{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,30]],"date-time":"2026-03-30T10:16:24Z","timestamp":1774865784221,"version":"3.50.1"},"reference-count":61,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2022,8,30]],"date-time":"2022-08-30T00:00:00Z","timestamp":1661817600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Natural Science Foundation of China","award":["41730109"],"award-info":[{"award-number":["41730109"]}]},{"name":"National Natural Science Foundation of China","award":["41874040"],"award-info":[{"award-number":["41874040"]}]},{"name":"National Natural Science Foundation of China","award":["2022ZZCX06"],"award-info":[{"award-number":["2022ZZCX06"]}]},{"name":"Double-First Class","award":["41730109"],"award-info":[{"award-number":["41730109"]}]},{"name":"Double-First Class","award":["41874040"],"award-info":[{"award-number":["41874040"]}]},{"name":"Double-First Class","award":["2022ZZCX06"],"award-info":[{"award-number":["2022ZZCX06"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Global navigation satellite systems (GNSS) has been applied to the sounding of precipitable water vapor (PWV) due to its high accuracy and high spatiotemporal resolutions. PWV obtained from GNSS (GNSS-PWV) can be used to investigate extreme weather phenomena, such as the formation mechanism and prediction of rainfalls. In the study, a new, improved model for rainfall forecasting was developed based on GNSS data and rainfall data for the 9-year period from 2010 to 2018 at 66 stations located in the USA. The new model included three prediction factors\u2014PWV value, PWV increase, maximum hourly PWV increase. The two key tasks involved for the development of the model were the determination of the thresholds for each prediction factor and the selection of the optimal strategy for using the three prediction factors together. For determining the thresholds, both critical success index (CSI) and true skill statistic (TSS) were tested, and results showed that TSS outperformed CSI for all rainfall events tested. Then, various strategies by combining the three prediction factors together were also tested, and results indicated that the best forecast result was from the case that any two of the prediction factors were over their own thresholds. Finally, the new model was evaluated using the GNSS data for the 2-year period from 2019 to 2020 at the above mentioned 66 stations, and the probability of detection (POD) and false-alarms rate (FAR) were adopted to measure the model performances. Over the 66 stations, the POD values ranged from 73% to 97% with the mean of 87%, and the FARs ranged from 26% to 77% with the mean of 53%. Moreover, it was also found that both POD and FAR values were related to the region of the station; e.g., the results at the stations that are located in humid regions were better than the ones located in dry regions. All these results suggest the feasibility and good performance of using GNSS-PWV for forecasting rainfall.<\/jats:p>","DOI":"10.3390\/rs14174280","type":"journal-article","created":{"date-parts":[[2022,8,31]],"date-time":"2022-08-31T00:13:56Z","timestamp":1661904836000},"page":"4280","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":37,"title":["An Improved Method for Rainfall Forecast Based on GNSS-PWV"],"prefix":"10.3390","volume":"14","author":[{"given":"Longjiang","family":"Li","sequence":"first","affiliation":[{"name":"School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9376-1148","authenticated-orcid":false,"given":"Kefei","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China"},{"name":"Satellite Positioning for Atmosphere, Climate and Environment (SPACE) Research Centre, RMIT University, Melbourne, VIC 3001, Australia"}]},{"given":"Suqin","family":"Wu","sequence":"additional","affiliation":[{"name":"School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5441-2818","authenticated-orcid":false,"given":"Haobo","family":"Li","sequence":"additional","affiliation":[{"name":"Satellite Positioning for Atmosphere, Climate and Environment (SPACE) Research Centre, RMIT University, Melbourne, VIC 3001, Australia"},{"name":"State Key Laboratory of Hydroscience and Engineering, Tsinghua University, Beijing 100084, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1720-6630","authenticated-orcid":false,"given":"Xiaoming","family":"Wang","sequence":"additional","affiliation":[{"name":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"}]},{"given":"Andong","family":"Hu","sequence":"additional","affiliation":[{"name":"Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, Boulder, CO 80309, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6526-1509","authenticated-orcid":false,"given":"Wang","family":"Li","sequence":"additional","affiliation":[{"name":"Faculty of Land Resources Engineering, Kunming University of Science and Technology, Kunming 650031, China"}]},{"given":"Erjiang","family":"Fu","sequence":"additional","affiliation":[{"name":"Bei-Stars Geospatial Information Innovation Institute, No. 1 Xinbei Road, Pukou District, Nanjing 211899, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5786-7436","authenticated-orcid":false,"given":"Minghao","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China"}]},{"given":"Zhen","family":"Shen","sequence":"additional","affiliation":[{"name":"School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China"}]}],"member":"1968","published-online":{"date-parts":[[2022,8,30]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"557","DOI":"10.1007\/s10712-011-9157-8","article-title":"The role of water vapour in earth\u2019s energy flows","volume":"33","author":"Allan","year":"2012","journal-title":"Surv. 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