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Remote Sensing Technology and Application  2019, Vol. 34 Issue (5): 1121-1132    DOI: 10.11873/j.issn.1004-0323.2019.5.1121
    
Evaluation of the GSMaP Estimates on Monitoring Extreme Precipitation Events
Yue Gao1(),Hui Xu1(),Guo Liu2
1.College of Hydrology and Water Resources,Hohai University,Nanjing 210098,China
2.School of Earth Sciences and Engineering,Hohai University,Nanjing 211100,China
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Abstract  

Heavy rainfall attacked Hunan province during late June to early July in 2017, causing various secondary disasters and severe financial losses. Here, three GSMaP (Global Satellite Mapping of Precipitation) datasets (i.e., GSMaP_NRT, GSMaP_MVK and GSMaP_Gauge) were investigated based on several statistical metrics and the error decomposition model, in an effort to analyze their error structure and variation characteristics, assess the capability of GSMaP products for monitoring heavy rain events. Results show that: (1) All datasets can well capture the spatial distribution and temporal characteristics of the heavy rainfall. (2) Due to the interference of orographic convection, all three datasets show uncertainties over mountainous regions. In the error structure, hit bias contributes most to the total error. (3) GSMaP_Gauge performs best for monitoring extremely heavy rainfall, missed error has a significant decrease after applying the gauge adjustments. Compared to IMERG products, GSMaP products shows much higher accuracy in monitoring heavy rainfall. We expected the results documented here can provide feedback for further improving the GSMaP retrieving algorithm and strengthening data quality during heavy rainfall periods.

Key words:  Hunan      Heavy rainfall      Data calibration      Error decomposition      GSMaP     
Received:  19 December 2018      Published:  05 December 2019
ZTFLH:  TP79  
Corresponding Authors:  Hui Xu     E-mail:  gaoyue@hhu.edu.cn;njxh@hhu.edu.cn
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Yue Gao
Hui Xu
Guo Liu

Cite this article: 

Yue Gao,Hui Xu,Guo Liu. Evaluation of the GSMaP Estimates on Monitoring Extreme Precipitation Events. Remote Sensing Technology and Application, 2019, 34(5): 1121-1132.

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http://www.rsta.ac.cn/EN/10.11873/j.issn.1004-0323.2019.5.1121     OR     http://www.rsta.ac.cn/EN/Y2019/V34/I5/1121

Fig.1  Geography survey of the study area
评价指标计算方法量纲最优值
相关系数(CC)CC=i=1nGi-GˉSi-Sˉi=1nGi-Gˉ2×i=1nSi-Sˉ21
均方根误差(RMSE)RMSE=1n×i=1nSi-Gi2mm0
平均误差(ME)ME=1ni=1nSi-Gimm0
相对偏差(BIAS)BIAS=i=1nSi-Gii=1nGi×100%%0
命中率(POD)POD=HH+M1
误报率(FAR)FAR=FH+F0
关键成功指数(CSI)CSI=HH+M+F1
Table 1  List of the statistical metrics used for validating GSMaP products
Fig.2  Spatial distributions of rainfall accumulation (from June 16, 2017 to July 15, 2017)
Fig.3  Mean Rainfall Accumulations for Different Basins (From June 16, 2017 to July 15, 2017)
Fig.4  Temporal variations in daily precipitation for different basins
Fig.5  Spatial distributions of statistical indices (CC、ME、BIAS & RMSE) derived from GSMaP products vs. Observations at hourly scale
Fig.6  Spatial Distributions of Total Error and Error Components for GSMaP Products
Fig.7  Scatter plots of GSMaP products vs. observations on daily scale
遥感降水产品相关系数

平均误差

/mm

均方根误差

/mm

相对偏差

/%

命中率误报率关键成功指数
GSMaP_NRT0.49-3.9535.85-7.840.690.300.53
GSMaP_MVK0.58-0.2934.63-0.570.750.260.59
GSMaP_Gauge0.60-2.4931.08-4.830.850.240.67
IMERG-Early0.473.8538.427.800.760.310.56
IMERG-Late0.533.8836.447.620.790.270.61
IMERG-Final0.598.5434.2117.690.850.310.61
Table 2  Statistical Summary of the Comparison between GSMaP Products and Observations in torrential rainfall events
遥感降水产品

相对偏差

/%

偏差相对贡献率/%
命中漏测误报
GSMaP_NRT-7.84-8.57-12.5913.32
GSMaP_MVK-0.57-2.59-8.9310.94
GSMaP_Gauge-4.83-10.66-3.929.74
IMERG-Early7.801.63-9.6015.77
IMERG-Late7.622.69-7.7612.69
IMERG-Final17.696.24-4.8016.25
Table 3  Relative Bias Ratio for the error components of GSMaP Products in torrential rainfall events
1 IPCC. Climate Change 2014: Synthesis Report. Contribution of Working Groups I, II and III to The Fifth Assessment Report of the Intergovernmental Panel on Climate Change [M]. Geneva: Switzerland, 2014.
2 IPCC. Managing The Risks of Extreme Events and Disasters to Advance Climate Change Adaptation. A Special Report of Working Groups I and II of the Intergovernmental Panel on Climate Change [M]. New York: Cambridge University Press, 2012.
3 Ren Guoyu, Feng Guolin, Yan Zhongwei. Progresses in Observation Studies of Climate Extremes and Changes in Mainland China [J]. Climatic and Environmental Research, 2010, 15(4):337-353.
3 任国玉, 封国林, 严中伟. 中国极端气候变化观测研究回顾与展望 [J]. 气候与环境研究, 2010, 15(4):337-353.
4 Zhai Panmao, Wang Zhiwei, Zou Xukai. The Change of Extreme Climate Events in the Whole Country and Major River Basin Climate Change and Water Resources[M]. Beijing: China Meteorological Press, 2007: 91-112.翟盘茂, 王志伟, 邹旭恺. 全国及主要流域极端气候事件变化. 气候变化与中国水资源 [M], 北京: 气象出版社, 2007: 91-112.
5 Guo Ruifang, Liu Yuanbo. Multi-satellite Retrieval of High Resolution Precipitation: An Overview [J]. Advances in Earth Science, 2015, 30(8):891-903.
5 郭瑞芳, 刘元波. 多传感器联合反演高分辨率降水方法综述 [J]. 地球科学进展, 2015, 30(8):891-903.
6 Liu Yuanbo, Fu Qiaoni, Song Ping, et al. Satellite Retrieval of Precipitation: An Overview [J]. Advance in Earth Science, 2011, 26(11):1162-1172.
6 刘元波, 傅巧妮, 宋平, 等. 卫星遥感反演降水研究综述 [J]. 地球科学进展, 2011, 26(11):1162-1172.
7 Omranian E, Sharif H O. Evaluation of The Global Precipitation Measurement (GPM) Satellite Rainfall Products over The Lower Colorado River Basin, Texas[J]. Journal of the American Water Resources Association, 2018, 54(D2):882-998.
8 Yi W, Reid I M, Xue X H, et al. High and Middle Latitude Neutral Mesospheric Density Response to Geomagnetic Storms[J]. Geophysical Research Letters, 2018, 45(1):436-444.
9 Chen S, Hu J J, Zhang A, et al. Performance of Near Real-time Global Satellite Mapping of Precipitation Estimates during Heavy Precipitation Events over Northern China[J]. Theoretical & Applied Climatology, 2018, 6:1-15.
10 Maggioni V, Massari C. On the Performance of Satellite Precipitation Products in Riverine Flood Modeling: A Review[J]. Journal of Hydrology, 2018, 558:214-224.
11 Tang Guoqiang, Long Di, Wan Wei, et al. An Overview and Outlook of Global Water Remote Sensing Technology and Applications[J]. Scientia Sinica Technologica, 2015, 45(10):1013-1023.
11 唐国强, 龙笛, 万玮, 等. 全球水遥感技术及其应用研究的综述与展望 [J]. 中国科学:技术科学, 2015, 45(10):1013-1023.
12 Prat O, Nelson B. Evaluation of Extreme Precipitation Derived from Long-term Global Satellite Quantitative Precipitation Estimates (QPEs) [C]// EGU General Assembly Conference. EGU General Assembly Conference Abstracts, 2017.
13 Scofield R A, Kuligowski R J. Satellite Precipitation Algorithms for Extreme Precipitation Events[M]∥Measuring Precipitation From Space. Springer Netherlands, 2007:485-495.
14 Tian Y D, Peterslidard C D, Adler R F, et al. Evaluation of GSMaP Precipitation Estimates over the Contiguous United States [J]. Journal of Hydrometeorology, 2010, 11(2):566-574.
15 Huang Y, Chen S, Cao Q, et al. Evaluation of Version-7 TRMM Multi-satellite Precipitation Analysis Product during the Beijing Extreme Heavy Rainfall Event of 21 July 2012 [J]. Water, 2014, 6(1):32-44.
16 Chen Xiaohong, Zhong Ruida, Wang Zhaoli, et al. Evaluation on the Accuracy and Hydrological Performance of The Latest-generation GPM IMERG Product over South China [J]. Journal of Hydraulic Engineering, 2017, 48(10):1147-1156.
16 陈晓宏, 钟睿达, 王兆礼, 等. 新一代GPM IMERG卫星遥感降水数据在中国南方地区的精度及水文效用评估 [J]. 水利学报, 2017, 48(10):1147-1156.
17 He Zhihua. Research on Hydrological Modeling in High Mountain Basins [D]. Beijing: Tsinghua University, 2015.
17 贺志华. 高山流域降水径流过程机理及模拟研究[D]. 北京: 清华大学, 2015.
18 Li Zhe. Multi-Source Precipitation Observations and Fusion for Hydrological Applications in the Yangtze River Basin[D]. Beijing: Tsinghua University, 2015.
18 李哲. 多源降雨观测与融合及其在长江流域的水文应用[D]. 北京: 清华大学, 2015.
19 Jiang Shanhu, Ren Liliang, Yong Bin, et al. Hydrological Evaluation of the TRMM Multi-satellite Precipitation Estimates over the Mishui Basin [J]. Advances in Water Science, 2014, 25(5):641-649.
19 江善虎, 任立良, 雍斌, 等. TRMM卫星降水数据在洣水流域径流模拟中的应用 [J]. 水科学进展, 2014, 25(5):641-649.
20 Tang Guoqiang, Wan Wei, Zeng Ziyue, et al. An Overview of the Global Precipitation Measurement (GPM) Mission and It’s Latest Development [J]. Remote Sensing Technology and Application, 2015, 30(4):607-615.
20 唐国强, 万玮, 曾子悦, 等. 全球降水测量(GPM)计划及其最新进展综述 [J]. 遥感技术与应用, 2015, 30(4):607-615.
21 Tang G Q, Zeng Z Y, Long D, et al. Statistical and Hydrological Comparisons between TRMM and GPM Level-3 Products over A Midlatitude Basin: Is Day-1 IMERG A Good Successor for TMPA 3B42V7? [J]. Journal of Hydrometeorology, 2015, 17:121-137.
22 Okamoto K, Ushio T, Iguchi T, et al. The Global Satellite Mapping of Precipitation (GSMaP) Project [C]∥ Geoscience and Remote Sensing Symposium, IEEE International Geoscience and Remote Sensing Symposium Proceedings, 2005:3414-3416.
23 Kachi M, Kubota T, Aonashi K, et al. Recent Improvements in The Global Satellite Mapping of Precipitation (GSMaP) [C]∥ IEEE Geoscience and Remote Sensing Symposium, 2014:3762-3765.
24 Tsujimoto K, Ohta T, Koike T. Validation of Satellite Precipitation Product GSMaP/NRT with Ground Rain Gauges in Cambodia [J]. Glycobiology, 2003, 13(10):693-706.
25 Ushio T, Kachi M. Kalman Filtering Applications for Global Satellite Mapping of Precipitation (GSMaP)[C]∥ Satellite Rainfall Applications for Surface Hydrology. Springer Netherlands, 2010:105-123.
26 Mega T, Ushio T, Kubota T, et al. Gauge Adjusted Global Satellite Mapping of Precipitation (GSMaP_Gauge)[C]∥ IEEE General Assembly and Scientific Symposium, 2014:1-4.
27 Zhou Wenbin. Moderately Unbalanced Development - Exploration of Regional Economic Layout in Hunan [J]. Journal of Changsha University of Science and Technology (Social Science), 1990(1):187-189.
27 周文斌. 适度非均衡发展——湖南区域经济布局探索 [J]. 长沙理工大学学报(社会科学版), 1990(1):187-189.
28 Liu Dongrun, Liu Shenbai, Zhang Zaifeng. Analysis on The Current Situation and Sustainable Utilization of Water Resources in Hunan [C]// China Society for Hydropower Engineering, Hydrologic and Sediment Committee. 2003.
28 刘东润, 刘慎柏, 张在峰. 湖南省水资源现状与可持续利用对策分析(会议)// 中国水力发电工程学会水文泥沙专业委员会学术讨论会. 2003.
29 Shi Sha, Yang Jin, Hu Jun. The Flood Fighting! The Central Enterprises Are Coming [J]. China State-Owned Enterprise Management, 2017(15):67-67.
29 史莎, 杨进, 胡俊. 抗洪! 央企来了 [J]. 国企管理, 2017(15):67-67.
30 Kida S, Shige S, Kubota T, et al. Improvement of Rain/No-Rain Classification Methods for Microwave Radiometer Observations over the Ocean Using a 37 GHz Emission Signature [J]. Journal of The Meteorological Society of Japan, 2009, 87:165-181.
31 Yamamoto M K, Shige S. Implementation of An Orographic/Nonorographic Rainfall Classification Scheme in The GSMaP Algorithm for Microwave Radiometers[J]. Atmospheric Research, 2015, 163:36-47.
32 Takahashi N, Awaka J. Introduction of A Melting Layer Model to A Rain Retrieval Algorithm for Microwave Radiometers [C]// IEEE International Geoscience and Remote Sensing Symposium, 2005:3404-3409.
33 Ushio T. On the Use of Split Window Data in Deriving the Cloud Motion Vector for Filling the Gap of Passive Microwave Rainfall Estimation [J]. Sola, 2007, 3(623):1-4.
34 Ushio T, Sasashige K, Kubota T, et al. A Kalman Filter Approach to the Global Satellite Mapping of Precipitation (GSMaP) from Combined Passive Microwave and Infrared Radiometric Data [J]. Journal of The Meteorological Society of Japan, 2009, 87A(3):137-151.
35 Shen Y, Zhao P, Pan Y, et al. A High Spatio-temporal Gauge-satellite Merged Precipitation Analysis over China [J]. Journal of Geophysical Research: Atmospheres, 2014, 119(6):3063-3075.
36 Shen Yan, Pan Yang, Yu Jingjing, et al. Quality Assessment of Hourly Merged Precipitation Product over China [J]. Transactions of Atmospheric Sciences, 2013, 36(1):37-46.
36 沈艳, 潘旸, 宇婧婧, 等. 中国区域小时降水量融合产品的质量评估 [J]. 大气科学学报, 2013, 36(1):37-46.
37 Yong B, Ren L L, Hong Y, et al. Hydrologic Evaluation of Multisatellite Precipitation Analysis Standard Precipitation Products in Basins beyond Its Inclined Latitude Band: A Case Study in Laohahe Basin, China [J]. Water Resources Research, 2010, 46(7):759-768.
38 Tian Y D, Peters-Lidard C D, Eylander J B, et al. Component Analysis of Errors in Satellite-basd Precipitation Estimates [J]. Journal of Geophysical Research: Atmospheres, 2009, 114(D24).doi: .
doi: 10.1029/2009JD011949
39 Yong B, Chen B, Tian Y D, et al. Error-component Analysis of TRMM-based Multi-satellite Precipitation Estimates over Mainland China [J]. Remote Sensing, 2016, 8(5):440.doi: .
doi: 10.3390/rs8050440
40 Tian Y D, Peters-lidard C D. Systematic Anomalies over Inland Water Bodies in Satellite-based Precipitation Estimates[J]. Geophysical Research Letters, 2007, 34(14): L14403.
41 Tang G Q, Long D, Hong Y. Systematic Anomalies over Inland Water Bodies of High Mountain Asia in TRMM Precipitation Estimates: No Longer A Problem for the GPM Era? [C]// Agu Fall Meeting. AGU Fall Meeting Abstracts, 2016.
42 Huffman G J, Bolvin D T, Nelkin E J. Integrated Multi-Satellite Retrievals for GPM (IMERG) Technical Documentation [EB/OL]. , 2018.
43 Huffman G J, Bolvin D T, Braithwaite D, et al. NASA Global Precipitation Measurement Integrated Multi-satellite Retrievals for GPM (IMERG),Algorithm Theoretical Basis Doc,Version 5.2[EB/OL]. , 2018.
[1] . [J]. Remote Sensing Technology and Application, 1992, 7(3): 38 -41 .
[2] GAN Fu-ping, WANG Run-sheng, MA Ai-nai, ZHANG Gong-gu. The Development and Tendency of Both Basis and Techniques of Discrimination for Minerals and Rocks Using
Spectral Remote Sensing Data
[J]. Remote Sensing Technology and Application, 2002, 17(3): 140 -147 .
[3] TANG Li-yu, ZHU Quan-feng,SHI Song. Research and Implementation of Constructing Delaunay TIN Based on STL[J]. Remote Sensing Technology and Application, 2005, 20(3): 346 -349 .
[4] SUN Mao-hua, ZHENG Zhen-fan, ZHANG Sheng-wei, LAN Ai-lan. The Redundancy Scheme of Data Processing and System Managing in FY-3 Satellite Microwave Humidity Sounder[J]. Remote Sensing Technology and Application, 2007, 22(2): 147 -151 .
[5] . [J]. Remote Sensing Technology and Application, 1994, 9(2): 44 -49 .
[6] . Radar Altimeter Measurement of PreeiPitation[J]. Remote Sensing Technology and Application, 1995, 10(3): 27 -32 .
[7] . Integrated System for Rice Production Estimation [J]. Remote Sensing Technology and Application, 1996, 11(2): 45 -53 .
[8] ZHU Su-yun, LIU Hao, DONG Xiao-long. Signal Processing System of Microwave Scatterometer on HY-II[J]. Remote Sensing Technology and Application, 2007, 22(2): 152 -154 .
[9] SHI Jian-Zong, NAN Zhuo-Tong, SHI Wei, WANG Liang-Xu, ZHANG Xiu-Min. An Information System for the Permafrost Background Investigation over the Qinghai-Tibet Plateau[J]. Remote Sensing Technology and Application, 2010, 25(5): 725 -732 .
[10] . Remote Sensing of the Atmosphere with the Millimeter and Sub m illimeter Wave Radiometry from the Space[J]. Remote Sensing Technology and Application, 1999, 14(2): 49 -54 .