TRMM卫星降水数据在川渝地区的适用性分析

doi:10.11820/dlkxjz.2014.10.009

摘要/Abstract

摘要：

在地形复杂的川渝地区,利用72个气象站点的实测降水数据对TRMM( Tropical Rainfall Measurement Mission) 卫星降水数据的精度分别在年、季和月尺度上进行验证,并进一步分析了高程和坡度对月尺度验证结果的影响,同时借助主成分分析法,对比了高程与坡度对TRMM 3B43降水数据的影响程度。结果表明：TRMM 3B43估算的年降水量在川渝地区平均偏高5.38%,其中西部高原区估算结果比中东部地区相对精确。TRMM 3B43与气象站点的季尺度降水数据拟合优度较高,但各季拟合优度之间存在差异,其中春季降水的拟合优度高于其余季节。而TRMM 3B43的月数据与站点实测降水数据拟合优度R²=0.7615,相关系数R=0.87,表明两者之间相关性显著,数据精度较高;就单个站点而言,大部分站点相关系数较高,误差较小,但叙永站相关系数相对较低,小金、雅安、雷波、盐源以及攀枝花站点数据误差相对较大。高程对数据精度的影响较坡度大,且呈现三次非线性回归的变化特征,随着高程的升高,R呈现增大的变化趋势,|Bias(%)|则呈现出增大—减小—增大的变化趋势;坡度对降水数据精度的影响相对较小且变化规律也较复杂,整体上随坡度变化,TRMM 3B43数据精度受到明显的影响。

关键词: TRMM 3B43, 降水, 复杂地形, 川渝地区

Abstract:

Precipitation data is often needed for hydrological, meteorological, ecological, and other environmental and geographic applications. Currently there are mainly two sources of precipitation estimates: observation at meteorological stations and remote sensing data. However, a large number of studies has demonstrated that measurements at conventional meteorological stations are point data and they cannot reflect the spatial variation of precipitation effectively, especially in areas of more complex terrain. Remote sensing technology, on the other hand, is able to produce reasonably high resolution gridded precipitation fields. Precipitation products obtained by satellites have been widely used in previous studies in the world. The Sichuan-Chongqing region is a typical area with complicated terrain and climate characteristics. The meteorological stations are very unevenly distributed in this region, especially in the western area. Precipitation estimation using satellite data provides potential alternatives to precipitation measurements in this region. In this study,the performance of the TRMM (Tropical Rainfall Measurement Mission) 3B43 monthly precipitation data over 2000-2011 was evaluated in the Sichuan-Chongqing region with rainfall records from 72 meteorological stations at different time intervals. The influence of elevation and slope on the verification result was analyzed at the monthly scale. Finally, principal component analysis was used to compare the effects of elevation and slope on the accuracy of TRMM 3B43 precipitation estimates. The results show that: (1) Regional average annual precipitation estimated by TRMM 3B43 is higher than the observed data from meteorological stations by 5.38%, and the eastern area estimation results are less accurate than the western plateau. Goodness of fit of seasonal precipitation between TRMM 3B43 estimates and observed data is high, but varies between the seasons—the goodness of fit of spring precipitation is higher than other seasons. Correlation between observations at the 72 stations and TRMM 3B43 estimates is high and shows little numerical biases in the whole study area at the monthly scale. (2) For individual stations, at most stations the correlation coefficients are reasonably high and the estimation biases are small, but the correlation coefficient at the Xuyong Station is comparatively low and the estimation biases at the Xiaojin Station, Yaan Station, Leibo Station, Yanyuan Station, and Panzhihua Station are comparatively high. (3) Compared with slope, elevation has greater influence on the accuracy of TRMM 3B43 estimates, which can be characterized by a cubic nonlinear relationship. With the increase of Elevation, R shows an increasing trend and |Bias(%)| increases-decreases-increases. (4) The influence of slope on the accuracy of TRMM 3B43 estimates is more complicated. Generally speaking, slope significantly affects the accuracy of TRMM 3B43 estimates

Key words: TRMM 3B43, precipitation, complex terrain, Sichuan-Chongqing region

中图分类号:

F293.35

嵇涛, 杨华, 刘睿, 何太蓉, 吴建峰. TRMM卫星降水数据在川渝地区的适用性分析[J]. 地理科学进展, 2014, 33(10): 1375-1386.

Tao JI, Hua YANG, Rui LIU, Tairong HE, Jianfeng WU. Applicability analysis of the TRMM precipitation data in the Sichuan-Chongqing region[J]. PROGRESS IN GEOGRAPHY, 2014, 33(10): 1375-1386.

图/表 13

图1

图2

表1

2000-2011年72个气象站点年均降水量与TRMM 3B43对应像元年平均降水量对比"

气象站	气象站年降水量/mm	TRMM年降水量/mm	Bias/%	气象站	气象站年降水量/mm	TRMM年降水量/mm	Bias/%
城口	1276.5	1269.5	-0.55	德格	601.0	580.6	-3.39
开县	1279.8	1360.9	6.34	甘孜	629.5	640.9	1.81
云阳	1164.2	1316.5	13.08	色达	663.5	678.0	2.20
巫溪	1112.6	1289.3	15.88	道孚	585.5	695.9	18.87
奉节	1070.6	1295.8	21.03	马尔康	766.3	835.6	9.05
巫山	1018.2	1244.3	22.21	红原	705.0	715.0	1.42
潼南	949.9	1006.1	5.92	小金	631.6	862.9	36.63
垫江	1123.2	1177.2	4.81	松潘	704.1	750.3	6.56
梁平	1154.5	1222.5	5.90	都江堰	1047.4	805.2	-23.13
万州	1147.7	1325.0	15.45	绵阳	836.8	840.9	0.50
忠县	1130.7	1233.7	9.12	巴塘	488.1	564.3	15.61
石柱	1025.2	1285.9	25.43	新龙	649.6	643.0	-1.00
大足	980.2	1004.1	2.43	理塘	765.1	634.0	-17.13
荣昌	957.6	986.2	2.99	雅安	1618.9	1127.5	-30.36
永川	923.5	988.6	7.05	稻城	663.2	657.5	-0.86
万盛	1237.7	1023.0	-17.35	康定	865.1	882.8	2.04
铜梁	1036.2	995.1	-3.97	峨眉山	1545.8	1321.1	-14.54
北碚	1099.7	1047.5	-4.75	乐山	1147.1	1288.1	12.30
合川	1095.4	1047.5	-4.37	木里	761.1	919.5	20.82
渝北	1091.0	1050.1	-3.75	九龙	926.8	892.1	-3.74
璧山	1069.0	1019.2	-4.66	越西	1074.8	1216.3	13.17
沙坪坝	1067.8	1050.1	-1.66	昭觉	1009.7	1044.5	3.45
江津	940.2	1028.1	9.35	雷波	809.6	1188.1	46.75
巴南	1015.4	1046.1	3.02	宜宾	914.1	1025.7	12.21
南川	1024.5	1050.0	2.48	盐源	740.1	1029.5	39.10
长寿	1061.4	1101.6	3.79	西昌	965.1	1090.3	12.98
涪陵	1041.2	1091.7	4.85	攀枝花	815.2	1171.8	43.74
丰都	970.5	1162.6	19.79	会理	1088.4	1181.1	8.52
武隆	991.4	1186.5	19.68	广元	907.9	856.4	-5.67
黔江	1140.4	1280.3	12.27	万源	1360.1	1268.1	-6.77
彭水	1180.1	1248.5	5.79	阆中	1062.1	1026.9	-3.31
綦江	964.8	1028.2	6.57	巴中	1150.7	1112.3	-3.33
酉阳	1302.2	1270.8	-2.42	达县	1261.8	1336.2	5.90
秀山	1318.8	1283.6	-2.68	遂宁	932.3	1003.4	7.62
石渠	563.1	516.7	-8.25	南充	1006.4	1021.1	1.46
若尔盖	627.2	621.9	-0.83	叙永	1078.3	949.3	-11.96

表1

图3

图4

表2

图5

表3

表4

图6

图7

表5

图8

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方程	回归模型检验					参数估算值
方程	R²	F	df1	df2	Sig.	Constant	b1	b2	b3
三次方	0.462	19.439	3	68	.000	0.836	8.667E-5	-2.536E-8	2.673E-12
三次方	0.202	5.739	3	68	.001	-0.745	0.034	-1.588E-5	1.911E-9

方程	回归模型检验					参数估算值
方程	R²	F	df1	df2	Sig.	Constant	b1	b2	b3
三次方	0.133	3.485	3	68	.020	0.909	-0.009	0.001	-8.630E-6
反函数	0.080	6.076	1	70	.016	8.886	6.756