Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 15, issue 8
Articles | Volume 15, issue 8
https://doi.org/10.5194/gmd-15-3183-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-15-3183-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 15, issue 8
Methods for assessment of models
 | 
19 Apr 2022
Methods for assessment of models |  | 19 Apr 2022

An ensemble-based statistical methodology to detect differences in weather and climate model executables

Christian Zeman and Christoph Schär

Data sets

Data for "An Ensemble-Based Statistical Methodology to Detect Differences in Weather and Climate Model Executables" Part 1/2 C. Zeman and C. Schär https://doi.org/10.5281/zenodo.6354200

Data for "An Ensemble-Based Statistical Methodology to Detect Differences in Weather and Climate Model Executables" Part 2/2 C. Zeman and C. Schär https://doi.org/10.5281/zenodo.6355647

Model code and software

Source Code for "An Ensemble-Based Statistical Methodology to Detect Differences in Weather and Climate Model Executables" C. Zeman and C. Schär https://doi.org/10.5281/zenodo.6355694

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Short summary
Our atmosphere is a chaotic system, where even a tiny change can have a big impact. This makes it difficult to assess if small changes, such as the move to a new hardware architecture, will significantly affect a weather and climate model. We present a methodology that allows to objectively verify this. The methodology is applied to several test cases, showing a high sensitivity. Results also show that a major system update of the underlying supercomputer did not significantly affect our model.
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