10个CMIP5模式预估中亚地区未来50a降水时空变化特征

Projection of the spatial and temporal variation characteristics of precipitation over Central Asia of 10 CMIP5 models in the next 50 years

利用CRU月降水资料首先对参与IPCC第五次评估报告(IPCC AR5)的10个CMIP5模式对1951-2005年中亚地区年降水气候平均态、年际变率以及线性趋势等特征参数的模拟能力进行了系统评估,并选取具有较好模拟性能模式的未来预估试验结果作多模式集合平均预估未来50 a(2011-2060年)中亚地区在不同代表性浓度路径下降水量各特征参数的空间分布特征,结果表明:多数模式能够模拟出中亚地区年降水气候平均态、年际变率以及线性趋势的空间分布特征,同时发现中亚地区年降水量在过去50 a整体以轻微增加为主,趋势不显著。根据定量评估结果,从10个模式中选取4个具有较好模拟性能的模式结果做集合平均,同时利用历史回报试验数据进行检验,发现集合平均的模拟结果无论在量级还是高、低值中心的位置和范围与CRU资料非常接近。未来预估结果表明4种排放情景下4模式集合平均的中亚年降水在未来50 a增加较为明显,尤其在中国新疆南部(由低值区转变为高值区)。总体来看,未来50 a中亚降水增加趋势随着RCPs的增加而增加,且降水增加显著的区域随着RCPs的增加而明显增大。

Global warming in the last 100 years has caused tremendous impacts on global and regional climate changes. As one of the largest arid areas in the world, Central Asia covers the territory of five countries （Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan and Uzbekistan）and part of northwest China （Xinjiang Province）.Central Asia is a typical temperate desert steppe continental climate, precipitation is scarce, temperature changes severely and ecosystem is fragile. Freshwater mainly comes from precipitation in Central Asia. However, systematic researches for climate change of Central Asia under global warming are rare. As Xinjiang of China is a part of the Central Asia, so the research for climate in Central Asia is necessary to understand the climate change in China. Based on the CRU （Climatic Research Unit）dataset and the outputs of the historical and 4 representative concentration pathways （RCPs）future projection experiments from 10 climate models of Coupled Model Intercomparison Phase 5 （CMIP5）, the climatic feature, interannual variability, and linear trend of the annual rainfall over Central Asia during 1951 to 2005 have been studied firstly. Then the statistical parameters of the 10 models and CRU dataset such as mean field, interannual variability and linear trend were used to calculate NSTD , spatial correlation and RRMSE between model results and CRU dataset to evaluate these models＇ performance, after this assessment some models with rela- tively better performance among the 10 models are selected to establish a multi-model ensemble to project the spa- tial and temporal distribution of the annual rainfall over Central Asia during 2011 to 2060 under different green- house gas emission. The results showed that most models well simulated the spatial distribution of annual precipita- tion over Central Asia. The annual precipitation slightly increased but not significant over Central Asia during 1951 to 2005, and the simulation of MRI-CGCM3, MIROC5 and CNRM-CM5 performed relatively better. According to the assessment, 4 models with relatively better performance among the 10 models were selected to establish a multi-model ensemble. Comparison of the 4 models＇ ensemble mean precipitation with the CRU data show that the modeled location and extent of the high/low precipitation centers are in good agreement with CRU data during 1951-2005. The precipitation projected by the 4 models＇ ensemble display that the spatial distribution of the annual rainfall over Central Asia are very similar under different representative concentration pathways （RCPs）during 2011-2060. In the future 50 years, the annual precipitation over Central Asia will increase significantly, especially in the southern part of Xinjiang, China （the low value area will change into a high value area）. Overall, in the next 50 years the annual precipitation increasing rates and the extent of regions with significant precipitation increasing rates over Central Asia expand with the increased RCPs.