Prediction of future climate change in northwest inland arid areas of China under multi-mode and multiple scenarios
YAN Churui1,2, LIU Liu1,2*, HUANG Guanhua1,2
1.College of Water Resources and Civil Engineering, China Agricultural University, Beijing 100083, China; 2.Center for Agricultural Water Research in China, China Agricultural University, Beijing 100083, China
Abstract:Based on three RCP scenarios(RCP2.6, RCP4.5, RCP8.5), a statistical downscaling model(SDSM)was established by using observed meteorological data, ERA-40 reanalysis data and 5 preferred GCMs output selected from 23 GCMs of CMIP5. Then, the climate change scenarios were predicted, including daily precipitation, highest and lowest ambient temperatures during 2021-2050 in the Heihe River basin, which is the second largest inland river basin in Northwest China. Results showed that the SDSM had a good predicting capacity for the ambient temperature in the basin. During calibration and validation periods, the coefficient of determination(R2)and the coefficient of Nash-Sutcliffe efficiency coefficient(NSE)were both larger than 0.9, while the root mean square error(RMSE)was less than 20%. However, the SDSM showed relatively lower simulation efficiency for precipitation with R2 and NSE values of above 0.5 in most meteorological stations, except the stations located in the downstream desert areas. Compared with the baseline period(1976—2005), the annual mean precipitation simulated by different GCMs during 2021—2050 showed a decline globally in one RCP scenario only; in the rest RCP scenarios, however, the precipitation fluctuated in a range of(-10-+10)%. Specially, the precipitation depended on season and month largely, and it was more summer but less in spring in most RCP scenarios. Note that the highest and lowest ambient temperatures exhibited a similar increasing tendency during 2021—2050 under all RCP scenarios. The increment of the highest ambient temperature was lower than the increment of the lowest ambient temperature, especially, both increments rose with increasing concentration of RCP.
颜楚睿,, 刘浏,*, 黄冠华,. 多模式多情景下西北内陆干旱区未来气候变化预估[J]. 排灌机械工程学报, 2018, 36(11): 1193-1199.
YAN Churui,, LIU Liu,*, HUANG Guanhua,. Prediction of future climate change in northwest inland arid areas of China under multi-mode and multiple scenarios. Journal of Drainage and Irrigation Machinery Engin, 2018, 36(11): 1193-1199.
[1]陈亚宁, 王怀军, 王志成, 等. 西北干旱区极端气候水文事件特征分析[J]. 干旱区地理, 2017, 40(1): 1-9. CHEN Yaning, WANG Huaijun, WANG Zhicheng, et al. Characteristics of extreme climatic/hydrological events in the arid region of northwestern China[J]. Arid land geography, 2017,40(1):1-9.(in Chinese)[2]FOLEY A, KELMAN I. EURO-CORDEX regional climate model simulation of precipitation on Scottish islands(1971—2000): model performance and implications for decision-making in topographically complex regions[J]. International journal of climatology, 2018,38(2): 1087-1095.[3]TANG Jianping, NIU Xiaorui, WANG Shuyu, et al. Statistical downscaling and dynamical downscaling of regional climate in China: present climate evaluations and future climate projections[J]. Journal of geophysical research: atmospheres, 2016,121(5):2110-2129.[5]徐宗学, 刘浏. 太湖流域气候变化检测与未来气候变化情景预估[J]. 水利水电科技进展, 2012, 32(1): 1-7. XU Zongxue, LIU Liu. Detection of climate change and projection of future climate change scenarios in Taihu Lake Basin[J]. Advances in science and technology of water resources, 2012,32(1): 1-7.(in Chinese)[6]WILBY R L, DAWSON C W, BARROW E M. SDSM—a decision support tool for the assessment of regional climate change impacts[J]. Environmental modelling & software, 2002,17(2): 145-157.[7]CHEN Jie, BRISSETTE F P, POULIN A, et al. Overall uncertainty study of the hydrological impacts of climate change for a Canadian watershed[J]. Water resources research, 2011,47(12): 1-16.[8]FU Guobin, LIU Zhaofei, CHARLES S P, et al. A score-based method for assessing the performance of GCMs: a case study of southeastern Australia[J]. Journal of geophysical research atmospheres, 2013,118(10): 4154-4167.[9]郭巧玲, 杨云松, 畅祥生, 等. 1957—2008年黑河流域径流年内分配变化[J]. 地理科学进展, 2011, 30(5): 550-556. GUO Qiaoling, YANG Yunsong, CHANG Xiangsheng, et al. Annual variation of Heihe river runoff during 1957—2008[J]. Progress in geography, 2011,30(5): 550-556.(in Chinese)[10]成晓裕, 王艳华, 李国春, 等. 三套再分析降水资料在中国区域的对比评估[J]. 气候变化研究进展, 2013,9(4): 258-265. CHENG Xiaoyu, WANG Yanhua, LI Guochun, et al. Evaluation of three reanalysis precipitation datasets in China[J]. Progressus inquisitiones de mutatione climatis, 2013,9(4): 258-265.(in Chinese)[11]郭泽忠. 气候变化条件下黑河中游灌区水分生产率评价[D]. 北京:中国农业大学,2017.[12]刘文丰, 徐宗学, 李发鹏, 等. 基于秩评分方法定量评估大气环流模式在雅鲁藏布江流域的模拟能力[J]. 北京师范大学学报(自然科学版), 2013,49(2/3):304-311. LIU Wenfeng, XU Zongxue, LI Fapeng, et al. GCM performance on simulating climatological factors in Yarlung Zangbo River Basin on a ranked score method[J]. Journal of Beijing Normal University(natural science), 2013,49(2/3): 304-311.(in Chinese)[13]蒋昕昊, 徐宗学, 刘兆飞, 等. 大气环流模式在长江流域的适用性评价[J]. 长江流域资源与环境, 2011, 31(增1): 51-58. JIANG Xinhao, XU Zongxue, LIU Zhaofei, et al. Evaluating the general circulation models over the Yangtze River Basin[J]. Resources and environment in the Yangtze Basin, 2011,31(S1): 51-58.(in Chinese)[14]殷志远, 赖安伟, 公颖, 等. 气象水文耦合中的降尺度方法研究进展[J]. 暴雨灾害, 2010,29(1): 89-95. YIN Zhiyuan, LAN Anwei, GONG Ying, et al. Research development on downscaling method in meteorology and hydrology coupling[J]. Torrential rain and disasters, 2010,29(1): 89-95.(in Chinese)