{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,28]],"date-time":"2025-11-28T12:26:56Z","timestamp":1764332816467,"version":"build-2065373602"},"reference-count":36,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2019,12,20]],"date-time":"2019-12-20T00:00:00Z","timestamp":1576800000000},"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":["41604019","41474004"],"award-info":[{"award-number":["41604019","41474004"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"The Wuhan Science and Technology Plan Project","award":["2019010702011314"],"award-info":[{"award-number":["2019010702011314"]}]},{"name":"The Key Laboratory of Geospace Environment and Geodesy, Ministry of Education, Wuhan University","award":["18-01-01"],"award-info":[{"award-number":["18-01-01"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Surface temperature and pressure are indispensable variables in Global Navigation Satellite System (GNSS) meteorology. The lack of meteorological observations located at or near the GNSS sites is a big challenge for the calculation of accurate zenith hydrostatic delay (ZHD). Therefore, various empirical models with different model forms were established to provide temperature and pressure values. In this study, the influence of different modelling factors, including model forms, temporal resolution of the data sources, and the spatial resolution of the data sources, is evaluated and the temperature and pressure model with the best performance is developed. On the basis of the meteorological parameters estimated by the above model, we analyzed the global performance of the three most commonly used ZHD models, that is, the Saastamoinen, Hopfield, and Black models. The numerical results show that the model with the idea of time-segmented modelling performs best, of which the global mean root mean square (RMS), mean absolute error (MAE), and standard deviation (SD) are 7.87\/6.33\/7.17 hPa and 2.95\/2.31\/2.79 K for pressure and temperature, respectively, using the data sources with temporal resolution of 2 h and spatial resolution of 2.5\u00b0 \u00d7 2\u00b0 in the reanalysis data comparison. In comparison with the radiosonde data, the mean RMS\/MAE\/SD are 7.02\/5.24\/6.46 hPa and 4.05\/3.17\/3.86 K for pressure and temperature, respectively. The Saastamoinen model with a global mean bias\/RMS of 1.01\/16.9 mm achieved the best ZHD estimated values compared with the other two ZHD models.<\/jats:p>","DOI":"10.3390\/rs12010035","type":"journal-article","created":{"date-parts":[[2019,12,23]],"date-time":"2019-12-23T03:15:01Z","timestamp":1577070901000},"page":"35","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["The Influence of Different Modelling Factors on Global Temperature and Pressure Models and Their Performance in Different Zenith Hydrostatic Delay (ZHD) Models"],"prefix":"10.3390","volume":"12","author":[{"given":"Fei","family":"Yang","sequence":"first","affiliation":[{"name":"School of Geodesy and Geomatics, Wuhan University, Wuhan 430079, China"},{"name":"Nottingham Geospatial Institute, University of Nottingham, Nottingham NG7 2TU, UK"},{"name":"Guangxi Key Laboratory of Spatial Information and Geomatics, Guilin 541004, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2440-8054","authenticated-orcid":false,"given":"Xiaolin","family":"Meng","sequence":"additional","affiliation":[{"name":"Nottingham Geospatial Institute, University of Nottingham, Nottingham NG7 2TU, UK"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5427-6481","authenticated-orcid":false,"given":"Jiming","family":"Guo","sequence":"additional","affiliation":[{"name":"School of Geodesy and Geomatics, Wuhan University, Wuhan 430079, China"}]},{"given":"Junbo","family":"Shi","sequence":"additional","affiliation":[{"name":"School of Geodesy and Geomatics, Wuhan University, Wuhan 430079, China"}]},{"given":"Xiangdong","family":"An","sequence":"additional","affiliation":[{"name":"Nottingham Geospatial Institute, University of Nottingham, Nottingham NG7 2TU, UK"}]},{"given":"Qiyi","family":"He","sequence":"additional","affiliation":[{"name":"Nottingham Geospatial Institute, University of Nottingham, Nottingham NG7 2TU, UK"}]},{"given":"Lv","family":"Zhou","sequence":"additional","affiliation":[{"name":"College of Geomatics and Geoinformation, Guilin University of Technology, Guilin 541004, China"}]}],"member":"1968","published-online":{"date-parts":[[2019,12,20]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"5019","DOI":"10.1029\/97JB03534","article-title":"Estimating horizontal gradients of tropospheric path delay with a single GPS receiver","volume":"103","author":"Kroger","year":"1998","journal-title":"J. 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