Evaluation of Eight High-Resolution Gridded Precipitation Products in the Heihe River Basin, Northwest China
文献类型：期刊论文
| 作者 | Wang, Yuwei1,3; Zhao, Na1,2,3 |
| 刊名 | REMOTE SENSING
 |
| 出版日期 | 2022-03-01 |
| 卷号 | 14期号:6页码:26 |
| 关键词 | high-resolution gridded precipitation product evaluation accuracy the Heihe River basin |
| DOI | 10.3390/rs14061458 |
| 通讯作者 | Zhao, Na(zhaon@lreis.ac.cn) |
| 英文摘要 | The acquisition of the precise spatial distribution of precipitation is of great importance and necessity in many fields, such as hydrology, meteorology and ecological environments. However, in the arid and semiarid regions of Northwest China, especially over mountainous areas such as the Heihe River basin (HRB), the scarcity and uneven distribution of rainfall stations have created certain challenges in gathering information that accurately describes the spatial distribution of precipitation for use in applications. In this study, the accuracy of precipitation estimates from eight high-resolution gridded precipitation products (CMORPHv1-CRT, CRU TSv.4.05, ERA5, GSMaP_NRT, IMERG V06B-Final, MSWEPv2.0, PERSIANN-CDR and TRMM 3B42v7) are comprehensively evaluated by referring to the precipitation observations from 23 stations over the HRB using six indices (root mean square error, standard deviation, Pearson correlation coefficient, relative deviation, mean error and Kling-Gupta efficiency) from different spatial and temporal scales. The results show that at an annual scale, MSWEP has the highest accuracy over the entire basin, while PERSIANN, CRU and ERA5 show the most accurate results in the upper, middle and lower reaches of the HRB, respectively. At a seasonal scale, the performance of IMERG, CRU and ERA5 is superior to that of the other products in all seasons in the upper, middle and lower reaches, respectively. Over the entire HRB, PERSIANN displays the smallest deviation in all seasons except for spring. TRMM shows the highest accuracy in spring and autumn, while MSWEP and CRU show the highest accuracy in summer and winter, respectively. At a monthly scale, TRMM is superior to the other products, with a relatively stronger correlation almost every month, while GSMaP is inferior to the other products. Moreover, MSWEP and PERSIANN perform relatively best, with favorable statistical results around almost every station, while GSMaP shows the worse performance. In addition, ERA5 tends to overestimate higher values, while GSMaP tends to overestimate lower values over the entire basin. Moreover, the overestimation of ERA5 tends to appear in the upper reach area, while that of GSMaP tends to appear in the lower reach area. Only CRU and PERSIANN yield underestimations of precipitation, with the strongest tendency appearing in the upper reach area. The results of this study display some findings on the uncertainties of several frequently used precipitation datasets in the high mountains and poorly gauged regions in the HRB and will be helpful to researchers in various fields who need high-resolution gridded precipitation datasets over the HRB, as well as to data producers who want to improve their products. |
| WOS关键词 | ANALYSIS TMPA ; SATELLITE ; MODEL ; TEMPERATURE ; PERFORMANCE ; REANALYSIS ; ENSEMBLE ; DATASET ; CMORPH ; ERROR |
| 资助项目 | National Natural Science Foundation of China[42071374] ; National Natural Science Foundation of China[41930647] ; Strategic Priority Research Program (A) of the Chinese Academy of Sciences[XDA20030203] |
| WOS研究方向 | Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology |
| 语种 | 英语 |
| WOS记录号 | WOS:000774307800001 |
| 出版者 | MDPI |
| 资助机构 | National Natural Science Foundation of China ; Strategic Priority Research Program (A) of the Chinese Academy of Sciences |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/173329]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Zhao, Na |
| 作者单位 | 1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China 2.Jiangsu Ctr Collaborat Innovat Geog Informat Reso, Nanjing 210023, Peoples R China 3.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100101, Peoples R China |
| 推荐引用方式 GB/T 7714 | Wang, Yuwei,Zhao, Na. Evaluation of Eight High-Resolution Gridded Precipitation Products in the Heihe River Basin, Northwest China[J]. REMOTE SENSING,2022,14(6):26. |
| APA | Wang, Yuwei,&Zhao, Na.(2022).Evaluation of Eight High-Resolution Gridded Precipitation Products in the Heihe River Basin, Northwest China.REMOTE SENSING,14(6),26. |
| MLA | Wang, Yuwei,et al."Evaluation of Eight High-Resolution Gridded Precipitation Products in the Heihe River Basin, Northwest China".REMOTE SENSING 14.6(2022):26. |
入库方式： OAI收割
来源：地理科学与资源研究所
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