Quantifying uncertainty and sensitivity in climate risk assessments: Varying hazard, exposure and vulnerability modelling choices

Open-source climate risk assessment platforms allow for accessible and efficient estimation of current future by combining information about hazard, exposure vulnerability. Such assessments require making a number choices, such as which hazard data source to use, the approach taken represent As these choices are, some extent, subjective, when assessing informing adaptation decisions, alternative options should be considered understand uncertainty sensitivity uncertain input assumptions. We present novel quantify estimates, using CLIMADA open-source platform. This work builds upon recently developed extension CLIMADA, uses statistical modelling techniques model stochastically simulate realisations risk, allowing richer quantification ensemble uncertainty. Here, we further analyse propagation vulnerability uncertainties varying factors based on discrete, scientifically justified set options. explore variations, PAWN (PiAnosi WagNer) method global analysis, an attribution different drivers total budget. demonstrate through application assess heat-stress outdoor physical working capacity in UK. In this application, how estimated across plausible settings better captures extreme outcomes (important decision making); that all uncalibrated/non-bias-adjusted sources underestimate recent past (highlighting need calibration); warming level framing is used it choice most sensitive (2 °C or 4 warmer than pre-industrial), particularly south highlights importance mitigating change reduce risk.