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Assessing teleconnection pathways with causal inference techniques

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  • UserMarlene Kretschmer, University of Reading, Department of Meteorology
  • ClockTuesday 11 February 2020, 12:00-13:15
  • HouseBullard Lab, Seminar Room.

If you have a question about this talk, please contact Jonathan Rosser.

Chair: Emily Shuckburgh Abstract: Teleconnections refer to recurrent large-scale pressure patterns, affecting e.g. the jet stream position, storm track intensity or Monsoon strength and thus have a strong impact on our weather. However, extracting the relevant teleconnection pathways from observation or model data remains challenging. One major issue is separating the signal from the noise given large internal atmospheric variability, which is further compounded by varying spatio-temporal dimensions and competing effects of different processes. Here, I discuss how novel data-driven causal methods beyond the commonly adopted correlation techniques can overcome some of these limitations. I give an overview of causal inference frameworks and identify application cases common in climate science.

This talk is part of the AI4ER Seminar Series series.

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