Profile
Abstract
I am an assistant professor of climate causality at the Leipzig Institute for Meteorology. My research focuses on the causal drivers of extreme weather events. I investigate which large-scale atmospheric circulation patterns and 'teleconnections' are responsible for the occurrence of extreme weather events and how they change in a warmer climate. Answering these questions is important to improve (sub-)seasonal forecasts of extreme events and reduce uncertainties in regional climate projections. In my research, I use a variety of new statistical methods from the field of machine learning and, in particular, methods of causal inference. I am interested in how such new data-centric methods can be optimally combined with classical climate physics approaches to extract useful and interpretable climate information from climate data.
Professional career
- 05/2018 - 09/2019
Postdoc, Potsdam Institute for Climate Impact Research - 10/2019 - 09/2022
Postdoc, University of Reading, UK - since 10/2022
Junior Professor for Climate Causality (with Tenure Track to W3)Institute for Meteorology, University of Leipzig
Education
- 10/2008 - 04/2014
MSci in Mathematics, Humboldt University Berlin - 05/2014 - 04/2018
PhD in Climate Physics, Potsdam University & Potsdam Institute for Climate Impact Research
- Large-scale atmospheric circulations and teleconnections and their role in causing extreme weather events
- Effects of Arctic changes on weather in the mid-latitudes
- Detection and attribution of extreme events
- Uncertainties of regional climate projections
- Subseasonal to seasonal predictions (S2S)
- Impacts of extreme weather events (e.g. for renewable energies)
- Statistical and machine learning methods and their application in climate research with a focus on causality methods (causal inference and causal discovery) and explainable AI (XAI)
- show detailsKretschmer, M.; Zappa, G.; Shepherd, G.; Shepherd, T. G.The role of Barents–Kara sea ice loss in projected polar vortex changesWeather and Climate Dynamics. 2020.
- show detailsKretschmer, M.; Adams, S.; Arribas, A.; Saggioro, E.; Prudden, R.; Robinson, N.; Shepherd, T.Quantifying causal teleconnection pathways (2021)Bulletin of the American Meteorological Society. 2020.
- show detailsKretschmer, M.; Coumou, D.; Agel, L.; Barlow, M.; Cohen, J.; Tziperman, E.More-Persistent Weak Stratospheric Polar Vortex States Linked to Cold ExtremesBulletin of the American Meteorological Society. 2018. pp. 49–60.
- show detailsKretschmer, M.; Cohen, J.; Matthias, V.; Runge, J.; Coumou, D.The different stratospheric influence on cold-extremes in Eurasia and North Americanpj Climate and Atmospheric Science. 2018.
- show detailsKretschmer, M.; Coumou, D.; Donges, J. F.; Runge, J.Using Causal Effect Networks to analyze different Arctic drivers of mid-latitude winter circulationJournal of Climate. 2016. pp. 4069–4081.
- Teleconnections and large-scale circulation
- Climate variability and extreme events
- Methods for attribution of trends and extreme events in meteorology and climate science
- Statistical and machine learning methods in meteorology, climate and earth system sciences
- Causal inference
For possible theses (B.Sc., M.Sc.) please feel free to email me.
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Introduction to Data Science
Introduction to Advanced Data Analytics (5 ECTS)
- Lecture Introduction to Data Science. Thursday, 9.30 - 11.00, HS2 (1.12), Talstr. 35
- Practicals Introduction to Data Science. Thursday, 11:15 -12:45, CP III, Talstr. 35