4 papers
CRPS-LAM: Probabilistic Regional Weather Forecasting with Continuous Ranked Probability Score
Erik Larsson, Joel Oskarsson, Tomas Landelius +1
Limited-Area Models (LAMs) enable weather forecasting over regional domains at higher resolutions than what is computationally feasible for global models. At such high resolutions,…
DAISI: Data Assimilation with Inverse Sampling using Stochastic Interpolants
Martin Andrae, Erik Wikingsson, So Takao +2
Data assimilation (DA) is a cornerstone of scientific and engineering applications, combining model forecasts with sparse and noisy observations to estimate latent system states. C…
Climate Downscaling with Stochastic Interpolants (CDSI)
Erik Larsson, Ramon Fuentes-Franco, Mikhail Ivanov +1
Global climate projections rely on computationally demanding Earth System Models (ESMs), which are typically limited to coarse spatial resolutions due to their high cost. To obtain…
Diffusion-LAM: Probabilistic Limited Area Weather Forecasting with Diffusion
Erik Larsson, Joel Oskarsson, Tomas Landelius +1
Machine learning methods have been shown to be effective for weather forecasting, based on the speed and accuracy compared to traditional numerical models. While early efforts prim…