Modelling the evolution of the financial impacts of flood and storm surge between 2015 and 2050 in France

Abstract

CCR (Caisse Centrale de Réassurance) is a French reinsurance company playing a major role in the natural catastrophe coverage in France. Since 2003, CCR has been developing tools for the estimation of its exposure to climatic risks. These tools cover three main perils: flood, storm surge and drought. Models are used to estimate the insurance losses and are systematically used for all major climatic events. Both modelling calibration and validation are based on an important policy and claim database. It was created in 2003 and supplied every year with insurer's data. In order to evaluate the financial exposure for insurance of extreme events, a stochastic approach has been developed since 2011, for flood, storm surge and drought. The simulation of the stochastic event set allows us to estimate the mean annual losses and losses associated with different return periods. The objective of this approach is to connect the impact models for all perils with a large set of climate simulations. ARPEGE-Climate (Météo-France) is a model that is used to generate two sets of 200 years of hourly atmospheric time series: at current conditions and at year 2050 conditions according to RCP (Representative Concentration Pathways) 4.5. The main climate data used are: hourly rainfall, wind speed and atmospheric pressure and the Soil Wetness Index that is issued from a complementary surface model. The hazard and vulnerability models developed are based on the climatic data to compute continuous loss estimations. The method proposed will take into consideration development scenarios to evaluate the consequences of demographic growth and insured values evolution. The simulations show a global loss increase in 2050 which can be attributed to climatic factors such as extreme rainfall increase or sea level rise as well as, for a major part, the population and insured value growth in areas at risk.

An Innovative Damage Model for Crop Insurance, Combining Two Hazards into a Single Climatic Index

“…The next steps of the project, in partnership with Meteo-France, will be to apply our model on the ARPEGE-Climat simulations to predict evolution of the yield losses due to climate change for the 2050 horizon [19,54,55]. For this future study, two sets of climatic simulations will be available for this project: 400 simulations of the same year in current climate conditions (year 2000) and 400 simulations in future climate conditions, with the RCP 8.5 (Representative Concentration Pathway) forcing values (year 2050).…”

“…is part of the reflections. For many years, CCR has developed catastrophe models to evaluate the financial impact of natural disasters on residential and commercial insured values [17][18][19]. To improve knowledge on agriculture exposure to climatic events, CCR, in association with Agrocampus Ouest, is supervising a PhD project.…”

Urban surface water flood modelling – a comprehensive review of current models and future challenges

“…Apart from the models reviewed in Sect. 3.1 and 3.2, an emerging method, the hydrogeomorphic approach, has been recently developed for flood hazard management and mapping (Nardi et al, 2013;Zheng et al, 2018). Unlike the physical-based models above, hydrogeomorphic approaches are based on the concept of fractal river basins or hydrogeomorphic theories, and floodplains are identified as unique morphologic landscape features.…”

“…the diffusive version of LISFLOOD-FP (Bates et al, 2010), CityCAT (Glenis et al, 2018), and HiPIMS (Xia et al, 2019); (3) hydrogeomorphic approaches that predict the inundation area based on geomorphic features (e.g. Nardi et al, 2013;Di Baldassarre et al, 2020); and (4) other methods such as cellular automata (CA) and artificial neural networks (ANNs) (Ghimire et al, 2013;Guidolin et al, 2016;Berkhahn et al, 2019).…”

Urban surface water flood modelling – a comprehensive review of current models and future challenges

“…CC BY 4.0 License. 2013; Moncoulon et al, 2016). Therefore, it is crucial for effective flood risk management and to develop modelling techniques that simulate and predict the dynamic processes of cloudburst-induced urban flooding.…”