Flood event attribution and damage estimation using national‐scale grid‐based modelling: Winter 2013/2014 in Great Britain

Abstract

A sequence of major flood events in Britain over the last two decades has prompted questions about the influence of anthropogenic greenhouse gas emissions on flood risk. Such questions are difficult to answer definitively, as a range of other factors are involved, but modelling techniques allow an assessment of how much the chance of occurrence of an event could have been altered by emissions. Here the floods of winter 2013/2014 in Great Britain are assessed by combining ensembles of climate model data with a national‐scale hydrological model and, for one severely impacted river basin (the Thames), a detailed analysis of flood inundation and the increased number of residential properties placed at risk. One climate model ensemble represents the range of possible weather under the current climate, while 11 alternative ensembles represent the weather as it could have been had past emissions not occurred. The pooled ensemble results show that emissions are likely to have increased the chance of occurrence of these floods across much of the country, with a stronger influence on longer duration peaks (~10 days or more) than for shorter durations (consistent with observations). However, there is substantial variation in results between alternative ensembles, with some suggesting likely decreases in the chance of flood occurrence, at least in some regions of the country. The influence on flows and property flooding varies spatially, due to both spatial variation in the influence on precipitation and variation in physical properties that affect the transformation of precipitation to river flow and flood impacts, including flood defences. This complexity highlights the importance of using hydrological modelling to attribute hydrological impacts from meteorological changes. Changes in snow occurrence in a warming climate are also shown to be important, with effects varying spatially.

Linking weather patterns to regional extreme precipitation for highlighting potential flood events in medium‐ to long‐range forecasts

“…The initial impacts were from strong winds in northern regions, but from late December, the focus switched to fluvial and pluvial flooding. Widespread heavy precipitation fell on already saturated ground, causing flooding with significant impacts on the River Thames and Somerset Levels (Huntingford et al ., 2014; Kendon and McCarthy, 2015; Muchan et al ., 2015; Kay et al ., 2018). For SWE, regional average precipitation on December 23 was 40 mm, and 18 days between December 23, 2013, and February 9, 2014, experienced > 10 mm·day –1 (Figure 9).…”

Knowledge gaps in our perceptual model of Great Britain's hydrology

“…Probabilistic event attribution studies have shown that historical greenhouse gas emissions have already contributed to increased risk of flooding within the context of specific extreme events (quantified for the floods in winter 2013-14, which affected large parts of GB, by Schaller et al, 2016 andKay et al, 2018). Future GB precipitation and temperature extremes are expected to change in both magnitude and frequency, and even in the type of event (De Luca et al, 2019;Kendon et al, 2014).…”

Climate change attribution and the economic costs of extreme weather events: a study on damages from extreme rainfall and drought

“…Furthermore, cascading impacts-impacts in which anthropogenic climate change effects are mediated by other systems-present additional challenges for climate change attribution frameworks (Otto et al 2017;Challinor et al 2018;Lawrence et al 2019). One future development that is directly relevant is the integration of climate and hydrological work within an attribution setting (Hidalgo et al 2009;Kay et al 2018;Philip et al 2019). Utilising an integrated hydrological and climate infrastructure to calculate FARs would allow better quantification of flood risk, as well as improvements in our understanding of current and future climate risks.…”

“…A few studies have made quantitative attribution statements about damaging impacts of climate change, e.g. on flood risk (Schaller et al 2016), on numbers of homes flooded (Kay et al 2018) and on extreme heat-related deaths (Mitchell et al 2016). Such studies are, however, very few in number compared with those on the attribution of the meteorological events themselves, and do not address disaster losses in financial terms, as done here.…”