Probabilistic weather forecasting with machine learning

Authors Anna Allen · Stratis Markou · Will Tebbutt · James Requeima · Wessel P. Bruinsma · Tom R. Andersson · Michael Herzog · Nicholas D. Lane · Matthew Chantry · J. Scott Hosking · Richard E. Turner

AI summaryTakes observations directly as input and produces global gridded and local station forecasts, connecting several stages of weather prediction in a trainable system.

Authors Cristian Bodnar · Wessel P. Bruinsma · Ana Lucic · Megan Stanley · Anna Allen · Johannes Brandstetter · Patrick Garvan · Maik Riechert · Jonathan A. Weyn · Haiyu Dong · Jayesh K. Gupta · Kit Thambiratnam · Alexander T. Archibald · Chun-Chieh Wu · Elizabeth Heider · Max Welling · Richard E. Turner · Paris Perdikaris

AI summaryPretrains on diverse geophysical data and adapts to forecasting weather, ocean waves, air quality and tropical cyclone tracks, exploring a foundation model for multiple Earth-system tasks.

Authors Dmitrii Kochkov · Janni Yuval · Ian Langmore · Peter Norgaard · Jamie Smith · Griffin Mooers · Milan Klöwer · James Lottes · Stephan Rasp · Peter Düben · Sam Hatfield · Peter Battaglia · Alvaro Sanchez-Gonzalez · Matthew Willson · Michael P. Brenner · Stephan Hoyer

AI summaryCombines a differentiable dynamical core with neural-network parameterisations to study weather forecasting and climate simulation, including physical consistency over long integrations.

Authors Kaifeng Bi · Lingxi Xie · Hengheng Zhang · Xin Chen · Xiaotao Gu · Qi Tian

AI summaryIntroduces a three-dimensional architecture for Earth data and hierarchical temporal aggregation, improving medium-range forecasts under the study’s reanalysis-based evaluation and reducing iterative errors.