P. Köhler, L. Stap, A. S. Heydt, B. Boer, R. Wal, J. Bloch‐Johnson
{"title":"A State-Dependent Quantification of Climate Sensitivity Based on Paleodata of the Last 2.1 Million Years","authors":"P. Köhler, L. Stap, A. S. Heydt, B. Boer, R. Wal, J. Bloch‐Johnson","doi":"10.1002/2017PA003190","DOIUrl":null,"url":null,"abstract":"The evidence from both data and models indicates that specific equilibrium climate sensitivity S[X] — the global annual mean surface temperature change (ΔTg) as a response to a change in radiative forcing X (ΔR[X]) — is state-dependent. Such a state dependency implies that the best fit in the scatter plot of ΔTg versus ΔR[X] is not a linear regression, but can be some non-linear or even non-smooth function. While for the conventional linear case the slope (gradient) of the regression is correctly interpreted as the specific equilibrium climate sensitivity S[X], the interpretation is not straightforward in the non-linear case. We here explain how such a state-dependent scatter plot needs to be interpreted, and provide a theoretical understanding — or generalization — how to quantify S[X] in the non-linear case. Finally, from data covering the last 2.1 Myr we show that — due to state dependency — the specific equilibrium climate sensitivity which considers radiative forcing of CO2 and land ice sheet (LI) albedo, S[CO2,LI], is larger during interglacial states than during glacial conditions by more than a factor two.","PeriodicalId":19882,"journal":{"name":"Paleoceanography","volume":"32 1","pages":"1102-1114"},"PeriodicalIF":0.0000,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1002/2017PA003190","citationCount":"20","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Paleoceanography","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1002/2017PA003190","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 20
Abstract
The evidence from both data and models indicates that specific equilibrium climate sensitivity S[X] — the global annual mean surface temperature change (ΔTg) as a response to a change in radiative forcing X (ΔR[X]) — is state-dependent. Such a state dependency implies that the best fit in the scatter plot of ΔTg versus ΔR[X] is not a linear regression, but can be some non-linear or even non-smooth function. While for the conventional linear case the slope (gradient) of the regression is correctly interpreted as the specific equilibrium climate sensitivity S[X], the interpretation is not straightforward in the non-linear case. We here explain how such a state-dependent scatter plot needs to be interpreted, and provide a theoretical understanding — or generalization — how to quantify S[X] in the non-linear case. Finally, from data covering the last 2.1 Myr we show that — due to state dependency — the specific equilibrium climate sensitivity which considers radiative forcing of CO2 and land ice sheet (LI) albedo, S[CO2,LI], is larger during interglacial states than during glacial conditions by more than a factor two.