Lost (and found) in latent land
AI and machine learning boost weather and climate models’ accuracy. Analysing latent spaces reveals new insights on water, carbon, and atmospheric processes, improving model understanding.
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Data: 14 novembre 2025 dalle 16:30 alle 17:30
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Luogo: AULA 4 - FISICA Piano Primo Interrato viale Berti Pichat 6-6/2 BOLOGNA
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Modalità d'accesso: Ingresso libero
EVENTO IN FORMATO IBRIDO
Machine learning and artificial intelligence have been revolutionizing weather and climate modeling and data analysis over the past few years. However, it remains unclear how much understanding has been gained from those models, even though they are reaching unprecedented accuracy. Through the study and analysis of carefully chosen latent spaces, I will demonstrate how we can get new understanding on the terrestrial water and carbon cycle as well as on atmospheric processes, specifically on convection. Those latent spaces can also be used to better characterize complex stochastic processes such as turbulence and combined with data assimilation in order to achieve improved performance in those models.
Partecipanti:
Pierre Gentine, Department of Earth and Environmental Engineering & Department of Earth and Environmental Sciences, Columbia University, USA