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cs.LG2026
EC-EarthFlow: Probabilistic emulation of daily transient global climate model simulations with flow matching
Kirien Whan, Nikolaj T. Mücke, Karin van der Wiel
We introduce EC-EarthFlow, a generative flow matching model that emulates simulations from the physical climate model EC-Earth3. The model is trained on transient simulations from…
cs.LG2026
Xaurora: Generative Weather Forecasting with Denoising Stochastic Interpolants from a Foundation Model Prior
Eliot Walt, Miltiadis Kofinas, Nikolaj Mücke +2
Deep learning has revolutionised weather forecasting in recent years, especially through atmospheric foundation models, which offer competitive skill for a fraction of the computat…
cs.LG2026
A Unified Framework for Bayesian Data Assimilation with Generative Models and Observation Interpolants
Nikolaj T. Mücke, Benjamin Sanderse
Bayesian data assimilation combines model forecasts with noisy observations, but sampling high-dimensional, non-Gaussian posteriors remains challenging. We introduce an observation…