Uncertainty and sensitivity analysis for  probabilistic weather and climate risk modelling: an implementation in CLIMADA v.3.1.

This is a Preprint and has not been peer reviewed. The published version of this Preprint is available: https://doi.org/10.5194/gmd-2021-437. This is version 3 of this Preprint.

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Authors

Chahan M. Kropf , Alessio Ciullo, Laura Otth, Simona Meiler, Arun Rana, Emanuel Schmid, Jamie W. McCaughey, David N. Bresch

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.

DOI

https://doi.org/10.31223/X5GS7B

Subjects

Applied Statistics, Climate, Design of Experiments and Sample Surveys, Earth Sciences, Environmental Studies, Natural Resources Management and Policy, Nature and Society Relations, Numerical Analysis and Computation, Numerical Analysis and Scientific Computing, Risk Analysis, Statistical Methodology

Keywords

uncertainty, sensitivity, climate risk, adaptation options

Dates

Published: 2022-02-23 04:52

Last Updated: 2022-04-25 12:49

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License

CC BY Attribution 4.0 International

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