Advanced climate model evaluation with ESMValTool v2.11.0 using parallel, out-of-core, and distributed computing

Schlund, Manuel; Andela, Bouwe; Benke, Jörg; Comer, Ruth; Hassler, Birgit; Hogan, Emma; Kalverla, Peter; Lauer, Axel; Little, Bill; Loosveldt Tomas, Saskia; Nattino, Francesco; Peglar, Patrick; Predoi, Valeriu; Smeets, Stef; Worsley, Stephen; Yeo, Martin; Zimmermann, Klaus

doi:https://doi.org/10.5194/gmd-18-4009-2025

Articles | Volume 18, issue 13

https://doi.org/10.5194/gmd-18-4009-2025

© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/gmd-18-4009-2025

© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 18, issue 13

Methods for assessment of models

|

02 Jul 2025

Methods for assessment of models |

| 02 Jul 2025

Advanced climate model evaluation with ESMValTool v2.11.0 using parallel, out-of-core, and distributed computing

Manuel Schlund, Bouwe Andela, Jörg Benke, Ruth Comer, Birgit Hassler, Emma Hogan, Peter Kalverla, Axel Lauer, Bill Little, Saskia Loosveldt Tomas, Francesco Nattino, Patrick Peglar, Valeriu Predoi, Stef Smeets, Stephen Worsley, Martin Yeo, and Klaus Zimmermann

Model code and software

Supplementary material for "Advanced climate model evaluation with ESMValTool v2.11.0 using parallel, out-of-core, and distributed computing" Manuel Schlund and Bouwe Andela https://doi.org/10.5281/zenodo.14361733

Iris Iris contributors https://doi.org/10.5281/zenodo.595182

ESMValTool Bouwe Andela et al. https://doi.org/10.5281/zenodo.12654299

ESMValCore Bouwe Andela et al. https://doi.org/10.5281/zenodo.14224938

Short summary

The Earth System Model Evaluation Tool (ESMValTool) is a community diagnostics and performance metrics tool for the evaluation of Earth system models. Here, we describe recent significant improvements of ESMValTool’s computational efficiency including parallel, out-of-core, and distributed computing. Evaluations with the enhanced version of ESMValTool are faster, use less computational resources, and can handle input data larger than the available memory.