed using as gateway.


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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Christina Papagiannopoulou
    • 1
    Email author
  • Stijn Decubber
    • 1
  • Diego G. Miralles
    • 2
    • 3
  • Matthias Demuzere
    • 2
  • Niko E. C. Verhoest
    • 2
  • Willem Waegeman
    • 1
  1. 1.Department of Mathematical Modelling, Statistics and BioinformaticsGhent UniversityGhentBelgium
  2. 2.Laboratory of Hydrology and Water ManagementGhent UniversityGhentBelgium
  3. 3.Department of Earth SciencesVU University AmsterdamAmsterdamThe Netherlands

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