Physical and data-driven modelling for Earth observation
talk on Physical and data-driven modelling for Earth observation at the Workshop on Challenges and Benchmarks for quantitative AI in Complex Fluids and Complex Flows organised by Luca Biferale et al..
Abstract: The European Space Agency (ESA) Φ-lab investigates the use of new Artificial Intelligence methods which can accelerate and transform Earth observation and Earth system modelling. We present a few use-cases in Earth sciences where the physical modelling of phenomena (e.g., by means of fluid dynamics of the atmosphere) could be combined and improved by machine learning based on observations from satellites and meteorological records. We will discuss cloud dynamics, rain prediction, cyclone forecasts, etc.
Slides: Physical and data-driven modelling for Earth observation