Tropospheric water vapor: A comprehensive high resolution data collection for the transnational Upper Rhine Graben region

Fersch, Benjamin; Wagner, Andreas; Kamm, Bettina; Shehaj, Endrit; Schenk, Andreas; Peng, Yingguo; Geiger, Alain; Möller, Gregor; Heck, Bernhard; Hinz, Stefan; Kunstmann, Harald

doi:10.5194/essd-2022-57

Cited by 3 publications

(4 citation statements)

References 1 publication

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“…The final product are high resolution IWV maps, which are generated through transformation of the ZWD using mean temperatures from ERA5 data. For details of this transformation, see (Fersch et al, 2021).…”

Section: Methodsmentioning

confidence: 99%

“…Those resulting double differential slant delays are corrected for any linear deformations. The data is available online (Fersch et al, 2021).…”

Section: Data and Preprocessingmentioning

confidence: 99%

“…Additionally 5 stations are chosen as validation stations for specific analysis. More on this separation of the stations can be read in (Fersch et al, 2021).…”

Section: Gnss Observations From the Gurn (Gnss Upper Rhinementioning

confidence: 99%

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Mathematical and Physical Approaches to Infer Absolute Zenith Wet Delays From Double Differential Interferometric Observations Using Era5 Atmospheric Reanalysis

Kamm

Schenk

Peng

et al. 2023

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. Atmospheric water vapor (WV) is one of the driving constituents of the atmosphere. The modelling and forecasting of WV and derived quantities like precipitable water is reliable on regional scales but challenging on small scales because of its high spatial and temporal variation. Interferometric synthetic aperture radar (InSAR) can be exploited to retrieve integrated atmospheric water vapor (IWV) from path delay observations along the radar line of sight. InSAR-derived IWV maps feature a very high spatial resolution but the double-differential interferometric observations only provide changes of IWV between acquisition times and with respect to a certain spatial reference. In this study we present a method to derive the absolute IWV by combining ERA5 numerical weather model data with differential path delay observations from InSAR time series. We propose different functional approaches to merge the regional trend of WV from ERA5 with the high resolution IWV signal from InSAR. We apply this to a Sentinel-1 Persistent Scatterer InSAR time series in the Upper Rhine Graben and validate against IWV observations at GNSS stations of the Upper Rhine Graben Network.

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Section: Methodsmentioning

confidence: 99%

“…Those resulting double differential slant delays are corrected for any linear deformations. The data is available online (Fersch et al, 2021).…”

Section: Data and Preprocessingmentioning

confidence: 99%

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Mathematical and Physical Approaches to Infer Absolute Zenith Wet Delays From Double Differential Interferometric Observations Using Era5 Atmospheric Reanalysis

Kamm

Schenk

Peng

et al. 2023

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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“…CC BY 4.0 License. 2021), and GURN (Yuan and Kutterer, 2021;Wagner et al, 2022;Fersch et al, 2022). Combining their solutions for an integrated analysis is possible but it could be impacted by systematic differences due to various software packages and strategies used in their GPS data processing as well as approaches adopted for the conversion of IWV.…”

Section: Introductionmentioning

confidence: 99%

An enhanced integrated water vapour dataset from more than 10,000 global ground-based GPS stations in 2020

Peng

Blewitt²,

Kreemer³

et al. 2022

Preprint

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Abstract. We developed a high-quality global Integrated Water Vapour (IWV) dataset from 12,552 ground-based Global Positioning System (GPS) stations in 2020. It consists of 5-min GPS IWV estimates with a total number of 1,093,591,492 datapoints. The completeness rates of the IWV estimates are higher than 95 % at 7253 (58 %) stations. The dataset is an enhanced version of the existing operational GPS IWV dataset provided by Nevada Geodetic Laboratory (NGL). The enhancement is reached by employing accurate meteorological information from the fifth generation of European ReAnalysis (ERA5) for the GPS IWV retrieval with a significantly higher spatiotemporal resolution. A dedicated data screening algorithm is also implemented. The GPS IWV dataset has a good agreement with in-situ radiosonde observations at 182 collocated stations worldwide. The IWV biases are within ±3.0 kg m-2 with a Mean Absolute Bias (MAB) value of 0.69 kg m-2. The standard deviations (SD) of IWV differences are no larger than 3.4 kg m-2. In addition, the enhanced IWV product shows substantial improvements compared to NGL’s operational version, and it is thus recommended for high-accuracy applications, such as research of extreme weather events and diurnal variations of IWV, and intercomparisons with other IWV retrieval techniques. Taking the radiosonde-derived IWV as reference, the MAB and SD of IWV differences are reduced by 19.5 % and 6.2 % on average, respectively. The number of unrealistic negative GPS IWV estimates are also substantially reduced by 92.4 % owing to the accurate Zenith Hydrostatic Delay (ZHD) derived by ERA5. The dataset is available at: https://doi.org/10.5281/zenodo.6973528 (Yuan et al., 2022).

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Tropospheric water vapor: a comprehensive high-resolution data collection for the transnational Upper Rhine Graben region

Fersch

Wagner

Kamm

et al. 2022

Earth Syst. Sci. Data

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Abstract. Tropospheric water vapor is one of the most important trace gases of the Earth's climate system, and its temporal and spatial distribution is critical for the genesis of clouds and precipitation. Due to the pronounced dynamics of the atmosphere and the nonlinear relation of air temperature and saturated vapor pressure, it is highly variable, which hampers the development of high-resolution and three-dimensional maps of regional extent. With their complementary high temporal and spatial resolutions, Global Navigation Satellite Systems (GNSS) meteorology and Interferometric Synthetic Aperture Radar (InSAR) satellite remote sensing represent a significant alternative to generally sparsely distributed radio sounding observations. In addition, data fusion with collocation and tomographical methods enables the construction of detailed maps in either two or three dimensions. Finally, by assimilation of these observation-derived datasets with dynamical regional atmospheric models, tropospheric water vapor fields can be determined with high spatial and continuous temporal resolution. In the following, a collection of basic and processed datasets, obtained with the above-listed methods, is presented that describes the state and course of atmospheric water vapor for the extent of the GNSS Upper Rhine Graben Network (GURN) region. The dataset contains hourly 2D fields of integrated water vapor (IWV) and 3D fields of water vapor density (WVD) for four multi-week, variable season periods between April 2016 and October 2018 at a spatial resolution of (2.1 km)2. Zenith total delay (ZTD) from GNSS and collocation and refractivities are provided as intermediate products. InSAR (Sentinel-1A/B)-derived double differential slant total delay phases (ddSTDPs) and GNSS-based ZTDs are available for March 2015 to July 2019. The validation of data assimilation with five independent GNSS stations for IWV shows improving Kling–Gupta efficiency (KGE) scores for all seasons, most notably for summer, with collocation data assimilation (KGE = 0.92) versus the open-cycle simulation (KGE = 0.69). The full dataset can be obtained from https://doi.org/10.1594/PANGAEA.936447 (Fersch et al., 2021).

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Tropospheric water vapor: A comprehensive high resolution data collection for the transnational Upper Rhine Graben region

Cited by 3 publications

References 1 publication

Mathematical and Physical Approaches to Infer Absolute Zenith Wet Delays From Double Differential Interferometric Observations Using Era5 Atmospheric Reanalysis

Mathematical and Physical Approaches to Infer Absolute Zenith Wet Delays From Double Differential Interferometric Observations Using Era5 Atmospheric Reanalysis

An enhanced integrated water vapour dataset from more than 10,000 global ground-based GPS stations in 2020

Tropospheric water vapor: a comprehensive high-resolution data collection for the transnational Upper Rhine Graben region

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