How deep learning improves weather forecasts and reduces energy demands

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 today's 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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The views and opinions expressed are those of the panelists and do not reflect the official policy of the ITU.