Deep Learning for Weather and Air Quality

Team Goals:

  • Develop the advanced foundation model AtmoRep for atmospheric dynamcis
  • Enhance statistical downscaling methods for meteorological and air quality data
  • Establish novel timeseries prediction methods for air pollutants with deep learning
  • Investigate the application of physical constraints in data-driven deep learning techniques
  • Fuse observations, geospatial data and numerical simulation output
  • Optimize scalability of deep learning on HPC systems

Projects

Members

+49 2461/61-9004
+49 2461/61-9004
+49 2461/61-9004

News from IntelliC&W

jülich - Oct 2022

MAELSTROM hackathon

The main goal is to train the PhD and master to get familiar with ML in WC domain

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Last Modified: 09.08.2023