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Title of Journal: Clim Dyn

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Abbravation: Climate Dynamics

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Springer-Verlag

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10.1007/s10841-008-9165-2

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1432-0894

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Sensitivity of the southern annular mode to greenh

Authors: Graham R Simpkins Alexey Yu Karpechko
Publish Date: 2011/06/19
Volume: 38, Issue: 3-4, Pages: 563-572
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Abstract

The leading mode of southern hemisphere SH climatic variability the southern annular mode SAM has recently seen a shift towards its positive phase due to stratospheric ozone depletion and increasing greenhouse gas GHG concentrations Here we examine how sensitive the SAM defined as the leading empirical orthogonal function of SH sea level pressure anomalies is to future GHG concentrations We determine its likely evolution for three intergovernmental panel on climate change IPCC special report on emission scenarios SRES for austral summer and winter using a multimodel ensemble of IPCC fourth assessment report models which resolve stratospheric ozone recovery During the period of summer ozone recovery 2000–2050 the SAM index exhibits weakly negative statistically insignificant trends due to stratospheric ozone recovery which offsets the positive forcing imposed by increasing GHG concentrations Thereafter positive SAM index trends occur with magnitudes that show sensitivity to the SRES scenario utilised and thus future GHG emissions Trends are determined to be strongest for SRES A2 followed by A1B and B1 respectively The winter SAM maintains a similar dependency upon GHG as summer but over the entire twentyfirst century and to a greater extent We also examine the influence of ozone recovery by comparing results to models that exclude stratospheric ozone recovery Projections are shown to be statistically different from the aforementioned results highlighting the importance of ozone recovery in governing SAMevolution We therefore demonstrate that the future SAM will depend both upon GHG emissions and stratospheric ozone recoveryThis work was funded in part by a NERC Postgraduate Masters Studentship AK was funded by NERC Project NE/E006787/1 and by the Finnish Academy We acknowledge the modelling groups the Program for Climate Model Diagnosis and Intercomparison PCMDI and the WCRP’s Working Group on Coupled Modelling WGCM for their role in making the WCRP CMIP3 multimodel dataset available The authors thank the anonymous reviewer for their constructive comments which improved this manuscript and Dr Laura Ciasto for insightful discussions of results

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