Jun.-Prof. Dr. Sebastian Sippel

Jun.-Prof. Dr. Sebastian Sippel

Junior Professor

Klima-Attribution (JP)
Talstraße 35, Room 1-07
04103 Leipzig

Phone: +49 341 97-32882


I'm a Junior Professor for Climate Attribution at the Leipzig Institute for Meteorology with a key research interest in improving our understanding of climate variability, extremes and their changes at global and regional scales. My research interests also include the implications of global climate changes for impact-relevant variables such as the hydrological cycle at regional scale, ecosystem water-carbon cycling, and society at large. The bulk of my research is closely linked to climate change detection and attribution. I use modern empirical-quantitative statistical and machine learning methods to address these broad research questions, integrating various climate and Earth science data streams such as gridded climate observations and climate model simulations.

Professional career

  • since 04/2023
    Junior Professor for Climate Attribution at Leipzig University, Institute for Meteorology.
  • 03/2018 - 03/2023
    PostDoc and Senior Scientist (2021 onwards) at ETH Zurich, Climate Physics Group.
  • 09/2017 - 03/2018
    Research Scientist (Forsker) at the Norwegian Institute of Bioeconomy Research, Ås.
  • 05/2017 - 08/2017
    PostDoc at the Max Planck Institute for Biogeochemistry, Jena
  • 04/2014 - 05/2017
    PhD thesis at the Max Planck Institute for Biogeochemistry and ETH Zurich, Thesis title: ‘Climate extremes and their impact on ecosystem–atmosphereinteractions’.


  • 09/2012 - 09/2013
    Master of Sciences in Environmental Change and Management, University of Oxford.
  • 10/2011 - 03/2014
    M.Sc. in Geoecology-Environmental Sciences, Major in Environmental Physics, Bayreuth University.
  • Detection, attribution, and understanding of forced climate change and climate variability at global and regional scale
  • Water & carbon cycling under climate variability and extremes, and their interactions
  • Data Science and statistical learning for meteorology, climate and Earth system science
  • Data diagnostics and model evaluation

  • Climate variability and extreme events
  • Biogeochemical cycles
  • 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

For possible thesis topics (B.Sc., M.Sc.) around the above mentioned topics please contact me.

  • Introduction to Advanced Data Analytics (5 ECTS)

    • Lecture Statistical and Machine Learning for Earth System Sciences. Mon, 13-14.30 Seminarraum 1 0.06, Talstr. 35
    • Practicals Data Analysis with Statistical and Machine Learning. Mon, 14.30-16 biweekly, Seminarraum 1 0.06, Talstr. 35