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MOOC MLWC - 1. ML in Weather & Climate

This course includes 6 modules and is as introduction to the main topics, from the processing of observations to data assimilation, forecasting and post-processing.


Last updated: 29 June 2023
Enrolled students: 10.6K+

Multi-lesson course

Course Content

  • Experts' opinions on Machine Learning (🕓25 min)
  • What is Machine Learning and what types of Machine Learning are there? (🕓 10 min)
  • Why should we consider machine learning for weather and climate modelling? (🕓 15 min)
  • Challenges for Machine Learning in weather and climate modelling (🕓 10 min)
  • State-of-the-art and challenges of using observations in NWP (🕓 15 min)
  • How can Machine Learning help for observation processing in NWP? (🕓 10 min)
  • Machine learning for the processing of spatial data (🕓 15 min)
  • Concept and state-of-the-art (🕓 15 min)
  • Forecasting with ML (🕓 10 min)
  • WeatherBench (🕓 30 min)
  • Quiz
  • A 10 minute Introduction to Data Assimilation (🕓 12 min)
  • Similarities between Data Assimilation and Machine Learning (🕓 18 min)
  • Concept and state-of-the-art (🕓 15 min)
  • Post-processing with ML (🕓 12 min)
  • The WMO S2S challenge (🕓 9 min)
  • The synergies between machine learning and high-performance computing (🕓 15 min)
  • Interactive map of supercomputers (🕓 10 min)
  • Machine Learning with HPC (🕓 15 min)
  • Cloud Computing and European Weather Cloud (🕓 18 min)

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