Projecting ozone hole recovery using an ensemble of chemistry–climate models weighted by model performance and independence
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...
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European Geosciences Union
2020
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Online Access: | https://publikationen.bibliothek.kit.edu/1000123312 https://publikationen.bibliothek.kit.edu/1000123312/86536349 https://doi.org/10.5445/IR/1000123312 |
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ftubkarlsruhe:oai:EVASTAR-Karlsruhe.de:1000123312 2023-05-15T13:38:51+02:00 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, N. 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 2020-09-03 application/pdf https://publikationen.bibliothek.kit.edu/1000123312 https://publikationen.bibliothek.kit.edu/1000123312/86536349 https://doi.org/10.5445/IR/1000123312 eng eng European Geosciences Union info:eu-repo/semantics/altIdentifier/wos/000566345900005 info:eu-repo/semantics/altIdentifier/doi/10.5194/acp-20-9961-2020 info:eu-repo/semantics/altIdentifier/issn/1680-7324 https://publikationen.bibliothek.kit.edu/1000123312 https://publikationen.bibliothek.kit.edu/1000123312/86536349 https://doi.org/10.5445/IR/1000123312 https://creativecommons.org/licenses/by/4.0/deed.de info:eu-repo/semantics/openAccess CC-BY Atmospheric chemistry and physics, 20 (16), 9961–9977 ISSN: 1680-7324 ddc:004 DATA processing & computer science info:eu-repo/classification/ddc/004 doc-type:article Text info:eu-repo/semantics/article article info:eu-repo/semantics/publishedVersion 2020 ftubkarlsruhe https://doi.org/10.5445/IR/1000123312 https://doi.org/10.5194/acp-20-9961-2020 2022-03-23T17:17:23Z 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 ... Article in Journal/Newspaper Antarc* Antarctic KITopen (Karlsruhe Institute of Technologie) Antarctic |
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Open Polar |
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KITopen (Karlsruhe Institute of Technologie) |
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ftubkarlsruhe |
language |
English |
topic |
ddc:004 DATA processing & computer science info:eu-repo/classification/ddc/004 |
spellingShingle |
ddc:004 DATA processing & computer science info:eu-repo/classification/ddc/004 Amos, Matt Young, Paul J. Hosking, J. Scott Lamarque, Jean-François Abraham, N. 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 |
ddc:004 DATA processing & computer science info:eu-repo/classification/ddc/004 |
description |
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 ... |
format |
Article in Journal/Newspaper |
author |
Amos, Matt Young, Paul J. Hosking, J. Scott Lamarque, Jean-François Abraham, N. 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, N. 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 |
European Geosciences Union |
publishDate |
2020 |
url |
https://publikationen.bibliothek.kit.edu/1000123312 https://publikationen.bibliothek.kit.edu/1000123312/86536349 https://doi.org/10.5445/IR/1000123312 |
geographic |
Antarctic |
geographic_facet |
Antarctic |
genre |
Antarc* Antarctic |
genre_facet |
Antarc* Antarctic |
op_source |
Atmospheric chemistry and physics, 20 (16), 9961–9977 ISSN: 1680-7324 |
op_relation |
info:eu-repo/semantics/altIdentifier/wos/000566345900005 info:eu-repo/semantics/altIdentifier/doi/10.5194/acp-20-9961-2020 info:eu-repo/semantics/altIdentifier/issn/1680-7324 https://publikationen.bibliothek.kit.edu/1000123312 https://publikationen.bibliothek.kit.edu/1000123312/86536349 https://doi.org/10.5445/IR/1000123312 |
op_rights |
https://creativecommons.org/licenses/by/4.0/deed.de info:eu-repo/semantics/openAccess |
op_rightsnorm |
CC-BY |
op_doi |
https://doi.org/10.5445/IR/1000123312 https://doi.org/10.5194/acp-20-9961-2020 |
_version_ |
1766111679008997376 |