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dc.contributor.authorZhong, S
dc.contributor.authorYing, J
dc.contributor.authorCollins, M
dc.date.accessioned2023-06-20T08:23:59Z
dc.date.issued2023-03-15
dc.date.updated2023-06-20T05:51:48Z
dc.description.abstractDetermining the time of emergence of anthropogenic climate change signals from natural variability, for both the tropical Pacific mean state and El Niño–Southern Oscillation (ENSO), are critical for early climate warning and adaptation planning. However, there remains considerable uncertainty in estimating those times of emergence in state-of-the-art climate models. In this study, the role of internal variability in the uncertainty of the times of emergence of tropical Pacific annual-mean sea surface temperature (SST) and rainfall, and ENSO-related SST and rainfall are investigated by using three large ensembles of model simulations under the historical and RCP8.5 emission scenarios, as well as the multimodel ensemble from phase 6 of the Coupled Model Intercomparison Project under the historical and SSP5–8.5 emission scenarios. Specific attention is paid to the eastern equatorial Pacific. It is found that internal variability contributes to less than half of the total uncertainty in both the times of emergence of annual-mean SST and rainfall in all the three large ensembles, with more contribution to the latter than to the former. Hence, model differences dominate. Conversely, internal variability contributes to a major part of the total uncertainty in the times of emergence of ENSO-related SST and rainfall in one large ensemble that has sufficient members to show emergent signals. These results imply that we could have a relatively high confidence in claiming that anthropogenic climate change has impacted the annual-mean state, if an emergent annual-mean signal is observed in the real world. However, in claiming changes in ENSO variability, the signal is easily obscured by internal variability.en_GB
dc.description.sponsorshipNatural Environment Research Council (NERC)en_GB
dc.description.sponsorshipNational Natural Science Foundation of Chinaen_GB
dc.description.sponsorshipSecond Institute of Oceanography, Ministry of Natural Resourcesen_GB
dc.description.sponsorshipSouthern Marine Science and Engineering Guangdong Laboratory (Zhuhai)en_GB
dc.identifier.citationVol. 36, No. 8, pp. 2535–2549en_GB
dc.identifier.doihttps://doi.org/10.1175/JCLI-D-22-0554.1
dc.identifier.grantnumberNE/S004645/1en_GB
dc.identifier.grantnumber42227901en_GB
dc.identifier.grantnumberQNYC2001en_GB
dc.identifier.grantnumber311021001en_GB
dc.identifier.urihttp://hdl.handle.net/10871/133425
dc.identifierORCID: 0000-0003-3785-6008 (Collins, Matthew)
dc.language.isoenen_GB
dc.publisherAmerican Meteorological Societyen_GB
dc.relation.urlhttps://esgf-node.llnl.gov/projects/cmip6/en_GB
dc.relation.urlhttp://www.cesm.ucar.edu/projects/community-projects/LENS/en_GB
dc.relation.urlhttps://open.canada.ca/data/en/dataset/aa7b6823-fd1e-49ff-a6fb-68076a4a477cen_GB
dc.relation.urlhttps://esgf541 data.dkrz.de/projects/mpi-ge/en_GB
dc.rights© 2023 American Meteorological Society. This version is made available under the CC-BY 4.0 license: https://creativecommons.org/licenses/by/4.0/  en_GB
dc.titleSources of uncertainty in the time of emergence of tropical Pacific climate change signal: role of internal variabilityen_GB
dc.typeArticleen_GB
dc.date.available2023-06-20T08:23:59Z
dc.identifier.issn0894-8755
dc.descriptionThis is the author accepted manuscript. The final version is available from the American Meteorological Society via the DOI in this recorden_GB
dc.descriptionData Availability Statement: The CMIP6 model outputs are derived from: https://esgf-node.llnl.gov/projects/cmip6/. The large ensembles of CESM1 are derived from: http://www.cesm.ucar.edu/projects/community-projects/LENS/. The large ensembles of CanESM2 are derived from: https://open.canada.ca/data/en/dataset/aa7b6823-fd1e-49ff-a6fb-68076a4a477c. The large ensembles of MPI-ESM are derived from: https://esgf541 data.dkrz.de/projects/mpi-ge/.en_GB
dc.identifier.eissn1520-0442
dc.identifier.journalJournal of Climateen_GB
dc.relation.ispartofJournal of Climate
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_GB
dcterms.dateAccepted2022-12-11
dcterms.dateSubmitted2022-11-01
rioxxterms.versionAMen_GB
rioxxterms.licenseref.startdate2023-03-15
rioxxterms.typeJournal Article/Reviewen_GB
refterms.dateFCD2023-06-20T05:51:53Z
refterms.versionFCDAM
refterms.dateFOA2023-06-20T08:24:01Z
refterms.panelBen_GB
refterms.dateFirstOnline2023-03-15


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© 2023 American Meteorological Society. This version is made available under the CC-BY 4.0 license: https://creativecommons.org/licenses/by/4.0/  
Except where otherwise noted, this item's licence is described as © 2023 American Meteorological Society. This version is made available under the CC-BY 4.0 license: https://creativecommons.org/licenses/by/4.0/