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dc.contributor.authorCos, Pep
dc.contributor.authorMarcos Matamoros, Raül
dc.contributor.authorDonat, Markus
dc.contributor.authorMahmood, Rashed
dc.contributor.authorDoblas-Reyes, Francisco
dc.contributor.otherBarcelona Supercomputing Center
dc.date.accessioned2024-09-04T14:40:37Z
dc.date.available2024-09-04T14:40:37Z
dc.date.issued2024-06
dc.identifier.citationCos, P. [et al.]. Near-term Mediterranean summer temperature climate projections: a comparison of constraining methods. "Journal of Climate (JCLI)", Juny 2024, vol. 37, núm. 17, p. 4367-4388.
dc.identifier.issn0894-8755
dc.identifier.issn1520-0442
dc.identifier.urihttp://hdl.handle.net/2117/413832
dc.description.abstractThere are several methods to constrain multimodel projections of future climate. This study assesses the quality of four constraining methods in representing the near-term summer temperature projections of the Mediterranean region. Three are based on phasing in ocean surface temperature variations based on observations or decadal predictions, and the method is based on the measuring performance and independence of the individual simulations. The comparison has been carried out with a new framework inspired by the forecast quality assessment of decadal predictions. The framework led to quality estimates of the constrained projection approaches obtained by producing 20-yr temperature estimates every year from 1970 to 2000 and computing quality metrics against observational references. The evaluation results show some differences between constraining approaches. The improvement or deterioration against quality measures of the full, unconstrained, phase 6 of the Coupled Model Intercomparison Project (CMIP6) ensemble shows strong spatial heterogeneity. From the analysis of the selection approaches it is found that the constraints based on sea surface temperature (SST) fields are affected not only by the variability but also by the warming trend. The weighting method generally shows small quality differences with respect to the full CMIP6 ensemble. Despite caveats of the different methods, there is potential to improve the near-term climate projections as some significant quality enhancements were found in some approaches according to the evaluation metrics used. This study suggests a good understanding of the constraining methods, and their forecast quality is required before using them to take informed decisions. Our study opens the door to optimizing these methods for the Mediterranean climate and highlights the need for evaluating the constraints through retrospective assessments against observational references.
dc.description.sponsorshipThe work of the two anonymous reviewers has also greatly contributed to the quality of this text. This work was partly supported by the European Commission Horizon Europe projects ASPECT (Grant 101081460) and PATHFINDER (Grant PID2021-127943NB-I00 funded by MICIU/AEI/10.13039/501100011033 and by ERDF, EU). Dr. Markus G. Donat is grateful for the kind support through the AXA Research Fund. Dr. Raül Marcos-Matamoros is a Serra Húnter fellow.
dc.language.isoeng
dc.publisherAmerican Meteorological Society
dc.rightsAttribution 4.0 International
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectÀrees temàtiques de la UPC::Enginyeria agroalimentària::Ciències de la terra i de la vida::Climatologia i meteorologia
dc.subject.lcshClimate science
dc.subject.lcshClimatology--Computer programs.
dc.subject.otherClimate sensitivity
dc.subject.otherStatistical techniques
dc.subject.otherForecast verification/skill
dc.subject.otherClimate models
dc.subject.otherModel evaluation/performance
dc.subject.otherClimate variability
dc.titleNear-term Mediterranean summer temperature climate projections: a comparison of constraining methods
dc.typeArticle
dc.subject.lemacSimulació per ordinador
dc.identifier.doi10.1175/JCLI-D-23-0494.1
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttps://journals.ametsoc.org/view/journals/clim/aop/JCLI-D-23-0494.1/JCLI-D-23-0494.1.xml
dc.rights.accessOpen Access
dc.description.versionPostprint (published version)
dc.relation.projectidinfo:eu-repo/grantAgreement/EC/HE/101081460/EU/Adaptation-oriented Seamless Predictions of European ClimaTe/ASPECT
dc.relation.projectidinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/PID2021-127943NB-I00/ES/NUEVAS VIAS PARA SOLVENTAR PROBLEMAS PERSISTENTES EN LA PREDICCION CLIMATICA GLOBAL/
local.citation.publicationNameJournal of Climate (JCLI)
local.citation.volume37
local.citation.number17
local.citation.startingPage4367
local.citation.endingPage4388
dc.relation.datasetAll the data used are publicly available or restricted to the signed-up users of the C3S CDS portal. The observational data used are obtained from Berkeley Earth (https://berkeleyearth.org/data/) and HadSLP (https://doi.org/10.1175/JCLI3937.1). CMIP data: all the CMIP6 datasets were downloaded from the Earth System Grid Federation (ESGF). The models used are listed in Tables S1 and S2. The tool used for the diagnostics (ESMValTool) can be found at https://github.com/ESMValGroup/. ESMValTool and ESMValCore are developed on the GitHub repositories available at https://github.com/ESMValGroup. The evaluation metrics were run with the s2dv package (https://cran.r-project.org/web/packages/s2dv/index.html). The software developed and used to make the calculations in this study is available at https://doi.org/10.5281/zenodo.11160789.


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