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Projecting ozone hole recovery using an ensemble of chemistry-climate models weighted by model performance and independence

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Projecting ozone hole recovery using an ensemble of chemistry-climate models weighted by model performance and independence. / Amos, Matt; Young, Paul; Hosking, J. S.; Lamarque, Jean-François; Abraham, N. L.; Akiyoshi, Hideharu; Archibald, Alex; Bekki, Slimane; Deushi, Makoto; Jöckel, Patrick; Kinnison, Douglas E.; Kirner, Ole; Kunze, Markus; Marchand, Marion; Plummer, David A; Saint-Martin, D.; Sudo, Kengo; Tilmes, Simone; Yamashita, Yousuke.

In: Atmospheric Chemistry and Physics , Vol. 20, 26.08.2020, p. 9961–9977.

Research output: Contribution to journalJournal articlepeer-review

Harvard

Amos, M, Young, P, Hosking, JS, Lamarque, J-F, Abraham, NL, Akiyoshi, H, Archibald, A, Bekki, S, Deushi, M, Jöckel, P, Kinnison, DE, Kirner, O, Kunze, M, Marchand, M, Plummer, DA, Saint-Martin, D, Sudo, K, Tilmes, S & Yamashita, Y 2020, 'Projecting ozone hole recovery using an ensemble of chemistry-climate models weighted by model performance and independence', Atmospheric Chemistry and Physics , vol. 20, pp. 9961–9977. https://doi.org/10.5194/acp-20-9961-2020

APA

Amos, M., Young, P., Hosking, J. S., Lamarque, J-F., Abraham, N. L., Akiyoshi, H., Archibald, A., Bekki, S., Deushi, M., Jöckel, P., Kinnison, D. E., Kirner, O., Kunze, M., Marchand, M., Plummer, D. A., Saint-Martin, D., Sudo, K., Tilmes, S., & Yamashita, Y. (2020). Projecting ozone hole recovery using an ensemble of chemistry-climate models weighted by model performance and independence. Atmospheric Chemistry and Physics , 20, 9961–9977. https://doi.org/10.5194/acp-20-9961-2020

Vancouver

Amos M, Young P, Hosking JS, Lamarque J-F, Abraham NL, Akiyoshi H et al. Projecting ozone hole recovery using an ensemble of chemistry-climate models weighted by model performance and independence. Atmospheric Chemistry and Physics . 2020 Aug 26;20:9961–9977. https://doi.org/10.5194/acp-20-9961-2020

Author

Amos, Matt ; Young, Paul ; Hosking, J. S. ; Lamarque, Jean-François ; Abraham, N. L. ; Akiyoshi, Hideharu ; Archibald, Alex ; Bekki, Slimane ; Deushi, Makoto ; Jöckel, Patrick ; Kinnison, Douglas E. ; Kirner, Ole ; Kunze, Markus ; Marchand, Marion ; Plummer, David A ; Saint-Martin, D. ; Sudo, Kengo ; Tilmes, Simone ; Yamashita, Yousuke. / Projecting ozone hole recovery using an ensemble of chemistry-climate models weighted by model performance and independence. In: Atmospheric Chemistry and Physics . 2020 ; Vol. 20. pp. 9961–9977.

Bibtex

@article{946e2cfaaa1c46a4a3fcd5d2802bdfe0,
title = "Projecting ozone hole recovery using an ensemble of chemistry-climate models weighted by model performance and independence",
abstract = "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 providesinsight 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.",
author = "Matt Amos and Paul Young and Hosking, {J. S.} and Jean-Fran{\c c}ois Lamarque and Abraham, {N. L.} and Hideharu Akiyoshi and Alex Archibald and Slimane Bekki and Makoto Deushi and Patrick J{\"o}ckel and Kinnison, {Douglas E.} and Ole Kirner and Markus Kunze and Marion Marchand and Plummer, {David A} and D. Saint-Martin and Kengo Sudo and Simone Tilmes and Yousuke Yamashita",
year = "2020",
month = aug,
day = "26",
doi = "10.5194/acp-20-9961-2020",
language = "English",
volume = "20",
pages = "9961–9977",
journal = "Atmospheric Chemistry and Physics ",
issn = "1680-7316",
publisher = "Copernicus GmbH (Copernicus Publications) on behalf of the European Geosciences Union (EGU)",

}

RIS

TY - JOUR

T1 - Projecting ozone hole recovery using an ensemble of chemistry-climate models weighted by model performance and independence

AU - Amos, Matt

AU - Young, Paul

AU - Hosking, J. S.

AU - Lamarque, Jean-François

AU - Abraham, N. L.

AU - Akiyoshi, Hideharu

AU - Archibald, Alex

AU - Bekki, Slimane

AU - Deushi, Makoto

AU - Jöckel, Patrick

AU - Kinnison, Douglas E.

AU - Kirner, Ole

AU - Kunze, Markus

AU - Marchand, Marion

AU - Plummer, David A

AU - Saint-Martin, D.

AU - Sudo, Kengo

AU - Tilmes, Simone

AU - Yamashita, Yousuke

PY - 2020/8/26

Y1 - 2020/8/26

N2 - 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 providesinsight 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.

AB - 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 providesinsight 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.

U2 - 10.5194/acp-20-9961-2020

DO - 10.5194/acp-20-9961-2020

M3 - Journal article

VL - 20

SP - 9961

EP - 9977

JO - Atmospheric Chemistry and Physics

JF - Atmospheric Chemistry and Physics

SN - 1680-7316

ER -