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

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.

Intercomparison of regional loss estimates from global synthetic tropical cyclone models

“…Besides, we suggest investigating the uncertainty and sensitivity of the TC impact model to the numerous input variables; including, but not limited to, the different TC track sets. This may be achieved by applying readily available uncertainty and (global) sensitivity analysis software [51][52][53] . The resulting insights can guide where the next improvements in TC impact modeling can be achieved.…”

Intercomparison of regional loss estimates from global synthetic tropical cyclone models

“…Besides, we suggest investigating the uncertainty and sensitivity of the TC impact model to the numerous input variables; including, but not limited to, the different TC track sets. This may be achieved by applying readily available uncertainty and (global) sensitivity analysis software [49][50][51] .…”

A Generalized Natural Hazard Risk Modelling Framework for Infrastructure Failure Cascades

“…More in-depth characterization of the uncertainties can then be carried-out by focusing on the identified sensitivities (see [58] for a comprehensive discussion on best practices and recommendations, catering specifically to the field of environmental modelling, and [59] for an exemplary computational workflow designed for uncertainty propagating in and multi-level sensitivity analysis of hierarchical systems, particularly interdependent CI networks). Much can be done directly in CLIMADA using the 'unsequa' module that provides readily usable methods for state-of-the art global uncertainty quantification and sensitivity analysis based on quasi-Monte Carlo sampling [60]. In addition, the probabilistic hazard modelling approach may help estimating representational uncertainties on the trigger side.…”