基于SDSM的赣江流域未来降水与气温的时空变化分析
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摘要
利用赣江流域6个气象站数据(1961年～2005年)和NCEP再分析资料,建立了气候要素的SDSM降尺度模型,并将模型应用于Can ESM2模式的RCP4. 5情景,得到了流域未来气温与降水的变化趋势。即SDSM降尺度模型对赣江流域气温的模拟效果较好,降水略差;赣江流域未来降水均呈增加的趋势,降水空间分布基本呈南低北高趋势;未来气温均呈增加的趋势,各时期最高气温稍大于基准期;各时期最低气温稍大于基准期;赣江流域未来不同季节的平均气温均大于基准期;赣江流域未来气温空间分布呈现南高北低,西高东低的趋势。
Based on the data of six meteorological stations in Ganjiang River Basin from 1961 to 2005 and the NCEP reanalysis data, the SDSM statistical downscaling model is established. The model is applied in Can ESM2 mode and RCP4. 5 scenario of CMIP5, and then the precipitation and temperature in Ganjiang River Basin are predicted. The results show that,( a) the SDSM model has a good prediction capacity for the tendency of temperature, but not for precipitation;( b) future precipitation has a rising trend in general and the spatial distribution is basically low in the south and high in the north;( c) the temperature in the future has a rising trend in general, the highest temperature in each period is slightly larger than that in the baseline period, and the lowest temperature in each period is slightly larger than that in the baseline period;( d) the daily average temperature of different seasons in Ganjiang River Basin is greater than that in the base period; and( e) future temperature in Ganjiang River Basin shows a gradual decrease trend from the south to the north and from the west to the east.
Based on the data of six meteorological stations in Ganjiang River Basin from 1961 to 2005 and the NCEP reanalysis data, the SDSM statistical downscaling model is established. The model is applied in Can ESM2 mode and RCP4. 5 scenario of CMIP5, and then the precipitation and temperature in Ganjiang River Basin are predicted. The results show that,( a) the SDSM model has a good prediction capacity for the tendency of temperature, but not for precipitation;( b) future precipitation has a rising trend in general and the spatial distribution is basically low in the south and high in the north;( c) the temperature in the future has a rising trend in general, the highest temperature in each period is slightly larger than that in the baseline period, and the lowest temperature in each period is slightly larger than that in the baseline period;( d) the daily average temperature of different seasons in Ganjiang River Basin is greater than that in the base period; and( e) future temperature in Ganjiang River Basin shows a gradual decrease trend from the south to the north and from the west to the east.
引文
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[12]田鹏.气候与土地利用变化对径流的影响研究[D].杨凌:西北农林科技大学,2012.
[2]雷江群,畅建霞,涂欢,等.统计降尺度方法对渭河流域气候要素的模拟及预估[J].武汉大学学报:工学版,2015,48(2):176-181.
[3] WANG Lin, CHEN Wen. Equiratio cumulative distribution function matching as an improvement to the equidistant approach in biascorrection of precipitation[J]. Atmospheric Science Letters,2014,15(1):1-6.
[4]代慧慧,杨汉波,胡庆芳.基于SDSM的疏勒河流域气候变化统计降尺度研究[J].水利水运工程学报,2015(5):46-53.
[5] CROSBIE R S, DAWES W R, CHARLES S P, et al. Differences in future recharge estimates due to GCMs, downscaling methods and hydrological models[J]. Geophysical Research Letters,2011,38(11):417-417.
[6]杨肖丽,郑巍斐,林长清,等.基于统计降尺度和SPI的黄河流域干旱预测[J].河海大学学报:自然科学版,2017,45(5):377-383.
[7]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.
[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]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.
[10] ZHANG Qiang, XIAO Mingzhong, LI Jianfeng, et al. Topographybased spatial patterns of precipitation extremes in the Poyang Lake Basin, China:Changing properties and causes[J]. Journal of Hydrology,2014,512:229-239.
[11]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.
[12]田鹏.气候与土地利用变化对径流的影响研究[D].杨凌:西北农林科技大学,2012.