Sensitivity of Asian climate change to radiative forcing during the last millennium in a multi-model analysis
Sensitivity of Asian climate change to radiative forcing during the last millennium in a multi-model analysis
复制标题
多模型分析亚洲近千年气候变化对辐射强迫的敏感性
DOI:
10.1016/j.gloplacha.2016.02.007
复制
发表时间:
2016-04
影响因子:
3.9
通讯作者:
Wang Hongli
中科院分区:
文献类型:
--
作者:
Shi Zhengguo;Xu Tingting;Wang Hongli
The outputs of last millennium (A.D. 850–1850) experiments from seven climate models of the Paleoclimate Modeling Intercomparison Project 3, have been used to analyze decadal to centennial climatic variations over Asia, including the Indian monsoon, the East Asian monsoon and the westerly jet. In particular, the differences between the Medieval Warm Period (MWP, A.D. 901–1200) and the Little Ice Age (LIA, A.D. 1551–1850) are focused on. Statistically, significant temperature contrasts between the MWP and LIA are simulated by all of the models, and larger temperature deviations occur during colder periods. Although discrepancies exist, stronger Indian and East Asian summer monsoon circulations, as well as a stronger Asian westerly jet stream in winter, are found during the MWP compared to the LIA, in most of the models. These changes primarily originate from different atmospheric thermal structures over the two periods, which occur in response to the external radiative forcings. However, the monsoon-associated precipitation is quite complicated, with distinctly different patterns simulated among the models. There are phase differences in the multi-decadal variability of precipitation among the models, which consistently fail to detect a weakening in the precipitation at the minima of the radiative forcings. Only limited models are able to simulate the quasi-100-year solar cycles in the changes of precipitation over India and East Asia. Thus, although the climate system is certainly affected by external radiative forcings, our results imply that the natural forcings may not exert such a substantial influence on the Asian monsoon rainfall, or the models may underestimate the response.
登录
查看更多内容
影响因子:
4.6
作者:
Jian Liu, Bin Wang, Hongli Wang et al
通讯作者:
Jian Liu, Bin Wang, Hongli Wang et al
影响因子:
4.6
作者:
Zhengguo Shi;Xiao-dong Liu;Yimin Liu;Y. Sha;Tingting Xu
通讯作者:
Zhengguo Shi;Xiao-dong Liu;Yimin Liu;Y. Sha;Tingting Xu
影响因子:
2.2
作者:
Yongjin Wang
通讯作者:
Yongjin Wang
影响因子:
64.8
作者:
D. Verschuren;K. Laird;B. Cumming
通讯作者:
D. Verschuren;K. Laird;B. Cumming
影响因子:
6.7
作者:
C. Ummenhofer;A. Sen Gupta;Yue Li;A. Taschetto;M. England
通讯作者:
C. Ummenhofer;A. Sen Gupta;Yue Li;A. Taschetto;M. England