{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T02:52:22Z","timestamp":1760151142788,"version":"build-2065373602"},"reference-count":35,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2022,2,23]],"date-time":"2022-02-23T00:00:00Z","timestamp":1645574400000},"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":["41904036"],"award-info":[{"award-number":["41904036"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Chongqing Science and Technology Bureau","award":["cstc2020jxjl00001"],"award-info":[{"award-number":["cstc2020jxjl00001"]}]},{"name":"Education Commission of Hubei Province of China","award":["Grant No. Q20212801"],"award-info":[{"award-number":["Grant No. Q20212801"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The conversion factor is a key parameter for converting zenith wet delays (ZWD) into precipitable water vapour (PWV) with a mean value of 0.15, and the traditional method of calculating it is to model the weighted average temperature in the process of conversion factor calculation. Here, we overcome the dependence on high-precision atmospheric weighted average temperature for mapping ZWD onto PWV and build a global non-meteorological parametric model for conversion factor G\u03a0 model by using the gridded data of global conversion factor time series from 2006 to 2013 provided by the Global Geodetic Observing System (GGOS) Atmosphere. Internal and external accuracy tests were performed using data from four times (UTC 00:00, 06:00, 12:00, and 18:00) per day throughout 2012 and 2014 as provided by the GGOS Atmosphere, and the statistical average root-mean-square (RMS) and mean absolute errors (MAE) on a global scale are 0.0031\/0.0026 and 0.0030\/0.0026, respectively, which only account for 1.5\u20132% of the conversion factor value. In addition, the observed GPS data are also used to validate the established G\u03a0 model, and the RMS of the PWV differences between the established model and the observed meteorological data was less than 3.2 mm. The results show that the established G\u03a0 model has a high accuracy, which can be used to calculate the PWV value where no observed meteorological parameters are available.<\/jats:p>","DOI":"10.3390\/rs14051086","type":"journal-article","created":{"date-parts":[[2022,2,24]],"date-time":"2022-02-24T00:53:26Z","timestamp":1645664006000},"page":"1086","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["A Global Conversion Factor Model for Mapping Zenith Total Delay onto Precipitable Water"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6715-0877","authenticated-orcid":false,"given":"Qingzhi","family":"Zhao","sequence":"first","affiliation":[{"name":"College of Geomatics, Xi\u2019an University of Science and Technology, Xi\u2019an 710054, China"}]},{"given":"Kang","family":"Liu","sequence":"additional","affiliation":[{"name":"College of Geomatics, Xi\u2019an University of Science and Technology, Xi\u2019an 710054, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6194-9661","authenticated-orcid":false,"given":"Tengxu","family":"Zhang","sequence":"additional","affiliation":[{"name":"College of Resources and Environmental Science and Engineering, Hubei University of Science and Technology, Xianning 437100, China"}]},{"given":"Lin","family":"He","sequence":"additional","affiliation":[{"name":"College of Resources and Environmental Science and Engineering, Hubei University of Science and Technology, Xianning 437100, China"}]},{"given":"Ziyu","family":"Shen","sequence":"additional","affiliation":[{"name":"College of Resources and Environmental Science and Engineering, Hubei University of Science and Technology, Xianning 437100, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3370-3955","authenticated-orcid":false,"given":"Si","family":"Xiong","sequence":"additional","affiliation":[{"name":"School of Geodesy and Geomatics, Wuhan University, Wuhan 430072, China"}]},{"given":"Yun","family":"Shi","sequence":"additional","affiliation":[{"name":"College of Geomatics, Xi\u2019an University of Science and Technology, Xi\u2019an 710054, China"}]},{"given":"Lichuan","family":"Chen","sequence":"additional","affiliation":[{"name":"Chongqing Institute of Geology and Mineral Resources, Chongqing 402574, China"}]},{"given":"Weiming","family":"Liao","sequence":"additional","affiliation":[{"name":"Chongqing Institute of Geology and Mineral Resources, Chongqing 402574, China"}]}],"member":"1968","published-online":{"date-parts":[[2022,2,23]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"12465","DOI":"10.1038\/s41598-017-12593-z","article-title":"Establishing a method of short-term rainfall forecasting based on GNSS-derived PWV and its application","volume":"7","author":"Yao","year":"2017","journal-title":"Sci. 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(1946\u20131975)"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/5\/1086\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T22:26:16Z","timestamp":1760135176000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/5\/1086"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,2,23]]},"references-count":35,"journal-issue":{"issue":"5","published-online":{"date-parts":[[2022,3]]}},"alternative-id":["rs14051086"],"URL":"https:\/\/doi.org\/10.3390\/rs14051086","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2022,2,23]]}}}