Validation of CMIP5 multimodel ensembles through the smoothness of climate variables

Handle URI:
http://hdl.handle.net/10754/555652
Title:
Validation of CMIP5 multimodel ensembles through the smoothness of climate variables
Authors:
Lee, Myoungji; Jun, Mikyoung; Genton, Marc G. ( 0000-0001-6467-2998 )
Abstract:
Smoothness is an important characteristic of a spatial process that measures local variability. If climate model outputs are realistic, then not only the values at each grid pixel but also the relative variation over nearby pixels should represent the true climate. We estimate the smoothness of long-term averages for land surface temperature anomalies in the Coupled Model Intercomparison Project Phase 5 (CMIP5), and compare them by climate regions and seasons. We also compare the estimated smoothness of the climate outputs in CMIP5 with those of reanalysis data. The estimation is done through the composite likelihood approach for locally self-similar processes. The composite likelihood that we consider is a product of conditional likelihoods of neighbouring observations. We find that the smoothness of the surface temperature anomalies in CMIP5 depends primarily on the modelling institution and on the climate region. The seasonal difference in the smoothness is generally small, except for some climate regions where the average temperature is extremely high or low.
KAUST Department:
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Citation:
Validation of CMIP5 multimodel ensembles through the smoothness of climate variables 2015, 67 (0) Tellus A
Publisher:
Co-Action Publishing
Journal:
Tellus A
Issue Date:
14-May-2015
DOI:
10.3402/tellusa.v67.23880
Type:
Article
ISSN:
1600-0870; 0280-6495
Additional Links:
http://www.tellusa.net/index.php/tellusa/article/view/23880
Appears in Collections:
Articles; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

Full metadata record

DC FieldValue Language
dc.contributor.authorLee, Myoungjien
dc.contributor.authorJun, Mikyoungen
dc.contributor.authorGenton, Marc G.en
dc.date.accessioned2015-05-25T08:36:05Zen
dc.date.available2015-05-25T08:36:05Zen
dc.date.issued2015-05-14en
dc.identifier.citationValidation of CMIP5 multimodel ensembles through the smoothness of climate variables 2015, 67 (0) Tellus Aen
dc.identifier.issn1600-0870en
dc.identifier.issn0280-6495en
dc.identifier.doi10.3402/tellusa.v67.23880en
dc.identifier.urihttp://hdl.handle.net/10754/555652en
dc.description.abstractSmoothness is an important characteristic of a spatial process that measures local variability. If climate model outputs are realistic, then not only the values at each grid pixel but also the relative variation over nearby pixels should represent the true climate. We estimate the smoothness of long-term averages for land surface temperature anomalies in the Coupled Model Intercomparison Project Phase 5 (CMIP5), and compare them by climate regions and seasons. We also compare the estimated smoothness of the climate outputs in CMIP5 with those of reanalysis data. The estimation is done through the composite likelihood approach for locally self-similar processes. The composite likelihood that we consider is a product of conditional likelihoods of neighbouring observations. We find that the smoothness of the surface temperature anomalies in CMIP5 depends primarily on the modelling institution and on the climate region. The seasonal difference in the smoothness is generally small, except for some climate regions where the average temperature is extremely high or low.en
dc.publisherCo-Action Publishingen
dc.relation.urlhttp://www.tellusa.net/index.php/tellusa/article/view/23880en
dc.rightsThis is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0 International License, allowing third parties to copy and redistribute the material in any medium or format and to remix, transform, and build upon the material for any purpose, even commercially, provided the original work is properly cited and states its license.en
dc.subjectcomposite likelihooden
dc.subjectGaussian processen
dc.subjectNCEP/NCAR reanalysisen
dc.subjectrestricted likelihooden
dc.subjectsurface temperature anomalyen
dc.subjectuncertainty quantificationen
dc.subjectvariogramen
dc.titleValidation of CMIP5 multimodel ensembles through the smoothness of climate variablesen
dc.typeArticleen
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
dc.identifier.journalTellus Aen
dc.eprint.versionPublisher's Version/PDFen
dc.contributor.institutionInstitute for Applied Mathematics and Computational Science, Texas A&M University, College Station, TX, USAen
dc.contributor.institutionDepartment of Statistics, Texas A&M University, College Station, TX, USAen
kaust.authorGenton, Marc G.en
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