{"@context":{"@vocab":"https://cir.nii.ac.jp/schema/1.0/","rdfs":"http://www.w3.org/2000/01/rdf-schema#","dc":"http://purl.org/dc/elements/1.1/","dcterms":"http://purl.org/dc/terms/","foaf":"http://xmlns.com/foaf/0.1/","prism":"http://prismstandard.org/namespaces/basic/2.0/","cinii":"http://ci.nii.ac.jp/ns/1.0/","datacite":"https://schema.datacite.org/meta/kernel-4/","ndl":"http://ndl.go.jp/dcndl/terms/","jpcoar":"https://github.com/JPCOAR/schema/blob/master/2.0/"},"@id":"https://cir.nii.ac.jp/crid/1361699996336537600.json","@type":"Article","productIdentifier":[{"identifier":{"@type":"DOI","@value":"10.1002/env.2140"}},{"identifier":{"@type":"URI","@value":"https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Fenv.2140"}},{"identifier":{"@type":"URI","@value":"https://onlinelibrary.wiley.com/doi/pdf/10.1002/env.2140"}}],"dc:title":[{"@value":"Bayesian estimation of climate sensitivity based on a simple climate model fitted to observations of hemispheric temperatures and global ocean heat content"}],"description":[{"type":"abstract","notation":[{"@value":"<jats:p>Predictions of climate change are uncertain mainly because of uncertainties in the emissions of greenhouse gases and how sensitive the climate is to changes in the abundance of the atmospheric constituents. The equilibrium climate sensitivity is defined as the temperature increase because of a doubling of the CO<jats:sub>2</jats:sub> concentration in the atmosphere when the climate reaches a new steady state. CO<jats:sub>2</jats:sub> is only one out of the several external factors that affect the global temperature, called radiative forcing mechanisms as a collective term. In this paper, we present a model framework for estimating the climate sensitivity. The core of the model is a simple, deterministic climate model based on elementary physical laws such as energy balance. It models yearly hemispheric surface temperature and global ocean heat content as a function of historical radiative forcing. This deterministic model is combined with an empirical, stochastic model and fitted to observations on global temperature and ocean heat content, conditioned on estimates of historical radiative forcing. We use a Bayesian framework, with informative priors on a subset of the parameters and flat priors on the climate sensitivity and the remaining parameters. The model is estimated by Markov Chain Monte Carlo techniques. Copyright © 2012 John Wiley & Sons, Ltd.</jats:p>"}]}],"creator":[{"@id":"https://cir.nii.ac.jp/crid/1381699996336537600","@type":"Researcher","foaf:name":[{"@value":"Magne Aldrin"}],"jpcoar:affiliationName":[{"@value":"Norwegian Computing Center  Norway"},{"@value":"Department of Mathematics University of Oslo  Oslo Norway"}]},{"@id":"https://cir.nii.ac.jp/crid/1381699996336537601","@type":"Researcher","foaf:name":[{"@value":"Marit Holden"}],"jpcoar:affiliationName":[{"@value":"Norwegian Computing Center  Norway"}]},{"@id":"https://cir.nii.ac.jp/crid/1381699996336537602","@type":"Researcher","foaf:name":[{"@value":"Peter Guttorp"}],"jpcoar:affiliationName":[{"@value":"Norwegian Computing Center  Norway"},{"@value":"Department of Statistics University of Washington  WA U.S.A."}]},{"@id":"https://cir.nii.ac.jp/crid/1381699996336537604","@type":"Researcher","foaf:name":[{"@value":"Ragnhild Bieltvedt Skeie"}],"jpcoar:affiliationName":[{"@value":"Center for International Climate and Environmental Research ‐ Oslo  Oslo Norway"}]},{"@id":"https://cir.nii.ac.jp/crid/1381699996336537603","@type":"Researcher","foaf:name":[{"@value":"Gunnar Myhre"}],"jpcoar:affiliationName":[{"@value":"Center for International Climate and Environmental Research ‐ Oslo  Oslo Norway"}]},{"@id":"https://cir.nii.ac.jp/crid/1381699996336537605","@type":"Researcher","foaf:name":[{"@value":"Terje Koren Berntsen"}],"jpcoar:affiliationName":[{"@value":"Center for International Climate and Environmental Research ‐ Oslo  Oslo Norway"},{"@value":"Department of Geosciences University of Oslo  Oslo Norway"}]}],"publication":{"publicationIdentifier":[{"@type":"PISSN","@value":"11804009"},{"@type":"EISSN","@value":"1099095X"}],"prism:publicationName":[{"@value":"Environmetrics"}],"dc:publisher":[{"@value":"Wiley"}],"prism:publicationDate":"2012-02-24","prism:volume":"23","prism:number":"3","prism:startingPage":"253","prism:endingPage":"271"},"reviewed":"false","dc:rights":["http://onlinelibrary.wiley.com/termsAndConditions#vor"],"url":[{"@id":"https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Fenv.2140"},{"@id":"https://onlinelibrary.wiley.com/doi/pdf/10.1002/env.2140"}],"createdAt":"2012-02-24","modifiedAt":"2023-10-30","relatedProduct":[{"@id":"https://cir.nii.ac.jp/crid/1390287772332351104","@type":"Article","resourceType":"学術雑誌論文(journal article)","relationType":["isReferencedBy"],"jpcoar:relatedTitle":[{"@language":"en","@value":"A New Graphical Method to Diagnose the Impacts of Model Changes on Climate Sensitivity"},{"@language":"ja","@value":"モデルチェンジの気候感度への影響を診断する新たなグラフ手法"}]},{"@id":"https://cir.nii.ac.jp/crid/2051996266842852864","@type":"Article","resourceType":"学術雑誌論文(journal article)","relationType":["isReferencedBy"],"jpcoar:relatedTitle":[{"@value":"A review of progress towards understanding the transient global mean surface temperature response to radiative perturbation"}]}],"dataSourceIdentifier":[{"@type":"CROSSREF","@value":"10.1002/env.2140"},{"@type":"CROSSREF","@value":"10.1186/s40645-016-0096-3_references_DOI_VzdmehIrRMuLSMerSSFhpyK8BYR"},{"@type":"CROSSREF","@value":"10.2151/jmsj.2021-021_references_DOI_VzdmehIrRMuLSMerSSFhpyK8BYR"}]}