Communicating global climate change using simple indices: an update

被引:20
作者
Drost, Frank [1 ]
Karoly, David [1 ]
Braganza, Karl [2 ]
机构
[1] Univ Melbourne, Sch Earth Sci, Melbourne, Vic 3010, Australia
[2] Natl Climate Ctr, Bur Meteorol, Melbourne, Vic 3001, Australia
基金
澳大利亚研究理事会;
关键词
Climate change; Climate indices; Surface temperature; Climate model simulations; CMIP3; data; PART II; TEMPERATURE; MODEL; VARIABILITY; ATTRIBUTION; SYSTEM; TRENDS;
D O I
10.1007/s00382-011-1227-6
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
Previous studies have shown that there are several indices of global-scale temperature variations, in addition to global-mean surface air temperature, that are useful for distinguishing natural internal climate variations from anthropogenic climate change. Appropriately defined, such indices have the ability to capture spatio-temporal information in a similar manner to optimal fingerprints of climate change. These indices include the contrast between the average temperatures over land and over oceans, the Northern Hemisphere meridional temperature gradient, the temperature contrast between the Northern and Southern Hemisphere and the magnitude of the annual cycle of average temperatures over land. They contain information independent of the global-mean temperature for internal climate variations at decadal time scales and represent different aspects of the climate system, yet they show common responses to anthropogenic climate change. In addition, the ratio of average temperature changes over land to those over the oceans should be nearly constant for transient climate change. Hence, supplementing analysis of global-mean surface temperature with analyses of these indices can strengthen results of attribution studies of causes of observed climate variations. In this study, we extend the previous work by including the last 10 years of observational data and the CMIP3 climate model simulations analysed for the IPCC AR4. We show that observed changes in these indices over the last 10 years provide increased evidence of an anthropogenic influence on climate. We also show the usefulness of these indices for evaluating the performance of climate models in simulating large-scale variability of surface temperature.
引用
收藏
页码:989 / 999
页数:11
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