Estimating unprecedented extremes in UK summer daily rainfall
The UNSEEN (unprecedented simulated extremes using ensemble) method involves using a large ensemble of climate model simulations to increase the sample size of rare events. Here we extend UNSEEN to focus on intense summertime daily rainfall, estimating plausible rainfall extremes in the current clim...
Published in: | Environmental Research Letters |
---|---|
Main Authors: | , , , , , , , , |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
IOP Publishing
2022
|
Subjects: | |
Online Access: | https://doi.org/10.1088/1748-9326/ac42fb https://doaj.org/article/7fafc4cc3a3f4383996a64c8414022e1 |
id |
ftdoajarticles:oai:doaj.org/article:7fafc4cc3a3f4383996a64c8414022e1 |
---|---|
record_format |
openpolar |
spelling |
ftdoajarticles:oai:doaj.org/article:7fafc4cc3a3f4383996a64c8414022e1 2023-09-05T13:21:42+02:00 Estimating unprecedented extremes in UK summer daily rainfall Chris Kent Nick Dunstone Simon Tucker Adam A Scaife Simon Brown Elizabeth J Kendon Doug Smith Lynsay McLean Shirley Greenwood 2022-01-01T00:00:00Z https://doi.org/10.1088/1748-9326/ac42fb https://doaj.org/article/7fafc4cc3a3f4383996a64c8414022e1 EN eng IOP Publishing https://doi.org/10.1088/1748-9326/ac42fb https://doaj.org/toc/1748-9326 doi:10.1088/1748-9326/ac42fb 1748-9326 https://doaj.org/article/7fafc4cc3a3f4383996a64c8414022e1 Environmental Research Letters, Vol 17, Iss 1, p 014041 (2022) unprecedented extremes UK summer rainfalls Environmental technology. Sanitary engineering TD1-1066 Environmental sciences GE1-350 Science Q Physics QC1-999 article 2022 ftdoajarticles https://doi.org/10.1088/1748-9326/ac42fb 2023-08-13T00:36:48Z The UNSEEN (unprecedented simulated extremes using ensemble) method involves using a large ensemble of climate model simulations to increase the sample size of rare events. Here we extend UNSEEN to focus on intense summertime daily rainfall, estimating plausible rainfall extremes in the current climate. To address modelling limitations simulations from two climate models were used; an initialised 25 km global model that uses parameterised convection, and a dynamically downscaled 2.2 km model that uses explicit convection. In terms of the statistical characteristics that govern very rare return periods, the models are not significantly different from the observations across much of the UK. Our analysis provides more precise estimates of 1000 year return levels for extreme daily rainfall, reducing sampling uncertainty by 70%–90% compared to using observations alone. This framework enables observed daily storm profiles to be adjusted to more statistically robust estimates of extreme rainfall. For a damaging storm in July 2007 which led to surface water flooding, we estimate physically plausible increases in the total daily rainfall of 50%–100%. For much of the UK the annual chance of record-breaking daily summertime rainfall is estimated to be around 1% per year in the present-day climate. Analysis of the dynamical states in our UNSEEN events indicates that heavy daily rainfall is associated with a southward displaced and meandering North Atlantic jet stream, increasing the advection of warm moist air from across Southern Europe and the Mediterranean, and intensifying extratropical storms. This work represents an advancement in the use of climate modelling for estimating present-day climate hazards and outlines a framework for applying UNSEEN at higher spatial and temporal resolutions. Article in Journal/Newspaper North Atlantic Directory of Open Access Journals: DOAJ Articles Environmental Research Letters 17 1 014041 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
unprecedented extremes UK summer rainfalls Environmental technology. Sanitary engineering TD1-1066 Environmental sciences GE1-350 Science Q Physics QC1-999 |
spellingShingle |
unprecedented extremes UK summer rainfalls Environmental technology. Sanitary engineering TD1-1066 Environmental sciences GE1-350 Science Q Physics QC1-999 Chris Kent Nick Dunstone Simon Tucker Adam A Scaife Simon Brown Elizabeth J Kendon Doug Smith Lynsay McLean Shirley Greenwood Estimating unprecedented extremes in UK summer daily rainfall |
topic_facet |
unprecedented extremes UK summer rainfalls Environmental technology. Sanitary engineering TD1-1066 Environmental sciences GE1-350 Science Q Physics QC1-999 |
description |
The UNSEEN (unprecedented simulated extremes using ensemble) method involves using a large ensemble of climate model simulations to increase the sample size of rare events. Here we extend UNSEEN to focus on intense summertime daily rainfall, estimating plausible rainfall extremes in the current climate. To address modelling limitations simulations from two climate models were used; an initialised 25 km global model that uses parameterised convection, and a dynamically downscaled 2.2 km model that uses explicit convection. In terms of the statistical characteristics that govern very rare return periods, the models are not significantly different from the observations across much of the UK. Our analysis provides more precise estimates of 1000 year return levels for extreme daily rainfall, reducing sampling uncertainty by 70%–90% compared to using observations alone. This framework enables observed daily storm profiles to be adjusted to more statistically robust estimates of extreme rainfall. For a damaging storm in July 2007 which led to surface water flooding, we estimate physically plausible increases in the total daily rainfall of 50%–100%. For much of the UK the annual chance of record-breaking daily summertime rainfall is estimated to be around 1% per year in the present-day climate. Analysis of the dynamical states in our UNSEEN events indicates that heavy daily rainfall is associated with a southward displaced and meandering North Atlantic jet stream, increasing the advection of warm moist air from across Southern Europe and the Mediterranean, and intensifying extratropical storms. This work represents an advancement in the use of climate modelling for estimating present-day climate hazards and outlines a framework for applying UNSEEN at higher spatial and temporal resolutions. |
format |
Article in Journal/Newspaper |
author |
Chris Kent Nick Dunstone Simon Tucker Adam A Scaife Simon Brown Elizabeth J Kendon Doug Smith Lynsay McLean Shirley Greenwood |
author_facet |
Chris Kent Nick Dunstone Simon Tucker Adam A Scaife Simon Brown Elizabeth J Kendon Doug Smith Lynsay McLean Shirley Greenwood |
author_sort |
Chris Kent |
title |
Estimating unprecedented extremes in UK summer daily rainfall |
title_short |
Estimating unprecedented extremes in UK summer daily rainfall |
title_full |
Estimating unprecedented extremes in UK summer daily rainfall |
title_fullStr |
Estimating unprecedented extremes in UK summer daily rainfall |
title_full_unstemmed |
Estimating unprecedented extremes in UK summer daily rainfall |
title_sort |
estimating unprecedented extremes in uk summer daily rainfall |
publisher |
IOP Publishing |
publishDate |
2022 |
url |
https://doi.org/10.1088/1748-9326/ac42fb https://doaj.org/article/7fafc4cc3a3f4383996a64c8414022e1 |
genre |
North Atlantic |
genre_facet |
North Atlantic |
op_source |
Environmental Research Letters, Vol 17, Iss 1, p 014041 (2022) |
op_relation |
https://doi.org/10.1088/1748-9326/ac42fb https://doaj.org/toc/1748-9326 doi:10.1088/1748-9326/ac42fb 1748-9326 https://doaj.org/article/7fafc4cc3a3f4383996a64c8414022e1 |
op_doi |
https://doi.org/10.1088/1748-9326/ac42fb |
container_title |
Environmental Research Letters |
container_volume |
17 |
container_issue |
1 |
container_start_page |
014041 |
_version_ |
1776202287714140160 |