Articles | Volume 15, issue 18
Geosci. Model Dev., 15, 7177–7201, 2022
https://doi.org/10.5194/gmd-15-7177-2022
Geosci. Model Dev., 15, 7177–7201, 2022
https://doi.org/10.5194/gmd-15-7177-2022
Development and technical paper
23 Sep 2022
Development and technical paper | 23 Sep 2022

Uncertainty and sensitivity analysis for probabilistic weather and climate-risk modelling: an implementation in CLIMADA v.3.1.0

Chahan M. Kropf et al.

Data sets

Probabilistic storm surge hazard event set for Vietnam on 30 arcsecond resolution (2020 and 2050) C. M. Kropf, Arun Rana, and Qinhan Zhu https://doi.org/10.3929/ethz-b-000566528

Model code and software

CLIMADA-project/climada_python: v3.1.0 Chahan M. Kropf, Emanuel Schmid, Gabriela Aznar-Siguan, Samuel Eberenz, Thomas Vogt, Carmen B. Steinmann, Thomas Röösli, Samuel Lüthi, Inga J. Sauer, Evelyn Mühlhofer, Jan Hartman, Benoit P. Guillod, Zélie Stalhandske, Alessio Ciullo, Chris Fairless, Pui Man (Mannie) Kam, wjan262, Simona Meiler, Rachel Bungener, Veronica Bozzini, Dario Stocker, and David N. Bresch https://doi.org/10.5281/zenodo.5947271

Probabilistic storm surge hazard event set for Vietnam on 30 arcsecond resolution (2020 and 2050) C. M. Kropf, Arun Rana, and Qinhan Zhu https://doi.org/10.3929/ethz-b-000566528

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Short summary
Mathematical models are approximations, and modellers need to understand and ideally quantify the arising uncertainties. Here, we describe and showcase the first, simple-to-use, uncertainty and sensitivity analysis module of the open-source and open-access climate-risk modelling platform CLIMADA. This may help to enhance transparency and intercomparison of studies among climate-risk modellers, help focus future research, and lead to better-informed decisions on climate adaptation.