Projecting ozone hole recovery using an ensemble of chemistry–climate models weighted by model performance and independence
International audience Calculating a multi-model mean, a commonly used method for ensemble averaging, assumes model independence and equal model skill. Sharing of model components amongst families of models and research centres, conflated by growing ensemble size, means model independence cannot be...
Published in: | Atmospheric Chemistry and Physics |
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Main Authors: | , , , , , , , , , , , , , , , , , , |
Other Authors: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
HAL CCSD
2020
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Subjects: | |
Online Access: | https://insu.hal.science/insu-02464298 https://insu.hal.science/insu-02464298/document https://insu.hal.science/insu-02464298/file/acp-20-9961-2020.pdf https://doi.org/10.5194/acp-20-9961-2020 |
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ftutoulouse3hal:oai:HAL:insu-02464298v1 |
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openpolar |
institution |
Open Polar |
collection |
Université Toulouse III - Paul Sabatier: HAL-UPS |
op_collection_id |
ftutoulouse3hal |
language |
English |
topic |
[PHYS.PHYS.PHYS-AO-PH]Physics [physics]/Physics [physics]/Atmospheric and Oceanic Physics [physics.ao-ph] [SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology |
spellingShingle |
[PHYS.PHYS.PHYS-AO-PH]Physics [physics]/Physics [physics]/Atmospheric and Oceanic Physics [physics.ao-ph] [SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology Amos, Matt Young, Paul J. Hosking, J. Scott Lamarque, Jean-François Abraham, Nathan Luke Akiyoshi, Hideharu Archibald, Alexander T. Bekki, Slimane Deushi, Makoto Jöckel, Patrick Kinnison, Douglas Kirner, Ole Kunze, Markus Marchand, Marion Plummer, David A. Saint-Martin, David Sudo, Kengo Tilmes, Simone Yamashita, Yousuke Projecting ozone hole recovery using an ensemble of chemistry–climate models weighted by model performance and independence |
topic_facet |
[PHYS.PHYS.PHYS-AO-PH]Physics [physics]/Physics [physics]/Atmospheric and Oceanic Physics [physics.ao-ph] [SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology |
description |
International audience Calculating a multi-model mean, a commonly used method for ensemble averaging, assumes model independence and equal model skill. Sharing of model components amongst families of models and research centres, conflated by growing ensemble size, means model independence cannot be assumed and is hard to quantify. We present a methodology to produce a weighted-model ensemble projection, accounting for model performance and model independence. Model weights are calculated by comparing model hindcasts to a selection of metrics chosen for their physical relevance to the process or phenomena of interest. This weighting methodology is applied to the Chemistry–Climate Model Initiative (CCMI) ensemble to investigate Antarctic ozone depletion and subsequent recovery. The weighted mean projects an ozone recovery to 1980 levels, by 2056 with a 95 % confidence interval (2052–2060), 4 years earlier than the most recent study. Perfect-model testing and out-of-sample testing validate the results and show a greater projective skill than a standard multi-model mean. Interestingly, the construction of a weighted mean also provides insight into model performance and dependence between the models. This weighting methodology is robust to both model and metric choices and therefore has potential applications throughout the climate and chemistry–climate modelling communities. |
author2 |
Lancaster Environment Centre Lancaster University Centre for Excellence in Environmental Data Science (CEEDS) Lancaster University-UK Centre of Ecology and Hydrology (UKCEH) British Antarctic Survey (BAS) Natural Environment Research Council (NERC) Atmospheric Chemistry Observations and Modeling Laboratory (ACOML) National Center for Atmospheric Research Boulder (NCAR) Department of Chemistry Cambridge, UK University of Cambridge UK (CAM) National Centre for Atmospheric Science Leeds (NCAS) National Institute for Environmental Studies (NIES) STRATO - LATMOS Laboratoire Atmosphères, Milieux, Observations Spatiales (LATMOS) Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS) Meteorological Research Institute Tsukuba (MRI) Japan Meteorological Agency (JMA) DLR Institut für Physik der Atmosphäre = DLR Institute of Atmospheric Physics (IPA) Deutsches Zentrum für Luft- und Raumfahrt Oberpfaffenhofen-Wessling (DLR) Steinbuch Centre for Computing Karlsruhe (SCC) Karlsruhe Institute of Technology = Karlsruher Institut für Technologie (KIT) Institut für Meteorologie Berlin Freie Universität Berlin Canadian Centre for Climate Modelling and Analysis (CCCma) Environment and Climate Change Canada (ECCC) Centre national de recherches météorologiques (CNRM) Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP) Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3) Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales Toulouse (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France-Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3) Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales Toulouse (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France-Centre National de la Recherche Scientifique (CNRS) Graduate School of Environmental Studies Nagoya Nagoya University Japan Agency for Marine-Earth Science and Technology (JAMSTEC) |
format |
Article in Journal/Newspaper |
author |
Amos, Matt Young, Paul J. Hosking, J. Scott Lamarque, Jean-François Abraham, Nathan Luke Akiyoshi, Hideharu Archibald, Alexander T. Bekki, Slimane Deushi, Makoto Jöckel, Patrick Kinnison, Douglas Kirner, Ole Kunze, Markus Marchand, Marion Plummer, David A. Saint-Martin, David Sudo, Kengo Tilmes, Simone Yamashita, Yousuke |
author_facet |
Amos, Matt Young, Paul J. Hosking, J. Scott Lamarque, Jean-François Abraham, Nathan Luke Akiyoshi, Hideharu Archibald, Alexander T. Bekki, Slimane Deushi, Makoto Jöckel, Patrick Kinnison, Douglas Kirner, Ole Kunze, Markus Marchand, Marion Plummer, David A. Saint-Martin, David Sudo, Kengo Tilmes, Simone Yamashita, Yousuke |
author_sort |
Amos, Matt |
title |
Projecting ozone hole recovery using an ensemble of chemistry–climate models weighted by model performance and independence |
title_short |
Projecting ozone hole recovery using an ensemble of chemistry–climate models weighted by model performance and independence |
title_full |
Projecting ozone hole recovery using an ensemble of chemistry–climate models weighted by model performance and independence |
title_fullStr |
Projecting ozone hole recovery using an ensemble of chemistry–climate models weighted by model performance and independence |
title_full_unstemmed |
Projecting ozone hole recovery using an ensemble of chemistry–climate models weighted by model performance and independence |
title_sort |
projecting ozone hole recovery using an ensemble of chemistry–climate models weighted by model performance and independence |
publisher |
HAL CCSD |
publishDate |
2020 |
url |
https://insu.hal.science/insu-02464298 https://insu.hal.science/insu-02464298/document https://insu.hal.science/insu-02464298/file/acp-20-9961-2020.pdf https://doi.org/10.5194/acp-20-9961-2020 |
genre |
Antarc* Antarctic |
genre_facet |
Antarc* Antarctic |
op_source |
ISSN: 1680-7316 EISSN: 1680-7324 Atmospheric Chemistry and Physics https://insu.hal.science/insu-02464298 Atmospheric Chemistry and Physics, 2020, 20 (16), pp.9961-9977. ⟨10.5194/acp-20-9961-2020⟩ |
op_relation |
info:eu-repo/semantics/altIdentifier/doi/10.5194/acp-20-9961-2020 insu-02464298 https://insu.hal.science/insu-02464298 https://insu.hal.science/insu-02464298/document https://insu.hal.science/insu-02464298/file/acp-20-9961-2020.pdf doi:10.5194/acp-20-9961-2020 |
op_rights |
info:eu-repo/semantics/OpenAccess |
op_doi |
https://doi.org/10.5194/acp-20-9961-2020 |
container_title |
Atmospheric Chemistry and Physics |
container_volume |
20 |
container_issue |
16 |
container_start_page |
9961 |
op_container_end_page |
9977 |
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1810492622094991360 |
spelling |
ftutoulouse3hal:oai:HAL:insu-02464298v1 2024-09-15T17:44:56+00:00 Projecting ozone hole recovery using an ensemble of chemistry–climate models weighted by model performance and independence Amos, Matt Young, Paul J. Hosking, J. Scott Lamarque, Jean-François Abraham, Nathan Luke Akiyoshi, Hideharu Archibald, Alexander T. Bekki, Slimane Deushi, Makoto Jöckel, Patrick Kinnison, Douglas Kirner, Ole Kunze, Markus Marchand, Marion Plummer, David A. Saint-Martin, David Sudo, Kengo Tilmes, Simone Yamashita, Yousuke Lancaster Environment Centre Lancaster University Centre for Excellence in Environmental Data Science (CEEDS) Lancaster University-UK Centre of Ecology and Hydrology (UKCEH) British Antarctic Survey (BAS) Natural Environment Research Council (NERC) Atmospheric Chemistry Observations and Modeling Laboratory (ACOML) National Center for Atmospheric Research Boulder (NCAR) Department of Chemistry Cambridge, UK University of Cambridge UK (CAM) National Centre for Atmospheric Science Leeds (NCAS) National Institute for Environmental Studies (NIES) STRATO - LATMOS Laboratoire Atmosphères, Milieux, Observations Spatiales (LATMOS) Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS) Meteorological Research Institute Tsukuba (MRI) Japan Meteorological Agency (JMA) DLR Institut für Physik der Atmosphäre = DLR Institute of Atmospheric Physics (IPA) Deutsches Zentrum für Luft- und Raumfahrt Oberpfaffenhofen-Wessling (DLR) Steinbuch Centre for Computing Karlsruhe (SCC) Karlsruhe Institute of Technology = Karlsruher Institut für Technologie (KIT) Institut für Meteorologie Berlin Freie Universität Berlin Canadian Centre for Climate Modelling and Analysis (CCCma) Environment and Climate Change Canada (ECCC) Centre national de recherches météorologiques (CNRM) Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP) Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3) Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales Toulouse (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France-Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3) Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales Toulouse (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France-Centre National de la Recherche Scientifique (CNRS) Graduate School of Environmental Studies Nagoya Nagoya University Japan Agency for Marine-Earth Science and Technology (JAMSTEC) 2020 https://insu.hal.science/insu-02464298 https://insu.hal.science/insu-02464298/document https://insu.hal.science/insu-02464298/file/acp-20-9961-2020.pdf https://doi.org/10.5194/acp-20-9961-2020 en eng HAL CCSD European Geosciences Union info:eu-repo/semantics/altIdentifier/doi/10.5194/acp-20-9961-2020 insu-02464298 https://insu.hal.science/insu-02464298 https://insu.hal.science/insu-02464298/document https://insu.hal.science/insu-02464298/file/acp-20-9961-2020.pdf doi:10.5194/acp-20-9961-2020 info:eu-repo/semantics/OpenAccess ISSN: 1680-7316 EISSN: 1680-7324 Atmospheric Chemistry and Physics https://insu.hal.science/insu-02464298 Atmospheric Chemistry and Physics, 2020, 20 (16), pp.9961-9977. ⟨10.5194/acp-20-9961-2020⟩ [PHYS.PHYS.PHYS-AO-PH]Physics [physics]/Physics [physics]/Atmospheric and Oceanic Physics [physics.ao-ph] [SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology info:eu-repo/semantics/article Journal articles 2020 ftutoulouse3hal https://doi.org/10.5194/acp-20-9961-2020 2024-06-25T00:15:26Z International audience Calculating a multi-model mean, a commonly used method for ensemble averaging, assumes model independence and equal model skill. Sharing of model components amongst families of models and research centres, conflated by growing ensemble size, means model independence cannot be assumed and is hard to quantify. We present a methodology to produce a weighted-model ensemble projection, accounting for model performance and model independence. Model weights are calculated by comparing model hindcasts to a selection of metrics chosen for their physical relevance to the process or phenomena of interest. This weighting methodology is applied to the Chemistry–Climate Model Initiative (CCMI) ensemble to investigate Antarctic ozone depletion and subsequent recovery. The weighted mean projects an ozone recovery to 1980 levels, by 2056 with a 95 % confidence interval (2052–2060), 4 years earlier than the most recent study. Perfect-model testing and out-of-sample testing validate the results and show a greater projective skill than a standard multi-model mean. Interestingly, the construction of a weighted mean also provides insight into model performance and dependence between the models. This weighting methodology is robust to both model and metric choices and therefore has potential applications throughout the climate and chemistry–climate modelling communities. Article in Journal/Newspaper Antarc* Antarctic Université Toulouse III - Paul Sabatier: HAL-UPS Atmospheric Chemistry and Physics 20 16 9961 9977 |