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| Keywords | |
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decadal prediction |
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global warming |
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multi-decadal climate variability |
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the Ensemble Empirical Mode Decomposition |
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CMIP3 multi-model |
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| PubMed | |
Projection of global mean surface air temperature changes in next 40 years: Uncertainties of climate models and an alternative approach
FU CongBin1,2*, QIAN Cheng2, WU ZhaoHua3
1. Institute for Climate and Global Change Research, School of Atmospheric Sciences, Nanjing University, Nanjing 210093, China;
2. Key Laboratory of Regional Climate-Environment for Temperate East Asia, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China;
3. Department of Earth, Ocean, and Atmospheric Science & Center for Ocean-Atmospheric Prediction Studies, Florida State University, Tallahassee, Fl32308 USA
The Fourth Assessment Report (AR4) of the Intergovernmental Panel of Climate Change (IPCC) concluded that the climate projection using climate models that took account of both human and natural factors provided credible quantitative estimates of future climate change; however, the mismatches between the IPCC AR4 model ensembles and the observations, especially the multi-decadal variability (MDV), have cast shadows on the confidence of the model-based decadal projections of future climate. This paper reports an evaluation of many individual runs of AR4 models in the simulation of past global mean temperature. We find that most of the individual model runs fail to reproduce the MDV of past climate, which may have led to the overestimation of the projection of global warming for the next 40 years or so. Based on such an evaluation, we propose an alternative approach, in which the MDV signal is taken into account, to project the global mean temperature for the next 40 years and obtain that the global warming during 2011-2050 could be much smaller than the AR4 projection.
This work was supported by the National Basic Research Program of China (Grant No. 2011CB952000) and the National Natural Science Foundation of China (Grant No. 40810059003); Qian Cheng was partly supported by the "Strategic Priority Research Program" of the Chinese Academy of Sciences (Grant No. XDA05090103); and Wu Zhaohua was supported by the Natural Science Foundation of USA (Grant No. ATM-0917743). The authors thank Dr. Zhou Tianjun for helping collection of CMIP3 data. We also thank two anonymous reviewers for helpful suggestions.