Reliability of Gridded Precipitation Products in the Yellow River Basin, China

被引:22
作者
Yang, Yanfen [1 ]
Wu, Jing [2 ]
Bai, Lei [3 ]
Wang, Bing [1 ]
机构
[1] Northwest A&F Univ, Inst Soil & Water Conservat, State Key Lab Soil Eros & Dryland Farming Loess P, Yangling 712100, Shaanxi, Peoples R China
[2] Lanzhou Cent Meteorol Observ, Lanzhou 730020, Peoples R China
[3] Wuhan Univ Technol, Sch Nav, Wuhan 430070, Peoples R China
关键词
precipitation datasets; evaluation; spatial scale; temporal scale; climate; Yellow River Basin; PASSIVE MICROWAVE; ANALYSIS TMPA; PERSIANN-CDR; HYDROLOGICAL APPLICATION; GAUGE OBSERVATIONS; SATELLITE; RAINFALL; MULTISATELLITE; ACCURACY; PERFORMANCE;
D O I
10.3390/rs12030374
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Gridded precipitation products are the potential alternatives in hydrological studies, and the evaluation of their accuracy and potential use is very important for reliable simulations. The objective of this study was to investigate the applicability of gridded precipitation products in the Yellow River Basin of China. Five gridded precipitation products, i.e., Multi-Source Weighted-Ensemble Precipitation (MSWEP), CPC Morphing Technique (CMORPH), Global Satellite Mapping of Precipitation (GSMaP), Tropical Rainfall Measuring Mission (TRMM) Multi-Satellite Precipitation Analysis 3B42, and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN), were evaluated against observations made during 2001-2014 at daily, monthly, and annual scales. The results showed that MSWEP had a higher correlation and lower percent bias and root mean square error, while CMORPH and GSMaP made overestimations compared to the observations. All the datasets underestimated the frequency of dry days, and overestimated the frequency and the intensity of wet days (0-5 mm/day). MSWEP and TRMM showed consistent interannual variations and spatial patterns while CMORPH and GSMaP had larger discrepancies with the observations. At the sub-basin scale, all the datasets performed poorly in the Beiluo River and Qingjian River, whereas they were applicable in other sub-basins. Based on its superior performance, MSWEP was identified as more suitable for hydrological applications.
引用
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页数:24
相关论文
共 84 条
[1]  
[Anonymous], 2020, Statistical Methods in the Atmospheric Sciences
[2]   PERSIANN-CDR Daily Precipitation Climate Data Record from Multisatellite Observations for Hydrological and Climate Studies [J].
Ashouri, Hamed ;
Hsu, Kuo-Lin ;
Sorooshian, Soroosh ;
Braithwaite, Dan K. ;
Knapp, Kenneth R. ;
Cecil, L. Dewayne ;
Nelson, Brian R. ;
Prat, Olivier P. .
BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY, 2015, 96 (01) :69-+
[3]   Global-scale evaluation of 22 precipitation datasets using gauge observations and hydrological modeling [J].
Beck, Hylke E. ;
Vergopolan, Noemi ;
Pan, Ming ;
Levizzani, Vincenzo ;
van Dijk, Albert I. J. M. ;
Weedon, Graham P. ;
Brocca, Luca ;
Pappenberger, Florian ;
Huffman, George J. ;
Wood, Eric F. .
HYDROLOGY AND EARTH SYSTEM SCIENCES, 2017, 21 (12) :6201-6217
[4]   MSWEP: 3-hourly 0.25° global gridded precipitation (1979-2015) by merging gauge, satellite, and reanalysis data [J].
Beck, Hylke E. ;
van Dijk, Albert I. J. M. ;
Levizzani, Vincenzo ;
Schellekens, Jaap ;
Miralles, Diego G. ;
Martens, Brecht ;
de Roo, Ad .
HYDROLOGY AND EARTH SYSTEM SCIENCES, 2017, 21 (01) :589-615
[5]   SAMPLING ERRORS FOR SATELLITE-DERIVED TROPICAL RAINFALL - MONTE-CARLO STUDY USING A SPACE-TIME STOCHASTIC-MODEL [J].
BELL, TL ;
ABDULLAH, A ;
MARTIN, RL ;
NORTH, GR .
JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 1990, 95 (D3) :2195-2205
[6]   Comparison of TRMM precipitation retrievals with rain gauge data from ocean buoys [J].
Bowman, KP .
JOURNAL OF CLIMATE, 2005, 18 (01) :178-190
[7]   An analysis of the performance of hybrid infrared and microwave satellite precipitation algorithnis over India and adjacent regions [J].
Brown, JEM .
REMOTE SENSING OF ENVIRONMENT, 2006, 101 (01) :63-81
[8]   Multiscale Comparative Evaluation of the GPM IMERG v5 and TRMM 3B42 v7 Precipitation Products from 2015 to 2017 over a Climate Transition Area of China [J].
Chen, Cheng ;
Chen, Qiuwen ;
Duan, Zheng ;
Zhang, Jianyun ;
Mo, Kangle ;
Li, Zhe ;
Tang, Guoqiang .
REMOTE SENSING, 2018, 10 (06)
[9]  
Cheng Kai-yu, 2016, Water Resources and Power, V34, P15
[10]  
[成璐 Cheng Lu], 2014, [气象, Meteorological Monthly], V40, P1372