Articles | Volume 32, issue 8
https://doi.org/10.5194/angeo-32-911-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/angeo-32-911-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Regular paper
| 
06 Aug 2014
Regular paper |
| 06 Aug 2014
Near real-time water vapor tomography using ground-based GPS and meteorological data: long-term experiment in Hong Kong
P. Jiang
GNSS Research Center, Wuhan University, Wuhan, 430079, China
S. R. Ye
GNSS Research Center, Wuhan University, Wuhan, 430079, China
Y. Y. Liu
GNSS Research Center, Wuhan University, Wuhan, 430079, China
J. J. Zhang
CMA, Institute of Urban Meteorology, Beijing, 100089, China
P. F. Xia
GNSS Research Center, Wuhan University, Wuhan, 430079, China
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Cited
34 citations as recorded by crossref.
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- Construction of a meteorological application system based on BDS ground-based augmentation network and water vapor products validation M. Du et al. https://doi.org/10.1007/s10291-024-01612-y
- Monitoring urban heat island intensity based on GNSS tomography technique P. Xia et al. https://doi.org/10.1007/s00190-023-01804-3
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- Weighted Mean Temperature Modelling Using Regional Radiosonde Observations for the Yangtze River Delta Region in China L. Li et al. https://doi.org/10.3390/rs14081909
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- Troposphere Water Vapour Tomography: A Horizontal Parameterised Approach Q. Zhao et al. https://doi.org/10.3390/rs10081241
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- An Investigation of Near Real-Time Water Vapor Tomography Modeling Using Multi-Source Data L. Tong et al. https://doi.org/10.3390/atmos13050752
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- A troposphere tomography method considering the weighting of input information Q. Zhao et al. https://doi.org/10.5194/angeo-35-1327-2017
- A method for predicting short‐time changes in fine particulate matter (PM2.5) mass concentration based on the global navigation satellite system zenith tropospheric delay M. Guo et al. https://doi.org/10.1002/met.1866
- A Method to Improve the Distribution of Observations in GNSS Water Vapor Tomography F. Yang et al. https://doi.org/10.3390/s18082526
- Maximally Using GPS Observation for Water Vapor Tomography Y. Yao & Q. Zhao https://doi.org/10.1109/TGRS.2016.2597241
- Analysis of GNSS-Derived Tropospheric Zenith Non-Hydrostatic Delay Anomaly during Sandstorms in Northern China on 15th March 2021 M. Zhou et al. https://doi.org/10.3390/rs14184678
- Optimization of GPS water vapor tomography technique with radiosonde and COSMIC historical data S. Ye et al. https://doi.org/10.5194/angeo-34-789-2016
- Developing a novel model to estimate zenith hydrostatic delay using surface meteorological data for GNSS-PWV retrieval Q. Zhang et al. https://doi.org/10.1016/j.asr.2026.03.057
- New parameterized model for GPS water vapor tomography N. Ding et al. https://doi.org/10.5194/angeo-35-311-2017
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- Enhanced ground-based GNSS tomography for accurate water vapor retrieval X. Pengfei et al. https://doi.org/10.1016/j.jastp.2025.106709
- Adaptive Voxel-Division Method of GNSS Water Vapor Tomography and Its Application in Data Assimilation Y. Ma et al. https://doi.org/10.1109/JSTARS.2025.3580555
- Establishing a high-precision real-time ZTD model of China with GPS and ERA5 historical data and its application in PPP P. Xia et al. https://doi.org/10.1007/s10291-022-01338-9
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- An Adaptive Non-Uniform Vertical Stratification Method for Troposphere Water Vapor Tomography H. Wang et al. https://doi.org/10.3390/rs13193818
- Spatiotemporal Analysis of GNSS-Derived Water Vapor Variations and Moisture Convergence Mechanism During Extreme Rainfall Events: A Hong Kong Case Study H. Qiu et al. https://doi.org/10.1109/JSTARS.2025.3605166
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