Comparison of past and future simulations of ENSO in CMIP5/PMIP3 and CMIP6/PMIP4 models

Josephine R. Brown; Chris M. Brierley; Soon Il An; Maria Vittoria Guarino; Samantha Stevenson; Charles J.R. Williams; Qiong Zhang; Anni Zhao; Ayako Abe-Ouchi; Pascale Braconnot; Esther C. Brady; Deepak Chandan; Roberta D'Agostino; Chuncheng Guo; Allegra N. Legrande; Gerrit Lohmann; Polina A. Morozova; Rumi Ohgaito; Ryouta O'Ishi; Bette L. Otto-Bliesner; W. Richard Peltier; Xiaoxu Shi; Louise Sime; Evgeny M. Volodin; Zhongshi Zhang; Weipeng Zheng

doi:10.5194/cp-16-1777-2020

Comparison of past and future simulations of ENSO in CMIP5/PMIP3 and CMIP6/PMIP4 models

Josephine R. Brown, Chris M. Brierley, Soon Il An, Maria Vittoria Guarino, Samantha Stevenson, Charles J.R. Williams, Qiong Zhang, Anni Zhao, Ayako Abe-Ouchi, Pascale Braconnot, Esther C. Brady, Deepak Chandan, Roberta D'Agostino, Chuncheng Guo, Allegra N. Legrande, Gerrit Lohmann, Polina A. Morozova, Rumi Ohgaito, Ryouta O'Ishi, Bette L. Otto-BliesnerW. Richard Peltier, Xiaoxu Shi, Louise Sime, Evgeny M. Volodin, Zhongshi Zhang, Weipeng Zheng

Research output: Contribution to journal › Article › peer-review

48 Citations (Scopus)

Abstract

El Niño Southern Oscillation (ENSO) is the strongest mode of interannual climate variability in the current climate, influencing ecosystems, agriculture, and weather systems across the globe, but future projections of ENSO frequency and amplitude remain highly uncertain. A comparison of changes in ENSO in a range of past and future climate simulations can provide insights into the sensitivity of ENSO to changes in the mean state, including changes in the seasonality of incoming solar radiation, global average temperatures, and spatial patterns of sea surface temperatures. As a comprehensive set of coupled model simulations is now available for both palaeoclimate time slices (the Last Glacial Maximum, mid-Holocene, and last interglacial) and idealised future warming scenarios (1 % per year CO2 increase, abrupt four-time CO2 increase), this allows a detailed evaluation of ENSO changes in this wide range of climates. Such a comparison can assist in constraining uncertainty in future projections, providing insights into model agreement and the sensitivity of ENSO to a range of factors. The majority of models simulate a consistent weakening of ENSO activity in the last interglacial and mid-Holocene experiments, and there is an ensemble mean reduction of variability in the western equatorial Pacific in the Last Glacial Maximum experiments. Changes in global temperature produce a weaker precipitation response to ENSO in the cold Last Glacial Maximum experiments and an enhanced precipitation response to ENSO in the warm increased CO2 experiments. No consistent relationship between changes in ENSO amplitude and annual cycle was identified across experiments.

Original language	English
Pages (from-to)	1777-1805
Number of pages	29
Journal	Climate of the Past
Volume	16
Issue number	5
DOIs	https://doi.org/10.5194/cp-16-1777-2020
Publication status	Published - 2020 Sept 28

Bibliographical note

Funding Information:
Acknowledgements. Josephine R. Brown acknowledges support from the ARC Centre of Excellence for Climate Extremes (CE170100023). Chris M. Brierley, Charles J. R. Williams, Pas-cale Braconnot, Roberta D’Agostino, Gerrit Lohmann, and Xiaoxu Shi acknowledge the JPI-Belmont-funded PACMEDY programme (NE/P006752/1; ANR-15-JCLI-0003-01; BMBF 01LP1607A). Soon-Il An was supported by the National Research Foundation of Korea (NRF) grant (NRF-2018R1A5A1024958). Chris M. Brierley was also funded in part by NERC (NE/S009736/1). Maria-Vittoria Guarino acknowledges support from NERC research grant NE/P013279/1. Qiong Zhang acknowledges support from the Swedish Research Council VR projects 2013-06476 and 2017-04232. The EC-Earth simulations are performed on resources provided by the Swedish National Infrastructure for Computing (SNIC) at the National Supercomputer Centre (NSC), partially funded by the Swedish Research Council through grant no. 2016-07213. Rumi Ohgaito acknowledges support from the Integrated Research Program for Advancing Climate Models (TOUGOU programme) from the Ministry of Education, Culture, Sports, Science and Technology (MEXT), Japan. The simulations using MIROC-ES2L were conducted on the Earth Simulator of JAMSTEC. Ryouta O’ishi and Ayako Abe-Ouchi acknowledge support from Arctic Challenge for Sustainability (ArCS) project (grant no. JPMXD1300000000), JSPS KAKENHI (grant no. 17H06104) and MEXT KAKENHI (grant no. 17H06323), and JAMSTEC for use of the Earth Simulator supercomputer. Bette L. Otto-Bliesner and Esther C. Brady acknowledge the CESM project, supported primarily by the National Science Foundation (NSF). The CESM2 simulations are based upon work supported by the National Center for Atmospheric Research (NCAR), which is a major facility sponsored by the NSF under cooperative agreement no. 1852977. Computing and data storage resources, including the Cheyenne supercomputer (https://doi.org/10.5065/D6RX99HX), were provided by the Computational and Information Systems Laboratory (CISL) at NCAR. Polina A. Morozova was supported by state assignment project 0148-2019-0009. Evgeny M. Volodin was supported by RSF grant no. 20-17-00190. We acknowledge the World Climate Research Programme, which, through its Working Group on Coupled Modelling, coordinated and promoted CMIP6. We thank the climate modelling groups for producing and making available their model output, the Earth System Grid Federation (ESGF) for archiving the data and providing access, and the multiple funding agencies who support CMIP6 and ESGF. PMIP is endorsed by both WCRP/WGCM and Future Earth/PAGES. This research arose out of a workshop hosted at University College London by the PMIP working group on Past2Future: insights from a constantly varying past.

Funding Information:
Financial support. This research has been supported by the JPI-Belmont-funded PACMEDY programme (grant nos. NE/P006752/1, ANR-15-JCLI-0003-01, and BMBF 01LP1607A); the National Research Foundation of Korea (grant no. NRF-2018R1A5A1024958); the UK NERC (grant nos. NE/S009736/1 and NE/P013279/1); the Swedish Research Council (VR projects 2013-06476, 2017-04232, and 2016-07213); the Integrated Research Program for Advancing Climate Models (TOUGOU programme) from the Ministry of Education, Culture, Sports, Science and Technology (MEXT), Japan; the Arctic Challenge for Sustainability (ArCS) project (grant no. JPMXD1300000000), JSPS KAKENHI (grant no. 17H06104) and MEXT KAKENHI (grant no. 17H06323); the US National Science Foundation (NSF) under cooperative agreement no. 1852977; the Russian State Assignment Project 0148-2019-0009; and the Russian Science Foundation (RSF) (grant no. 20-17-00190).

Publisher Copyright:
© 2020 Author(s).

All Science Journal Classification (ASJC) codes

Global and Planetary Change
Stratigraphy
Palaeontology

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.5194/cp-16-1777-2020

Cite this

Brown, J. R., Brierley, C. M., An, S. I., Guarino, M. V., Stevenson, S., Williams, C. J. R., Zhang, Q., Zhao, A., Abe-Ouchi, A., Braconnot, P., Brady, E. C., Chandan, D., D'Agostino, R., Guo, C., Legrande, A. N., Lohmann, G., Morozova, P. A., Ohgaito, R., O'Ishi, R., ... Zheng, W. (2020). Comparison of past and future simulations of ENSO in CMIP5/PMIP3 and CMIP6/PMIP4 models. Climate of the Past, 16(5), 1777-1805. https://doi.org/10.5194/cp-16-1777-2020

@article{f2d4a0db7a90435bb62ef2abfb5baf99,

title = "Comparison of past and future simulations of ENSO in CMIP5/PMIP3 and CMIP6/PMIP4 models",

abstract = "El Ni{\~n}o Southern Oscillation (ENSO) is the strongest mode of interannual climate variability in the current climate, influencing ecosystems, agriculture, and weather systems across the globe, but future projections of ENSO frequency and amplitude remain highly uncertain. A comparison of changes in ENSO in a range of past and future climate simulations can provide insights into the sensitivity of ENSO to changes in the mean state, including changes in the seasonality of incoming solar radiation, global average temperatures, and spatial patterns of sea surface temperatures. As a comprehensive set of coupled model simulations is now available for both palaeoclimate time slices (the Last Glacial Maximum, mid-Holocene, and last interglacial) and idealised future warming scenarios (1 % per year CO2 increase, abrupt four-time CO2 increase), this allows a detailed evaluation of ENSO changes in this wide range of climates. Such a comparison can assist in constraining uncertainty in future projections, providing insights into model agreement and the sensitivity of ENSO to a range of factors. The majority of models simulate a consistent weakening of ENSO activity in the last interglacial and mid-Holocene experiments, and there is an ensemble mean reduction of variability in the western equatorial Pacific in the Last Glacial Maximum experiments. Changes in global temperature produce a weaker precipitation response to ENSO in the cold Last Glacial Maximum experiments and an enhanced precipitation response to ENSO in the warm increased CO2 experiments. No consistent relationship between changes in ENSO amplitude and annual cycle was identified across experiments.",

author = "Brown, {Josephine R.} and Brierley, {Chris M.} and An, {Soon Il} and Guarino, {Maria Vittoria} and Samantha Stevenson and Williams, {Charles J.R.} and Qiong Zhang and Anni Zhao and Ayako Abe-Ouchi and Pascale Braconnot and Brady, {Esther C.} and Deepak Chandan and Roberta D'Agostino and Chuncheng Guo and Legrande, {Allegra N.} and Gerrit Lohmann and Morozova, {Polina A.} and Rumi Ohgaito and Ryouta O'Ishi and Otto-Bliesner, {Bette L.} and {Richard Peltier}, W. and Xiaoxu Shi and Louise Sime and Volodin, {Evgeny M.} and Zhongshi Zhang and Weipeng Zheng",

note = "Funding Information: Acknowledgements. Josephine R. Brown acknowledges support from the ARC Centre of Excellence for Climate Extremes (CE170100023). Chris M. Brierley, Charles J. R. Williams, Pas-cale Braconnot, Roberta D{\textquoteright}Agostino, Gerrit Lohmann, and Xiaoxu Shi acknowledge the JPI-Belmont-funded PACMEDY programme (NE/P006752/1; ANR-15-JCLI-0003-01; BMBF 01LP1607A). Soon-Il An was supported by the National Research Foundation of Korea (NRF) grant (NRF-2018R1A5A1024958). Chris M. Brierley was also funded in part by NERC (NE/S009736/1). Maria-Vittoria Guarino acknowledges support from NERC research grant NE/P013279/1. Qiong Zhang acknowledges support from the Swedish Research Council VR projects 2013-06476 and 2017-04232. The EC-Earth simulations are performed on resources provided by the Swedish National Infrastructure for Computing (SNIC) at the National Supercomputer Centre (NSC), partially funded by the Swedish Research Council through grant no. 2016-07213. Rumi Ohgaito acknowledges support from the Integrated Research Program for Advancing Climate Models (TOUGOU programme) from the Ministry of Education, Culture, Sports, Science and Technology (MEXT), Japan. The simulations using MIROC-ES2L were conducted on the Earth Simulator of JAMSTEC. Ryouta O{\textquoteright}ishi and Ayako Abe-Ouchi acknowledge support from Arctic Challenge for Sustainability (ArCS) project (grant no. JPMXD1300000000), JSPS KAKENHI (grant no. 17H06104) and MEXT KAKENHI (grant no. 17H06323), and JAMSTEC for use of the Earth Simulator supercomputer. Bette L. Otto-Bliesner and Esther C. Brady acknowledge the CESM project, supported primarily by the National Science Foundation (NSF). The CESM2 simulations are based upon work supported by the National Center for Atmospheric Research (NCAR), which is a major facility sponsored by the NSF under cooperative agreement no. 1852977. Computing and data storage resources, including the Cheyenne supercomputer (https://doi.org/10.5065/D6RX99HX), were provided by the Computational and Information Systems Laboratory (CISL) at NCAR. Polina A. Morozova was supported by state assignment project 0148-2019-0009. Evgeny M. Volodin was supported by RSF grant no. 20-17-00190. We acknowledge the World Climate Research Programme, which, through its Working Group on Coupled Modelling, coordinated and promoted CMIP6. We thank the climate modelling groups for producing and making available their model output, the Earth System Grid Federation (ESGF) for archiving the data and providing access, and the multiple funding agencies who support CMIP6 and ESGF. PMIP is endorsed by both WCRP/WGCM and Future Earth/PAGES. This research arose out of a workshop hosted at University College London by the PMIP working group on Past2Future: insights from a constantly varying past. Funding Information: Financial support. This research has been supported by the JPI-Belmont-funded PACMEDY programme (grant nos. NE/P006752/1, ANR-15-JCLI-0003-01, and BMBF 01LP1607A); the National Research Foundation of Korea (grant no. NRF-2018R1A5A1024958); the UK NERC (grant nos. NE/S009736/1 and NE/P013279/1); the Swedish Research Council (VR projects 2013-06476, 2017-04232, and 2016-07213); the Integrated Research Program for Advancing Climate Models (TOUGOU programme) from the Ministry of Education, Culture, Sports, Science and Technology (MEXT), Japan; the Arctic Challenge for Sustainability (ArCS) project (grant no. JPMXD1300000000), JSPS KAKENHI (grant no. 17H06104) and MEXT KAKENHI (grant no. 17H06323); the US National Science Foundation (NSF) under cooperative agreement no. 1852977; the Russian State Assignment Project 0148-2019-0009; and the Russian Science Foundation (RSF) (grant no. 20-17-00190). Publisher Copyright: {\textcopyright} 2020 Author(s).",

year = "2020",

month = sep,

day = "28",

doi = "10.5194/cp-16-1777-2020",

language = "English",

volume = "16",

pages = "1777--1805",

journal = "Climate of the Past",

issn = "1814-9324",

publisher = "European Geosciences Union",

number = "5",

}

Brown, JR, Brierley, CM, An, SI, Guarino, MV, Stevenson, S, Williams, CJR, Zhang, Q, Zhao, A, Abe-Ouchi, A, Braconnot, P, Brady, EC, Chandan, D, D'Agostino, R, Guo, C, Legrande, AN, Lohmann, G, Morozova, PA, Ohgaito, R, O'Ishi, R, Otto-Bliesner, BL, Richard Peltier, W, Shi, X, Sime, L, Volodin, EM, Zhang, Z & Zheng, W 2020, 'Comparison of past and future simulations of ENSO in CMIP5/PMIP3 and CMIP6/PMIP4 models', Climate of the Past, vol. 16, no. 5, pp. 1777-1805. https://doi.org/10.5194/cp-16-1777-2020

TY - JOUR

T1 - Comparison of past and future simulations of ENSO in CMIP5/PMIP3 and CMIP6/PMIP4 models

AU - Brown, Josephine R.

AU - Brierley, Chris M.

AU - An, Soon Il

AU - Guarino, Maria Vittoria

AU - Stevenson, Samantha

AU - Williams, Charles J.R.

AU - Zhang, Qiong

AU - Zhao, Anni

AU - Abe-Ouchi, Ayako

AU - Braconnot, Pascale

AU - Brady, Esther C.

AU - Chandan, Deepak

AU - D'Agostino, Roberta

AU - Guo, Chuncheng

AU - Legrande, Allegra N.

AU - Lohmann, Gerrit

AU - Morozova, Polina A.

AU - Ohgaito, Rumi

AU - O'Ishi, Ryouta

AU - Otto-Bliesner, Bette L.

AU - Richard Peltier, W.

AU - Shi, Xiaoxu

AU - Sime, Louise

AU - Volodin, Evgeny M.

AU - Zhang, Zhongshi

AU - Zheng, Weipeng

N1 - Funding Information: Acknowledgements. Josephine R. Brown acknowledges support from the ARC Centre of Excellence for Climate Extremes (CE170100023). Chris M. Brierley, Charles J. R. Williams, Pas-cale Braconnot, Roberta D’Agostino, Gerrit Lohmann, and Xiaoxu Shi acknowledge the JPI-Belmont-funded PACMEDY programme (NE/P006752/1; ANR-15-JCLI-0003-01; BMBF 01LP1607A). Soon-Il An was supported by the National Research Foundation of Korea (NRF) grant (NRF-2018R1A5A1024958). Chris M. Brierley was also funded in part by NERC (NE/S009736/1). Maria-Vittoria Guarino acknowledges support from NERC research grant NE/P013279/1. Qiong Zhang acknowledges support from the Swedish Research Council VR projects 2013-06476 and 2017-04232. The EC-Earth simulations are performed on resources provided by the Swedish National Infrastructure for Computing (SNIC) at the National Supercomputer Centre (NSC), partially funded by the Swedish Research Council through grant no. 2016-07213. Rumi Ohgaito acknowledges support from the Integrated Research Program for Advancing Climate Models (TOUGOU programme) from the Ministry of Education, Culture, Sports, Science and Technology (MEXT), Japan. The simulations using MIROC-ES2L were conducted on the Earth Simulator of JAMSTEC. Ryouta O’ishi and Ayako Abe-Ouchi acknowledge support from Arctic Challenge for Sustainability (ArCS) project (grant no. JPMXD1300000000), JSPS KAKENHI (grant no. 17H06104) and MEXT KAKENHI (grant no. 17H06323), and JAMSTEC for use of the Earth Simulator supercomputer. Bette L. Otto-Bliesner and Esther C. Brady acknowledge the CESM project, supported primarily by the National Science Foundation (NSF). The CESM2 simulations are based upon work supported by the National Center for Atmospheric Research (NCAR), which is a major facility sponsored by the NSF under cooperative agreement no. 1852977. Computing and data storage resources, including the Cheyenne supercomputer (https://doi.org/10.5065/D6RX99HX), were provided by the Computational and Information Systems Laboratory (CISL) at NCAR. Polina A. Morozova was supported by state assignment project 0148-2019-0009. Evgeny M. Volodin was supported by RSF grant no. 20-17-00190. We acknowledge the World Climate Research Programme, which, through its Working Group on Coupled Modelling, coordinated and promoted CMIP6. We thank the climate modelling groups for producing and making available their model output, the Earth System Grid Federation (ESGF) for archiving the data and providing access, and the multiple funding agencies who support CMIP6 and ESGF. PMIP is endorsed by both WCRP/WGCM and Future Earth/PAGES. This research arose out of a workshop hosted at University College London by the PMIP working group on Past2Future: insights from a constantly varying past. Funding Information: Financial support. This research has been supported by the JPI-Belmont-funded PACMEDY programme (grant nos. NE/P006752/1, ANR-15-JCLI-0003-01, and BMBF 01LP1607A); the National Research Foundation of Korea (grant no. NRF-2018R1A5A1024958); the UK NERC (grant nos. NE/S009736/1 and NE/P013279/1); the Swedish Research Council (VR projects 2013-06476, 2017-04232, and 2016-07213); the Integrated Research Program for Advancing Climate Models (TOUGOU programme) from the Ministry of Education, Culture, Sports, Science and Technology (MEXT), Japan; the Arctic Challenge for Sustainability (ArCS) project (grant no. JPMXD1300000000), JSPS KAKENHI (grant no. 17H06104) and MEXT KAKENHI (grant no. 17H06323); the US National Science Foundation (NSF) under cooperative agreement no. 1852977; the Russian State Assignment Project 0148-2019-0009; and the Russian Science Foundation (RSF) (grant no. 20-17-00190). Publisher Copyright: © 2020 Author(s).

PY - 2020/9/28

Y1 - 2020/9/28

N2 - El Niño Southern Oscillation (ENSO) is the strongest mode of interannual climate variability in the current climate, influencing ecosystems, agriculture, and weather systems across the globe, but future projections of ENSO frequency and amplitude remain highly uncertain. A comparison of changes in ENSO in a range of past and future climate simulations can provide insights into the sensitivity of ENSO to changes in the mean state, including changes in the seasonality of incoming solar radiation, global average temperatures, and spatial patterns of sea surface temperatures. As a comprehensive set of coupled model simulations is now available for both palaeoclimate time slices (the Last Glacial Maximum, mid-Holocene, and last interglacial) and idealised future warming scenarios (1 % per year CO2 increase, abrupt four-time CO2 increase), this allows a detailed evaluation of ENSO changes in this wide range of climates. Such a comparison can assist in constraining uncertainty in future projections, providing insights into model agreement and the sensitivity of ENSO to a range of factors. The majority of models simulate a consistent weakening of ENSO activity in the last interglacial and mid-Holocene experiments, and there is an ensemble mean reduction of variability in the western equatorial Pacific in the Last Glacial Maximum experiments. Changes in global temperature produce a weaker precipitation response to ENSO in the cold Last Glacial Maximum experiments and an enhanced precipitation response to ENSO in the warm increased CO2 experiments. No consistent relationship between changes in ENSO amplitude and annual cycle was identified across experiments.

AB - El Niño Southern Oscillation (ENSO) is the strongest mode of interannual climate variability in the current climate, influencing ecosystems, agriculture, and weather systems across the globe, but future projections of ENSO frequency and amplitude remain highly uncertain. A comparison of changes in ENSO in a range of past and future climate simulations can provide insights into the sensitivity of ENSO to changes in the mean state, including changes in the seasonality of incoming solar radiation, global average temperatures, and spatial patterns of sea surface temperatures. As a comprehensive set of coupled model simulations is now available for both palaeoclimate time slices (the Last Glacial Maximum, mid-Holocene, and last interglacial) and idealised future warming scenarios (1 % per year CO2 increase, abrupt four-time CO2 increase), this allows a detailed evaluation of ENSO changes in this wide range of climates. Such a comparison can assist in constraining uncertainty in future projections, providing insights into model agreement and the sensitivity of ENSO to a range of factors. The majority of models simulate a consistent weakening of ENSO activity in the last interglacial and mid-Holocene experiments, and there is an ensemble mean reduction of variability in the western equatorial Pacific in the Last Glacial Maximum experiments. Changes in global temperature produce a weaker precipitation response to ENSO in the cold Last Glacial Maximum experiments and an enhanced precipitation response to ENSO in the warm increased CO2 experiments. No consistent relationship between changes in ENSO amplitude and annual cycle was identified across experiments.

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Comparison of past and future simulations of ENSO in CMIP5/PMIP3 and CMIP6/PMIP4 models

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