1 code implementation • 13 Nov 2023 • 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
Here we present the first GCM that combines a differentiable solver for atmospheric dynamics with ML components, and show that it can generate forecasts of deterministic weather, ensemble weather and climate on par with the best ML and physics-based methods.
no code implementations • 20 Jan 2021 • Matthew Chantry, Sam Hatfield, Peter Duben, Inna Polichtchouk, Tim Palmer
By training on an increased complexity version of the existing parameterisation scheme we build emulators that produce more accurate forecasts.
Weather Forecasting Atmospheric and Oceanic Physics Computational Physics