4 papers · 1 filter
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…
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…
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…
Integrating Score-Based Diffusion Models with Machine Learning-Enhanced Localization for Advanced Data Assimilation in Geological Carbon Storage
Gabriel Serrão Seabra, Nikolaj T. Mücke, Vinicius Luiz Santos Silva +3
Accurate characterization of subsurface heterogeneity is important for the safe and effective implementation of geological carbon storage (GCS) projects. This paper explores how ma…