{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,18]],"date-time":"2025-12-18T14:27:55Z","timestamp":1766068075722,"version":"build-2065373602"},"reference-count":73,"publisher":"MDPI AG","issue":"20","license":[{"start":{"date-parts":[[2024,10,18]],"date-time":"2024-10-18T00:00:00Z","timestamp":1729209600000},"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":["42474015"],"award-info":[{"award-number":["42474015"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Currently, ground-based global navigation satellite system (GNSS) techniques have become widely recognized as a reliable and effective tool for atmospheric monitoring, enabling the retrieval of zenith total delay (ZTD) and precipitable water vapor (PWV) for meteorological and climate research. The International GNSS Service analysis centers (ACs) have initiated their third reprocessing campaign, known as IGS Repro3. In this campaign, six ACs conducted a homogeneous reprocessing of the ZTD time series spanning the period from 1994 to 2022. This paper primarily focuses on ZTD products. First, the data processing strategies and station conditions of six ACs were compared and analyzed. Then, formal errors within the data were examined, followed by the implementation of quality control processes. Second, a combination method is proposed and applied to generate the final ZTD products. The resulting combined series was compared with the time series submitted by the six ACs, revealing a mean bias of 0.03 mm and a mean root mean square value of 3.02 mm. Finally, the time series submitted by the six ACs and the combined series were compared with VLBI data, radiosonde data, and ERA5 data. In comparison, the combined solution performs better than most individual analysis centers, demonstrating higher quality. Therefore, the advanced method proposed in this study and the generated high-quality dataset have considerable implications for further advancing GNSS atmospheric sensing and offer valuable insights for climate modeling and prediction.<\/jats:p>","DOI":"10.3390\/rs16203885","type":"journal-article","created":{"date-parts":[[2024,10,21]],"date-time":"2024-10-21T09:58:24Z","timestamp":1729504704000},"page":"3885","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["The Zenith Total Delay Combination of International GNSS Service Repro3 and the Analysis of Its Precision"],"prefix":"10.3390","volume":"16","author":[{"given":"Qiuying","family":"Huang","sequence":"first","affiliation":[{"name":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"},{"name":"School of Electronic, Electrical and Communicating Engineering, University of Chinese Academy of Sciences, Beijing 101408, 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"},{"name":"College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5441-2818","authenticated-orcid":false,"given":"Haobo","family":"Li","sequence":"additional","affiliation":[{"name":"School of Science, Royal Melbourne Institute of Technology (RMIT) University, Melbourne, VIC 3001, Australia"}]},{"given":"Jinglei","family":"Zhang","sequence":"additional","affiliation":[{"name":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"}]},{"given":"Zhaowei","family":"Han","sequence":"additional","affiliation":[{"name":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"},{"name":"School of Electronic, Electrical and Communicating Engineering, University of Chinese Academy of Sciences, Beijing 101408, China"}]},{"given":"Dingyi","family":"Liu","sequence":"additional","affiliation":[{"name":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"},{"name":"School of Electronic, Electrical and Communicating Engineering, University of Chinese Academy of Sciences, Beijing 101408, China"}]},{"given":"Yaping","family":"Li","sequence":"additional","affiliation":[{"name":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"}]},{"given":"Hongxin","family":"Zhang","sequence":"additional","affiliation":[{"name":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"},{"name":"School of Electronic, Electrical and Communicating Engineering, University of Chinese Academy of Sciences, Beijing 101408, China"}]}],"member":"1968","published-online":{"date-parts":[[2024,10,18]]},"reference":[{"key":"ref_1","unstructured":"WMO (2023). State of the Global Climate 2022(WMO-No.1316), World Meteorological Organization."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"15787","DOI":"10.1029\/92JD01517","article-title":"GPS Meteorology: Remote Sensing of Atmospheric Water Vapor Using the Global Positioning System","volume":"97","author":"Bevis","year":"1992","journal-title":"J. Geophys. Res."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"14925","DOI":"10.1029\/93JD00948","article-title":"Sensing Climate Change Using the Global Positioning System","volume":"98","author":"Yuan","year":"1993","journal-title":"J. Geophys. Res."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"468","DOI":"10.1175\/1520-0426(1995)012<0468:GSOAWV>2.0.CO;2","article-title":"GPS\/STORM\u2014GPS Sensing of Atmospheric Water Vapor for Meteorology","volume":"12","author":"Rocken","year":"1995","journal-title":"J. Atmos. Ocean. Technol."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"5802214","DOI":"10.1109\/TGRS.2024.3447832","article-title":"A Fusion Framework for Producing an Accurate PWV Map with Spatiotemporal Continuity Based on GNSS, ERA5 and MODIS Data","volume":"62","author":"Zhu","year":"2024","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"2631","DOI":"10.1029\/93GL02935","article-title":"Sensing Atmospheric Water Vapor with the Global Positioning System","volume":"20","author":"Rocken","year":"1993","journal-title":"Geophys. Res. Lett."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"379","DOI":"10.1175\/1520-0450(1994)033<0379:GMMZWD>2.0.CO;2","article-title":"GPS Meteorology: Mapping Zenith Wet Delays onto Precipitable Water","volume":"33","author":"Bevis","year":"1994","journal-title":"J. Appl. Meteor."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"5385","DOI":"10.5194\/amt-9-5385-2016","article-title":"Review of the State of the Art and Future Prospects of the Ground-Based GNSS Meteorology in Europe","volume":"9","author":"Guerova","year":"2016","journal-title":"Atmos. Meas. Tech."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"3008","DOI":"10.1175\/2008JAMC1920.1","article-title":"Integrated Water Vapor Field and Multiscale Variations over China from GPS Measurements","volume":"47","author":"Jin","year":"2008","journal-title":"J. Appl. Meteorol. Climatol."},{"key":"ref_10","first-page":"20","article-title":"Recent progresses and future prospectives of ground-based GNSS water vapor sounding","volume":"51","author":"Zhang","year":"2022","journal-title":"Cehui Xuebao\/Acta Geod. Cartogr. Sin."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"109","DOI":"10.1002\/joc.3412","article-title":"A Multi-sensor Study of Water Vapour from Radiosonde, MODIS and AERONET: A Case Study of Hong Kong","volume":"33","author":"Liu","year":"2013","journal-title":"Int. J. Climatol."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"830","DOI":"10.1175\/1520-0426(2001)018<0830:COMOAW>2.0.CO;2","article-title":"Comparison of Measurements of Atmospheric Wet Delay by Radiosonde, Water Vapor Radiometer, GPS, and VLBI","volume":"18","author":"Niell","year":"2001","journal-title":"J. Atmos. Ocean. Technol."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Li, H., Wang, X., Wu, S., Zhang, K., Chen, X., Qiu, C., Zhang, S., Zhang, J., Xie, M., and Li, L. (2020). Development of an Improved Model for Prediction of Short-Term Heavy Precipitation Based on GNSS-Derived PWV. Remote Sens., 12.","DOI":"10.3390\/rs12244101"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Li, L., Zhang, K., Wu, S., Li, H., Wang, X., Hu, A., Li, W., Fu, E., Zhang, M., and Shen, Z. (2022). An Improved Method for Rainfall Forecast Based on GNSS-PWV. Remote Sens., 14.","DOI":"10.3390\/rs14174280"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"113778","DOI":"10.1016\/j.rse.2023.113778","article-title":"A Novel Regional Drought Monitoring Method Using GNSS-Derived ZTD and Precipitation","volume":"297","author":"Zhao","year":"2023","journal-title":"Remote Sens. Environ."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"130961","DOI":"10.1016\/j.jhydrol.2024.130961","article-title":"Flash Drought Monitoring Using Diurnal-Provided Evaporative Demand Drought Index","volume":"633","author":"Li","year":"2024","journal-title":"J. Hydrol."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Li, H., Choy, S., Zaminpardaz, S., Carter, B., Sun, C., Purwar, S., Liang, H., Li, L., and Wang, X. (2023). Investigating the Inter-Relationships among Multiple Atmospheric Variables and Their Responses to Precipitation. Atmosphere, 14.","DOI":"10.3390\/atmos14030571"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"106424","DOI":"10.1016\/j.atmosres.2022.106424","article-title":"Estimation of Diurnal-Provided Potential Evapotranspiration Using GNSS and Meteorological Products","volume":"280","author":"Li","year":"2022","journal-title":"Atmos. Res."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"2006GL028039","DOI":"10.1029\/2006GL028039","article-title":"Multiscale Analysis of Precipitable Water Vapor over Africa from GPS Data and ECMWF Analyses","volume":"34","author":"Bock","year":"2007","journal-title":"Geophys. Res. Lett."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"329","DOI":"10.1029\/2012JD018053","article-title":"Evaluation of the Atmospheric Water Vapor Content in a Regional Climate Model Using Ground-based GPS Measurements","volume":"118","author":"Ning","year":"2013","journal-title":"JGR Atmos."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"10967","DOI":"10.1029\/2018JD028703","article-title":"On the Statistical Significance of Climatic Trends Estimated From GPS Tropospheric Time Series","volume":"123","author":"Alshawaf","year":"2018","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"3117","DOI":"10.5194\/amt-10-3117-2017","article-title":"Estimating Trends in Atmospheric Water Vapor and Temperature Time Series over Germany","volume":"10","author":"Alshawaf","year":"2017","journal-title":"Atmos. Meas. Tech."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Ding, J., Chen, J., Tang, W., and Song, Z. (2022). Spatial\u2013Temporal Variability of Global GNSS-Derived Precipitable Water Vapor (1994\u20132020) and Climate Implications. Remote Sens., 14.","DOI":"10.3390\/rs14143493"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.rse.2018.06.029","article-title":"The Correlation between GNSS-Derived Precipitable Water Vapor and Sea Surface Temperature and Its Responses to El Ni\u00f1o\u2013Southern Oscillation","volume":"216","author":"Wang","year":"2018","journal-title":"Remote Sens. Environ."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"5392","DOI":"10.1109\/JSTARS.2021.3079699","article-title":"An Improved Model for Detecting Heavy Precipitation Using GNSS-Derived Zenith Total Delay Measurements","volume":"14","author":"Li","year":"2021","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Zhao, Q., Yao, Y., Yao, W., and Li, Z. (2018). Real-Time Precise Point Positioning-Based Zenith Tropospheric Delay for Precipitation Forecasting. Sci. Rep., 8.","DOI":"10.1038\/s41598-018-26299-3"},{"key":"ref_27","first-page":"4105718","article-title":"A New Cumulative Anomaly-Based Model for the Detection of Heavy Precipitation Using GNSS-Derived Tropospheric Products","volume":"60","author":"Li","year":"2022","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"2443","DOI":"10.1175\/JCLI-D-15-0158.1","article-title":"Homogenized Time Series of the Atmospheric Water Vapor Content Obtained from the GNSS Reprocessed Data","volume":"29","author":"Ning","year":"2016","journal-title":"J. Clim."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"89","DOI":"10.5194\/cp-8-89-2012","article-title":"Benchmarking Homogenization Algorithms for Monthly Data","volume":"8","author":"Venema","year":"2012","journal-title":"Clim. Past"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"1689","DOI":"10.5194\/amt-10-1689-2017","article-title":"EPN-Repro2: A Reference GNSS Tropospheric Data Set over Europe","volume":"10","author":"Pacione","year":"2017","journal-title":"Atmos. Meas. Tech."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"2008JD010415","DOI":"10.1029\/2008JD010415","article-title":"On the Homogeneity and Interpretation of Precipitable Water Time Series Derived from Global GPS Observations","volume":"114","author":"Vey","year":"2009","journal-title":"J. Geophys. Res."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"744","DOI":"10.1109\/JSTARS.2012.2191392","article-title":"Trends in the Atmospheric Water Vapor Content From Ground-Based GPS: The Impact of the Elevation Cutoff Angle","volume":"5","author":"Ning","year":"2012","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"4861","DOI":"10.5194\/amt-9-4861-2016","article-title":"Comparison of GPS Tropospheric Delays Derived from Two Consecutive EPN Reprocessing Campaigns from the Point of View of Climate Monitoring","volume":"9","author":"Baldysz","year":"2016","journal-title":"Atmos. Meas. Tech."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"503","DOI":"10.1007\/s00190-006-0124-y","article-title":"Comparisons of Homogeneously Reprocessed GPS and VLBI Long Time-Series of Troposphere Zenith Delays and Gradients","volume":"81","author":"Steigenberger","year":"2007","journal-title":"J. Geod."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"D04107","DOI":"10.1029\/2010JD013889","article-title":"Precipitable Water Vapor Estimates from Homogeneously Reprocessed GPS Data: An Intertechnique Comparison in Antarctica","volume":"116","author":"Thomas","year":"2011","journal-title":"J. Geophys. Res."},{"key":"ref_36","first-page":"189","article-title":"EUREF\u2019s Contribution to National, European and Global Geodetic Infrastructures","volume":"Volume 139","author":"Rizos","year":"2014","journal-title":"Earth on the Edge: Science for a Sustainable Planet"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"2989","DOI":"10.5194\/amt-9-2989-2016","article-title":"Benchmark Campaign and Case Study Episode in Central Europe for Development and Assessment of Advanced GNSS Tropospheric Models and Products","volume":"9","author":"Dick","year":"2016","journal-title":"Atmos. Meas. Tech."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Jones, J., Guerova, G., Dou\u0161a, J., Dick, G., De Haan, S., Pottiaux, E., Bock, O., Pacione, R., and Van Malderen, R. (2020). Advanced GNSS Tropospheric Products for Monitoring Severe Weather Events and Climate: COST Action ES1206 Final Action Dissemination Report, Springer International Publishing.","DOI":"10.1007\/978-3-030-13901-8"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1007\/1345_2022_158","article-title":"An Experimental Combination of IGS Repro3 Campaign\u2019s Orbit Products Using a Variance Component Estimation Strategy","volume":"Volume 154","author":"Freymueller","year":"2022","journal-title":"Geodesy for a Sustainable Earth"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"87","DOI":"10.1007\/s00190-023-01777-3","article-title":"Combination and SLR Validation of IGS Repro3 Orbits for ITRF2020","volume":"97","author":"Zajdel","year":"2023","journal-title":"J. Geod."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1007\/s00190-024-01870-1","article-title":"Analysis of the IGS Contribution to ITRF2020","volume":"98","author":"Rebischung","year":"2023","journal-title":"J. Geod."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"611","DOI":"10.1007\/s00190-016-0897-6","article-title":"The IGS Contribution to ITRF2014","volume":"90","author":"Rebischung","year":"2016","journal-title":"J. Geod."},{"key":"ref_43","unstructured":"Byram, S., and Hackman, C. (2012). Computation of the IGS Final Troposphere Product by the USNO, IGS Workshop 2012."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"1263","DOI":"10.1016\/j.asr.2021.04.046","article-title":"Review of Recent GNSS Modelling Improvements Based on CODEs Repro3 Contribution","volume":"68","author":"Dach","year":"2021","journal-title":"Adv. Space Res."},{"key":"ref_45","unstructured":"Selmke, I., Dach, R., Arnold, D., Prange, L., Schaer, S., Sidorov, D., Stebler, P., Villiger, A., J\u00e4ggi, A., and Hugentobler, U. (2020). CODE Repro3 Product Series for the IGS, Astronomical Institute, University of Bern."},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Schoenemann, E., Dilssner, F., Mayer, V., Gini, F., Otten, M., Springer, T., Bruni, S., Enderle, W., and Zandbergen, R. (2021, January 19\u201330). ESA\u2019s Efforts for More Consistent Geodetic Products. Proceedings of the 23rd EGU General Assembly, vEGU21, Online.","DOI":"10.5194\/egusphere-egu21-8899"},{"key":"ref_47","first-page":"37","article-title":"Status of IGS Reprocessing Activities at GFZ","volume":"Volume 152","author":"Freymueller","year":"2020","journal-title":"Beyond 100: The Next Century in Geodesy"},{"key":"ref_48","unstructured":"M\u00e4nnel, B., Brandt, A., Bradke, M., Sakic, P., Brack, A., and Nischan, T. (2021). GFZ Repro3 Product Series for the International GNSS Service (IGS), GFZ Data Services."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"21","DOI":"10.5194\/amt-15-21-2022","article-title":"Towards Operational Multi-GNSS Tropospheric Products at GFZ Potsdam","volume":"15","author":"Wilgan","year":"2022","journal-title":"Atmos. Meas. Tech."},{"key":"ref_50","doi-asserted-by":"crossref","unstructured":"Michel, A., Santamar\u00eda-G\u00f3mez, A., Boy, J.-P., Perosanz, F., and Loyer, S. (2021). Analysis of GNSS Displacements in Europe and Their Comparison with Hydrological Loading Models. Remote Sens., 13.","DOI":"10.3390\/rs13224523"},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"1045","DOI":"10.1007\/s00190-018-1223-2","article-title":"Processing of GNSS Constellations and Ground Station Networks Using the Raw Observation Approach","volume":"93","author":"Strasser","year":"2019","journal-title":"J. Geod."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"42","DOI":"10.1515\/jogs-2022-0136","article-title":"Quality Control of SIRGAS ZTD Products","volume":"12","author":"Mackern","year":"2022","journal-title":"J. Geod. Sci."},{"key":"ref_53","unstructured":"Dach, R., Lutz, S., Walser, P., and Fridez, P. (2015). Bernese GNSS Software Version 5.2, University of Bern, Bern Open Publishing. Available online: http:\/\/www.bernese.unibe.ch\/docs\/DOCU52.pdf."},{"key":"ref_54","unstructured":"Bardella, M., and Casotto, S. (2012). Extending ESA\u2019s NAPEOS S\/W System for Ocean Tide Parameter Recovery. ISSFD."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"1295","DOI":"10.1016\/S1364-6826(00)00248-0","article-title":"First Experience with near Real-Time Water Vapor Estimation in a German GPS Network","volume":"63","author":"Dick","year":"2001","journal-title":"J. Atmos. Sol.-Terr. Phys."},{"key":"ref_56","unstructured":"Marty, J.-C., Loyer, S., Perosanz, F., Mercier, F., Bracher, G., Legr\u00e9sy, B., Portier, L., Capdeville, H., Lemoine, J.M., and Biancale, R. (September, January 31). GINS: THE CNES\/GRGS GNSS SCIENTIFIC SOFTWARE. Proceedings of the 3rd International Colloquium Scientific and Fundamental Aspects of the Galileo Programme, Copenhagen, Danemark. ESA Proceedings WPP326."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"469","DOI":"10.1016\/j.asr.2020.04.015","article-title":"GipsyX\/RTGx, a New Tool Set for Space Geodetic Operations and Research","volume":"66","author":"Bertiger","year":"2020","journal-title":"Adv. Space Res."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"104864","DOI":"10.1016\/j.cageo.2021.104864","article-title":"GROOPS: A Software Toolkit for Gravity Field Recovery and GNSS Processing","volume":"155","author":"Behzadpour","year":"2021","journal-title":"Comput. Geosci."},{"key":"ref_59","unstructured":"Savcenko, R., and Bosch, W. (2012). EOT11A\u2014Empirical Ocean Tide Model from Multi-Mission Satellite Altimetry, Deutsches Geod\u00e4tisches Forschungsinstitut (DGFI)."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"4570","DOI":"10.1002\/jgrc.20336","article-title":"Precise Comparisons of Bottom-pressure and Altimetric Ocean Tides","volume":"118","author":"Ray","year":"2013","journal-title":"JGR Ocean."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"615","DOI":"10.5194\/os-17-615-2021","article-title":"FES2014 Global Ocean Tide Atlas: Design and Performance","volume":"17","author":"Lyard","year":"2021","journal-title":"Ocean Sci."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"2005GL025546","DOI":"10.1029\/2005GL025546","article-title":"Global Mapping Function (GMF): A New Empirical Mapping Function Based on Numerical Weather Model Data","volume":"33","author":"Boehm","year":"2006","journal-title":"Geophys. Res. Lett."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"2003GL018984","DOI":"10.1029\/2003GL018984","article-title":"Vienna Mapping Functions in VLBI Analyses","volume":"31","author":"Boehm","year":"2004","journal-title":"Geophys. Res. Lett."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"679","DOI":"10.1007\/s00190-007-0135-3","article-title":"Short Note: A Global Model of Pressure and Temperature for Geodetic Applications","volume":"81","author":"Boehm","year":"2007","journal-title":"J. Geod."},{"key":"ref_65","first-page":"17","article-title":"Global Reanalysis: Goodbye ERA-Interim, Hello ERA5","volume":"159","author":"Hersbach","year":"2019","journal-title":"ECMWF Newsl."},{"key":"ref_66","doi-asserted-by":"crossref","unstructured":"Wang, X., Chen, Y., Zhang, J., Qiu, C., Zhou, K., Li, H., and Huang, Q. (2024). Assessment of BDS-3 PPP-B2b Service and Its Applications for the Determination of Precipitable Water Vapour. Atmosphere, 15.","DOI":"10.3390\/atmos15091048"},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"1547","DOI":"10.1175\/1520-0450(2003)042<1547:AAVOGT>2.0.CO;2","article-title":"Accuracy and Variability of GPS Tropospheric Delay Measurements of Water Vapor in the Western Mediterranean","volume":"42","author":"Haase","year":"2003","journal-title":"J. Appl. Meteor."},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"2807","DOI":"10.5194\/amt-10-2807-2017","article-title":"Determination of Zenith Hydrostatic Delay and Its Impact on GNSS-Derived Integrated Water Vapor","volume":"10","author":"Wang","year":"2017","journal-title":"Atmos. Meas. Tech."},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"833","DOI":"10.1002\/2015JD024181","article-title":"Water Vapor-weighted Mean Temperature and Its Impact on the Determination of Precipitable Water Vapor and Its Linear Trend","volume":"121","author":"Wang","year":"2016","journal-title":"JGR Atmos."},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"323","DOI":"10.1016\/j.asr.2010.07.021","article-title":"Combination Methods of Tropospheric Time Series","volume":"47","author":"Pacione","year":"2011","journal-title":"Adv. Space Res."},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"1347","DOI":"10.5194\/amt-11-1347-2018","article-title":"Reduction of ZTD Outliers through Improved GNSS Data Processing and Screening Strategies","volume":"11","author":"Stepniak","year":"2018","journal-title":"Atmos. Meas. Tech."},{"key":"ref_72","doi-asserted-by":"crossref","unstructured":"Giannaros, C., Kotroni, V., Lagouvardos, K., Giannaros, T.M., and Pikridas, C. (2020). Assessing the Impact of GNSS ZTD Data Assimilation into the WRF Modeling System during High-Impact Rainfall Events over Greece. Remote Sens., 12.","DOI":"10.3390\/rs12030383"},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"349","DOI":"10.1007\/s00190-017-1066-2","article-title":"VMF3\/GPT3: Refined Discrete and Empirical Troposphere Mapping Functions","volume":"92","author":"Landskron","year":"2018","journal-title":"J. Geod."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/16\/20\/3885\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T16:16:27Z","timestamp":1760112987000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/16\/20\/3885"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,10,18]]},"references-count":73,"journal-issue":{"issue":"20","published-online":{"date-parts":[[2024,10]]}},"alternative-id":["rs16203885"],"URL":"https:\/\/doi.org\/10.3390\/rs16203885","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2024,10,18]]}}}