Articles | Volume 9, issue 9
https://doi.org/10.5194/amt-9-4487-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/amt-9-4487-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
12 Sep 2016
Research article |
| 12 Sep 2016
High-spatial-resolution mapping of precipitable water vapour using SAR interferograms, GPS observations and ERA-Interim reanalysis
State Key Laboratory of Information Engineering in
Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan,
China
Mingsheng Liao
State Key Laboratory of Information Engineering in
Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan,
China
Collaborative Innovation Center for Geospatial Technology,
Wuhan University, Wuhan, China
Lu Zhang
CORRESPONDING AUTHOR
State Key Laboratory of Information Engineering in
Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan,
China
Wei Li
Shanghai Academy of Spaceflight Technology, Shanghai,
China
Weimin Yu
Shanghai Institute of Satellite Engineering, Shanghai,
China
Viewed
Total article views: 3,820 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 27 Jan 2016)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 2,103 | 1,594 | 123 | 3,820 | 144 | 178 |
- HTML: 2,103
- PDF: 1,594
- XML: 123
- Total: 3,820
- BibTeX: 144
- EndNote: 178
Total article views: 3,124 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 12 Sep 2016)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 1,716 | 1,299 | 109 | 3,124 | 138 | 170 |
- HTML: 1,716
- PDF: 1,299
- XML: 109
- Total: 3,124
- BibTeX: 138
- EndNote: 170
Total article views: 696 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 27 Jan 2016)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 387 | 295 | 14 | 696 | 6 | 8 |
- HTML: 387
- PDF: 295
- XML: 14
- Total: 696
- BibTeX: 6
- EndNote: 8
Cited
12 citations as recorded by crossref.
- A New Weighting Method by Considering the Physical Characteristics of Atmospheric Turbulence and Decorrelation Noise in SBAS-InSAR M. Duan et al. https://doi.org/10.3390/rs12162557
- Retrieval of high-precision precipitable water vapour maps using Sentinel-1A and Beidou satellite data Q. Guo et al. https://doi.org/10.1080/01431161.2023.2282403
- Estimating atmospheric precipitable water vapor in northern Morocco: A ground-based GNSS approach R. Drissi El Bouzaidi et al. https://doi.org/10.1016/j.sciaf.2025.e02681
- Construction of a Continuous High-Resolution PWV Using GNSS/ERA5, InSAR, and FY-4A Data: A Case Study of the Jiaodong Peninsula and Adjacent Seas Q. Guo et al. https://doi.org/10.3390/app16115391
- Spatial and temporal changes of precipitable water vapour in Thailand S. Buntoung et al. https://doi.org/10.1080/02723646.2019.1710433
- Mapping Precipitable Water Vapor Time Series From Sentinel-1 Interferometric SAR P. Mateus et al. https://doi.org/10.1109/TGRS.2019.2946077
- Excess Path Delays From Sentinel Interferometry to Improve Weather Forecasts N. Pierdicca et al. https://doi.org/10.1109/JSTARS.2020.2988724
- Error Evaluation of L-Band InSAR Precipitable Water Vapor Measurements by Comparison with GNSS Observations in Japan K. Matsuzawa & Y. Kinoshita https://doi.org/10.3390/rs13234866
- A novel GNSS–InSAR Zenith Wet Delay Model for High-Resolution PWV Mapping in the Indian Himalayan Region S. Saxena et al. https://doi.org/10.1016/j.asr.2026.08.025
- Non-differential water vapor estimation from SBAS-InSAR M. Duan et al. https://doi.org/10.1016/j.jastp.2020.105284
- Evaluating Tropospheric Mapping Functions for GPS-Derived PWV in a Tropical Region: Insights from Southwestern Mexico L. Santiago-Sánchez et al. https://doi.org/10.3390/geomatics6040084
- An Optimized Framework for Precipitable Water Vapor Mapping Using TS-InSAR and GNSS Q. Guo et al. https://doi.org/10.3390/atmos14111674
12 citations as recorded by crossref.
- A New Weighting Method by Considering the Physical Characteristics of Atmospheric Turbulence and Decorrelation Noise in SBAS-InSAR M. Duan et al. https://doi.org/10.3390/rs12162557
- Retrieval of high-precision precipitable water vapour maps using Sentinel-1A and Beidou satellite data Q. Guo et al. https://doi.org/10.1080/01431161.2023.2282403
- Estimating atmospheric precipitable water vapor in northern Morocco: A ground-based GNSS approach R. Drissi El Bouzaidi et al. https://doi.org/10.1016/j.sciaf.2025.e02681
- Construction of a Continuous High-Resolution PWV Using GNSS/ERA5, InSAR, and FY-4A Data: A Case Study of the Jiaodong Peninsula and Adjacent Seas Q. Guo et al. https://doi.org/10.3390/app16115391
- Spatial and temporal changes of precipitable water vapour in Thailand S. Buntoung et al. https://doi.org/10.1080/02723646.2019.1710433
- Mapping Precipitable Water Vapor Time Series From Sentinel-1 Interferometric SAR P. Mateus et al. https://doi.org/10.1109/TGRS.2019.2946077
- Excess Path Delays From Sentinel Interferometry to Improve Weather Forecasts N. Pierdicca et al. https://doi.org/10.1109/JSTARS.2020.2988724
- Error Evaluation of L-Band InSAR Precipitable Water Vapor Measurements by Comparison with GNSS Observations in Japan K. Matsuzawa & Y. Kinoshita https://doi.org/10.3390/rs13234866
- A novel GNSS–InSAR Zenith Wet Delay Model for High-Resolution PWV Mapping in the Indian Himalayan Region S. Saxena et al. https://doi.org/10.1016/j.asr.2026.08.025
- Non-differential water vapor estimation from SBAS-InSAR M. Duan et al. https://doi.org/10.1016/j.jastp.2020.105284
- Evaluating Tropospheric Mapping Functions for GPS-Derived PWV in a Tropical Region: Insights from Southwestern Mexico L. Santiago-Sánchez et al. https://doi.org/10.3390/geomatics6040084
- An Optimized Framework for Precipitable Water Vapor Mapping Using TS-InSAR and GNSS Q. Guo et al. https://doi.org/10.3390/atmos14111674
Saved (final revised paper)
Latest update: 24 Aug 2026
Short summary
Interferometric radar meteorology (IRM) is a new technique for meteorological
applications and atmospheric studies. It can be used to study the water vapour content in the atmosphere with a spatial resolution of 20 m and an accuracy of about 2 mm. This high spatial resolution of water vapour distribution can be important for short-scale weather forecasting and climate research.
Interferometric radar meteorology (IRM) is a new technique for meteorological
applications and...
