干旱区生态环境知识资源中心(Arid): Evaluation of the Radar QPE and Rain Gauge Data Merging Methods in Northern China

Arid

DOI	10.3390/rs12030363
	Evaluation of the Radar QPE and Rain Gauge Data Merging Methods in Northern China
	Qiu, Qingtai 1; Liu, Jia 1; Tian, Jiyang 1; Jiao, Yufei 1; Li, Chuanzhe 1; Wang, Wei 1,2; Yu, Fuliang 1
通讯作者	Liu, Jia
来源期刊	REMOTE SENSING
EISSN	2072-4292
出版年	2020
卷号	12 期号:3
英文摘要	Radar-rain gauge merging methods have been widely used to produce high-quality precipitation with fine spatial resolution by combing the advantages of the rain gauge observation and the radar quantitative precipitation estimation (QPE). Different merging methods imply a specific choice on the treatment of radar and rain gauge data. In order to improve their applicability, significant studies have focused on evaluating the performances of the merging methods. In this study, a categorization of the radar-rain gauge merging methods was proposed as: (1) Radar bias adjustment category, (2) radar-rain gauge integration category, and (3) rain gauge interpolation category for a total of six commonly used merging methods, i.e., mean field bias (MFB), regression inverse distance weighting (RIDW), collocated co-kriging (CCok), fast Bayesian regression kriging (FBRK), regression kriging (RK), and kriging with external drift (KED). Eight different storm events were chosen from semi-humid and semi-arid areas of Northern China to test the performance of the six methods. Based on the leave-one-out cross validation (LOOCV), conclusions were obtained that the integration category always performs the best, the bias adjustment category performs the worst, and the interpolation category ranks between them. The quality of the merging products can be a function of the merging method that is affected by both the quality of radar QPE and the ability of the rain gauge to capture small-scale rainfall features. In order to further evaluate the applicability of the merging products, they were then used as the input to a rainfall-runoff model, the Hybrid-Hebei model, for flood forecasting. It is revealed that a higher quality of the merging products indicates a better agreement between the observed and the simulated runoff.
英文关键词	weather radar quantitative precipitation estimation rain gauge radar-rain gauge merging leave-one-out cross validation verification
类型	Article
语种	英语
国家	Peoples R China
开放获取类型	gold
收录类别	SCI-E
WOS记录号	WOS:000515393800022
WOS关键词	X-BAND RADAR ; PRECIPITATION ESTIMATION ; INTERPOLATION ; UNCERTAINTY ; COMBINATION ; CALIBRATION ; SIMULATION ; ADJUSTMENT ; PREDICTION ; NETWORKS
WOS类目	Environmental Sciences ; Geosciences, Multidisciplinary ; Remote Sensing ; Imaging Science & Photographic Technology
WOS研究方向	Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology
来源机构	河海大学
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/315414
作者单位	1.China Inst Water Resources & Hydropower Res, State Key Lab Simulat & Regulat Water Cycle River, Beijing 100038, Peoples R China; 2.Hohai Univ, Coll Hydrol & Water Resources, Nanjing 210098, Peoples R China
推荐引用方式 GB/T 7714	Qiu, Qingtai,Liu, Jia,Tian, Jiyang,et al. Evaluation of the Radar QPE and Rain Gauge Data Merging Methods in Northern China[J]. 河海大学,2020,12(3).
APA	Qiu, Qingtai.,Liu, Jia.,Tian, Jiyang.,Jiao, Yufei.,Li, Chuanzhe.,...&Yu, Fuliang.(2020).Evaluation of the Radar QPE and Rain Gauge Data Merging Methods in Northern China.REMOTE SENSING,12(3).
MLA	Qiu, Qingtai,et al."Evaluation of the Radar QPE and Rain Gauge Data Merging Methods in Northern China".REMOTE SENSING 12.3(2020).