Quantifying uncertainty in stochastic tropical cyclone hazard generators

Valentina and Tom have been working with scientists at U. Bristol, Potsdam and VU Amsterdam to quantify uncertainty and sensitivity test key uncertainty parameters in stochastic Tropical Cyclone (TC) track generators. 
We have developed an open-source modelling platform for the transparent quantification and attribution of uncertainty, by combining an open-source Global Sensitivity Analysis tool (SAFE, Sensitivity Analysis For Everybody [Pianosi et al., 2015]) with an open source, risk-focused, Tropical Cyclone hazard generator (STORM, Synthetic Tropical cyclOne geneRation Model [Bloemendaal et al., 2020]) freely available on GitHub. We have quantified the impact uncertainty in the historical hurricane dataset (IBTrACs) has on the model output (expressed as the number of hurricanes making landfall per year) and translated this impact to insurance losses as parametric insurance payouts. 
Quantifying TC uncertainty openly in the present will enable extrapolation and communication of expected changes in this peril due to climate change.