EMS Annual Meeting Abstracts
Vol. 22, EMS2025-551, 2025, updated on 30 Jun 2025
https://doi.org/10.5194/ems2025-551
EMS Annual Meeting 2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Developing guidelines for working with climate multi-model ensembles in CMIP7
Nina Črnivec1, Anja Katzenberger2,3, Evgenia Galytska4,5, Keighan Gemmell6, Jhayron S. Perez-Carrasquilla7, Punya Puthukulangara8, Christine Leclerc9, Indrani Roy10, Arianna Varuolo-Clarke11,12, and Milica Tošić13
Nina Črnivec et al.
  • 1University of Ljubljana, Faculty of mathematics and physics, Ljubljana, Slovenia (nina.crnivec@fmf.uni-lj.si)
  • 2Potsdam Institute of Climate Impact Research, RD4, Potsdam, Germany
  • 3University of Potsdam, Potsdam, Germany
  • 4University of Bremen, Institute of Environmental Physics, Bremen, Germany
  • 5Deutsches Zentrum für Luft- und Raumfahrt (DLR), Institut für Physik der Atmosphäre, Oberpfaffenhofen, Germany
  • 6Department of Chemistry, The University of British Columbia, Vancouver, Canada
  • 7Atmospheric and Oceanic Science Department, University of Maryland, College Park, United States
  • 8Department of Earth and Space Sciences, Indian Institute of Space Science and Technology, Trivandrum, India
  • 9Department of Geography, Simon Fraser University, Burnaby, Canada
  • 10University College London, Earth Science Department, London, UK
  • 11Cooperative Programs for the Advancement of Earth System Science, University Corporation for Atmospheric Research, Boulder, United States
  • 12Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, United States
  • 13University of Belgrade, Faculty of Physics, Belgrade, Serbia

The Earth system models (ESMs) of the WCRP Coupled Model Intercomparison Project (CMIP) are a key tool for making future climate projections and have been continuously developed by various climate modeling communities all over the world over the past decades. The resulting contemporary ESMs are sophisticated tools encoding numerous processes occurring in multiple components of the Earth System such as the atmosphere, ocean, cryosphere, land, and produce a large amount of simulation output data. It remains challenging to analyze, evaluate and interpret the results of such an ensemble of climate models, commonly referred to as the climate multi-model ensemble (MME), to derive actionable information for policy makers and society. Within the international Fresh Eyes on CMIP initiative we have conducted a comprehensive literature review summarizing the newest research studies addressing various issues related to working with climate MMEs. This spans a wide range of matters such as model evaluation including process-oriented assessment, systematic model biases, model selection, model dependencies, weighting methods accounting for model performance and interdependence, uncertainty sources and their characterization, as well as downscaling approaches to acquire regional climate change information. We also discuss how to utilize MMEs to study high-impact weather and climate extreme events, as well as emerging machine learning techniques for analyzing MMEs, single model initial-condition large ensembles (SMILES), and computational resource considerations. We finally give an overview of available open-source software tools and tutorials developed by a broader climate science community which facilitate the MME analysis. We thereby strive to provide guidance on how to best exploit the climate MME in future phases of CMIP particularly in the upcoming CMIP7.

How to cite: Črnivec, N., Katzenberger, A., Galytska, E., Gemmell, K., Perez-Carrasquilla, J. S., Puthukulangara, P., Leclerc, C., Roy, I., Varuolo-Clarke, A., and Tošić, M.: Developing guidelines for working with climate multi-model ensembles in CMIP7, EMS Annual Meeting 2025, Ljubljana, Slovenia, 7–12 Sep 2025, EMS2025-551, https://doi.org/10.5194/ems2025-551, 2025.