27 citations · 28 across the 11 of their papers we have counts for
4 papers · 1 filter
EBCC v0.2: Error bounded compression for weather and climate applications
Langwen Huang, Luigi Fusco, Florian Scheidl +5
As the resolution of weather and climate simulations increases, the amount of data produced is growing rapidly from hundreds of terabytes to tens of petabytes. These data volumes l…
FedRAIN-Lite: Federated Reinforcement Algorithms for Improving Idealised Numerical Weather and Climate Models
Pritthijit Nath, Sebastian Schemm, Henry Moss +3
Sub-grid parameterisations in climate models are traditionally static and tuned offline, limiting adaptability to evolving states. This work introduces FedRAIN-Lite, a federated re…
Finetuning a Weather Foundation Model with Lightweight Decoders for Unseen Physical Processes
Fanny Lehmann, Firat Ozdemir, Benedikt Soja +3
Recent advances in AI weather forecasting have led to the emergence of so-called "foundation models", typically defined by expensive pretraining and minimal fine-tuning for downstr…
Building Machine Learning Limited Area Models: Kilometer-Scale Weather Forecasting in Realistic Settings
Simon Adamov, Joel Oskarsson, Leif Denby +8
Machine learning is revolutionizing global weather forecasting, with models that efficiently produce highly accurate forecasts. Apart from global forecasting there is also a large…