TEAM

Gunnar Behrens

Gunnar Behrens

  • Affiliation: DLR & CU
  • PhD Student – WP2
  • Machine learning based parametrizations of sub-grid-scale processes in climate models to enhance understanding on convection and its predictability.


Kevin Debeire

Kevin Debeire

  • Affiliation: DLR (Oberpfaffenhofen & Jena)
  • PhD Student – WP3
  • Causal discovery methods for climate model evaluation and for constraining uncertaninty in climate projection.


Julia Gottfriedsen

Julia Gottfriedsen

  • Affiliation: DLR, Ludwig Maximilian University of Munich
  • PhD Student – WP3
  • Deep learning based drought characterization and understanding of observational and climate model data.


Carolin Grumbach

Carolin Grumbach

  • Affiliation: University of Bremen, DLR, CU
  • PhD Student – WP2
  • Machine learning based schemes for the physical parameterizations in the ICON-A model with focus on the radiation parameterization.


Arthur Grundner

Arthur Grundner

  • Affiliation: DLR & CU
  • PhD Student – WP2
  • Improvement of cloud parameterizations in a climate model by utilizing high-resolution data for the training of machine learning parameterizations.


Fernando Iglesias-Suarez

Dr. Fernando Iglesias-Suarez

  • Affiliation: DLR
  • Postdoctoral Researcher – WP2
  • Climate scientist with a strong interest in developing and applying machine learning techniques to advance climate models and analysis, understanding links and interactions with other parts of the Earth system to address the scientific challenges of global change.
  • Personal webpage


Arndt Kaps

Arndt Kaps

  • Affiliation: DLR, University of Bremen
  • PhD Student – WP1
  • Machine learning based approaches to evaluate clouds in climate models to leverage the information available from satellites and bridge the gap to model data.


Soufiane Karmouche

Soufiane Karmouche

  • Affiliation: University of Bremen, DLR
  • PhD student – WP3
  • Investigating teleconnections between major modes of climate variability with causal discovery


Rémi Kazeroni

Dr. Rémi Kazeroni

  • Affiliation: DLR
  • Research Software Engineer – WP1-4
  • Technical development of the ESMValTool and of machine learning techniques in the ESMValTool framwork.


Aytaç Paçal

  • Affiliation: DLR
  • PhD student – WP3
  • Detecting and understanding extreme weather events using machine learning.


Manuel Schlund

Manuel Schlund

  • Affiliation: DLR
  • PhD Student – WP4
  • Constraining uncertainties in climate model projections with machine learning methods.


Breixo Soliño Fernández

Breixo Soliño Fernández

  • Affiliation: DLR
  • Research Software Engineer – WP1-4
  • Research Software Engineering for Artificial Intelligence topics.
  • Personal webpage


Katja Weigel

Dr. Katja Weigel

  • Affiliation: University of Bremen, DLR
  • Research Scientist – WP3
  • Analysis and detection of extreme events with the focus on droughts in climate model and reanalysis data using classical indices as well as testing new tool like the Maximal Divergent Interval (MDI) algorithm.