From GNSS Zenith Tropospheric Delay to Precipitable Water Vapor: Accuracy Assessment Using In-Situ and Reanalysis Meteorological Data Over China
With the continuous development of Global Navigation Satellite System (GNSS) and the abundance of ground-based observation sites, the research and practice of GNSS water vapor retrieval are becoming increasingly prosperous. However, how to convert the zenith tropospheric delay obtained from GNSS dat...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
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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/11003404/ |
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| Summary: | With the continuous development of Global Navigation Satellite System (GNSS) and the abundance of ground-based observation sites, the research and practice of GNSS water vapor retrieval are becoming increasingly prosperous. However, how to convert the zenith tropospheric delay obtained from GNSS data processing into the precipitable water vapor (PWV) for stations without meteorological sensors is a key issue. In this study, five schemes using different meteorological data, including NOAA data, fifth-generation European Center for Medium-Range Weather Forecasts reanalysis (ERA5) pressure-level data, ERA5 single-level data, CRA40 pressure-level data, and CRA40 single-level data, were proposed to complete the above conversion. The numerical results give a comprehensive comparison between the performance of GNSS PWV conversion using colocated meteorological stations and reanalysis data. Moreover, the accuracy of PWV conversion using different types of reanalysis data has also been evaluated, especially the performance of CRA40 data, which has been assessed for the first time to the best of the authors’ knowledge. In addition, the analysis of the pressure level and the single level of the two reanalysis data used for PWV conversion is also conducted. Specifically, the average root-mean-square error were 1.745, 1.584, 1.535, 1.403, and 1.823 mm for the five schemes listed above, respectively. Their different performances in different geographical locations, seasons, months, and epochs have also been explored in detail. |
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| ISSN: | 1939-1404 2151-1535 |