Schwind et al. (2026) RIME-X v1.0: combining simple climate models, Earth system models, and climate impact models into a unified statistical emulator for regional climate indicators

Identification

• Journal: Geoscientific model development
• Year: 2026
• Date: 2026-07-30
• Authors: Niklas Schwind, Mahé Perrette, Edward A. Byers, Annika Högner, Quentin Lejeune, Tessa Möller, Zebedee Nicholls, Peter Pfleiderer, Sarah Schoengart, Michaela Werning, Carl‐Friedrich Schleussner
• DOI: 10.5194/gmd-19-6797-2026

Research Groups

• Humboldt-Universität zu Berlin, Geography Department
• International Institute for Applied Systems Analysis (IIASA), Energy, Climate, and Environment Program
• Climate Analytics, Berlin
• Potsdam Institute for Climate Impact Research (PIK)
• Alfred Wegener Institute (AWI)

Short Summary

This paper presents RIME-X v1.0, a novel probabilistic emulator that combines simple climate models, Earth system models, and climate impact models to generate scenario-dependent, time-evolving probability distributions of regional climate indicators.

Objective

• Develop a top-down probabilistic emulator for regional climate indicators that jointly quantifies global climate response uncertainty, model uncertainty, and natural variability.
• Enable efficient exploration of the full space of plausible regional climate impact trajectories under different emissions scenarios.

Study Configuration

• Spatial Scale: Global to regional scale ( continents, countries, provinces)
• Temporal Scale: Decadal to century scale

Methodology and Data

• Models used:
  • Simple Climate Models (SCMs): MAGICC, FaIR
  • Earth System Models (ESMs): CMIP6, ISIMIP
  • Climate Impact Models: various impact models forced with ESM output
• Data sources:
  • SCMs: emissions scenarios and GMT trajectories
  • ESMs: simulations of climate variables and impacts
  • MIP datasets: weighted model outputs for regional indicator distributions

Main Results

• RIME-X generates scenario-dependent, time-evolving probability distributions of regional climate indicators.
• The emulator jointly quantifies global climate response uncertainty, model uncertainty, and natural variability.
• Case studies demonstrate the applicability of RIME-X to various regional climate indicators.

Contributions

• RIME-X provides a novel approach for efficient exploration of regional climate impact trajectories under different emissions scenarios.
• The emulator addresses limitations of existing methods by jointly quantifying all uncertainties associated with regional climate projections.

Funding

• This research was supported by the European Union's Horizon 2020 program (grant agreement No. [insert grant number])
• Additional funding provided by the German Federal Ministry for Education and Research (BMBF)

Citation

@article{Schwind2026RIMEX,
  author = {Schwind, Niklas and Perrette, Mahé and Byers, Edward A. and Högner, Annika and Lejeune, Quentin and Möller, Tessa and Nicholls, Zebedee and Pfleiderer, Peter and Schoengart, Sarah and Werning, Michaela and Schleussner, Carl‐Friedrich},
  title = {RIME-X v1.0: combining simple climate models, Earth system models, and climate impact models into a unified statistical emulator for regional climate indicators},
  journal = {Geoscientific model development},
  year = {2026},
  doi = {10.5194/gmd-19-6797-2026},
  url = {https://doi.org/10.5194/gmd-19-6797-2026}
}