基于TRMM卫星降水的太行山区降水时空分布格局
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摘要
基于TRMM 3B42V7数据,综合采用多元线性回归、偏最小二乘回归和地理加权回归3种方法,建立了太行山区卫星降水产品的降尺度校正模型,将遥感降水信息从0. 25°×0. 25°降尺度到0. 05°×0. 05°。在结果评估和优选的基础上,分析了"像元—集水区—全区"年、月降水的多时空尺度干湿季节分布和垂向分布特征,并从机理方面论证了研究的合理性。结果表明:①地理加权回归校正效果最优,可明显降低校正降水与实测降水系列的均方根误差和平均相对偏差且提高决定系数;偏最小二乘回归可降低两项误差,但对决定系数无提升;多元线性回归最差,各项指标均无改善。②处于夏季风迎风侧的东坡和南坡降水量普遍高于500 mm,背风侧的西坡和北坡降水量较低,最大年降水量位于东南坡海拔1 300～1 500 m的地带。③研究区7—9月降水量占全年的58. 7%,干湿季节降水量之比为1∶18,各集水区的变化范围为1∶13～1∶25。④季风风向影响降水中心的移动路径,各月降水量沿高程变化梯度区间为-5. 2～6. 7 mm/hm,且迎风坡降水的垂向分布更复杂。
A comprehensive understanding of the spatial and temporal distribution of precipitation in mountain areas is of great significance for improving the simulation accuracy of regional water cycle processes,as well as the level of water management. In view of the fact that there is a severe lack of ground monitoring in high altitude areas,as well as the disadvantage of downscaling of satellite precipitation products by a single method,this study selects the Taihang Mountain as the research region and establishes a downscaling correction model. The model consists of the validation module and the downscaling module,which includes the multiple linear regression,the partial least squares regression,and the geographically weighted regression. Using the model,the original TRMM data is scaled from 0. 25° to 0. 05°. The distribution of the wet and dry seasons and the vertical distribution of the annual and monthly precipitation of the "pixel-catchment-region"are analyzed on the basis of the evaluation and optimization of the downscaling results. The research results are as follows: ① The geographically weighted regression is the most effective,reducing the root mean square error and average relative deviation of the corrected and gauged precipitation series,as well as improving the coefficient of determination. The partial least squares regression can reduce the two errors,but it cannot improve the determination coefficient. The multiple linear regression cannot improve any of the three indicators.② The precipitation on the east and south slopes on the windward side of the summer monsoon is generally higher than 500 mm,while that on the west and north slopes on the leeward side is lower. The zones of the maximum annual precipitation are located in the southeast slope at an altitude of 1 300—1 500 m. ③ The precipitation from July to September accounts for 58. 7% of the entire year; the ratio of precipitation in the dry and wet season is 1∶ 18; and the ratio in each catchment ranges from 1∶ 13 to 1∶ 25. ④ The variations of wind direction of the monsoon affect the moving track of the precipitation center,and the vertical zonality is more complicated in the windward than in the leeward.
A comprehensive understanding of the spatial and temporal distribution of precipitation in mountain areas is of great significance for improving the simulation accuracy of regional water cycle processes,as well as the level of water management. In view of the fact that there is a severe lack of ground monitoring in high altitude areas,as well as the disadvantage of downscaling of satellite precipitation products by a single method,this study selects the Taihang Mountain as the research region and establishes a downscaling correction model. The model consists of the validation module and the downscaling module,which includes the multiple linear regression,the partial least squares regression,and the geographically weighted regression. Using the model,the original TRMM data is scaled from 0. 25° to 0. 05°. The distribution of the wet and dry seasons and the vertical distribution of the annual and monthly precipitation of the "pixel-catchment-region"are analyzed on the basis of the evaluation and optimization of the downscaling results. The research results are as follows: ① The geographically weighted regression is the most effective,reducing the root mean square error and average relative deviation of the corrected and gauged precipitation series,as well as improving the coefficient of determination. The partial least squares regression can reduce the two errors,but it cannot improve the determination coefficient. The multiple linear regression cannot improve any of the three indicators.② The precipitation on the east and south slopes on the windward side of the summer monsoon is generally higher than 500 mm,while that on the west and north slopes on the leeward side is lower. The zones of the maximum annual precipitation are located in the southeast slope at an altitude of 1 300—1 500 m. ③ The precipitation from July to September accounts for 58. 7% of the entire year; the ratio of precipitation in the dry and wet season is 1∶ 18; and the ratio in each catchment ranges from 1∶ 13 to 1∶ 25. ④ The variations of wind direction of the monsoon affect the moving track of the precipitation center,and the vertical zonality is more complicated in the windward than in the leeward.
引文
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[14]赵传成,丁永建,叶柏生,等.天山山区降水量的空间分布及其估算方法[J].水科学进展,2011,22(3):315-322.(ZHAO C C,DING Y J,YE B S,et al.Spatial distribution of precipitation in Tianshan Mountains and its estimation[J].Advances in Water Science,2011,22(3):315-322.(in Chinese))
[15]YAN D H,LIU S H,QIN T X,et al.Evaluation of TRMM precipitation and its application into distributed hydrological model in Naqu River basin of the Tibetan plateau[J].Hydrology Research,2016,48(3):832-839.
[16]LYU A F,ZHOU L.A rainfall model based on a geographically weighted regression algorithm for rainfall estimations over the arid Qaidam basin in China[J].Remote Sensing,2016,8(4):311.
[17]GELADI P,KOWALSKI B R.Partial least-squares regression:a tutorial[J].Analytica Chimica Acta,1986,185:1-17.
[18]BRUNSDON C,FOTHERINGHAM A S,CHARLTON M E.Geographically weighted regression:a method for exploring spatial non-stationarity[J].Geographical Analysis,2010,28(4):281-298.
[19]林之光.地形降水气候学[M].北京:科学出版社,1995.(LIN Z G.Topographic precipitation climatology[M].Beijing:Science Press,1995:96-104.(in Chinese))
[20]王宗敏,丁一汇,张迎新,等.太行山东麓焚风天气的统计特征和机理分析:Ⅰ:统计特征[J].高原气象,2012,31(2):547-554.(WANG Z M,DING Y H,ZHANG Y X,et al.Feature and mechanism of the Foehn weather on east slope Taihang mountains:I:statistic feature[J].Plateau Meteorology,2012,31(2):547-554.(in Chinese))
[21]何金海.大气科学概论[M].北京:气象出版社,2012.(HE J H.Introduction to atmospheric science[M].Beijing:Meteorological Press,2012:308-326.(in Chinese))
[22]张正勇,何新林,刘琳,等.中国天山山区降水空间分布模拟及成因分析[J].水科学进展,2015,26(4):500-508.(ZHANG Z Y,HE X L,LIU L,et al.Spatial distribution of rainfall simulation and the cause analysis in China's Tianshan mountains area[J].Advances in Water Science,2015,26(4):500-508.(in Chinese))
[2]HUFFMAN G J,BOLVIN D T,NELKIN E J,et al.The TRMM multi-satellite precipitation analysis(TMPA):quasi-global,multiyear,combined-sensor precipitation estimates at fine scales[J].Journal of Hydrometeorology,2007,8(1):38-55.
[3]ADLER R F,SAPIANO M R P,HUFFMAN G J,et al.The global precipitation climatology project(GPCP)monthly analysis(new version 2.3)and a review of 2017 global precipitation[J].Atmosphere,2018,9(4):138.
[4]JOYCE R J,JANOWIAK J E,ARKIN P A,et al.CMORPH:a method that produces global precipitation estimates from passive microwave and infrared data at high spatial and temporal resolution[J].Journal of Hydrometeorology,2003,5(3):287-296.
[5]ASHOURI H,HSU K L,SOROOSHIAN S,et al.PERSIANN-CDR:daily precipitation climate data record from multi-satellite observations for hydrological and climate studies[J].Bulletin of the American Meteorological Society,2014,96(1):197-210.
[6]TURK F J,MILLER S D.Toward improved characterization of remotely sensed precipitation regimes with MODIS/AMSR-E blended data techniques[J].IEEE Transactions on Geoscience&Remote Sensing,2005,43(5):1059-1069.
[7]PRAKASH S,MITRA A K,AGHAKOUCHAK A,et al.A preliminary assessment of GPM-based multi-satellite precipitation estimates over a monsoon dominated region[J].Journal of Hydrology,2016,556:865-876.
[8]刘少华,严登华,王浩,等.中国大陆流域分区TRMM降水质量评价[J].水科学进展,2016,27(5):639-651.(LIU SH,YAN D H,WANG H,et al.Evaluation of TRMM 3B42V7 at the basin scale over mainland China[J].Advances in Water Science,2016,27(5):639-651.(in Chinese))
[9]孙乐强,郝振纯,王加虎,等.TMPA卫星降水数据的评估与校正[J].水利学报,2014,45(10):1135-1146.(SUN LQ,HAO Z C,WANG J H,et al.Assessment and correction of TMPA products 3B42RT and 3B42V6[J].Journal of Hydraulic Engineering,2014,45(10):1135-1146.(in Chinese))
[10]唐国强,李哲,薛显武,等.赣江流域TRMM遥感降水对地面站点观测的可替代性[J].水科学进展,2015,26(3):340-346.(TANG G Q,LI Z,XUE X W,et al.A study of substitutability of TRMM remote sensing precipitation for gauge-based observation in Ganjiang River basin[J].Advances in Water Science,2015,26(3):340-346.(in Chinese))
[11]刘俊峰,陈仁升,卿文武,等.基于TRMM降水数据的山区降水垂直分布特征[J].水科学进展,2011,22(4):447-454.(LIU J F,CHEN R S,QIN W W,et al.Study on the vertical distribution of precipitation in mountainous regions using TRMM data[J].Advances in Water Science,2011,22(4):447-454.(in Chinese))
[12]穆振侠,姜卉芳,刘丰.基于TRMM/TMI与实测站点的降水垂直分布差异性探讨[J].干旱区研究,2010,27(4):515-521.(MU Z X,JIANG H F,LIU F.Discussion on difference of vertical distribution pattern of precipitation based on TRMM/TMIand observed data[J].Advances in Water Science,2010,27(4):515-521.(in Chinese))
[13]李慧,杨涛,何祺胜,等.新疆天山山区TRMM卫星降水数据的复合校正方法[J].干旱区研究,2017,34(3):585-590.(LI H,YANG T,HE Q S,et al.Composite correction method of TRMM satellite precipitation data in the Tianshan mountains,Xinjiang[J].Arid Zone Research,2017,34(3):585-590.(in Chinese))
[14]赵传成,丁永建,叶柏生,等.天山山区降水量的空间分布及其估算方法[J].水科学进展,2011,22(3):315-322.(ZHAO C C,DING Y J,YE B S,et al.Spatial distribution of precipitation in Tianshan Mountains and its estimation[J].Advances in Water Science,2011,22(3):315-322.(in Chinese))
[15]YAN D H,LIU S H,QIN T X,et al.Evaluation of TRMM precipitation and its application into distributed hydrological model in Naqu River basin of the Tibetan plateau[J].Hydrology Research,2016,48(3):832-839.
[16]LYU A F,ZHOU L.A rainfall model based on a geographically weighted regression algorithm for rainfall estimations over the arid Qaidam basin in China[J].Remote Sensing,2016,8(4):311.
[17]GELADI P,KOWALSKI B R.Partial least-squares regression:a tutorial[J].Analytica Chimica Acta,1986,185:1-17.
[18]BRUNSDON C,FOTHERINGHAM A S,CHARLTON M E.Geographically weighted regression:a method for exploring spatial non-stationarity[J].Geographical Analysis,2010,28(4):281-298.
[19]林之光.地形降水气候学[M].北京:科学出版社,1995.(LIN Z G.Topographic precipitation climatology[M].Beijing:Science Press,1995:96-104.(in Chinese))
[20]王宗敏,丁一汇,张迎新,等.太行山东麓焚风天气的统计特征和机理分析:Ⅰ:统计特征[J].高原气象,2012,31(2):547-554.(WANG Z M,DING Y H,ZHANG Y X,et al.Feature and mechanism of the Foehn weather on east slope Taihang mountains:I:statistic feature[J].Plateau Meteorology,2012,31(2):547-554.(in Chinese))
[21]何金海.大气科学概论[M].北京:气象出版社,2012.(HE J H.Introduction to atmospheric science[M].Beijing:Meteorological Press,2012:308-326.(in Chinese))
[22]张正勇,何新林,刘琳,等.中国天山山区降水空间分布模拟及成因分析[J].水科学进展,2015,26(4):500-508.(ZHANG Z Y,HE X L,LIU L,et al.Spatial distribution of rainfall simulation and the cause analysis in China's Tianshan mountains area[J].Advances in Water Science,2015,26(4):500-508.(in Chinese))