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Pattern Scaling: An Examination of the Accuracy of the Technique for Describing Future Climates

Pattern Scaling: An Examination of the Accuracy of the Technique for Describing Future Climates A fully probabilistic, or risk, assessment of future regional climate changeand its impacts involves more scenarios of radiative forcing than can besimulated by a general (GCM) or regional (RCM) circulation model. Additionalscenarios may be created by scaling a spatial response pattern from a GCM bya global warming projection from a simple climate model. I examine thistechnique, known as pattern scaling, using a particular GCM (HadCM2).Thecritical assumption is that there is a linear relationship between the scaler(annual global-mean temperature) and the response pattern. Previous studieshave found this assumption to be broadly valid for annual temperature; Iextend this conclusion to precipitation and seasonal (JJA) climate. However,slight non-linearities arise from the dependence of the climatic response onthe rate, not just the amount, of change in the scaler. These non-linearitiesintroduce some significant errors into the estimates made by pattern scaling,but nonetheless the estimates accurately represent the modelled changes. Aresponse pattern may be made more robust by lengthening the period from whichit is obtained, by anomalising it relative to the control simulation, and byusing least squares regression to obtain it. The errors arising from patternscaling may be minimised by interpolating from a stronger to a weaker forcingscenario. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Climatic Change Springer Journals

Pattern Scaling: An Examination of the Accuracy of the Technique for Describing Future Climates

Climatic Change , Volume 60 (3) – Oct 10, 2004

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References (42)

Publisher
Springer Journals
Copyright
Copyright © 2003 by Kluwer Academic Publishers
Subject
Earth Sciences; Atmospheric Sciences; Climate Change/Climate Change Impacts
ISSN
0165-0009
eISSN
1573-1480
DOI
10.1023/A:1026035305597
Publisher site
See Article on Publisher Site

Abstract

A fully probabilistic, or risk, assessment of future regional climate changeand its impacts involves more scenarios of radiative forcing than can besimulated by a general (GCM) or regional (RCM) circulation model. Additionalscenarios may be created by scaling a spatial response pattern from a GCM bya global warming projection from a simple climate model. I examine thistechnique, known as pattern scaling, using a particular GCM (HadCM2).Thecritical assumption is that there is a linear relationship between the scaler(annual global-mean temperature) and the response pattern. Previous studieshave found this assumption to be broadly valid for annual temperature; Iextend this conclusion to precipitation and seasonal (JJA) climate. However,slight non-linearities arise from the dependence of the climatic response onthe rate, not just the amount, of change in the scaler. These non-linearitiesintroduce some significant errors into the estimates made by pattern scaling,but nonetheless the estimates accurately represent the modelled changes. Aresponse pattern may be made more robust by lengthening the period from whichit is obtained, by anomalising it relative to the control simulation, and byusing least squares regression to obtain it. The errors arising from patternscaling may be minimised by interpolating from a stronger to a weaker forcingscenario.

Journal

Climatic ChangeSpringer Journals

Published: Oct 10, 2004

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