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遥感技术与应用  2019, Vol. 34 Issue (5): 1111-1120    DOI: 10.11873/j.issn.1004-0323.2019.5.1111
降水遥感观测专栏     
TRMM卫星3B43降水数据在黄河流域的精度分析
黄桂平1(),曹艳萍1,2()
1. 河南大学环境与规划学院,河南 开封 475004
2. 黄河中下游数字地理技术教育部重点实验室,河南 开封 475004
Accuracy Analysis of TRMM 3B43 Precipitation Data in theYellow River Basin
Guiping Huang1(),Yanping Cao1,2()
1. College of Environment and Planning, Henan University, Kaifeng 475004, China
2. Laboratory of Geospatial Technology for the Middle and Lower Yellow River Region, Kaifeng 475004, China
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摘要:

利用黄河流域90个气象站点实测降水数据,分别从流域和格网两个空间尺度,运用相关分析、相对误差等统计分析方法对TRMM卫星3B43 v7降水数据在黄河流域的精度进行了评估,在此基础上分析了精度评价指标的空间分布特征,讨论高程、降水强度等因素对精度的影响。结果表明:①在流域尺度上,TRMM月降水数据与站点实测月降水数据呈高度线性相关,TRMM降水数据比站点实测降水数据略微偏高。②在格网尺度上,大部分格网的TRMM月降水数据与站点实测月降水数据的相关系数较高,偏差较小。③TRMM降水精度与降水强度、高程相关,TRMM降水量与实测降水量的平均绝对误差呈自东南向西北递减规律,与黄河流域降水分布规律相一致;相对误差、平均误差和平均绝对误差等指标随着高程的增加呈现逐渐减小的趋势。整体上,对于黄河流域,随着降水量的增多,TRMM数据倾向于低估降水量;高海拔区域,TRMM低估降水量,低海拔区域,TRMM高估降水量。通过评估TRMM卫星降水产品在黄河流域的精度,为本地区地面降水产品提供有效补充。

关键词: TRMM降水黄河流域精度评估影响因素    
Abstract:

Based on the correlation analysis and relative error methods, the accuracy of TRMM 3B43 v7 precipitation data at the watershed and grid scale in the Yellow River Basin was validated using 90 meteorological stations data. The spatial distribution characteristics of the accuracy evaluation indexes were analyzed. The influence of elevation and precipitation intensity on the accuracy of TRMM precipitation was discussed. The results show that: (1) At the basin scale, the TRMM monthly precipitation data is highly linearly related to the measured precipitation data at the site. TRMM precipitation data is slightly higher than the site-measured precipitation data. (2) At the grid scale, the TRMM monthly precipitation data of most grids have a high correlation coefficient with the measured precipitation data at the site. The deviation between TRMM precipitation and in site measured precipitation is small. (3) The accuracy of TRMM precipitation is related to precipitation intensity and elevation. The average absolute error between TRMM precipitation and measured precipitation is decreasing from southeast to northwest, which is consistent with precipitation distribution in the Yellow River Basin. The relative error, average error and average absolute error tend to decrease with the increase of elevation. Overall, over the Yellow River Basin, TRMM data tend to underestimate precipitation as precipitation increases. TRMM data underestimates precipitation in high altitude areas, overestimates precipitation in low altitude areas. By assessing the accuracy of TRMM satellite precipitation products in the Yellow River Basin, it provides an effective supplement for ground precipitation products in the region.

Key words: TRMM Precipitation    Yellow River Basin    Accuracy Assessment    Influencing Factors
收稿日期: 2018-06-27 出版日期: 2019-12-05
ZTFLH:  TP75  
基金资助: 国家自然科学基金项目(41701503);河南大学引进博士科研启动基金项目(B2015060)
通讯作者: 曹艳萍     E-mail: 1299847273@qq.com;caoyp@henu.edu.cn
作者简介: 黄桂平(1996 - ),男,江西赣州人,学士,主要从事遥感、地理信息系统应用等方面的研究。E?mail:1299847273@qq.com
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引用本文:

黄桂平,曹艳萍. TRMM卫星3B43降水数据在黄河流域的精度分析[J]. 遥感技术与应用, 2019, 34(5): 1111-1120.

Guiping Huang,Yanping Cao. Accuracy Analysis of TRMM 3B43 Precipitation Data in theYellow River Basin. Remote Sensing Technology and Application, 2019, 34(5): 1111-1120.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2019.5.1111        http://www.rsta.ac.cn/CN/Y2019/V34/I5/1111

图1  黄河流域地理位置以及90个气象站点分布
图2  流域尺度上TRMM与站点月降水数据的散点图
评价指标

站点均值xˉ

/mm

TRMM均值yˉ/mm

相关系数

R

相对误差

BIAS/%

平均误差

EM/mm

平均绝对误差EMA /mm
流域月尺度38.4838.890.9931.090.422.68
表1  流域尺度上TRMM与站点降水数据比较(1998~2016年)
年份相关系数R相对误差BIAS /%年份相关系数R相对误差BIAS /%
19980.9980.4720080.9936.03
19990.997-1.0020090.9971.38
20000.9971.0820100.9952.16
20010.9950.9420110.995-1.74
20020.9881.7720120.9868.24
20030.990-2.9620130.9981.40
20040.9994.7720140.992-3.16
20050.995-1.4020150.994-0.07
20060.995-3.5020160.9985.49
20070.9972.29
表2  流域尺度上各年TRMM与站点降水数据比较
图3  格网尺度上TRMM与站点月降水数据的散点图
评价指标

站点均值

xˉ/mm

TRMM均值

yˉ/mm

相关系数

R

相对误差

BIAS /%

平均误差

EM /mm

平均绝对误差

EMA /mm

格网月尺度38.4840.390.9284.981.9110.09
表3  格网尺度上TRMM与站点降水数据比较(1998~2016年)
图4  TRMM降水精度及空间分布
图5  精度评价指标与各站点高程的关系
图6  精度评价指标与各站点多年平均降水量的关系
1 Tang Guoqiang, Li Zhe, Xue Xianwu, et al. A Study of Substitutability of TRMM Remote Sensing Precipitation for Gauge-based Observation in Ganjiang River Basin[J]. Advance in Water Science, 2015, 26(3): 340-346.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.
2 Hao Zhenchun, Tong Kai, Zhang Leilei, et al. Applicability Analysis of TRMM Precipitation Estimates in Tibetan Plateau[J]. Journal of China Hydrology, 2011, 31(5): 18-23.郝振纯, 童凯, 张磊磊, 等. TRMM降水资料在青藏高原的适用性分析[J]. 水文, 2011, 31(5): 18-23.
3 Yang Shaoe, Wu Bingfang, Xiong Jun, et al. Calculation of Monthly Precipitation Anomaly Percentage Using TRMM Rainfall Product[J]. Remote Sensing Information, 2010(5): 62-66.杨绍锷, 吴炳方, 熊隽, 等. 基于TRMM降水产品计算月降水量距平百分率[J]. 遥感信息, 2010(5): 62-66.
4 Li Jinggang, Li Jiren, Huang Shifeng, et al. Characteristics of the Recent 10-Year Flood/Drought over the Dongting Lake Basin based on TRMM Precipitation Data and Regional Integrated Z-Index[J]. Resources Science, 2010, 32(6): 1103-1110.李景刚, 李纪人, 黄诗峰, 等. 基于TRMM数据和区域综合Z指数的洞庭湖流域近10年旱涝特征分析[J]. 资源科学, 2010, 32(6): 1103-1110.
5 Yang Rongfang, Cao Genhua, Zhang Jing. Research of TRMM 3B43 Satellite Precipitation Data Applicability in Beijing-Tianjin-Hebei Region[J]. Journal of Glaciology and Geocryology, 2019, 41(4):1-8.杨荣芳,曹根华,张婧. TRMM 3B43卫星降水数据在京津冀地区的适用性研究[J].冰川冻土,2019,41(4):1-8.
6 Xu Dong, Zou Jin, Lu Ying, et al. Evaluation on Applicability of TRMM Satellite Precipitation Product in the NuJiang River Basin[J]. Research of Soil and Water Conservation, 2019,26(1):240-251.徐东,邹进,陆颖,等. TRMM卫星降水数据在怒江流域的适用性分析[J].水土保持研究, 2019,26(1):240-251.
7 Liu J Z, Zhu A X, Duan Z. Evaluation of TRMM 3B42 Precipitation Product Using Rain Gauge Data in Meichuan Watershed, Poyang Lake Basin, China[J]. Journal of Resources and Ecology, 2012, 3(4): 359-366.
8 Tarek M H, Hassan A, Bhattacharjee J, et al. Assessment of TRMM Data for Precipitation Measurement in Bangladesh[J]. Meteorological Applications, 2017, 24(3): 349-359.
9 Fensterseifer C, Allasia D G, Paz A R. Assessment of the TRMM 3B42 Precipitation Product in Southern Brazil[J]. Journal of The American Water Resources Association, 2016, 52(2): 367-375.
10 Lu Yang, Yang Shengtian, Cai Mingyong, et al. The Applicability Analysis of TRMM Precipitation Data in the Yarlung Zangbo River Basin[J]. Journal of Natural Resources, 2013, 28(8): 1414-1425.吕洋, 杨胜天, 蔡明勇, 等. TRMM卫星降水数据在雅鲁藏布江流域的适用性分析[J]. 自然资源学报, 2013, 28(8): 1414-1425.
11 Cai Xiaohui, Zou Songbing, Lu Zhixiang, et al. Evaluation of TRMM Mouthly Precipitation Data over the Inland River Basins of Northwest China[J]. Journal of Lanzhou University(Natural Sciences Edition), 2013, 49(3): 291-298.蔡晓慧, 邹松兵, 陆志翔, 等. TRMM月降水产品在西北内陆河流域的适应性定量分析[J]. 兰州大学学报(自然科学版), 2013, 49(3): 291-298.
12 Ji Tao, Yang Hua, Liu Rui, et al. Applicability Analysis of the TRMM Precipitation Data in the Sichuan-Chongqing Region[J]. Progress in Geography, 2014, 33(10): 1375-1386.嵇涛, 杨华, 刘睿, 等. 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.
13 Gu Huanghe, Yu Zhongbo, Yang Chuangguo, et al. Application of Satellite Radar Observed Precipitation to Accuracy Analysis in Yangtze River Basin[J]. Water Resources and Power, 2010, 28(8): 3-6.谷黄河, 余钟波, 杨传国, 等. 卫星雷达测雨在长江流域的精度分析[J]. 水电能源科学, 2010, 28(8): 3-6.
14 Zhu Guofeng, Pu Tao, Zhang Tao, et al. The Accuracy of TRMM Precipitation Data in Hengduan Mountainous Region, China[J]. Scientia Geographica Sinica, 2013, 33(9): 1125-1131.朱国锋, 蒲焘, 张涛, 等. TRMM降水数据在横断山区的精度[J]. 地理科学, 2013, 33(9): 1125-1131.
15 Qi Wenwen, Zhang Baiping, Pang yu, et al. TRMM-Data-based Spatial and Seasonal Patterns of Precipitation in the Qinghai-Tibet Plateau[J]. Scientia Geographica Sinica, 2013, 33(8): 999-1005.齐文文, 张百平, 庞宇, 等. 基于TRMM数据的青藏高原降水的空间和季节分布特征[J]. 地理科学, 2013,33(8): 999-1005.
16 Wang Chao, Zhao Chuanyan. A Study of the Spatio-Temporal Distribution of Precipitation in Upper Reaches of Heihe River of China Using TRMM Data[J]. Journal of Natural Resources, 2013, 28(5): 862-872.王超, 赵传燕. TRMM多卫星资料在黑河上游降水时空特征研究中的应用[J]. 自然资源学报, 2013, 28(5): 862-872.
17 Yang Wenyue, Ma Jinhui, Yang Wenkai. Variation Characteristics of Precipitation based on TRMM Data during 2001-2010 in Linxia of Gansu Province[J]. Journal of Arid Meteorology, 2014, 32(6): 934-939.杨文月, 马金辉, 杨文凯. 基于TRMM卫星的近10a甘肃临夏降水变化特征[J]. 干旱气象, 2014, 32(6): 934-939.
18 Kumar B, Lakshmi V. Accessing the Capability of TRMM 3B42 V7 to Simulate Streamflow during Extreme Rain Events: Case Study for a Himalayan River Basin[J]. Journal of Earth System Science, 2018, 127(2): 27.
19 Santos C A G, Neto R M B, Da Silva R M, et al. Integrated Spatiotemporal Trends using TRMM 3B42 Data for the Upper Sao Francisco River Basin, Brazil[J]. Environmental Monitoring and Assessment, 2018, 190(3): 175. doi:10.10071s10661-018-6536-3
doi: 10.10071s10661-018-6536-3
20 Hierro R, Llamedo P, de la Torre A, et al. Spatiotemporal Structures of Rainfall over the Amazon Basin derived from TRMM Data[J]. International Journal of Climatology, 2016, 36(3): 1565-1574.
21 Anandh P C, Vissa N K, Broderick C. Role of MJO in Modulating Rainfall Characteristics Observed over India in All Seasons Utilizing TRMM[J]. International Journal of Climatology, 2018, 38(5): 2352-2373.
22 Li Xianghu, Zhang Qi, Shao Min. Spatio-temporal Distribution of Precipitation in Poyang Lake Basin based on TRMM Data and Precision Evaluation[J]. Progress in Geography, 2012, 31(9): 1164-1170.李相虎, 张奇, 邵敏. 基于TRMM数据的鄱阳湖流域降雨时空分布特征及其精度评价[J]. 地理科学进展, 2012, 31(9): 1164-1170.
23 Wu Xuejiao, Yang Meixue, Wu Hongbo, et al. Verifying and Applying the TRMM TMPA in Heihe River Basin[J]. Journal of Glaciology and Geocryology, 2013, 35(2): 310-319.吴雪娇, 杨梅学, 吴洪波, 等. TRMM多卫星降水数据在黑河流域的验证与应用[J]. 冰川冻土, 2013, 35(2): 310-319.
24 Gao Jie. Accuracy Assessment of Rainfall Measurement based on TRMM Products[J]. Water Power, 2015, 41(6): 28-31.高洁. 基于TRMM卫星数据的降雨测量精度评价[J]. 水力发电, 2015, 41(6): 28-31.
25 Li Wei, Jiang Ping, Zhao Weiquan, et al. Analysis on Applicability of TRMM Precipitation Data in Karst Areas—A Case Study in Gui Zhou Province[J]. Research of Soil and Water Conservation, 2016, 23(1): 97-102.李威, 蒋平, 赵卫权, 等. TRMM卫星降水数据在喀斯特山区的适用性分析——以贵州省为例[J]. 水土保持研究, 2016, 23(1): 97-102.
26 Cai Yancong, Jin Changjie, Wang Anzhi, et al. Accuracy Evaluation of the TRMM Satellite-based Precipitation Data over the Mid-high Latitudes[J]. Chinese Journal of Applied Ecology, 2014, 25(11): 3296-3306.蔡研聪, 金昌杰, 王安志, 等. 中高纬度地区TRMM卫星降雨数据的精度评价[J]. 应用生态学报, 2014, 25(11): 3296-3306.
27 Wang Jialing, Chen Hua, Xu Chongyun, et al. Evaluation of Accuracy and Streamflow Simulation of TRMM Satellite Precipitation Data[J]. Journal of Water Resources Research, 2016, 5(5):434-445.王佳伶, 陈华, 许崇育, 等. TRMM卫星降雨数据的精度及径流模拟评估[J]. 水资源研究, 2016, 5(5):434-445.
28 He Zhen, He Junping. Temporal and Spatial Variation of Extreme Precipitation in the Yellow River Basin from 1960 to 2012[J]. Resources Science, 2014, 36(3): 490-501.贺振, 贺俊平. 1960年至2012年黄河流域极端降水时空变化[J]. 资源科学, 2014, 36(3): 490-501.
29 Sun Rui, Liu Changming, Zhu Qijiang. Relationship between the Fractional Vegetation Cover Change and Rainfall in the Yellow River Basin[J].Acta Geographica Sinica,2001,56(6): 667-672.孙睿, 刘昌明, 朱启疆. 黄河流域植被覆盖度动态变化与降水的关系[J]. 地理学报, 2001, 56(6): 667-672.
30 Fu Rong, Hu Liang, Gu Guojun, et al. A Comparison Stydy of Summer-time Synoptic-scale Waves in South China and the Yangtze River Basin Using the TRMM Multi-Satellite Precipitation Analysis Daily Product[J]. Science in China Series D: Earth Science, 2007, 37(9): 1252-1259.付容, 胡亮, 谷国军,等. 利用TRMM降水资料对华南和长江流域夏季天气尺度波的对比分析[J]. 中国科学(D辑: 地球科学), 2007(9): 1252-1259.
31 Zeng Hongwei, Li Lijuan. Accuracy Validation of TRMM 3B43 Data in Lancang River Basin[J]. Acta Geographica Sinica, 2011, 66(7): 994-1004.
31 曾红伟, 李丽娟. 澜沧江及周边流域TRMM 3B43数据精度检验[J]. 地理学报, 2011, 66(7): 994-1004.
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