{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,7]],"date-time":"2026-01-07T07:59:43Z","timestamp":1767772783513,"version":"build-2065373602"},"reference-count":42,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2021,9,6]],"date-time":"2021-09-06T00:00:00Z","timestamp":1630886400000},"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":["41864002; 41704027"],"award-info":[{"award-number":["41864002; 41704027"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Guangxi Natural Science Foundation of China","award":["2018GXNSFAA281182; 2020GXNSFBA297145; 2018GXNSFAA281279"],"award-info":[{"award-number":["2018GXNSFAA281182; 2020GXNSFBA297145; 2018GXNSFAA281279"]}]},{"name":"Innovation Project of Guangxi Graduate Education","award":["YCSW202109"],"award-info":[{"award-number":["YCSW202109"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Pressure, water vapor pressure, temperature, and weighted mean temperature (Tm) are tropospheric parameters that play an important role in high-precision global navigation satellite system navigation (GNSS). As accurate tropospheric parameters are obligatory in GNSS navigation and GNSS water vapor detection, high-precision modeling of tropospheric parameters has gained widespread attention in recent years. A new approach is introduced to develop an empirical tropospheric delay model named the China Tropospheric (CTrop) model, providing meteorological parameters based on the sliding window algorithm. The radiosonde data in 2017 are treated as reference values to validate the performance of the CTrop model, which is compared to the canonical Global Pressure and Temperature 3 (GPT3) model. The accuracy of the CTrop model in regards to pressure, water vapor pressure, temperature, and weighted mean temperature are 5.51 hPa, 2.60 hPa, 3.09 K, and 3.35 K, respectively, achieving an improvement of 6%, 9%, 10%, and 13%, respectively, when compared to the GPT3 model. Moreover, three different resolutions of the CTrop model based on the sliding window algorithm are also developed to reduce the amount of gridded data provided to the users, as well as to speed up the troposphere delay computation process, for which users can access model parameters of different resolutions for their requirements. With better accuracy of estimating the tropospheric parameters than that of the GPT3 model, the CTrop model is recommended to improve the performance of GNSS positioning and navigation.<\/jats:p>","DOI":"10.3390\/rs13173546","type":"journal-article","created":{"date-parts":[[2021,9,6]],"date-time":"2021-09-06T21:47:38Z","timestamp":1630964858000},"page":"3546","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["A New Approach for the Development of Grid Models Calculating Tropospheric Key Parameters over China"],"prefix":"10.3390","volume":"13","author":[{"given":"Ge","family":"Zhu","sequence":"first","affiliation":[{"name":"College of Geomatics and Geoinformation, Guilin University of Technology, Guilin 541004, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Liangke","family":"Huang","sequence":"additional","affiliation":[{"name":"College of Geomatics and Geoinformation, Guilin University of Technology, Guilin 541004, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lilong","family":"Liu","sequence":"additional","affiliation":[{"name":"College of Geomatics and Geoinformation, Guilin University of Technology, Guilin 541004, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chen","family":"Li","sequence":"additional","affiliation":[{"name":"Beidou Navigation Department, Natural Resources Information Center of Guangxi Zhuang Autonomous Region, Nanning 530028, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7523-2672","authenticated-orcid":false,"given":"Junyu","family":"Li","sequence":"additional","affiliation":[{"name":"College of Geomatics and Geoinformation, Guilin University of Technology, Guilin 541004, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ling","family":"Huang","sequence":"additional","affiliation":[{"name":"College of Geomatics and Geoinformation, Guilin University of Technology, Guilin 541004, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lv","family":"Zhou","sequence":"additional","affiliation":[{"name":"College of Geomatics and Geoinformation, Guilin University of Technology, Guilin 541004, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hongchang","family":"He","sequence":"additional","affiliation":[{"name":"College of Geomatics and Geoinformation, Guilin University of Technology, Guilin 541004, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2021,9,6]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"279","DOI":"10.1007\/BF02521844","article-title":"Contributions to the theory of atmospheric refraction","volume":"105","author":"Saastamoinen","year":"1972","journal-title":"Bull. G\u00e9od\u00e9sique"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Guo, J., Hou, R., Zhou, M., Jin, X., Li, C., Liu, X., and Gao, H. (2021). Monitoring 2019 Forest Fires in Southeastern Australia with GNSS Technique. Remote Sens., 13.","DOI":"10.3390\/rs13030386"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"5105","DOI":"10.1080\/01431161.2013.786850","article-title":"Preliminary study of GNSS meteorology techniques in Algeria","volume":"34","author":"Boutiouta","year":"2013","journal-title":"Int. J. Remote Sens."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"82","DOI":"10.1007\/s10291-019-0874-7","article-title":"GNSS PPP with different troposphere models during severe weather conditions","volume":"23","year":"2019","journal-title":"GPS Solut."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Li, Z., Wen, Y., Zhang, P., Liu, Y., and Zhang, Y. (2020). Joint Inversion of GPS, Leveling, and InSAR Data for the 2013 Lushan (China) Earthquake and Its Seismic Hazard Implications. Remote Sens., 12.","DOI":"10.3390\/rs12040715"},{"key":"ref_6","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_7","doi-asserted-by":"crossref","first-page":"4487","DOI":"10.1029\/JC074i018p04487","article-title":"Two-Quartic tropospheric refractivity profile for correcting satellite data","volume":"74","author":"Hopfield","year":"1969","journal-title":"J. Geophys. Res."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1825","DOI":"10.1029\/JB083iB04p01825","article-title":"An easily implemented algorithm for the tropospheric range correction","volume":"83","author":"Black","year":"1978","journal-title":"J. Geophys. Res."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Lu, C., Li, X., Cheng, J., Dick, G., Ge, M., Wickert, J., and Schuh, H. (2018). Real-time tropospheric delay retrieval from multi-GNSS PPP ambiguity resolution: Validation with final troposphere products and a numerical weather model. Remote Sens., 10.","DOI":"10.3390\/rs10030481"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Cao, L., Zhang, B., Li, J., Yao, Y., Liu, L., Ran, Q., and Xiong, Z. (2021). A Regional Model for Predicting Tropospheric Delay and Weighted Mean Temperature in China Based on GRAPES_MESO Forecasting Products. Remote Sens., 13.","DOI":"10.3390\/rs13132644"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1007\/s00190-021-01478-9","article-title":"Refining the empirical global pressure and temperature model with the ERA5 reanalysis and radiosonde data","volume":"95","author":"Li","year":"2021","journal-title":"J. Geod."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Wu, M., Jin, S., Li, Z., Cao, Y., Ping, F., and Tang, X. (2021). High-Precision GNSS PWV and Its Variation Characteristics in China Based on Individual Station Meteorological Data. Remote Sens., 13.","DOI":"10.3390\/rs13071296"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1065","DOI":"10.1016\/j.asr.2018.06.021","article-title":"A refined regional empirical pressure and temperature model over China","volume":"62","author":"Zhang","year":"2018","journal-title":"Adv. Space Res."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Li, J., Zhang, B., Yao, Y., Liu, L., Sun, Z., and Yan, X. (2020). A Refined Regional Model for Estimating Pressure, Temperature, and Water Vapor Pressure for Geodetic Applications in China. Remote Sens., 12.","DOI":"10.3390\/rs12111713"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"53","DOI":"10.3724\/SP.J.1246.2012.00053.1","article-title":"A zenith tropospheric delay correction model based on the regional CORS network","volume":"3","author":"Huang","year":"2012","journal-title":"Geod. Geodyn."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Huang, L., Xie, S., Liu, L., Li, J., Chen, J., and Kang, C. (2017). SSIEGNOS: A New Asian Single Site Tropospheric Correction Model. ISPRS Int. J. Geo-Inf., 6.","DOI":"10.3390\/ijgi6010020"},{"key":"ref_17","unstructured":"Leandro, R.F., Santos, M.C., and Langley, R.B. (2006, January 18\u201320). UNB neutral atmosphere models: Development and performance. Proceedings of the ION NTM 2006, Monterey, CA, USA."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"65","DOI":"10.1007\/s10291-007-0077-5","article-title":"UNB3m_pack: A neutral atmosphere delay package for radiometric space techniques","volume":"12","author":"Leandro","year":"2008","journal-title":"GPS Solut."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1017\/S0373463300001107","article-title":"Assessment of EGNOS tropospheric correction model","volume":"54","author":"Penna","year":"2001","journal-title":"J. Navig."},{"key":"ref_20","unstructured":"Krueger, E., Sch\u00fcler, T., Hein, G., Martellucci, A., and Blarzino, G. (2004, January 16\u201319). Galileo tropospheric correction approaches developed within GSTB-V1. Proceedings of the ENC-GNSS 2004, Rotterdam, The Netherlands."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"123","DOI":"10.1007\/s10291-013-0316-x","article-title":"The TropGrid2 standard tropospheric correction model","volume":"18","year":"2014","journal-title":"GPS Solut."},{"key":"ref_22","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":"Heinkelmann","year":"2007","journal-title":"J. Geod."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1069","DOI":"10.1002\/grl.50288","article-title":"GPT2: Empirical Slant Delay Modelfor Radio Space Geodetic Techniques","volume":"40","author":"Lagler","year":"2013","journal-title":"Geophys. Res. Lett."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"433","DOI":"10.1007\/s10291-014-0403-7","article-title":"Development of an improved blind model for slant delays in the troposphere (GPT2w)","volume":"19","author":"Schindelegger","year":"2015","journal-title":"GPS Solut."},{"key":"ref_25","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."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Ding, J., and Chen, J. (2020). Assessment of Empirical Troposphere Model GPT3 Based on NGL\u2019s Global Troposphere Products. Sensors, 20.","DOI":"10.3390\/s20133631"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"1926","DOI":"10.1029\/2019EA000701","article-title":"An ERA5-based model for estimating tropospheric delay and weighted mean temperature over China with improved spatiotemporal resolutions","volume":"6","author":"Sun","year":"2019","journal-title":"Earth Space Sci."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"461","DOI":"10.1016\/j.atmosres.2017.07.021","article-title":"Evaluation of radiosonde, MODIS-NIR-Clear, and AERONET precipitable water vapor using IGS ground-based GPS measurements over China","volume":"197","author":"Gui","year":"2017","journal-title":"Atmos Res."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"6823","DOI":"10.1175\/JCLI-D-16-0609.1","article-title":"The MERRA-2 Aerosol Reanalysis, 1980 Onward. Part I: System Description and Data Assimilation Evaluation","volume":"30","author":"Randles","year":"2017","journal-title":"J. Clim."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"5419","DOI":"10.1175\/JCLI-D-16-0758.1","article-title":"The Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2)","volume":"30","author":"Gelaro","year":"2017","journal-title":"J. Clim."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"1339","DOI":"10.5194\/gmd-8-1339-2015","article-title":"Development of the GEOS-5 atmospheric general circulation model: Evolution from MERRA to MERRA2","volume":"8","author":"Molod","year":"2015","journal-title":"Geosci. Model Dev."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"1046","DOI":"10.1175\/2008MWR2623.1","article-title":"Improving incremental balance in the GSI 3DVAR analysis system","volume":"137","author":"Kleist","year":"2009","journal-title":"Mon. Weather. Rev."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"2905","DOI":"10.1175\/1520-0493(2002)130<2905:TDVAWS>2.0.CO;2","article-title":"Three-dimensional variational analysis with spatially inhomogeneous covariances","volume":"130","author":"Wu","year":"2002","journal-title":"Mon. Weather. Rev."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"e2019EA000910","DOI":"10.1029\/2019EA000910","article-title":"Validation of surface temperature derived from MERRA-2 Reanalysis against IMD gridded data set over India","volume":"7","author":"Gupta","year":"2020","journal-title":"Earth Space Sci."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"e2020EA001516","DOI":"10.1029\/2020EA001516","article-title":"Evaluation of hourly PWV products derived from ERA5 and MERRA-2 over the Tibetan Plateau using ground-based GNSS observations by two enhanced models","volume":"8","author":"Huang","year":"2021","journal-title":"Earth Space Sci."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"159","DOI":"10.1007\/s00190-018-1148-9","article-title":"A new global grid model for the determination of atmospheric weighted mean temperature in GPS precipitable water vapor","volume":"93","author":"Huang","year":"2019","journal-title":"J. Geod."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"2340","DOI":"10.1007\/s11434-014-0275-9","article-title":"Analysis of the global T m-T s correlation and establishment of the latitude-related linear model","volume":"59","author":"Yao","year":"2014","journal-title":"Chin. Sci. Bull."},{"key":"ref_38","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_39","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. Meteorol."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"10273","DOI":"10.1038\/srep10273","article-title":"ITG: A New Global GNSS Tropospheric Correction Model","volume":"5","author":"Yao","year":"2015","journal-title":"Sci. Rep."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"379","DOI":"10.1029\/RS022i003p00379","article-title":"Estimation of tropospheric delay for microwaves from surface weather data","volume":"22","author":"Askne","year":"1987","journal-title":"Radio Sci."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"98","DOI":"10.1007\/s10291-021-01138-7","article-title":"A global grid model for the correction of the vertical zenith total delay based on a sliding window algorithm","volume":"25","author":"Huang","year":"2021","journal-title":"GPS Solut."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/17\/3546\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T06:57:29Z","timestamp":1760165849000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/17\/3546"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,9,6]]},"references-count":42,"journal-issue":{"issue":"17","published-online":{"date-parts":[[2021,9]]}},"alternative-id":["rs13173546"],"URL":"https:\/\/doi.org\/10.3390\/rs13173546","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2021,9,6]]}}}