collaborators

5 papers

stat.AP2026

Towards Fair Comparisons of AI- and Physics-Based Weather Models for Extreme Events via the Weighted Potential CRPS

Tobias Biegert, Sam Allen, Annika Alber +1

We study whether deterministic AI weather prediction (AIWP) models issue more informative forecasts for extreme weather events than deterministic numerical weather prediction (NWP)…

physics.ao-ph2025

Operational convection-permitting COSMO/ICON ensemble predictions at observation sites (CIENS)

Sebastian Lerch, Benedikt Schulz, Reinhold Hess +4

We present the CIENS dataset, which contains ensemble weather forecasts from the operational convection-permitting numerical weather prediction model of the German Weather Service.…

stat.AP2025

Probabilistic measures afford fair comparisons of AIWP and NWP model output

Tilmann Gneiting, Tobias Biegert, Kristof Kraus +3

We introduce a new measure for fair and meaningful comparisons of single-valued output from artificial intelligence based weather prediction (AIWP) and numerical weather prediction…

stat.AP2025

Probabilistic intraday electricity price forecasting using generative machine learning

Jieyu Chen, Sebastian Lerch, Melanie Schienle +2

The growing importance of intraday electricity trading in Europe calls for improved price forecasting and tailored decision-support tools. In this paper, we propose a novel generat…

cs.LG2025

Learning low-dimensional representations of ensemble forecast fields using autoencoder-based methods

Jieyu Chen, Kevin Höhlein, Sebastian Lerch

Large-scale numerical simulations often produce high-dimensional gridded data that is challenging to process for downstream applications. A prime example is numerical weather predi…