How deep learning improves weather forecasts and reduces energy demands

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  • Date
    15 January 2025
    Timeframe
    17:00 - 18:00 CET Geneva
    Duration
    60 minutes
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    Deep learning weather prediction (DLWP) models are about to outperform traditional numerical weather prediction (NWP) models. In this talk, we will review the evolution of deep learning for weather prediction and hypothesize what we may expect in the next years and what not. Beyond that, we will search for explanations by contrasting potentials and limitations of todays DLWP and NWP models. Among those, we will understand how DLWP can drastically reduce energy consumption and where machine learning helps us in understanding land-atmosphere interactions processes.

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