1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.LG2026
Advancing Subseasonal Forecasting with Machine Learning
Hannah Guan, Soukayna Mouatadid, Paulo Orenstein +10
Decision-makers rely on weather forecasts to plant crops, manage wildfires, allocate water and energy, and prepare for weather extremes. Today, such forecasts enjoy unprecedented a…
physics.ao-ph2024★ 1 cited
An ensemble of data-driven weather prediction models for operational sub-seasonal forecasting
Jonathan A. Weyn, Divya Kumar, Jeremy Berman +4
We present an operations-ready multi-model ensemble weather forecasting system which uses hybrid data-driven weather prediction models coupled with the European Centre for Medium-r…