21 citations · 49 across the 18 of their papers we have counts for
8 papers · 1 filter
ArchesWeather & ArchesWeatherGen: a deterministic and generative model for efficient ML weather forecasting
Guillaume Couairon, Renu Singh, Anastase Charantonis +2
Weather forecasting plays a vital role in today's society, from agriculture and logistics to predicting the output of renewable energies, and preparing for extreme weather events.…
Robustness of AI-based weather forecasts in a changing climate
Thomas Rackow, Nikolay Koldunov, Christian Lessig +9
Data-driven machine learning models for weather forecasting have made transformational progress in the last 1-2 years, with state-of-the-art ones now outperforming the best physics…
Machine Learning for the Physics of Climate
Annalisa Bracco, Julien Brajard, Henk A. Dijkstra +3
An exponential growth in computing power, which has brought more sophisticated and higher resolution simulations of the climate system, and an exponential increase in observations…
Data driven weather forecasts trained and initialised directly from observations
Anthony McNally, Christian Lessig, Peter Lean +11
Skilful Machine Learned weather forecasts have challenged our approach to numerical weather prediction, demonstrating competitive performance compared to traditional physics-based…
Emerging AI-based weather prediction models as downscaling tools
Nikolay Koldunov, Thomas Rackow, Christian Lessig +5
The demand for high-resolution information on climate change is critical for accurate projections and decision-making. Presently, this need is addressed through high-resolution cli…
AIFS -- ECMWF's data-driven forecasting system
Simon Lang, Mihai Alexe, Matthew Chantry +13
Machine learning-based weather forecasting models have quickly emerged as a promising methodology for accurate medium-range global weather forecasting. Here, we introduce the Artif…