基于CMIP5模式的干旱内陆河流域未来气候变化预估

摘要/Abstract

摘要： 我国西北干旱半干旱地区水资源短缺、生态环境脆弱，未来气候变化预估对水资源管理具有重要的现实意义。以黑河流域为研究区，基于1960-2014年月值NCEP再分析资料与气象要素实测资料，建立逐步回归降尺度模型；针对模型不足，提出一种补充逐步回归降尺度模型；经2006-2014年CMIP5中CNRM-CM5模式的区域适用性评价，选取适宜模型进行2016-2060年CNRM-CM5模式下的流域未来气候变化预估。主要结论为：（1）补充逐步回归模型的模拟效果总体要好于逐步回归模型，两模型对流域气温的模拟效果要好于降水。（2）降尺度模型的CNRMCM5模式适用性评价表明，RCP4.5与RCP8.5路径下，补充回归模型的适用性总体好于逐步回归模型。（3）两种路径下，黑河流域上中游未来年均降水量分别为324.94 mm、330.15 mm，未来流域降水分布的不均匀性增强。（4）两种路径下黑河流域中下游未来年均气温分别为10.25℃、10.77℃。

关键词: 气候变化, 统计降尺度, CMIP5模式, 气象要素, 黑河流域

Abstract: Climate change is a global issue of common concern to the international community today. Over the past century, great changes characterized by climate warming have taken place in both global climate and eco-environment. In recent years, with the implementation of NSFC major research plan, integrated study on eco-hydrological processes of Heihe River Basin(HRB)has become a hot spot of arid and semi-arid area research in China and great achievements have been made. Future climate change forecasting is one of the foundations of the research, but currently no forecasting has been made based on Global Climate Models(GCMs)and statistical downscaling methods. Such forecasting is in urgent need. Monthly meteorological monitoring data of the reaches and NCEP reanalysis data from 1960 to 2014, together with CNRM-CM5 data from 2006 to 2060 were used for the study. The research process of the paper is as follows:Firstly, statistical downscaling models for east watershed of HRB based on multivariable linear regression using the NCEP reanalysis data and meteorological monitoring data of air temperature and precipitation were built. Secondly, since the models cannot meet forecasting requirements, new complimentary statistical downscaling models were built based on residual analysis to improve forecasting results. Thirdly, regional applicability evaluation was employed to determine the models used for future climate forecasting based on GCM of Coupled Model Intercomparison Project Phase 5(CMIP5). Finally, future climate change prediction for HRB was made based on the chosen downscaling models and CNRM-CM5 model of CMIP5, and both time variations and regional distribution of future air temperature and precipitation of HRB were analyzed. The results show as follows:(1)The complementary downscaling models simulated better than the multivariable regression model overall, and the simulation results of air temperature were better than that of precipitation for both the two models.(2)Regional applicability evaluation of downscaling models based on the CNRM-CM5 model show that, the applicability of the complementary regression models were better than that of the multivariate regression models in general under both RCP4.5 and RCP8.5 pathways.(3)The future average annual precipitation of upstream and midstream of HRB were 324.94 mm and 330.15 mm under both RCP4.5 and RCP8.5 pathways respectively, and inhomogeneity enhancement was confirmed in the future.(4) The future average annual air temperatures of midstream and downstream of HRB under the two pathways were 10.25℃ and 10.77℃, respectively. It should be clear that, because of the uncertainty of the data, downscaling procedures, as well as the diversity of human emissions, uncertainty exists in the prediction of future climate change in HRB.

Key words: climate change, statistical downscaling model, CMIP5, meteorological elements, HRB

中图分类号:

P467

祁晓凡, 李文鹏, 李海涛, 刘宏伟. 基于CMIP5模式的干旱内陆河流域未来气候变化预估[J]. 干旱区地理, 2017, 40(5): 987-996.

QI Xiao-fan, LI Wen-peng, LI Hai-tao, LIU Hong-wei. Future climate change prediction of arid inland river basin based on CMIP5 model[J]. , 2017, 40(5): 987-996.

参考文献

[1] MORA C, FRAZIER A G, LONGMAN R J, et al. The projected timing of climate departure from recent variability[J]. Nature, 2013, 502:183-187.

[2] 核心撰写小组, PACHAURI, R K, MEYER L A. 气候变化2014:综合报告. 政府间气候变化专门委员会第五次评估报告第一工作组, 第二工作组和第三工作组报告[R]. 瑞士日内瓦:IPCC, 2014[. Core Writing Team, PACHAURI, R K, MEYER L A. Climate Change 2014:Synthesis Report. Contribution of working groups I, Ⅱ and Ⅲ to the fifth assessment report of the intergovernmental panel on climate change[R]. Geneva, Switzerland:IPCC, 2014.]

[3] 施雅风, 沈永平, 李栋梁, 等. 中国西北部气候由暖干向暖湿转型的特征和趋势探讨[J]. 第四纪研究, 2003, 23(2):152-164.[SHI Yafeng, SHEN Yongping, LI Dongliang, et al. Discussion on the present climatic change from warm-dry to warm-wet in northwest China[J]. Quaternary Sciences, 2003, 23(2):152-164.]

[4] 赵宗慈, 丁一汇, 徐影, 等. 人类活动对20世纪中国西北地区气候变化影响检测和21世纪预测[J]. 气候与环境研究, 2003, 8(1):26-34[. ZHAO Zongci, DING Yihui, XU Ying, et al. Detection and prediction of climate change for the 20th and 21st century due to human activity in Northwest China[J]. Climatic and Environment Research, 2003, 8(1):26-34.]

[5] 任国玉, 袁玉江, 柳艳菊, 等. 我国西北干燥区降水变化规律[J]. 干旱区研究, 2016, 33(1):1-19[. REN Yuguo, YUAN Yujiang, LIU Yanju, et al. Changes in precipitation over Northwest China[J]. Arid Zone Research, 2016, 33(1):1-19.]

[6] 赵雪雁, 王亚茹, 张钦, 等. 近50 a青藏高原东部夏半年强降水事件的气候特征[J]. 干旱区地理, 2015, 38(4):675-683.[ZHAO Xueyan,WANG Yaru,ZHANG Xin,et al. Climatic characteristics of heavy precipitation events during summer half year over the Eastern Tibetan Plateau in recent 50 years[J]. Arid Land Geography, 2015, 38(4):675-683.]

[7] 陈亚宁, 李稚, 范煜婷, 等. 西北干旱区气候变化对水文水资源影响研究进展[J]. 地理学报, 2014, 69(9):1295-1304[. CHEN Yaning, LI Zhi, FAN Yuting, et al. Research progress on the impact of climate change on water resources in the arid region of Northwest China[J]. Acta Geographica Sinica, 2014, 69(9):1295-1304.]

[8] 杨金虎, 江志红, 刘晓芸, 等. 近半个世纪中国西北干湿演变及持续性特征分析[J]. 干旱区地理, 2012, 35(1):10-22[. YANG Jinhu, JIANG Zhihong, LIU Xiaoyun, et al. Influence research on spring vegetation of Eurasia to summer drought-wetness over the northwest China[J]. Arid Land Geography, 2012, 35(1):10-22.]

[9] 李净, 刘红兵, 李龙, 等. 基于多源遥感数据集的近30 a西北地区植被动态变化研究[J]. 干旱区地理, 2016, 39(2):387-394.[LI Jing, LIU Hongbing, LI Long, et al. Vegetation dynamic changes in northwest China based on multi-source remote sensing datasets in recent 30 years[J]. Arid Land Geography, 2016, 39(2):387-394.]

[10] 刘昌明, 刘文彬, 傅国斌, 等. 气候影响评价中统计降尺度若干问题的探讨[J]. 水科学进展, 2012, 23(3):427-437.[LIU Changming, LIU Wenbin, FU Guobin, et al. A discussion of some aspects of statistical downscaling climate impacts assessment[J]. Advances in Water Science, 2012, 23(3):427-437.]

[11] WILBY R L, HARRIS I. A framework for assessing uncertainties in climate change impacts:Low-flow scenarios for the River Thames, UK[J]. Water Resource Research, 2006, 42(2):W02419.

[12] ACHARYA N, KAR S C, MOHANTY U C, et al. Performance of GCMs for seasonal prediction over India:a case study for 2009 monsoon[J]. Theoretical and Applied Climatology, 2011, 105(3/4):505-520.

[13] 赵传燕, 南忠仁, 程国栋, 等. 统计降尺度对西北地区未来气候变化预估[J]. 兰州大学学报(自然科学版), 2008, 44(5):12-18, 25[. ZHAO Chuanyan, NAN Zhongren, CHENG Guodong, et al. Predietion of the trend of the future climate change in Northwestern China by statistical downscaling[J]. Journal of Lanzhou University(Natural Sciences), 2008, 44(5):12-18, 25.]

[14] 杨淑群, 杨小波, 游泳, 等. 基于统计降尺度法的青藏高原东部地区未来气候变化预估[J]. 西南大学学报(自然科学版), 2013, 35(11):147-156[. YANG Shuqun, YANG Xiaobo, YOU Yong, et al. Projection for climate change of the eastern Qinghai-Tibetan plateau based on the statistical downscaling method[J]. Journal of Southwest University(Natural Science Edition), 2013, 35(11):147-156.]

[15] 郝丽娜, 粟晓玲, 王宁. 基于统计降尺度模型的河西走廊未来气温和降水的时空变化[J]. 西北农林科技大学学报(自然科学版), 2015, 43(10):219-228[. HAO Lina, SU Xiaoling, WANG Ning, et al. Future spatial and temporal changes of temperature and precipitation in Hexi corridor based on SDSM[J]. Journal of Northwest A&F University(Natural Science Edition), 2015, 43,(10):219-228.]

[16] 陈亚宁, 杨青, 罗毅, 等. 西北干旱区水资源问题研究思考[J]. 干旱区地理, 2012, 35(1):1-9[. CHEN Yaning, YANG Qing, LUO Yi, et al. Ponder on the issues of water resources in the arid region of northwest China[J]. Arid Land Geography, 2012, 35(1):1-9.]

[17] 李文鹏, 康卫东, 刘振英, 等. 西北典型内流盆地水资源调控与优化利用模式-以黑河流域为例[M]. 北京:地质出版社, 2010[. LI Wenpeng, KANG Weidong, LIU Zhenying, et al. Water resources regulation and optimal utilization modes of typical interior river basin in northwest China:a case study of Heihe River Basin[M]. Beijing:Geological Publishing House, 2010.]

[18] 祁晓凡, 李文鹏, 李海涛, 等. 黑河流域气象要素与全球性大气环流特征量的多尺度遥相关分析[J]. 干旱区地理, 2017, 40(3):564-572[. QI Xiaofan, LI Wenpeng, LI Haitao, et al. Multiscale teleconnections between meteorological elements of Heihe River Basin and global climate indices[J]. Arid Land Geography, 2017, 40(3):564-572.]

[19] 陈雯. 北半球高层环流、气温异常对我国地面气温变化的影响[D]. 南京:南京信息工程大学, 2008[. CHEN Wen. The influence of upper-level atmospheric circulation and temperature anomalies on the surface temperature in China[D]. Nanjing:Nanjing University of Information Science and Technology, 2008.]

[20] MOSS R, BABIKER M, BRINKMAN S, et al. Towards new scenarios for analysis of emissions, climate change, impacts, and response strategies:Technical summary[R]. Geneva, Switzerland:IPCC, 2008.

[21] 吴晶, 罗毅, 李佳, 等. CMIP5模式对中国西北干旱区模拟能力评价[J]. 干旱区地理, 2014, 37(3):499-508[. WU Jing, LUO Yi, LI Jia, et al. Evaluation of CMIP5 modes's simulation ability in the northwest arid areas of China[J]. Arid Land Geography, 2014, 37(3):499-508.]

[22] 刘赛艳, 黄强, 王义民, 等. 基于统计降尺度和CMIP5模式的泾河流域气候要素模拟与预估[J]. 农业工程学报, 2015, 31(23):138-144.[LIU Saiyan, HUANG Qiang, WANG Yimin, et al. Simulation and prediction of climatic elements in Jinghe River basin using downscaling method and CMIP5[J]. Transactions of the Chinese Society of Agricultural Engineering, 2015, 31(23):138-144.]

[23] WILBY R L, HAY L E, LEAVESLEY G H. A comparison of downscaled and raw GCM output:implications for climate change scenarios in the San Juan River basin, Colorado[J]. Journal of Hydrology, 1999, 225:67-91.

[24] WILBY R L, TOMLINSON O J, DAWSON C W. Multi-site simulation of precipitation by conditional resampling[J]. Climate Research, 2003, 23:183-194.

[25] 成爱芳, 冯起, 张健恺, 等. 未来气候情景下气候变化响应过程研究综述[J]. 地理科学, 2015, 3(1):84-90[. CHENG Aifang, FENG Qi, ZHANG Jiankai, et al. A review of climate change scenario for impacts process study[J]. Scientia Geographica Sinica, 2015, 3(1):84-90.]

[26] 赵天保, 陈亮, 马柱国. CMIP5多模式对全球典型干旱半干旱区气候变化的模拟与预估[J]. 科学通报, 2014, 59(12):1148-1163.[ZHAO Tianbao, CHEN Liang, MA Zhuguo. Simulation of historical and projected climate change in arid and semiarid areas by CMIP5 models[J]. Chinese Science Bulletin, 2014, 59(12):1148-1163.]

[27] 杨绚, 李栋梁, 汤绪. 基于CMIP5多模式集合资料的中国气温和降水预估及概率分析[J]. 中国沙漠, 2014, 34(3):795-804.[YANG Xuan, LI Dongliang, TANG Xu. Probability assessment of temperature and precipitation over China by CMIP5 mutimodel ensemble[J].Journal of Desert Research, 2014, 34(3):795-804.]

[28] 赵天保, 艾丽坤, 冯锦明. NCEP再分析资料和中国站点观测资料的分析与比较[J]. 气候与环境研究, 2004, 9(2):278-294.[ZHAO Tianbao, AI Likun, FENG Jinming. An intercomparison between NCEP reanalysis and observed data over China[J]. Climatic and Environmental Research, 2004, 9(2):278-294.]