Development of a New Vertical Water Vapor Model for GNSS Water Vapor Tomography
One of the main challenges of Global Navigation Satellite System (GNSS) tomography is in solving ill-conditioned system equations. Vertical constraint models are typically used in the solution procedure and play an important role in the quality of the GNSS tomography, in addition to helping resolve...
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MDPI AG
2022-11-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/14/22/5656 |
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| author | Moufeng Wan Kefei Zhang Suqin Wu Peng Sun Longjiang Li |
| author_facet | Moufeng Wan Kefei Zhang Suqin Wu Peng Sun Longjiang Li |
| author_sort | Moufeng Wan |
| collection | DOAJ |
| description | One of the main challenges of Global Navigation Satellite System (GNSS) tomography is in solving ill-conditioned system equations. Vertical constraint models are typically used in the solution procedure and play an important role in the quality of the GNSS tomography, in addition to helping resolve ill-posed problems in system equations. In this study, based on a water vapor (WV) parameter, namely IRPWV, a new vertical constraint model with six sets of coefficients for six different WV states was developed and tested throughout 2019 in the Hong Kong region with four tomographic schemes, which were carried out with the model and the traditional vertical constraint model using three different types of water vapor scale height parameters. Experimental results were numerically compared against their corresponding radiosonde-derived WV values. Compared with the tests that used the traditional model, our results showed that, first, for the daily relative error of WV density (WVD) less than 30%, the new model can lead to at least 10% and 49% improvement on average at the lower layers (below 3 km, except for the ground surface) and the upper layers (about 5–10 km), respectively. Second, the skill score of the monthly root-mean-square error (RMSE) of layered WVD above 10 accounted for about 83%, 87%, and 64%. Third, for the annual biases of layered WVD, the new model significantly decreased by 1.1–1.5 g/m<sup>3</sup> at layers 2–3 (about 1 km), where all schemes showed the maximal bias value. Finally, for the annual RMSE of layered WVD, the new model at the lower (about 0.6–3 km) and upper layers improved by 13–42% and 5–47%, respectively. Overall, the new model performed better on GNSS tomography and significantly improved the accuracy of GNSS tomographic results, compared to the traditional model. |
| first_indexed | 2024-03-09T18:01:47Z |
| format | Article |
| id | doaj.art-2f0c6feef6e14cadbfdaed5e6d3f8e81 |
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| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-09T18:01:47Z |
| publishDate | 2022-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-2f0c6feef6e14cadbfdaed5e6d3f8e812023-11-24T09:48:25ZengMDPI AGRemote Sensing2072-42922022-11-011422565610.3390/rs14225656Development of a New Vertical Water Vapor Model for GNSS Water Vapor TomographyMoufeng Wan0Kefei Zhang1Suqin Wu2Peng Sun3Longjiang Li4Jiangsu Key Laboratory of Resources and Environmental Information Engineering, China University of Mining and Technology, Xuzhou 221116, ChinaJiangsu Key Laboratory of Resources and Environmental Information Engineering, China University of Mining and Technology, Xuzhou 221116, ChinaJiangsu Key Laboratory of Resources and Environmental Information Engineering, China University of Mining and Technology, Xuzhou 221116, ChinaJiangsu Key Laboratory of Resources and Environmental Information Engineering, China University of Mining and Technology, Xuzhou 221116, ChinaJiangsu Key Laboratory of Resources and Environmental Information Engineering, China University of Mining and Technology, Xuzhou 221116, ChinaOne of the main challenges of Global Navigation Satellite System (GNSS) tomography is in solving ill-conditioned system equations. Vertical constraint models are typically used in the solution procedure and play an important role in the quality of the GNSS tomography, in addition to helping resolve ill-posed problems in system equations. In this study, based on a water vapor (WV) parameter, namely IRPWV, a new vertical constraint model with six sets of coefficients for six different WV states was developed and tested throughout 2019 in the Hong Kong region with four tomographic schemes, which were carried out with the model and the traditional vertical constraint model using three different types of water vapor scale height parameters. Experimental results were numerically compared against their corresponding radiosonde-derived WV values. Compared with the tests that used the traditional model, our results showed that, first, for the daily relative error of WV density (WVD) less than 30%, the new model can lead to at least 10% and 49% improvement on average at the lower layers (below 3 km, except for the ground surface) and the upper layers (about 5–10 km), respectively. Second, the skill score of the monthly root-mean-square error (RMSE) of layered WVD above 10 accounted for about 83%, 87%, and 64%. Third, for the annual biases of layered WVD, the new model significantly decreased by 1.1–1.5 g/m<sup>3</sup> at layers 2–3 (about 1 km), where all schemes showed the maximal bias value. Finally, for the annual RMSE of layered WVD, the new model at the lower (about 0.6–3 km) and upper layers improved by 13–42% and 5–47%, respectively. Overall, the new model performed better on GNSS tomography and significantly improved the accuracy of GNSS tomographic results, compared to the traditional model.https://www.mdpi.com/2072-4292/14/22/5656GNSS tomographyvertical constraintwater vapor spatio-temporal model |
| spellingShingle | Moufeng Wan Kefei Zhang Suqin Wu Peng Sun Longjiang Li Development of a New Vertical Water Vapor Model for GNSS Water Vapor Tomography Remote Sensing GNSS tomography vertical constraint water vapor spatio-temporal model |
| title | Development of a New Vertical Water Vapor Model for GNSS Water Vapor Tomography |
| title_full | Development of a New Vertical Water Vapor Model for GNSS Water Vapor Tomography |
| title_fullStr | Development of a New Vertical Water Vapor Model for GNSS Water Vapor Tomography |
| title_full_unstemmed | Development of a New Vertical Water Vapor Model for GNSS Water Vapor Tomography |
| title_short | Development of a New Vertical Water Vapor Model for GNSS Water Vapor Tomography |
| title_sort | development of a new vertical water vapor model for gnss water vapor tomography |
| topic | GNSS tomography vertical constraint water vapor spatio-temporal model |
| url | https://www.mdpi.com/2072-4292/14/22/5656 |
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