Details

Developing Guidelines for working with Multi-Model Ensembles in CMIP
ID Katzenberger, Anja (Author), ID Perez-Carrasquilla, Jhayron S. (Author), ID Gemmell, Keighan (Author), ID Galytska, Evgenia (Author), ID Leclerc, Christine (Author), ID Puthukulangara, Punya (Author), ID Roy, Indrani (Author), ID Varuolo-Clarke, Arianna (Author), ID Tošić, Milica (Author), ID Črnivec, Nina (Author)

URLURL - Source URL, Visit https://esd.copernicus.org/articles/17/495/2026/ This link opens in a new window
.pdfPDF - Presentation file, Download (5,38 MB)
MD5: 512F1DFC5F74530AE6C7C622FE41355E

Abstract
Earth System Models (ESMs) are a key tool for studying the climate under changing conditions. Over recent decades, it has been established to not only rely on projections of a single model but to combine various ESMs in multi-model ensembles (MMEs) to improve robustness and quantify the uncertainty of the projections. The data access for MME studies has been fundamentally facilitated by the World Climate Research Programme's Coupled Model Intercomparison Project (CMIP) – a collaborative effort bringing together ESMs from modelling communities all over the world. Despite the CMIP standardization processes, addressing specific research questions using MMEs requires unique ensemble design, analysis, and interpretation choices. Based on the collective expertise within the Fresh Eyes on CMIP initiative, mainly composed of early-career researchers engaged in CMIP, we have identified common issues and questions encountered while working with climate MMEs. Here, we provide a comprehensive literature review addressing these questions. We provide statistics tracing the development of the climate MMEs analysis field throughout the last decades, and, synthesizing existing studies, we outline guidelines regarding model evaluation, model dependence, weighting methods, and uncertainty treatment. We summarize a collection of useful resources for MME studies, we review common questions and strategies, and finally, we outline emerging scientific trends, such as the integration of machine learning (ML) techniques, single model initial-condition large ensembles (SMILEs), and computational resource considerations. We thereby aim to support researchers working with climate MMEs, particularly in the upcoming 7th phase of CMIP.

Language:English
Keywords:climatology, climate models, CMIP project, multi-model ensembles
Work type:Article
Typology:1.02 - Review Article
Organization:FMF - Faculty of Mathematics and Physics
Publication status:Published
Publication version:Version of Record
Year:2026
Number of pages:Str. 495–532
Numbering:Vol. 17, iss. 3
PID:20.500.12556/RUL-182478 This link opens in a new window
UDC:551.58
ISSN on article:2190-4987
DOI:10.5194/esd-17-495-2026 This link opens in a new window
COBISS.SI-ID:277848579 This link opens in a new window
Publication date in RUL:13.05.2026
Views:251
Downloads:211
Metadata:XML DC-XML DC-RDF
:
Copy citation
Share:Bookmark and Share

Record is a part of a journal

Title:Earth system dynamics
Publisher:Copernicus Publ.
ISSN:2190-4987
COBISS.SI-ID:522761753 This link opens in a new window

Licences

License:CC BY 4.0, Creative Commons Attribution 4.0 International
Link:http://creativecommons.org/licenses/by/4.0/
Description:This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.

Secondary language

Language:Slovenian
Keywords:klimatologija, klimatski modeli, projekt CMIP, večmodelni pristop

Projects

Funder:ARIS - Slovenian Research and Innovation Agency
Project number:P1-0188
Name:Astrofizika in fizika atmosfere

Funder:Other - Other funder or multiple funders
Funding programme:Univerza v Ljubljani
Project number:SN-ZRD/22-27/510
Name:Napredne podnebno odporne rešitve za trajnostno biogospodarstvo in družbeno-ekonomski razvoj
Acronym:A-RISE

Funder:NOAA - National Oceanic and Atmospheric Administration
Project number:NA20OAR4310390

Funder:NASA - National Aeronautics and Space Administration
Funding programme:Modeling, Analysis, and Prediction Program
Project number:80NSSC21K1134

Similar documents

Similar works from RUL:
Similar works from other Slovenian collections:

Back