{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,10]],"date-time":"2026-04-10T19:57:01Z","timestamp":1775851021365,"version":"3.50.1"},"reference-count":82,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2020,2,19]],"date-time":"2020-02-19T00:00:00Z","timestamp":1582070400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["51709218"],"award-info":[{"award-number":["51709218"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Key Program of National Natural Science Foundation of China","award":["91437220"],"award-info":[{"award-number":["91437220"]}]},{"name":"R&amp;D Special Fund for Public Welfare Industry (Meteorology)","award":["GYHY201506002"],"award-info":[{"award-number":["GYHY201506002"]}]},{"name":"National Key R&amp;D Program of China","award":["2018YFC1407405"],"award-info":[{"award-number":["2018YFC1407405"]}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["WUT: 2019IVA103"],"award-info":[{"award-number":["WUT: 2019IVA103"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Precipitation serves as a crucial factor in the study of hydrometeorology, ecology, and the atmosphere. Gridded precipitation data are available from a multitude of sources including precipitation retrieved by satellites, radar, the output of numerical weather prediction models, and extrapolation by ground rain gauge data. Evaluating different types of products in ungauged regions with complex terrain will not only help researchers in applying scientific data, but also provide useful information that can be used to improve gridded precipitation products. The present study aims to evaluate comprehensively 12 precipitation datasets made by raw retrieved products, blended with rain gauge data, and blended multiple source datasets in multi-temporal scales in order to develop a suitable method for creating gridded precipitation data in regions with snow-dominated regions with complex terrain. The results show that the Multi-Source Weighted-Ensemble Precipitation (MSWEP), Global Satellite Mapping of Precipitation with Gauge Adjusted (GSMaP_GAUGE), Tropical Rainfall Measuring Mission (TRMM_3B42), Climate Prediction Center Morphing Technique blended with Chinese observations (CMORPH_SUN), and Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) can represent the spatial pattern of precipitation in arid\/semi-arid and humid\/semi-humid areas of the Qinghai-Tibet Plateau on a climatological spatial pattern. On interannual, seasonal, and monthly scales, the TRMM_3B42, GSMaP_GAUGE, CMORPH_SUN, and MSWEP outperformed the other products. In general, the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Cloud Classification System (PERSIANN_CCS) has poor performance in basins of the Qinghai-Tibet Plateau. Most products overestimated the extreme indices of the 99th percentile of precipitation (R99), the maximal of daily precipitation in a year (Rmax), and the maximal of pentad accumulation of precipitation in a year (R5dmax). They were underestimated by the extreme index of the total number of days with daily precipitation less than 1 mm (dry day, DD). Compared to products blended with rain gauge data only, MSWEP blended with more data sources, and outperformed the other products. Therefore, multi-sources of blended precipitation should be the hotspot of regional and global precipitation research in the future.<\/jats:p>","DOI":"10.3390\/rs12040683","type":"journal-article","created":{"date-parts":[[2020,2,20]],"date-time":"2020-02-20T03:20:03Z","timestamp":1582168803000},"page":"683","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":27,"title":["Which Precipitation Product Works Best in the Qinghai-Tibet Plateau, Multi-Source Blended Data, Global\/Regional Reanalysis Data, or Satellite Retrieved Precipitation Data?"],"prefix":"10.3390","volume":"12","author":[{"given":"Lei","family":"Bai","sequence":"first","affiliation":[{"name":"Intelligent Transportation Systems Research Center, Wuhan University of Technology, Wuhan 430063, China"},{"name":"School of Navigation, Wuhan University of Technology, Wuhan 430063, China"},{"name":"National Meteorological Information Center, Beijing 100081, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuanqiao","family":"Wen","sequence":"additional","affiliation":[{"name":"Intelligent Transportation Systems Research Center, Wuhan University of Technology, Wuhan 430063, China"},{"name":"School of Navigation, Wuhan University of Technology, Wuhan 430063, China"},{"name":"Hubei Key Laboratory of Inland Shipping Technology, Wuhan 430063, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chunxiang","family":"Shi","sequence":"additional","affiliation":[{"name":"National Meteorological Information Center, Beijing 100081, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yanfen","family":"Yang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Institute of Soil and Water Conservation, Northwest A&F University, Yangling 712100, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fan","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Navigation, Wuhan University of Technology, Wuhan 430063, China"},{"name":"Hubei Key Laboratory of Inland Shipping Technology, Wuhan 430063, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jing","family":"Wu","sequence":"additional","affiliation":[{"name":"Lanzhou Central Meteorological Observatory, Lanzhou 730020, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Junxia","family":"Gu","sequence":"additional","affiliation":[{"name":"National Meteorological Information Center, Beijing 100081, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yang","family":"Pan","sequence":"additional","affiliation":[{"name":"National Meteorological Information Center, Beijing 100081, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shuai","family":"Sun","sequence":"additional","affiliation":[{"name":"National Meteorological Information Center, Beijing 100081, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Junyao","family":"Meng","sequence":"additional","affiliation":[{"name":"Chiyuan Science Technology, Beijing 101108, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,2,19]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"849","DOI":"10.1007\/s11069-014-1109-4","article-title":"The evolution analysis of flood and drought in Huai River Basin of China based on monthly precipitation characteristics","volume":"73","author":"Yan","year":"2014","journal-title":"Nat. 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