Publications (FIS)

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

Authored by

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

Organisation(s)
Institute of Environmental Planning
Digital Environmental Planning
External Organisation(s)
ETH Zurich
Type
Article
Journal
Nonlinear processes in geophysics
Volume
33
Pages
73-83
No. of pages
11
ISSN
1023-5809
Publication date
12.02.2026
Publication status
Published
Peer reviewed
Yes
Sustainable Development Goals
SDG 13 - Climate Action
Electronic version(s)
https://doi.org/10.5194/npg-33-73-2026 (Access: Open )

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