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Showing 1–4 of 4 results
Advanced filters: Author: Peter Dueben Clear advanced filters

  • The rapid emergence of deep learning is attracting growing private interest in the traditionally public enterprise of numerical weather and climate prediction. A public–private partnership would be a pioneering step to bridge between physics- and data-based methods, and necessary to effectively address future societal challenges.

    • Peter Bauer
    • Peter Dueben
    • Bjorn Stevens
    Comments & Opinion
    Nature Reviews Earth & Environment
    Volume: 4, P: 507-509

  • GenCast, a probabilistic weather model using artificial intelligence for weather forecasting, has greater skill and speed than the top operational medium-range weather forecast in the world and provides probabilistic, rather than deterministic, forecasts.

    • Ilan Price
    • Alvaro Sanchez-Gonzalez
    • Matthew Willson
    ResearchOpen Access
    Nature
    Volume: 637, P: 84-90

  • There have been substantial developments in weather and climate prediction over the past few decades, attributable to advances in computational science. The rise of new technologies poses challenges to these developments, but also brings opportunities for new progress in the field.

    • Peter Bauer
    • Peter D. Dueben
    • Nils P. Wedi
    Reviews
    Nature Computational Science
    Volume: 1, P: 104-113