Co-occurring wintertime flooding and extreme wind over Europe, from daily to seasonal timescales

Hannah Bloomfield; J Hillier; Francesca Pianosi; Rachel James; Paul D Bates; A Griffin

doi:10.1016/j.wace.2023.100550

Co-occurring wintertime flooding and extreme wind over Europe, from daily to seasonal timescales

Hannah Bloomfield^*, J Hillier, Francesca Pianosi, Rachel James, Paul D Bates, A Griffin

^*Corresponding author for this work

Research output: Contribution to journal › Article (Academic Journal) › peer-review

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Abstract

The risk posed by heavy rain and strong wind is now suspected to be exacerbated by the way they co-occur, yet this remains insufficiently understood to effectively plan and mitigate. This study systematically investigates the correlations between wintertime (Oct–Mar) extremes relating to wind and flooding at all timescales from daily to seasonal. Meteorological reanalysis and river flow datasets are used to explore the historical period, and climate projections at 12 km resolution are analysed to understand the possible effects of future climate change (2061–2080, RCP 8.5). A new flood severity index (FSI) is also developed to complement the existing storm severity index (SSI). Initially, Great Britain (GB) is taken as a comparatively simple yet informative study area, then analysis is extended to the full European domain.

Aggregated across GB, wind gusts and precipitation correlate strongly (

0.6–0.8) at timescales from daily to seasonal, but peak around 10 days. A later peak is seen when considering correlations between wind gusts and river flows (40–60 days). This time is likely needed for catchments’ soils to saturate. A conceptual multi-temporal, multi-process model of GB wintertime flood-wind co-occurrence is proposed as a basis for future investigation. When historical analysis is extended across Europe we find the timescale of maximum correlation varies strongly between nations, likely as a result of different meteorological drivers.

Impact focused correlation (FSI–SSI) is lower (
0.2) but increases notably with climate change at timescales of
40 days (
0.4). Tentatively, very severe episodes (i.e., both
99th percentile) appear heavily influenced by climate change, increasing roughly threefold by 2061–2080 (p
0.05). The return period of such an event is 16 years historically (compared to 56 years if the two hazards were independent), reduces to 5 years in future. Such metrics provide actionable information for insurers and other stakeholders.

Original language	English
Article number	100550
Number of pages	15
Journal	Weather and Climate Extremes
Volume	39
Early online date	1 Feb 2023
DOIs	https://doi.org/10.1016/j.wace.2023.100550
Publication status	Published - 1 Mar 2023

Bibliographical note

Funding Information:
This work was funded by the Natural Environment Research Council, UK as part of the UK Centre for Greening Finance and Investment (NERC CGFI Grant Number NE/V017756/1 ). Paul Bates is also supported by a Royal Society Wolfson Research Merit Award, UK . John Hillier is funded by a NERC, UK Knowledge Exchange Fellowship (Grant Number NE/V018698/1 ). Many thanks are given to the multiple insurance companies who provided feedback on this work and to the AquaCAT project, which developed the future river flow simulations.

Funding Information:
A list of the meteorological datasets used in this study is given in Table Table 1 . ERA5 and GLOFAS can be downloaded from the Copernicus climate data store https://cds.climate.copernicus.eu/\#!/home . The CAMELS-GB dataset is available from https://doi.org/10.5285/8344e4f3-d2ea-44f5-8afa-86d2987543a9 . Information about downloading the CHESS-MET dataset can be found from the UK CEH Environmental Information Platform https://eip.ceh.ac.uk/ . UKCP data was available through the JASMIN supercomputer. The UKCP-based GB river flow projections were developed in the AquaCAT project funded by UK Climate Resilience Programme and lead by Sayers and Partners in association with UKCEH.

Publisher Copyright:
© 2023 The Author(s)

Research Groups and Themes

Water and Environmental Engineering

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This is the final published version of the article (version of record). It first appeared online via Elsevier at https://doi.org/10.1016/j.wace.2023.100550. Please refer to any applicable terms of use of the publisher.
Final published version, 4.61 MBLicence: CC BY

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Climate and Environmental Risk Analytics for Resilient Finance (CERAF)
Bates, P. D. (Principal Investigator), James, R. (Co-Investigator) & Pianosi, F. (Co-Investigator)
1/04/21 → 31/03/24
Project: Research

Cite this

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title = "Co-occurring wintertime flooding and extreme wind over Europe, from daily to seasonal timescales",

abstract = "The risk posed by heavy rain and strong wind is now suspected to be exacerbated by the way they co-occur, yet this remains insufficiently understood to effectively plan and mitigate. This study systematically investigates the correlations between wintertime (Oct–Mar) extremes relating to wind and flooding at all timescales from daily to seasonal. Meteorological reanalysis and river flow datasets are used to explore the historical period, and climate projections at 12 km resolution are analysed to understand the possible effects of future climate change (2061–2080, RCP 8.5). A new flood severity index (FSI) is also developed to complement the existing storm severity index (SSI). Initially, Great Britain (GB) is taken as a comparatively simple yet informative study area, then analysis is extended to the full European domain.Aggregated across GB, wind gusts and precipitation correlate strongly ( 0.6–0.8) at timescales from daily to seasonal, but peak around 10 days. A later peak is seen when considering correlations between wind gusts and river flows (40–60 days). This time is likely needed for catchments{\textquoteright} soils to saturate. A conceptual multi-temporal, multi-process model of GB wintertime flood-wind co-occurrence is proposed as a basis for future investigation. When historical analysis is extended across Europe we find the timescale of maximum correlation varies strongly between nations, likely as a result of different meteorological drivers.Impact focused correlation (FSI–SSI) is lower (0.2) but increases notably with climate change at timescales of 40 days (0.4). Tentatively, very severe episodes (i.e., both 99th percentile) appear heavily influenced by climate change, increasing roughly threefold by 2061–2080 (p 0.05). The return period of such an event is 16 years historically (compared to 56 years if the two hazards were independent), reduces to 5 years in future. Such metrics provide actionable information for insurers and other stakeholders.",

author = "Hannah Bloomfield and J Hillier and Francesca Pianosi and Rachel James and Bates, {Paul D} and A Griffin",

note = "Funding Information: This work was funded by the Natural Environment Research Council, UK as part of the UK Centre for Greening Finance and Investment (NERC CGFI Grant Number NE/V017756/1 ). Paul Bates is also supported by a Royal Society Wolfson Research Merit Award, UK . John Hillier is funded by a NERC, UK Knowledge Exchange Fellowship (Grant Number NE/V018698/1 ). Many thanks are given to the multiple insurance companies who provided feedback on this work and to the AquaCAT project, which developed the future river flow simulations. Funding Information: A list of the meteorological datasets used in this study is given in Table Table 1 . ERA5 and GLOFAS can be downloaded from the Copernicus climate data store https://cds.climate.copernicus.eu/\#!/home . The CAMELS-GB dataset is available from https://doi.org/10.5285/8344e4f3-d2ea-44f5-8afa-86d2987543a9 . Information about downloading the CHESS-MET dataset can be found from the UK CEH Environmental Information Platform https://eip.ceh.ac.uk/ . UKCP data was available through the JASMIN supercomputer. The UKCP-based GB river flow projections were developed in the AquaCAT project funded by UK Climate Resilience Programme and lead by Sayers and Partners in association with UKCEH. Publisher Copyright: {\textcopyright} 2023 The Author(s)",

year = "2023",

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doi = "10.1016/j.wace.2023.100550",

language = "English",

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AU - Bloomfield, Hannah

AU - Hillier, J

AU - Pianosi, Francesca

AU - James, Rachel

AU - Bates, Paul D

AU - Griffin, A

N1 - Funding Information: This work was funded by the Natural Environment Research Council, UK as part of the UK Centre for Greening Finance and Investment (NERC CGFI Grant Number NE/V017756/1 ). Paul Bates is also supported by a Royal Society Wolfson Research Merit Award, UK . John Hillier is funded by a NERC, UK Knowledge Exchange Fellowship (Grant Number NE/V018698/1 ). Many thanks are given to the multiple insurance companies who provided feedback on this work and to the AquaCAT project, which developed the future river flow simulations. Funding Information: A list of the meteorological datasets used in this study is given in Table Table 1 . ERA5 and GLOFAS can be downloaded from the Copernicus climate data store https://cds.climate.copernicus.eu/\#!/home . The CAMELS-GB dataset is available from https://doi.org/10.5285/8344e4f3-d2ea-44f5-8afa-86d2987543a9 . Information about downloading the CHESS-MET dataset can be found from the UK CEH Environmental Information Platform https://eip.ceh.ac.uk/ . UKCP data was available through the JASMIN supercomputer. The UKCP-based GB river flow projections were developed in the AquaCAT project funded by UK Climate Resilience Programme and lead by Sayers and Partners in association with UKCEH. Publisher Copyright: © 2023 The Author(s)

PY - 2023/3/1

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N2 - The risk posed by heavy rain and strong wind is now suspected to be exacerbated by the way they co-occur, yet this remains insufficiently understood to effectively plan and mitigate. This study systematically investigates the correlations between wintertime (Oct–Mar) extremes relating to wind and flooding at all timescales from daily to seasonal. Meteorological reanalysis and river flow datasets are used to explore the historical period, and climate projections at 12 km resolution are analysed to understand the possible effects of future climate change (2061–2080, RCP 8.5). A new flood severity index (FSI) is also developed to complement the existing storm severity index (SSI). Initially, Great Britain (GB) is taken as a comparatively simple yet informative study area, then analysis is extended to the full European domain.Aggregated across GB, wind gusts and precipitation correlate strongly ( 0.6–0.8) at timescales from daily to seasonal, but peak around 10 days. A later peak is seen when considering correlations between wind gusts and river flows (40–60 days). This time is likely needed for catchments’ soils to saturate. A conceptual multi-temporal, multi-process model of GB wintertime flood-wind co-occurrence is proposed as a basis for future investigation. When historical analysis is extended across Europe we find the timescale of maximum correlation varies strongly between nations, likely as a result of different meteorological drivers.Impact focused correlation (FSI–SSI) is lower (0.2) but increases notably with climate change at timescales of 40 days (0.4). Tentatively, very severe episodes (i.e., both 99th percentile) appear heavily influenced by climate change, increasing roughly threefold by 2061–2080 (p 0.05). The return period of such an event is 16 years historically (compared to 56 years if the two hazards were independent), reduces to 5 years in future. Such metrics provide actionable information for insurers and other stakeholders.

AB - The risk posed by heavy rain and strong wind is now suspected to be exacerbated by the way they co-occur, yet this remains insufficiently understood to effectively plan and mitigate. This study systematically investigates the correlations between wintertime (Oct–Mar) extremes relating to wind and flooding at all timescales from daily to seasonal. Meteorological reanalysis and river flow datasets are used to explore the historical period, and climate projections at 12 km resolution are analysed to understand the possible effects of future climate change (2061–2080, RCP 8.5). A new flood severity index (FSI) is also developed to complement the existing storm severity index (SSI). Initially, Great Britain (GB) is taken as a comparatively simple yet informative study area, then analysis is extended to the full European domain.Aggregated across GB, wind gusts and precipitation correlate strongly ( 0.6–0.8) at timescales from daily to seasonal, but peak around 10 days. A later peak is seen when considering correlations between wind gusts and river flows (40–60 days). This time is likely needed for catchments’ soils to saturate. A conceptual multi-temporal, multi-process model of GB wintertime flood-wind co-occurrence is proposed as a basis for future investigation. When historical analysis is extended across Europe we find the timescale of maximum correlation varies strongly between nations, likely as a result of different meteorological drivers.Impact focused correlation (FSI–SSI) is lower (0.2) but increases notably with climate change at timescales of 40 days (0.4). Tentatively, very severe episodes (i.e., both 99th percentile) appear heavily influenced by climate change, increasing roughly threefold by 2061–2080 (p 0.05). The return period of such an event is 16 years historically (compared to 56 years if the two hazards were independent), reduces to 5 years in future. Such metrics provide actionable information for insurers and other stakeholders.

U2 - 10.1016/j.wace.2023.100550

DO - 10.1016/j.wace.2023.100550

M3 - Article (Academic Journal)

SN - 2212-0947

VL - 39

JO - Weather and Climate Extremes

JF - Weather and Climate Extremes

M1 - 100550

ER -

Co-occurring wintertime flooding and extreme wind over Europe, from daily to seasonal timescales

Abstract

Bibliographical note

Research Groups and Themes

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Projects

Climate and Environmental Risk Analytics for Resilient Finance (CERAF)

Cite this