A climate-conditioned catastrophe risk model for UK flooding

Abstract

We present a transparent and validated climate-conditioned catastrophe flood model for the UK, that simulates pluvial, fluvial and coastal flood risks at 1garcsec spatial resolution (g1/4g20-25gm). Hazard layers for 10 different return periods are produced over the whole UK for historic, 2020, 2030, 2050 and 2070 conditions using the UK Climate Projections 2018 (UKCP18) climate simulations. From these, monetary losses are computed for five specific global warming levels above pre-industrial values (0.6, 1.1, 1.8, 2.5 and 3.3ggC). The analysis contains a greater level of detail and nuance compared to previous work, and represents our current best understanding of the UK's changing flood risk landscape. Validation against historical national return period flood maps yielded critical success index values of 0.65 and 0.76 for England and Wales, respectively, and maximum water levels for the Carlisle 2005 flood were replicated to a root mean square error (RMSE) of 0.41gm without calibration. This level of skill is similar to local modelling with site-specific data. Expected annual damage in 2020 was GBPg730 million, which compares favourably to the observed value of GBPg714 million reported by the Association of British Insurers. Previous UK flood loss estimates based on government data are g1/4g3× higher, and lie well outside our modelled loss distribution, which is plausibly centred on the observations. We estimate that UK 1g% annual probability flood losses were g1/4g6g% greater for the average climate conditions of 2020 (g1/4g1.1ggC of warming) compared to those of 1990 (g1/4g0.6ggC of warming), and this increase can be kept to around g1/4g8g% if all countries' COP26 2030 carbon emission reduction pledges and "net zero"commitments are implemented in full. Implementing only the COP26 pledges increases UK 1g% annual probability flood losses by 23g% above average 1990 values, and potentially 37g% in a "worst case"scenario where carbon reduction targets are missed and climate sensitivity is high.