Publikationen (FIS)

MESMER-RCM: a probabilistic climate emulator for regional warming projections

Verfasst von

Hao Pan, Lukas Gudmundsson, Mathias Hauser, Jonas Schwaab, Yann Quilcaille, Sonia I. Seneviratne

Abstract

Abstract. Regional Climate Model (RCM) emulators enable rapid and computationally efficient RCM projections given Global Climate Model (GCM) inputs, complementing dynamical downscaling by approximating physical representations with statistical models. However, while existing RCM emulators perform well in deterministic emulations, they do not sample internal RCM variability and remain computationally expensive. Here, we present MESMER-RCM, a probabilistic RCM emulator designed for spatially resolved annual 2 m temperature. MESMER-RCM is a generative model that enables both data-efficient learning and interpretability. It can generate large ensembles of synthetic, yet physically plausible, RCM realizations, capturing the internal RCM variability at a fraction of the computational cost. This work offers a fast and reliable RCM emulation framework, supporting finer-scale what-if analyses of regional climate responses and informing local adaptation and mitigation strategies.

Details

Organisationseinheit(en)
Institut für Umweltplanung
Digitale Umweltplanung
Externe Organisation(en)
ETH Zürich
Typ
Artikel
Journal
Nonlinear processes in geophysics
Band
33
Seiten
73-83
Anzahl der Seiten
11
ISSN
1023-5809
Publikationsdatum
12.02.2026
Publikationsstatus
Veröffentlicht
Peer-reviewed
Ja
Ziele für nachhaltige Entwicklung
SDG 13 - Klimaschutzmaßnahmen
Elektronische Version(en)
https://doi.org/10.5194/npg-33-73-2026 (Zugang: Offen )