基于CMIP5模式和SDSM的赣江流域未来气候变化情景预估
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摘要
赣江流域未来气候变化预估,对于了解该流域未来水资源的变化、指导流域防洪抗旱和水资源的合理开发利用具有重要意义。为预估该流域未来气候变化,利用1961—2005年赣江流域6个气象站数据、NCEP再分析数据并选择了CMIP5中CanESM2模式下3种排放情景RCP2.6,RCP4.5,RCP8.5,采用SDSM模型研究了赣江流域未来气候变化。结果表明:(1)赣江流域未来温度和降水总体均呈上升趋势。(2)在RCP2.6,RCP4.5,RCP8.5这3种排放情景下赣江流域未来最高气温分别增加1.8,2.1,2.8℃;未来最低气温分别增加1,1.2,1.9℃;未来平均气温分别增加1.5,1.6,2.3℃;3种排放情景下未来温度空间分布都是南高北低,西高东低,并在南北方向呈带状和环状分布。(3)在未来3个时期(2020s,2050s,2080s)、3种排放情景下赣江流域气温呈上升趋势,且6月份增幅最大,2月份增幅最小。(4)在未来3个时期、3种排放情景下,赣江流域未来降水均呈增加的趋势;5—10月降水量均呈现下降趋势,1—4月、11—12月降水量呈现增加趋势;3种情景下的未来降水空间分布基本呈南低北高,在南北方向呈递增趋势。对赣江流域气候要素模拟与预估表明,赣江流域未来气候变化存在降水增加及极端天气事件发生的危险,分析结果可为赣江流域气候变化的水文响应及气候变化的适应性研究提供科学依据。
Estimating future climate change of Ganjiang River can provide important guidance for flood control, drought relief, development and utilization of water resources in the basin. Based on the meteorological data in Ganjiang River Basin from 1961 to 2005 and NCEP reanalysis data, SDSM statistical downscaling model has been established. Future precipitation and temperature in the Ganjiang River Basin were predicted by atmospheric circulation factors coming from CMIP5 experiments: RCP2.6(low emission of greenhouse gases) the RCP8.5(highest emission of greenhouse gases) and RCP4.5(median emission of greenhouse gases) forcing pathways under CanESM2. Finally, the characteristics of temporal and spatial patterns of future precipitation and temperature in the basin were analyzed. The results show that:(1) the temperature and precipitation of Ganjiang River Basin will present the rising trend in general in the future;(2) under the three emission scenarios of RCP2.6, RCP4.5 and RCP8.5, the maximum temperature in the Ganjiang River Basin will increase by 1.8℃, 2.1℃ and 2.8℃, respectively,and the minimum air temperature will increase by 1, 1.2 and 1.9℃, respectively, in the future, and the future average temperature will increase by 1.5, 1.6 and 2.3℃, respectively;(3) in the next three periods(2020 s, 2050 s and 2080 s) and three emission scenarios, the temperature of the Ganjiang River Basin will rise, and the largest increase will occur in June, the smallest increase will occur in February;(4) in the next three periods and three emission scenarios, the future precipitation in the Ganjiang River Basin will increase, and the precipitation from May to October will present the downward trend, and the precipitation form January to April, November and December will present the increasing trend. The results can provide the scientific basis for the study of the hydrological response of the climate change and the adaptability of the climate change in the Ganjiang River Basin.
Estimating future climate change of Ganjiang River can provide important guidance for flood control, drought relief, development and utilization of water resources in the basin. Based on the meteorological data in Ganjiang River Basin from 1961 to 2005 and NCEP reanalysis data, SDSM statistical downscaling model has been established. Future precipitation and temperature in the Ganjiang River Basin were predicted by atmospheric circulation factors coming from CMIP5 experiments: RCP2.6(low emission of greenhouse gases) the RCP8.5(highest emission of greenhouse gases) and RCP4.5(median emission of greenhouse gases) forcing pathways under CanESM2. Finally, the characteristics of temporal and spatial patterns of future precipitation and temperature in the basin were analyzed. The results show that:(1) the temperature and precipitation of Ganjiang River Basin will present the rising trend in general in the future;(2) under the three emission scenarios of RCP2.6, RCP4.5 and RCP8.5, the maximum temperature in the Ganjiang River Basin will increase by 1.8℃, 2.1℃ and 2.8℃, respectively,and the minimum air temperature will increase by 1, 1.2 and 1.9℃, respectively, in the future, and the future average temperature will increase by 1.5, 1.6 and 2.3℃, respectively;(3) in the next three periods(2020 s, 2050 s and 2080 s) and three emission scenarios, the temperature of the Ganjiang River Basin will rise, and the largest increase will occur in June, the smallest increase will occur in February;(4) in the next three periods and three emission scenarios, the future precipitation in the Ganjiang River Basin will increase, and the precipitation from May to October will present the downward trend, and the precipitation form January to April, November and December will present the increasing trend. The results can provide the scientific basis for the study of the hydrological response of the climate change and the adaptability of the climate change in the Ganjiang River Basin.
引文
[1]Gray V. Climate change 2007: the physical science basis summary for policymakers[J]. Energy & Environment, 2007,18(3): 433-440.
[2]Gleick P H, Adams R M, Amasino R M, et al. Climate change and the integrity of science[J]. Science, 2010,328(5979):689-690.
[3]Edenhofer O, Seyboth K. Intergovernmental panel on climate change(IPCC)[J]. Encyclopedia of Energy Natural Resource & Environmental Economics, 2005,26(2):48-56.
[4]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.
[5]Taylor K E, Stouffer R J, Meehl G A. An overview of CMIP5 and the experiment design[J]. Bulletin of the American Meteorological Society, 2012,93(4):485-498.
[6]Moss R H, Edmonds J A, Hibbard K A, et al. The next generation of scenarios for climate change research and assessment[J]. Nature, 2010, 463(7282):747-756.
[7]吴佳,周波涛,徐影.中国平均降水和极端降水对气候变暖的响应:CMIP5模式模拟评估和预估[J].地球物理学报,2015,58(9):3048-3060.
[8]刘敏,王冀,刘文军.SDSM统计降尺度方法对江淮地区地面气温模拟能力评估及其未来情景预估[J].气象科学,2012,32(5):500-507.
[9]刘永和,郭维栋,冯锦明,等.气象资料的统计降尺度方法综述[J].地球科学进展,2011,26(8):837-847.
[10]郝振纯,时芳欣,王加虎.统计降尺度法在黄河源区未来降水变化分析中的应用[J].水电能源科学,2011(3):1-4.
[11]魏凤英,黄嘉佑.我国东部夏季降水量统计降尺度的可预测性研究[J].热带气象学报,2010,26(4):483-490.
[12]翟文亮,李朋俊,林凯荣,等.基于SDSM-SWAT的气候变化下东江流域径流预测模拟[J].人民珠江,2016,37(4):1-6.
[13]邱冰,姜加虎,孙占东,等.基于统计降尺度模型的博斯腾湖流域未来气温和降水变化趋势分析[J].资源科学,2010,32(6):1133-1140.
[14]赵芳芳,徐宗学.黄河源区未来气候变化的水文响应[J].资源科学,2009,31(5):722-730.
[15]郭家力,郭生练,郭靖,等.鄱阳湖流域未来降水变化预测分析[J].长江科学院院报,2010,27(8):20-24.
[16]田鹏.气候与土地利用变化对径流的影响研究[D].陕西杨凌:西北农林科技大学,2012.
[17]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.
[2]Gleick P H, Adams R M, Amasino R M, et al. Climate change and the integrity of science[J]. Science, 2010,328(5979):689-690.
[3]Edenhofer O, Seyboth K. Intergovernmental panel on climate change(IPCC)[J]. Encyclopedia of Energy Natural Resource & Environmental Economics, 2005,26(2):48-56.
[4]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.
[5]Taylor K E, Stouffer R J, Meehl G A. An overview of CMIP5 and the experiment design[J]. Bulletin of the American Meteorological Society, 2012,93(4):485-498.
[6]Moss R H, Edmonds J A, Hibbard K A, et al. The next generation of scenarios for climate change research and assessment[J]. Nature, 2010, 463(7282):747-756.
[7]吴佳,周波涛,徐影.中国平均降水和极端降水对气候变暖的响应:CMIP5模式模拟评估和预估[J].地球物理学报,2015,58(9):3048-3060.
[8]刘敏,王冀,刘文军.SDSM统计降尺度方法对江淮地区地面气温模拟能力评估及其未来情景预估[J].气象科学,2012,32(5):500-507.
[9]刘永和,郭维栋,冯锦明,等.气象资料的统计降尺度方法综述[J].地球科学进展,2011,26(8):837-847.
[10]郝振纯,时芳欣,王加虎.统计降尺度法在黄河源区未来降水变化分析中的应用[J].水电能源科学,2011(3):1-4.
[11]魏凤英,黄嘉佑.我国东部夏季降水量统计降尺度的可预测性研究[J].热带气象学报,2010,26(4):483-490.
[12]翟文亮,李朋俊,林凯荣,等.基于SDSM-SWAT的气候变化下东江流域径流预测模拟[J].人民珠江,2016,37(4):1-6.
[13]邱冰,姜加虎,孙占东,等.基于统计降尺度模型的博斯腾湖流域未来气温和降水变化趋势分析[J].资源科学,2010,32(6):1133-1140.
[14]赵芳芳,徐宗学.黄河源区未来气候变化的水文响应[J].资源科学,2009,31(5):722-730.
[15]郭家力,郭生练,郭靖,等.鄱阳湖流域未来降水变化预测分析[J].长江科学院院报,2010,27(8):20-24.
[16]田鹏.气候与土地利用变化对径流的影响研究[D].陕西杨凌:西北农林科技大学,2012.
[17]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.