Simon Adamov

Stochastically Perturbed Weights: Ensembles from Deterministic Machine-Learning Weather Models

Machine-learning weather models (MLWMs) now match or outperform operational numerical weather prediction (NWP) at global medium-range forecasting, at far lower inference cost. Many deployed MLWMs are deterministic, producing a single forecast with no estimate of its own uncertainty, whereas a growing family of trained-...