Dr. Marlene Kretschmer

Marlene Kretschmer is Postdoctoral Researcher at the Meteorology Department at the University of Reading, UK. Her research focuses on large-scale climate variability and predictability, with a focus on the dynamical troposphere-stratosphere coupling and its role for causing temperature and precipitation extremes. She is particularly interested in applying novel statistical methods from machine learning, such as causal discovery algorithms, to tackle these issues.


Potsdam Institute for Climate Impact Research (PIK)
P.O. Box 60 12 03
14412 Potsdam



PhD in Climate Physics at Potsdam Institute for Climate Impact Research & Potsdam University (2018): 

Thesis: "Disentangling Causal Pathways of the Stratopsheric Polar Vortex - A Machine Learning Approach" 

Diploma (M.Sc.) in Mathematics at Humboldt University Berlin (2014): 

Thesis: "Serre´s conjecture on projective modules" 

10/2019 –

Postdoctoral Fellow, University of Reading, UK
Department of Meteorology
Advisor: Prof. Ted Shepherd

11/2017 – 09/2019

Postdoctoral Fellow, Potsdam Institute for Climate Impact Research, Germany
Department of Earth System Analysis
Advisor: Dr. Dim Coumou

05/2014 – 10/2017

Graduate studentship, Potsdam Institute for Climate Impact Research, Germany
Department of Earth System Analysis
Advisor: Dr. Dim Coumou


---- 2020 ----

Pfleiderer, P., C.-F. Schleussner, T. Geiger, M. Kretschmer, Robust Predictors for Seasonal Atlantic Hurricane Activity Identified with Causal Effect Networks, Weather and Climate Dynamics, doi:10.5194/wcd-1-313-2020

J. Lehmann, M. Kretschmer, B. Schauberger, F. Wechsung (2020), Potential for Early Forecast of Moroccan Wheat Yields Based on Climatic Drivers, Geophysical Research Letters, doi:10.1029/2020GL087516

V. Matthias & M. Kretschmer (2020), The Influence of Stratospheric Wave Reflection on North American Cold Spells, Monthly Weather Review, https://doi.org/10.1175/MWR-D-19-0339.1

Di Capua, G., M. Kretschmer, R. V. Donner, B. van den Hurk, R. Vellore, R. Krishnan, D. Coumou (2020), Tropical and mid-latitude teleconnections interacting with the Indian summer monsoon rainfall: a theory-guided causal effect network approach, Earth System Dynamics, doi: 10.5194/esd-11-17-2020

---- 2019 ----

Runge, J., Nowack, P.,  Kretschmer, M.,  Flaxman, S., Sejdinovic, D. (2019),  Detecting causal associations in large nonlinear time series datasets, Science Advances, doi: 10.1126/sciadv.aau4996

Di Capua, G., M. Kretschmer, J. Runge, A. Alessandri, R. V. Donner, B. van den Hurk, R. Vellore, R. Krishnan, D. Coumou (2019), Long-Lead Statistical Forecasts of the Indian Summer Monsoon Rainfall Based on Causal Precursors, Weather and Forecasting, doi:10.1175/WAF-D-19-0002.1

Runge, J., S. Bathiany, E. Bollt, G. Camps-Valls, D. Coumou, E. Deyle, C. Glymour, M. Kretschmer, M.D. Mahecha, E.H. van Nes, J. Peters, R. Quax, M. Reichstein, M. Scheffer, B. Schölkopf, P. Spirtes, G. Sugihara, J. Sun, K. Zhang, & J. Zscheischler, Inferring causation from time series with perspectives in Earth system sciences (2019), Nature Communication, doi: 10.1038/s41467-019-10105-3

Cohen, J., et al. (incl. Kretschmer, M.) (2019), Divergent consensuses on Arctic amplification influence on midlatitude severe winter weather, Nature Climate Change, doi: 10.1038/s41558-019-0662-y

---- 2018 ----

Kretschmer, M., J. Cohen, V. Matthias, J. Runge, D. Coumou (2018),The different stratospheric influence on cold-extremes in Eurasia and North America, npj Climate and Atmospheric Sciencedoi:10.1038/s41612-018-0054-4

Kretschmer, M., D. Coumou, L. Agel, M. Barlow, E. Tziperman, and J. Cohen (2018), More-persistent weak stratospheric polar vortex states linked to cold extremes, Bulletin of the American Meteorological Society, doi:10.1175/BAMS-D-16-0259.1

---- 2017----

Kretschmer, M., J. Runge, and D. Coumou (2017), Early prediction of extreme stratospheric polar vortex states based on causal precursors, Geophysical Research Letters, doi:10.1002/2017GL074696.

---- 2016 ---- 

Kretschmer, M., D. Coumou, J.F. Donges, J. Runge (2016), Using Causal Effect Networks to analyze different Arctic drivers of mid-latitude winter circulation, Journal of Climate, doi:10.1175/JCLI-D-15-0654.1