A comparison of model ensembles for attributing 2012 West African rainfall

In 2012, heavy rainfall resulted in flooding and devastating impacts across West Africa. With many people highly vulnerable to such events in this region, this study investigates whether anthropogenic climate change has influenced such heavy precipitation events. We use a probabilistic event attribu...

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Main Authors: Parker, H, Lott, F, Cornforth, R, Mitchell, D, Sparrow, S, Wallom, D
Format: Journal article
Published: IOP Publishing 2017
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author Parker, H
Lott, F
Cornforth, R
Mitchell, D
Sparrow, S
Wallom, D
author_facet Parker, H
Lott, F
Cornforth, R
Mitchell, D
Sparrow, S
Wallom, D
author_sort Parker, H
collection OXFORD
description In 2012, heavy rainfall resulted in flooding and devastating impacts across West Africa. With many people highly vulnerable to such events in this region, this study investigates whether anthropogenic climate change has influenced such heavy precipitation events. We use a probabilistic event attribution approach to assess the contribution of anthropogenic greenhouse gas emissions, by comparing the probability of such an event occurring in climate model simulations with all known climate forcings to those where natural forcings only are simulated. An ensemble of simulations from 10 models from the Coupled Model Intercomparison Project Phase 5 (CMIP5) is compared to two much larger ensembles of atmosphere-only simulations, from the Met Office model HadGEM3-A and from weather@home with a regional version of HadAM3P. These are used to assess whether the choice of model ensemble influences the attribution statement that can be made. Results show that anthropogenic greenhouse gas emissions have decreased the probability of high precipitation across most of the model ensembles. However, the magnitude and confidence intervals of the decrease depend on the ensemble used, with more certainty in the magnitude in the atmosphere-only model ensembles due to larger ensemble sizes from single models with more constrained simulations. Certainty is greatly decreased when considering a CMIP5 ensemble that can represent the relevant teleconnections due to a decrease in ensemble members. An increase in probability of high precipitation in HadGEM3-A using the observed trend in sea surface temperatures (SSTs) for natural simulations highlights the need to ensure that estimates of natural SSTs are consistent with observed trends in order for results to be robust. Further work is needed to establish how anthropogenic forcings are affecting the rainfall processes in these simulations in order to better understand the differences in the overall effect.
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spelling oxford-uuid:950c8175-7d30-40eb-ba6f-3d4a0d06411d2022-03-26T23:43:36ZA comparison of model ensembles for attributing 2012 West African rainfallJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:950c8175-7d30-40eb-ba6f-3d4a0d06411dSymplectic Elements at OxfordIOP Publishing2017Parker, HLott, FCornforth, RMitchell, DSparrow, SWallom, DIn 2012, heavy rainfall resulted in flooding and devastating impacts across West Africa. With many people highly vulnerable to such events in this region, this study investigates whether anthropogenic climate change has influenced such heavy precipitation events. We use a probabilistic event attribution approach to assess the contribution of anthropogenic greenhouse gas emissions, by comparing the probability of such an event occurring in climate model simulations with all known climate forcings to those where natural forcings only are simulated. An ensemble of simulations from 10 models from the Coupled Model Intercomparison Project Phase 5 (CMIP5) is compared to two much larger ensembles of atmosphere-only simulations, from the Met Office model HadGEM3-A and from weather@home with a regional version of HadAM3P. These are used to assess whether the choice of model ensemble influences the attribution statement that can be made. Results show that anthropogenic greenhouse gas emissions have decreased the probability of high precipitation across most of the model ensembles. However, the magnitude and confidence intervals of the decrease depend on the ensemble used, with more certainty in the magnitude in the atmosphere-only model ensembles due to larger ensemble sizes from single models with more constrained simulations. Certainty is greatly decreased when considering a CMIP5 ensemble that can represent the relevant teleconnections due to a decrease in ensemble members. An increase in probability of high precipitation in HadGEM3-A using the observed trend in sea surface temperatures (SSTs) for natural simulations highlights the need to ensure that estimates of natural SSTs are consistent with observed trends in order for results to be robust. Further work is needed to establish how anthropogenic forcings are affecting the rainfall processes in these simulations in order to better understand the differences in the overall effect.
spellingShingle Parker, H
Lott, F
Cornforth, R
Mitchell, D
Sparrow, S
Wallom, D
A comparison of model ensembles for attributing 2012 West African rainfall
title A comparison of model ensembles for attributing 2012 West African rainfall
title_full A comparison of model ensembles for attributing 2012 West African rainfall
title_fullStr A comparison of model ensembles for attributing 2012 West African rainfall
title_full_unstemmed A comparison of model ensembles for attributing 2012 West African rainfall
title_short A comparison of model ensembles for attributing 2012 West African rainfall
title_sort comparison of model ensembles for attributing 2012 west african rainfall
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