Sensitivity of bias adjustment methods to low-frequency internal climate variability over the reference period: an ideal model study
International audience Climate simulations often need to be adjusted before carrying out impact studies at a regional scale. Technically, bias adjustment methods are generally calibrated over the last few decades, in order to benefit from a more comprehensive and accurate observational network. At t...
Published in: | Environmental Research: Climate |
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Format: | Article in Journal/Newspaper |
Language: | English |
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HAL CCSD
2022
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Online Access: | https://hal.science/hal-03799293 https://hal.science/hal-03799293/document https://hal.science/hal-03799293/file/Bonnet_2022_Environ._Res.%20_Climate_1_011001.pdf https://doi.org/10.1088/2752-5295/ac6adc |
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ftepunivpsaclay:oai:HAL:hal-03799293v1 |
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openpolar |
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Open Polar |
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École Polytechnique, Université Paris-Saclay: HAL |
op_collection_id |
ftepunivpsaclay |
language |
English |
topic |
bias adjustment Internal climate variability climate change climate projection impact studies [SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology |
spellingShingle |
bias adjustment Internal climate variability climate change climate projection impact studies [SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology Bonnet, Rémy Boucher, Olivier Vrac, Mathieu Jin, Xia Sensitivity of bias adjustment methods to low-frequency internal climate variability over the reference period: an ideal model study |
topic_facet |
bias adjustment Internal climate variability climate change climate projection impact studies [SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology |
description |
International audience Climate simulations often need to be adjusted before carrying out impact studies at a regional scale. Technically, bias adjustment methods are generally calibrated over the last few decades, in order to benefit from a more comprehensive and accurate observational network. At these timescales, however, the climate state may be influenced by the low-frequency internal climate variability. There is therefore a risk of introducing a bias to the climate projections by bias-adjusting simulations with low-frequency variability in a different phase to that of the observations. In this study, we developed a new pseudo-reality framework using an ensemble of simulations from the IPSL-CM6A-LR climate model in order to assess the impact of the low-frequency internal climate variability of the North Atlantic sea surface temperatures on bias-adjusted projections of mean and extreme surface temperature over Europe. We show that using simulations in a similar phase of the Atlantic Multidecadal Variability reduces the pseudo-biases in temperature projections. Therefore, for models and regions where low frequency internal variability matters, it is recommended to sample relevant climate simulations to be bias adjusted in a model ensemble or alternatively to use a very long reference period when possible. |
author2 |
Institut Pierre-Simon-Laplace (IPSL (FR_636)) École normale supérieure - Paris (ENS-PSL) Université Paris Sciences et Lettres (PSL)-Université Paris Sciences et Lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales Toulouse (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité) Extrèmes : Statistiques, Impacts et Régionalisation (ESTIMR) Laboratoire des Sciences du Climat et de l'Environnement Gif-sur-Yvette (LSCE) Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Direction de Recherche Fondamentale (CEA) (DRF (CEA)) Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Direction de Recherche Fondamentale (CEA) (DRF (CEA)) Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA) ANR-17-EURE-0006,IPSL-CGS,IPSL Climate graduate school(2017) |
format |
Article in Journal/Newspaper |
author |
Bonnet, Rémy Boucher, Olivier Vrac, Mathieu Jin, Xia |
author_facet |
Bonnet, Rémy Boucher, Olivier Vrac, Mathieu Jin, Xia |
author_sort |
Bonnet, Rémy |
title |
Sensitivity of bias adjustment methods to low-frequency internal climate variability over the reference period: an ideal model study |
title_short |
Sensitivity of bias adjustment methods to low-frequency internal climate variability over the reference period: an ideal model study |
title_full |
Sensitivity of bias adjustment methods to low-frequency internal climate variability over the reference period: an ideal model study |
title_fullStr |
Sensitivity of bias adjustment methods to low-frequency internal climate variability over the reference period: an ideal model study |
title_full_unstemmed |
Sensitivity of bias adjustment methods to low-frequency internal climate variability over the reference period: an ideal model study |
title_sort |
sensitivity of bias adjustment methods to low-frequency internal climate variability over the reference period: an ideal model study |
publisher |
HAL CCSD |
publishDate |
2022 |
url |
https://hal.science/hal-03799293 https://hal.science/hal-03799293/document https://hal.science/hal-03799293/file/Bonnet_2022_Environ._Res.%20_Climate_1_011001.pdf https://doi.org/10.1088/2752-5295/ac6adc |
genre |
North Atlantic |
genre_facet |
North Atlantic |
op_source |
ISSN: 2752-5295 Environmental Research: Climate https://hal.science/hal-03799293 Environmental Research: Climate, 2022, 1, pp.011001. ⟨10.1088/2752-5295/ac6adc⟩ |
op_relation |
info:eu-repo/semantics/altIdentifier/doi/10.1088/2752-5295/ac6adc hal-03799293 https://hal.science/hal-03799293 https://hal.science/hal-03799293/document https://hal.science/hal-03799293/file/Bonnet_2022_Environ._Res.%20_Climate_1_011001.pdf doi:10.1088/2752-5295/ac6adc |
op_rights |
info:eu-repo/semantics/OpenAccess |
op_doi |
https://doi.org/10.1088/2752-5295/ac6adc |
container_title |
Environmental Research: Climate |
container_volume |
1 |
container_issue |
1 |
container_start_page |
011001 |
_version_ |
1801379897060360192 |
spelling |
ftepunivpsaclay:oai:HAL:hal-03799293v1 2024-06-09T07:48:15+00:00 Sensitivity of bias adjustment methods to low-frequency internal climate variability over the reference period: an ideal model study Bonnet, Rémy Boucher, Olivier Vrac, Mathieu Jin, Xia Institut Pierre-Simon-Laplace (IPSL (FR_636)) École normale supérieure - Paris (ENS-PSL) Université Paris Sciences et Lettres (PSL)-Université Paris Sciences et Lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales Toulouse (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité) Extrèmes : Statistiques, Impacts et Régionalisation (ESTIMR) Laboratoire des Sciences du Climat et de l'Environnement Gif-sur-Yvette (LSCE) Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Direction de Recherche Fondamentale (CEA) (DRF (CEA)) Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Direction de Recherche Fondamentale (CEA) (DRF (CEA)) Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA) ANR-17-EURE-0006,IPSL-CGS,IPSL Climate graduate school(2017) 2022 https://hal.science/hal-03799293 https://hal.science/hal-03799293/document https://hal.science/hal-03799293/file/Bonnet_2022_Environ._Res.%20_Climate_1_011001.pdf https://doi.org/10.1088/2752-5295/ac6adc en eng HAL CCSD IOPScience info:eu-repo/semantics/altIdentifier/doi/10.1088/2752-5295/ac6adc hal-03799293 https://hal.science/hal-03799293 https://hal.science/hal-03799293/document https://hal.science/hal-03799293/file/Bonnet_2022_Environ._Res.%20_Climate_1_011001.pdf doi:10.1088/2752-5295/ac6adc info:eu-repo/semantics/OpenAccess ISSN: 2752-5295 Environmental Research: Climate https://hal.science/hal-03799293 Environmental Research: Climate, 2022, 1, pp.011001. ⟨10.1088/2752-5295/ac6adc⟩ bias adjustment Internal climate variability climate change climate projection impact studies [SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology info:eu-repo/semantics/article Journal articles 2022 ftepunivpsaclay https://doi.org/10.1088/2752-5295/ac6adc 2024-05-16T11:54:18Z International audience Climate simulations often need to be adjusted before carrying out impact studies at a regional scale. Technically, bias adjustment methods are generally calibrated over the last few decades, in order to benefit from a more comprehensive and accurate observational network. At these timescales, however, the climate state may be influenced by the low-frequency internal climate variability. There is therefore a risk of introducing a bias to the climate projections by bias-adjusting simulations with low-frequency variability in a different phase to that of the observations. In this study, we developed a new pseudo-reality framework using an ensemble of simulations from the IPSL-CM6A-LR climate model in order to assess the impact of the low-frequency internal climate variability of the North Atlantic sea surface temperatures on bias-adjusted projections of mean and extreme surface temperature over Europe. We show that using simulations in a similar phase of the Atlantic Multidecadal Variability reduces the pseudo-biases in temperature projections. Therefore, for models and regions where low frequency internal variability matters, it is recommended to sample relevant climate simulations to be bias adjusted in a model ensemble or alternatively to use a very long reference period when possible. Article in Journal/Newspaper North Atlantic École Polytechnique, Université Paris-Saclay: HAL Environmental Research: Climate 1 1 011001 |