The ULR-repro3 GPS data reanalysis and its estimates of vertical land motion at tide gauges for sea level science
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essd-15-497-2023.pdf
Description
Published version
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5.39 MB
Format
Adobe PDF
Checksum (MD5)
b55c2b748447152d4506c874f4c2420c
Author(s)
Gravelle, Médéric
Wöppelmann, Guy
Gobron, Kevin
Altamimi, Zuheir
Guichard, Mikaël
Herring, Thomas
Rebischung, Paul
Date Issued
February 1, 2023
Journal
Earth System Science Data
Publisher
Copernicus GmbH
Citation
Gravelle, M., Wöppelmann, G., Gobron, K., Altamimi, Z., Guichard, M., Herring, T., and Rebischung, P.: The ULR-repro3 GPS data reanalysis and its estimates of vertical land motion at tide gauges for sea level science, Earth Syst. Sci. Data, 15, 497–509.
Version
Final published version
Abstract
A new reanalysis of Global Navigation Satellite System (GNSS) data at or near tide gauges worldwide was produced by the University of La Rochelle (ULR) group within the third International GNSS Service (IGS) reprocessing campaign (repro3). The new solution, called ULR-repro3, complies with the IGS standards adopted for repro3, implementing advances in data modelling and corrections since the previous reanalysis campaign and extending the average record length by about 7 years. The results presented here focus on the main products of interest for sea level science: the station position time series and associated velocities on the vertical component at tide gauges. These products are useful to estimate accurate vertical land motion at the coast and supplement data from satellite altimetry or tide gauges for an improved understanding of sea level changes and their impacts along coastal areas. To provide realistic velocity uncertainty estimates, the noise content in the position time series was investigated considering the impact of non-tidal atmospheric loading. Overall, the ULR-repro3 position time series show reduced white noise and power-law amplitudes and lower station velocity uncertainties compared with the previous reanalysis. The products are available via SONEL (https://doi.org/10.26166/sonel_ulr7a; Gravelle et al., 2022).
MIT Department
Massachusetts Institute of Technology. Department of Earth, Atmospheric, and Planetary Sciences
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DOI of Published Version
https://doi.org/10.5194/essd-15-497-2023
