Climate change, historical data and catastrophe modelling

This presentation will discuss climate change in the context of catastrophe modelling and tail risk. Given that the catastrophe modelling industry typical only has short historical records that provide limited information as to whether hazard is non-stationary, what are the methods and datasets that may aid the catastrophe modelling community to better understand how and whether risk is changing temporally? 

The issues will be framed by using examples of output from a multi-year multi-ensemble 60km global climate simulation, where extra-tropical windstorm daily maximum gust data has been converted into yearly aggregate European insurance loss with the help of PERILS European industry exposure data. The data is used to show how reliance on single historical datasets can produce misleading trends in catastrophe losses - but also potentially point to underlying trends in risk that single historical datasets may not be able to detect.