Preprints
https://doi.org/10.5194/gmd-2021-437
https://doi.org/10.5194/gmd-2021-437
Submitted as: development and technical paper
25 Apr 2022
Submitted as: development and technical paper | 25 Apr 2022
Status: this preprint is currently under review for the journal GMD.

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

Chahan M. Kropf1,2, Alessio Ciullo1,2, Laura Otth1, Simona Meiler1,2, Arun Rana3, Emanuel Schmid1, Jamie W. McCaughey1,2, and David N. Bresch1,2 Chahan M. Kropf et al.
  • 1Institute for Environmental Decisions, ETH Zurich, Universitätstr. 16, 8092 Zurich, Switzerland
  • 2Federal Office of Meteorology and Climatology MeteoSwiss, Operation Center 1, P.O. Box 257, 8058 Zurich-Airport, Switzerland
  • 3Frankfurt School of Finance and Management gemeinnützige GmbH, Adickesallee 32-34, 60322 Frankfurt am Main, Germany

Abstract. Modelling the risk of natural hazards for society, ecosystems, and the economy is subject to strong uncertainties, even more so in the context of a changing climate, evolving societies, growing economies, and declining ecosystems. Here we present a new feature of the climate risk modelling platform CLIMADA which allows to carry out global uncertainty and sensitivity analysis. CLIMADA underpins the Economics of Climate Adaptation (ECA) methodology which provides decision makers with a fact-base to understand the impact of weather and climate on their economies, communities, and ecosystems, including appraisal of bespoke adaptation options today and in future. We apply the new feature to an ECA analysis of risk from tropical cyclone storm surge to people in Vietnam to showcase the comprehensive treatment of uncertainty and sensitivity of the model outputs, such as the spatial distribution of risk exceedance probabilities or the benefits of different adaptation options. We argue that broader application of uncertainty and sensitivity analyses will enhance transparency and inter-comparison of studies among climate risk modellers and help focus future research. For decision-makers and other users of climate risk modelling, uncertainty and sensitivity analysis has the potential to lead to better-informed decisions on climate adaptation. Beyond provision of uncertainty quantification, the presented approach does contextualise risk assessment and options appraisal, and might be used to inform the development of story-lines and climate adaptation narratives.

Chahan M. Kropf et al.

Status: open (until 20 Jun 2022)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse

Chahan M. Kropf et al.

Chahan M. Kropf et al.

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