A Novel Global Grid Model for Atmospheric Weighted Mean Temperature in Real-Time GNSS Precipitable Water Vapor Sounding
The atmospheric weighted mean temperature (Tm) is an important parameter in calculating the precipitable water vapor from Global Navigation Satellite System (GNSS) signals. As both GNSS positioning and GNSS precipitable water vapor detection require high spatial and temporal resolutions for calculat...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2023-01-01
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| Series: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10081197/ |
| _version_ | 1797849342320574464 |
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| author | Liangke Huang Zhedong Liu Hua Peng Si Xiong Ge Zhu Fade Chen Lilong Liu Hongchang He |
| author_facet | Liangke Huang Zhedong Liu Hua Peng Si Xiong Ge Zhu Fade Chen Lilong Liu Hongchang He |
| author_sort | Liangke Huang |
| collection | DOAJ |
| description | The atmospheric weighted mean temperature (Tm) is an important parameter in calculating the precipitable water vapor from Global Navigation Satellite System (GNSS) signals. As both GNSS positioning and GNSS precipitable water vapor detection require high spatial and temporal resolutions for calculating Tm, high-precision modeling of Tm has gained widespread attention in recent years. The previous models for calculating Tm have the limitation of too many model parameters or single-grid data. Therefore, this study presents a global high-precision Tm model (GGTm-H model) developed from the latest Modern-Era Retrospective Analysis for Research and Applications, version-2 (MERRA-2) atmospheric reanalysis data provided by the United States National Aeronautics and Space Administration. The accuracy of the GGTm-H model was verified by combining the MERRA-2 surface Tm data and 319 radiosonde data. The results highlighted that 1) When the MERRA-2 Tm data were used as a reference value, the mean annual RMSE of the GGTm-H model was observed to be 2.72 K. When compared with the Bevis model, GPT2w-5 model, and GPT2w-1 model, the GGTm-H model showed an improvement of 1.5, 0.33, and 0.21 K, respectively. 2) When the radiosonde data were used as a reference value, the mean bias and RMSE of the GGTm-H model were −0.41 K and 3.82 K, respectively. Compared with the other models, the GGTm-H model had the lowest mean annual bias and RMSE. The developed model does not consider any meteorological parameters while calculating Tm. Therefore, it has important applications in the real-time and high-precision monitoring of precipitable water vapor from GNSS signals. |
| first_indexed | 2024-04-09T18:43:26Z |
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| id | doaj.art-ee3ea5d3b170440e8d566dc01d321624 |
| institution | Directory Open Access Journal |
| issn | 2151-1535 |
| language | English |
| last_indexed | 2024-04-09T18:43:26Z |
| publishDate | 2023-01-01 |
| publisher | IEEE |
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| series | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
| spelling | doaj.art-ee3ea5d3b170440e8d566dc01d3216242023-04-10T23:00:29ZengIEEEIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing2151-15352023-01-01163322333510.1109/JSTARS.2023.326138110081197A Novel Global Grid Model for Atmospheric Weighted Mean Temperature in Real-Time GNSS Precipitable Water Vapor SoundingLiangke Huang0https://orcid.org/0000-0002-4241-3730Zhedong Liu1Hua Peng2Si Xiong3Ge Zhu4https://orcid.org/0000-0001-5215-3488Fade Chen5https://orcid.org/0009-0009-4246-179XLilong Liu6Hongchang He7College of Geomatics and Geoinformation, Guilin University of Technology, Guilin, ChinaCollege of Geomatics and Geoinformation, Guilin University of Technology, Guilin, ChinaCollege of Geomatics and Geoinformation, Guilin University of Technology, Guilin, ChinaHubei University of Science and Technology, Xianning, ChinaCollege of Geomatics and Geoinformation, Guilin University of Technology, Guilin, ChinaCollege of Geomatics and Geoinformation, Guilin University of Technology, Guilin, ChinaCollege of Geomatics and Geoinformation, Guilin University of Technology, Guilin, ChinaCollege of Geomatics and Geoinformation, Guilin University of Technology, Guilin, ChinaThe atmospheric weighted mean temperature (Tm) is an important parameter in calculating the precipitable water vapor from Global Navigation Satellite System (GNSS) signals. As both GNSS positioning and GNSS precipitable water vapor detection require high spatial and temporal resolutions for calculating Tm, high-precision modeling of Tm has gained widespread attention in recent years. The previous models for calculating Tm have the limitation of too many model parameters or single-grid data. Therefore, this study presents a global high-precision Tm model (GGTm-H model) developed from the latest Modern-Era Retrospective Analysis for Research and Applications, version-2 (MERRA-2) atmospheric reanalysis data provided by the United States National Aeronautics and Space Administration. The accuracy of the GGTm-H model was verified by combining the MERRA-2 surface Tm data and 319 radiosonde data. The results highlighted that 1) When the MERRA-2 Tm data were used as a reference value, the mean annual RMSE of the GGTm-H model was observed to be 2.72 K. When compared with the Bevis model, GPT2w-5 model, and GPT2w-1 model, the GGTm-H model showed an improvement of 1.5, 0.33, and 0.21 K, respectively. 2) When the radiosonde data were used as a reference value, the mean bias and RMSE of the GGTm-H model were −0.41 K and 3.82 K, respectively. Compared with the other models, the GGTm-H model had the lowest mean annual bias and RMSE. The developed model does not consider any meteorological parameters while calculating Tm. Therefore, it has important applications in the real-time and high-precision monitoring of precipitable water vapor from GNSS signals.https://ieeexplore.ieee.org/document/10081197/Atmospheric weighted mean temperature (Tm)Global Navigation Satellite System (GNSS)precipitable water vapor (PWV)Tm lapse rate |
| spellingShingle | Liangke Huang Zhedong Liu Hua Peng Si Xiong Ge Zhu Fade Chen Lilong Liu Hongchang He A Novel Global Grid Model for Atmospheric Weighted Mean Temperature in Real-Time GNSS Precipitable Water Vapor Sounding IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Atmospheric weighted mean temperature (Tm) Global Navigation Satellite System (GNSS) precipitable water vapor (PWV) Tm lapse rate |
| title | A Novel Global Grid Model for Atmospheric Weighted Mean Temperature in Real-Time GNSS Precipitable Water Vapor Sounding |
| title_full | A Novel Global Grid Model for Atmospheric Weighted Mean Temperature in Real-Time GNSS Precipitable Water Vapor Sounding |
| title_fullStr | A Novel Global Grid Model for Atmospheric Weighted Mean Temperature in Real-Time GNSS Precipitable Water Vapor Sounding |
| title_full_unstemmed | A Novel Global Grid Model for Atmospheric Weighted Mean Temperature in Real-Time GNSS Precipitable Water Vapor Sounding |
| title_short | A Novel Global Grid Model for Atmospheric Weighted Mean Temperature in Real-Time GNSS Precipitable Water Vapor Sounding |
| title_sort | novel global grid model for atmospheric weighted mean temperature in real time gnss precipitable water vapor sounding |
| topic | Atmospheric weighted mean temperature (Tm) Global Navigation Satellite System (GNSS) precipitable water vapor (PWV) Tm lapse rate |
| url | https://ieeexplore.ieee.org/document/10081197/ |
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