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dc.contributor.authorHill, PG
dc.contributor.authorHolloway, CE
dc.contributor.authorByrne, MP
dc.contributor.authorLambert, FH
dc.contributor.authorWebb, MJ
dc.date.accessioned2023-11-16T15:47:26Z
dc.date.issued2023-08-02
dc.date.updated2023-11-16T15:38:55Z
dc.description.abstractCloud feedbacks are the leading cause of uncertainty in climate sensitivity. The complex coupling between clouds and the large-scale circulation in the tropics contributes to this uncertainty. To address this problem, the coupling between clouds and circulation in the latest generation of climate models is compared to observations. Significant biases are identified in the models. The implications of these biases are assessed by combining observations of the present day with future changes predicted by models to calculate observationally constrained feedbacks. For the dynamic cloud feedback (i.e., due to changes in circulation), the observationally constrained values are consistently larger than the model-only values. This is due to models failing to capture a nonlinear minimum in cloud brightness for weakly descending regimes. Consequently, while the models consistently predict that these regimes increase in frequency in association with a weakening tropical circulation, they underestimate the positive cloud feedback associated with this increase.en_GB
dc.description.sponsorshipNatural Environment Research Council (NERC)en_GB
dc.description.sponsorshipMet Office Hadley Centre Climate Programmeen_GB
dc.identifier.citationVol. 50(15), article e2023GL104573en_GB
dc.identifier.doihttps://doi.org/10.1029/2023gl104573
dc.identifier.grantnumberNE/T006315/1en_GB
dc.identifier.urihttp://hdl.handle.net/10871/134569
dc.identifierORCID: 0000-0002-4664-1327 (Lambert, FH)
dc.identifierScopusID: 56575686800 (Lambert, FH)
dc.language.isoenen_GB
dc.publisherAmerican Geophysical Union (AGU) / Wileyen_GB
dc.relation.urlhttps://esgf-node.llnl.gov/projects/cmip6en_GB
dc.relation.urlhttps://cds.climate.copernicus.euen_GB
dc.relation.urlhttps://disc.gsfc.nasa.gov/datasets?project=MERRA-2en_GB
dc.relation.urlhttps://rda.ucar.edu/en_GB
dc.relation.urlhttps://ceres.larc.nasa.gov/data/en_GB
dc.relation.urlhttps://github.com/PeterGHill/CMIP6_DynamicCloudFeedbacksen_GB
dc.rights© 2023. The Authors. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.en_GB
dc.titleClimate Models Underestimate Dynamic Cloud Feedbacks in the Tropicsen_GB
dc.typeArticleen_GB
dc.date.available2023-11-16T15:47:26Z
dc.identifier.issn0094-8276
dc.descriptionThis is the final version. Available on open access from the American Geophysical Union via the DOI in this recorden_GB
dc.descriptionData Availability Statement: The climate model data used in this study are available from the Earth System Grid Foundation https://esgf-node.llnl.gov/projects/cmip6/. ERA5 data are available from the Copernicus Climate Data Store https://cds.climate.copernicus.eu. MERRA2 data were downloaded from https://disc.gsfc.nasa.gov/datasets?project=MERRA-2. JRA55 were downloaded from the NCAR research data archive https://rda.ucar.edu/. CERES-EBAF data were downloaded from https://ceres.larc.nasa.gov/data/. Python code used to perform the analysis described in this study is available from https://github.com/PeterGHill/CMIP6_DynamicCloudFeedbacks.en_GB
dc.identifier.eissn1944-8007
dc.identifier.journalGeophysical Research Lettersen_GB
dc.relation.ispartofGeophysical Research Letters, 50(15)
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_GB
dcterms.dateAccepted2023-07-21
rioxxterms.versionVoRen_GB
rioxxterms.licenseref.startdate2023-08-02
rioxxterms.typeJournal Article/Reviewen_GB
refterms.dateFCD2023-11-16T15:45:34Z
refterms.versionFCDVoR
refterms.dateFOA2023-11-16T15:47:34Z
refterms.panelBen_GB
refterms.dateFirstOnline2023-08-02


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© 2023. The Authors.
This is an open access article under 
the terms of the Creative Commons 
Attribution License, which permits use, 
distribution and reproduction in any 
medium, provided the original work is 
properly cited.
Except where otherwise noted, this item's licence is described as © 2023. The Authors. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.