Diagnostic indicators for integrated assessment models of climate policy

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dc.contributor.authorKriegler, Elmarko
dc.contributor.authorPetermann, Nilsko
dc.contributor.authorKrey, Volkerko
dc.contributor.authorSchwanitz, Valeria Janako
dc.contributor.authorLuderer, Gunnarko
dc.contributor.authorAshina, Shuichiko
dc.contributor.authorBosetti, Valentinako
dc.contributor.authorEom, Jiyongko
dc.contributor.authorKitous, Albanko
dc.contributor.authorMejean, Aurelieko
dc.contributor.authorParoussos, Leonidasko
dc.contributor.authorSano, Fuminoriko
dc.contributor.authorTurton, Halko
dc.contributor.authorWilson, Charlieko
dc.contributor.authorDetlef P. Van Vuurenko
dc.date.accessioned2016-04-12T07:59:13Z-
dc.date.available2016-04-12T07:59:13Z-
dc.date.created2014-07-13-
dc.date.created2014-07-13-
dc.date.created2014-07-13-
dc.date.issued2015-01-
dc.identifier.citationTECHNOLOGICAL FORECASTING AND SOCIAL CHANGE, v.90, pp.45 - 61-
dc.identifier.issn0040-1625-
dc.identifier.urihttp://hdl.handle.net/10203/203436-
dc.description.abstractIntegrated assessments of how climate policy interacts with energy-economy systems can be performed by a variety of models with different functional structures. In order to provide insights into why results differ between models, this article proposes a diagnostic scheme that can be applied to a wide range of models. Diagnostics can uncover patterns of model behavior and indicate how results differ between model types. Such insights are informative since model behavior can have a significant impact on projections of climate change mitigation costs and other policy-relevant information. The authors propose diagnostic indicators to characterize model responses to carbon price signals and test these in a diagnostic study of 11 global models. Indicators describe the magnitude of emission abatement and the associated costs relative to a harmonized baseline, the relative changes in carbon intensity and energy intensity, and the extent of transformation in the energy system. This study shows a correlation among indicators suggesting that models can be classified into groups based on common patterns of behavior in response to carbon pricing. Such a classification can help to explain variations among policy-relevant model results. (C) 2014 The Authors. Published by Elsevier Inc.-
dc.languageEnglish-
dc.publisherELSEVIER SCIENCE INC-
dc.subjectMITIGATION-
dc.subjectEXERCISE-
dc.subjectENERGY-
dc.subjectCOSTS-
dc.titleDiagnostic indicators for integrated assessment models of climate policy-
dc.typeArticle-
dc.identifier.wosid000347605300004-
dc.identifier.scopusid2-s2.0-84916896405-
dc.type.rimsART-
dc.citation.volume90-
dc.citation.beginningpage45-
dc.citation.endingpage61-
dc.citation.publicationnameTECHNOLOGICAL FORECASTING AND SOCIAL CHANGE-
dc.identifier.doi10.1016/j.techfore.2013.09.020-
dc.contributor.localauthorEom, Jiyong-
dc.contributor.nonIdAuthorKriegler, Elmar-
dc.contributor.nonIdAuthorPetermann, Nils-
dc.contributor.nonIdAuthorKrey, Volker-
dc.contributor.nonIdAuthorSchwanitz, Valeria Jana-
dc.contributor.nonIdAuthorLuderer, Gunnar-
dc.contributor.nonIdAuthorAshina, Shuichi-
dc.contributor.nonIdAuthorBosetti, Valentina-
dc.contributor.nonIdAuthorKitous, Alban-
dc.contributor.nonIdAuthorMejean, Aurelie-
dc.contributor.nonIdAuthorParoussos, Leonidas-
dc.contributor.nonIdAuthorSano, Fuminori-
dc.contributor.nonIdAuthorTurton, Hal-
dc.contributor.nonIdAuthorWilson, Charlie-
dc.contributor.nonIdAuthorDetlef P. Van Vuuren-
dc.type.journalArticleArticle-
dc.subject.keywordAuthorClimate policy-
dc.subject.keywordAuthorIntegrated assessment models-
dc.subject.keywordAuthorEnergy system models-
dc.subject.keywordAuthorModel diagnostics-
dc.subject.keywordAuthorClimate change economics-
dc.subject.keywordPlusMITIGATION-
dc.subject.keywordPlusEXERCISE-
dc.subject.keywordPlusENERGY-
dc.subject.keywordPlusCOSTS-
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