Dienstag, 09. November 2021, 16:30 - 18:00 iCal

Vortrag von Alexander BIHLO

(Memorial University of Newfoundland, St. John's, Canada)


"Deep learning in dynamic meteorology"


Vortrag im Rahmen des Meteorologisch-Geophysikalischen Kolloquiums.



Abstract: Deep learning has seen an unprecedented rise in popularity over the last 10 years or so. The popularity of deep learning has also readily reached geophysical fluid dynamics and dynamic meteorology, with several groups around the world having successfully used deep neural networks for weather forecasting and weather analysis related tasks. In this talk I will showcase two applications of deep learning for weather prediction. The first one relates to the use of generative adversarial networks for weather forecasting based on reanalysis data. The second one illustrates the use of physics-informed neural networks for solving the shallow-water equations on the rotating sphere.


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Institut für Meteorologie und Geophysik


Andreas Plach/Herta Gassner
Institut für Meteorologie und Geophysik