Distributed double differential slant delays and IWV from PSI analysis of Sentinel-1 data
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| Format: | Dataset Open Access |
| Sprache: | en |
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PANGAEA
2021
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| _version_ | 1867170399753601024 |
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| author | Kamm, Bettina Yuan, Peng Schenk, Andreas Hinz, Stefan |
| author_facet | Kamm, Bettina Yuan, Peng Schenk, Andreas Hinz, Stefan |
| collection | Datos científicos de ciencias marinas y ambientales |
| contents | The provided dataset consists of double differential slant delays and absolute zenith wet delays in the region of the Upper Rhine Graben. Basis is the SLC data from Sentinel 1A+B satellites provided by the Copernicus program. 169 scenes were processed which had been acquired between April 2015 and July 2019, including data of four specific study events (11 – 22 Apr 2016, 13 – 24 Jul 2018, 16 – 31 Oct 2018, 06 – 21 Jan 2017). Interferometric processing was performed using the software SNAP, continued by a Persistent Scatterer Interferometric SAR (PS-InSAR) processing, using the program StaMPS. The first product are double differential slant delays which represent the phase delay in radiant in the satellites line of sight between the master acquisition (17 Mar 2012) and each acquisition-date respectively. Further processing uses ERA5 zenith wet delay (ZWD) and mean temperature to infer absolute zenith wet delays. A mean value is subtracted for each scene, resulting in an absolute value correction. In addition, long wavelength components are corrected by fitting the trend over the scene for each date to a 2D polynomial approximation from the ERA5 data, as those parts cannot reliably be estimated solely from the SAR data. The final product for every scene is the integrated water vapor (IWV) in kg/m² for each acquisition date at the distributed PS-points – on average about 50 points per square kilometer. |
| format | Dataset Open Access |
| id | pangaea_https___doi_org_10_1594_PANGAEA_936444 |
| institution | PANGAEA |
| language | en |
| publishDate | 2021 |
| publisher | PANGAEA |
| record_format | pangaea |
| spellingShingle | Distributed double differential slant delays and IWV from PSI analysis of Sentinel-1 data Kamm, Bettina Yuan, Peng Schenk, Andreas Hinz, Stefan Atmosphere; AtmoWater; Binary Object; Data Assimilation; File content; GNSS; GURN; High-Resolution Atmospheric Water Vapor Fields by Spaceborne Geodetic Sensing, Tomographic Fusion, and Atmospheric Modeling; InSAR; integrated water vapor; moisture; MULT; Multiple investigations; Upper_Rhine_Graben; WRF The provided dataset consists of double differential slant delays and absolute zenith wet delays in the region of the Upper Rhine Graben. Basis is the SLC data from Sentinel 1A+B satellites provided by the Copernicus program. 169 scenes were processed which had been acquired between April 2015 and July 2019, including data of four specific study events (11 – 22 Apr 2016, 13 – 24 Jul 2018, 16 – 31 Oct 2018, 06 – 21 Jan 2017). Interferometric processing was performed using the software SNAP, continued by a Persistent Scatterer Interferometric SAR (PS-InSAR) processing, using the program StaMPS. The first product are double differential slant delays which represent the phase delay in radiant in the satellites line of sight between the master acquisition (17 Mar 2012) and each acquisition-date respectively. Further processing uses ERA5 zenith wet delay (ZWD) and mean temperature to infer absolute zenith wet delays. A mean value is subtracted for each scene, resulting in an absolute value correction. In addition, long wavelength components are corrected by fitting the trend over the scene for each date to a 2D polynomial approximation from the ERA5 data, as those parts cannot reliably be estimated solely from the SAR data. The final product for every scene is the integrated water vapor (IWV) in kg/m² for each acquisition date at the distributed PS-points – on average about 50 points per square kilometer. |
| title | Distributed double differential slant delays and IWV from PSI analysis of Sentinel-1 data |
| topic | Atmosphere; AtmoWater; Binary Object; Data Assimilation; File content; GNSS; GURN; High-Resolution Atmospheric Water Vapor Fields by Spaceborne Geodetic Sensing, Tomographic Fusion, and Atmospheric Modeling; InSAR; integrated water vapor; moisture; MULT; Multiple investigations; Upper_Rhine_Graben; WRF |
| url | https://doi.org/10.1594/PANGAEA.936444 |