Preprints
https://doi.org/10.5194/cp-2016-23
https://doi.org/10.5194/cp-2016-23
15 Mar 2016
 | 15 Mar 2016
Status: this preprint was under review for the journal CP but the revision was not accepted.

Technical Note: Calculating state dependent equilibrium climate sensitivity from palaeodata

Peter Köhler, Lennert B. Stap, Anna S. von der Heydt, Bas de Boer, and Roderik S. W. van de Wal

Abstract. The evidence from both data and models indicate that specific equilibrium climate sensitivity S[X] – the global annual mean surface temperature change (∆Tg) as a response to a change in radiative forcing X (∆R[X]) – is state dependent. Such a state dependency implies that the best fit in the scatter plot of ∆Tg versus ∆R[X] is not a linear regression, but for instance a higher order polynomial. 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 elaborate how such a state dependent scatter plot needs to be interpreted, and provide a theoretical understanding how to calculate S[X] in the non-linear case.

Peter Köhler, Lennert B. Stap, Anna S. von der Heydt, Bas de Boer, and Roderik S. W. van de Wal
 
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Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement
Peter Köhler, Lennert B. Stap, Anna S. von der Heydt, Bas de Boer, and Roderik S. W. van de Wal
Peter Köhler, Lennert B. Stap, Anna S. von der Heydt, Bas de Boer, and Roderik S. W. van de Wal

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Short summary
Evidence indicate that specific equilibrium climate sensitivity, the global annual mean surface temperature change as a response to a change in radiative forcing, is state dependent. We here show that the interpretation of data in the state-dependent case is not straightforward. We analyse the differences of a point-wise approach and one based on a piece-wise linear analysis, combine both, compare with potential model results and apply the theoretical concepts to data of the last 800 kyr.