The ULR6a GPS solution is a preliminary version of the reanalysis of 19 years of GPS data from 1995 to 2014 that has been undertaken within the framework of the 2nd data reprocessing campaign of the International GNSS Service (IGS). Its associated vertical velocity field is expressed in ITRF2008.
Double-differenced ionosphere-free GPS carrier phase observations from a global network of 754 stations were reanalyzed using GAMIT/GLOBK software version 10.5. The data set covered the period January 1995 to December 2013. Station coordinates, satellite orbits, Earth orientation parameters (EOPs), and zenith tropospheric delay parameters every hour, were estimated. The data analysis strategy (models, corrections...) was compliant with the specifications adopted by the IGS for this reanalysis (more information here). Details can also be found in the IGS-like ULR analysis centre form associated with this solution.
The GPS velocities were obtained in the final step of the analysis which combined the daily GAMIT/GLOBK global network solutions (station coordinates with full co-variances) from the entire data time span into a long-term solution using CATREF software. This long-term solution (ULR6a) was aligned to ITRF2008 using minimal constraints over a selected set of IGS Reference Frame stations. A detailed description can be found in the reference below.
Analysis center: | ULR | Number of stations: | 674 |
Solution: | ULR6A | CGPS@TG | 482 |
Date of publication: | 2016 | Reference Frame | 194 |
Time span: | 1995.0 - 2013.9 | Others | 77 |
Reference Frame: | ITRF 2008 |
Estimated (robust) velocities: | 493 |
CGPS@TG | 349 |
Average of formal errors: | 0.54 mm/yr |
Median of formal errors: | 0.36 mm/yr |
To assign more realistic uncertainties on the GPS velocities, the noise content in the position time series was examined by the maximum likelihood estimation (MLE) technique using CATS software (Williams, 2008). Time series were detrended at the CATREF stage. Details on the GPS velocity uncertainty assessment are given in the reference below.
Vertical velocities table
The ULR6a_Vertical-Velocities_Table provides the vertical GPS velocities and uncertainties for the 497 stations fulfilling the criteria of 3 years of minimum length without discontinuities and with data gaps not exceeding 30%.
Daily residual time series
The ULR6_detrend.zip file contains individual station data files of daily residual position time series in ITRF2008 with respect to the linear long-term combined solution at the reference epoch. These residuals (detrended) are expressed in meters in the local frame (North, East, and Up). The reference position and the 3D velocity in the local coordinate system (East, North, Up) are provided in the header of each file.
Position discontinuities
The ULR6a_discontinuities_Table.txt file provides the position offsets that were estimated.
Solution file
The long-term solution ULR6a in SINEX format (567 Mo) can be downloaded too. However, we recommend its use only to those familiar with SINEX files, and having a good geodetic background and experience.
General information Access the data by clicking on the Download tab
Title: GPS Solution ULR6
DOI identifier: 10.26166/SONEL-GPS-ULR6
Publisher: SONEL Data Center
Publication year: 2016
Version: a
Temporal coverage: 1995-01-01 / 2014-12-31
Language: English
Creators
Alvaro Santamaria-Gomez [1], Médéric Gravelle [2], Guy Wöppelmann [2]
Affiliation: [1] GET, Observatoire Midi-Pyrénées/CNRS/IRD/UPS, Toulouse, France.
[2] LIENSs, CNRS/ULR, La Rochelle, France.
Keywords
GPS, tide gauge, vertical land movements
Contributors
LIENSs, La Rochelle, France
IGN, Saint Mandé, France
CNRS, France
La Rochelle Université, La Rochelle, France
Data use information
Citation: A. Santamaria-Gomez, M. Gravelle, G. Wöppelmann (2016): GPS Solution ULR6. SONEL Data Center. doi: 10.26166/SONEL-GPS-ULR6.
Use rights: The ULR6 solution is freely available to anyone. It is asked to all users to acknowledge the SONEL Data Centre in their research papers.
Description
The ULR6 solution has taken part to the second reprocessing campaign of the International GNSS Service (IGS). It corresponds to 749 stations for which the entire dataset between 1995.0 and 2013.9 was reprocessed using the most up-to-date models and corrections available at that time.
First, daily solutions are computed through the adjustment of positions of the global network of stations, Earth Orientation parameters, satellite orbits and zenith tropospheric delays. This process results in global daily solutions that are expressed in their own (daily) terrestrial frame.
Then, the daily times series are obtained after the combination of these daily solutions. The velocities are estimated simultaneously of the mean station position, station position offsets and transformation parameters (translation, rotation and scale) for the alignment to a unique terrestrial reference frame (ITRF0). A minimum of three continuous years without an offset (e.g., due to an equipment change or an earthquake) in the time series were required to estimate a “robust” vertical velocity, leading to a fields of 498 vertical velocities, among which 322 are nearby a tide gauge (<15 km).
The formal uncertainty of the estimated velocities has been computed taking into account the time-correlated noise in the residual time series to make them as realistic as possible. The median uncertainty on the estimated vertical velocities is about 0.36 mm/year.
Related identifiers
SONEL URL: http://www.sonel.org/
Acknowlegments
This solution has been proceeded thanks to the data provided by the Data Providers who collaborate with SONEL.
The ULR5 GPS solution is the result of a reanalysis of 16 years of GPS data from 1995 to 2010. Its vertical velocity field is published in Global and Planetary Change. It is expressed in ITRF2008.
Double-differenced ionosphere-free GPS carrier phase observations from a global network of 420 stations were reanalyzed using GAMIT/GLOBK software version 10.4. The data set covered the period January 1995 to December 2010 and 282 stations out of 420 were co-located with a tide gauge. Station coordinates, satellite orbits, Earth orientation parameters (EOPs), and zenith tropospheric delay parameters every hour, were estimated. Details on the GPS data processing strategy (models, corrections,...) can be found in the IGS-like ULR analysis centre form associated with this solution.
The GPS velocities were obtained in the final step of the analysis which combined the weekly GAMIT/GLOBK global network solutions (station coordinates with full co-variances) from the entire data time span into a long-term solution using CATREF software. This long-term solution (ULR5) was aligned to ITRF2008 using minimal constraints over a selected set of IGS Reference Frame stations. A detailed description can be found in the reference below.
Analysis center: | ULR | Number of stations: | 420 |
Solution: | ULR5 | CGPS@TG | 282 |
Date of publication: | 2012 | Reference Frame | 191 |
Time span: | 1994.0 - 2010.9 | Others | 6 |
Reference Frame: | ITRF 2008 |
Estimated (robust) velocities: | 326 |
CGPS@TG | 232 |
Average of formal errors: | 0.36 mm/yr |
Median of formal errors: | 0.28 mm/yr |
To assign more realistic uncertainties on the GPS velocities, the noise content in the position time series was examined by the maximum likelihood estimation (MLE) technique using CATS software. Time series were detrended and deseasoned (annual cycles) at the CATREF stage. Details on the GPS velocity uncertainty assessment will be given in the below-mentioned paper.
Vertical velocities table
The ULR5_Vertical-Velocities_Table provides the vertical GPS velocities and uncertainties for the 326 stations fulfilling the criterias of 3 years of minimum length without discontinuities and with data gaps not exceeding 30%.
Weekly residual time series
The ULR5_detrend.zip file contains individual station data files of weekly residual position time series in ITRF2008 with respect to the linear long-term combined solution at the reference epoch. These residuals (detrended and deseasoned) are expressed in meters in the local frame (North, East, and Up). The reference position and the 3D velocity in the local coordinate system (East, North, Up) are provided in the header of each file. The ulr5.kmz file shows a Google Earth presentation of the above weekly data files by cliking on a station symbol. The associated IGS-like sitelog can be accessed too, as well as a plot of the residual position time series in the vertical.
Position discontinuities
The ULR5_discontinuities_Table.txt file provides the position offsets that were estimated.
Solution file
The long-term solution ULR5 in SINEX format (250 Mo) can be downloaded too. However, we recommend its use only to those familiar with SINEX files, and having a good geodetic background and experience.
ULR5 on Google Earth
The ULR5_Vertical_Velocites.kmz file shows a Google Earth presentation of the ULR5 vertical velocities. For each GPS station a vertical cylinder whose height is proportionnal to the estimated velocity is drawn ( yellow for subsidence, red for uplift).
The ULR4 GPS solution is the result of a reanalysis of 13 years of GPS data from 1996 to 2008. Its vertical velocity field is published in Journal of Geophysical Research. It is expressed in ITRF2005.
Double-differenced ionosphere-free GPS carrier phase observations from a global network of 316 stations were reanalyzed using GAMIT/GLOBK software version 10.34. The data set covered the period January 1996 to December 2008 and 216 stations out of 316 were co-located with a tide gauge. Station coordinates, satellite orbits, Earth orientation parameters (EOPs), and zenith tropospheric delay parameters every 2 hours, were estimated. Details on the GPS data processing strategy (models, corrections,...) can be found in the IGS-like ULR analysis centre form associated with this solution.
The GPS velocities were obtained in the final step of the analysis which combined the weekly GAMIT/GLOBK global network solutions (station coordinates with full co-variances) from the entire data time span into a long-term solution using CATREF software. This long-term solution (ULR4) was aligned to ITRF2005 using minimal constraints over a selected set of IGS Reference Frame stations. A detailed description can be found in the reference below.
Under construction...
To assign more realistic uncertainties on the GPS velocities, the noise content in the position time series was examined by the maximum likelihood estimation (MLE) technique using CATS software. Time series were detrended and deseasoned (annual cycles) at the CATREF stage. Details on the GPS velocity uncertainty assessment will be given in the below-mentioned paper.
Vertical velocities table
The ulr4_vertical-velocities_table provides the vertical GPS velocities and uncertainties for the 275 stations fulfilling the criterias of 2.5 years of minimum length without discontinuities and with data gaps not exceeding 30%.
Weekly residual time series
The ulr4_detrend.zip file contains individual station data files of weekly residual position time series in ITRF2005 with respect to the linear long-term combined solution at the reference epoch. These residuals (detrended and deseasoned) are expressed in meters in the local frame (North, East, and Up). The reference position and the 3D velocity in the local coordinate system (East, North, Up) are provided in the header of each file. Theulr4.kmz file shows a Google Earth presentation of the above weekly data files by cliking on a station symbol. The associated IGS-like sitelog can be accessed too, as well as a plot of the residual position time series in the vertical.
Position discontinuities
The ulr4_discontinuities_table.txt file provides the position offsets that were estimated.
Solution file
The long-term solution ULR4 in SINEX format (47 Mo) can be downloaded too. However, we recommend its use only to those familiar with SINEX files, and having a good geodetic background and experience.
Santamaría-Gómez A., M. Gravelle, S. Dangendorf, M. Marcos, G. Spada, G. Wöppelmann (2017). Uncertainty of the 20th century sea-level rise due to vertical land motion errors. Earth and Planetary Science Letters, 473, 24-32.
The GNSS solution named ’NGL14’ is produced by the Nevada Geodetic Laboratory (NGL) using a Precise Point Positioning (PPP) data analysis strategy. The GipsyX software (version 1.0) from the Jet Propulsion Laboratory (JPL) is employed to produce daily position time series for over 17,000 globally distributed stations using JPL satellite orbits and clock products expressed in the IGS14 reference frame (Blewitt et al. 2018). The data set covers the period January 1996 to April 2019.
This GNSS data analysis strategy complies with the standards (models, corrections,...) of the International GNSS Service (IGS) reanalysis (reprocessing) campaigns ; hence the Sixteenth session of the Group of Experts for the Global Sea Level Observing System (GLOSS), held in Busan (Republic of Korea), 11-13 April 2019, tasked the SONEL data assembly centre to consider including the NGL solution (position time series and velocities) for the subset of GNSS stations nearby tide gauges. Among the more than 17,000 stations processed by NGL, as many as 1014 have actually been identified as co-located, or nearby, tide gauges.
The GNSS velocities, provided here for 904 stations (nearby tide gauges and reference frame stations included) with a minimum record length of 3 years and data gaps not exceeding 30%, are produced by NGL using the MIDAS estimator (Blewitt et al. 2016).
More details about the GNSS data analysis strategy can be found here or in Blewitt et al. (2016).
Estimated (robust) velocities: | 904 |
CGPS@TG | 812 |
Average of formal errors: | 0.88 mm/yr |
Median of formal errors: | 0.71 mm/yr |
Vertical velocities table
The NGL14_Vertical-Velocities_Table provides the vertical GPS velocities and uncertainties from the 904 stations fulfilling the criteria of 3 years of minimum length and data gaps not exceeding 30%, estimated by the NGL group using MIDAS (Blewitt et al. 2016).
Daily time series
The NGL14.zip file contains individual station data files of daily residual position time series in ITRF2014 with respect to the position at the mid time series epoch. These positions are expressed in meters in the local frame (North, East, and Up). The reference position and the 3D velocity (obtained using MIDAS) in the local coordinate system (East, North, Up) are provided in the header of each file.
Position discontinuities
The NGL14_discontinuities_Table.txt file provides the position offsets that can affect the station position and velocity estimates, as indicated by the NGL group. Note that MIDAS should be robust regarding the velocity estimates in presence of offsets, but not the parametric methods (e.g. least squares adjustment).
More information and data sets useful for other applications can be found at the Nevada Geodetic Laboratory website.
The GNSS solution named ’NGL08’ was produced by the Nevada Geodetic Laboratory (NGL) using a Precise Point Positioning (PPP) data analysis strategy. The GIPSY/OASIS-II software (version 6.1.1) from the Jet Propulsion Laboratory (JPL) was employed to produce daily position time series for over 17,000 globally distributed stations using JPL satellite orbits and clock products expressed in the IGS08 reference frame (Blewitt et al. 2018). The data set covers the period January 1996 to May 2018.
This GNSS data analysis strategy complies with the standards (models, corrections,...) of the International GNSS Service (IGS) reanalysis (reprocessing) campaigns ; hence the Sixteenth session of the Group of Experts for the Global Sea Level Observing System (GLOSS), held in Busan (Republic of Korea), 11-13 April 2019, tasked the SONEL data assembly centre to consider including the NGL solution (position time series and velocities) for the subset of GNSS stations nearby tide gauges. Among the more than 17,000 stations processed by NGL, as many as 989 were indeed identified as co-located, or nearby, tide gauges.
The GNSS velocities, provided here for 818 stations with a minimum record length of 3 years and data gaps not exceeding 30%, were produced by NGL using the MIDAS estimator (Blewitt et al. 2016).
More details about the GNSS data analysis strategy can be found here or in Blewitt et al. (2016).
Estimated (robust) velocities: | 818 |
CGPS@TG | 727 |
Average of formal errors: | 1.15 mm/yr |
Median of formal errors: | 0.92 mm/yr |
Vertical velocities table
The NGL08_Vertical-Velocities_Table provides the vertical GPS velocities and uncertainties from the 818 stations fulfilling the criteria of 3 years of minimum length and data gaps not exceeding 30%, estimated by the NGL group using MIDAS (Blewitt et al. 2016).
Daily time series
The NGL08.zip file contains individual station data files of daily residual position time series in ITRF2008 with respect to the position at the mid time series epoch. These positions are expressed in meters in the local frame (North, East, and Up). The reference position and the 3D velocity (obtained using MIDAS) in the local coordinate system (East, North, Up) are provided in the header of each file.
Position discontinuities
The NGL08_discontinuities_Table.txt file provides the position offsets that can affect the station position and velocity estimates, as indicated by the NGL group. Note that MIDAS should be robust regarding the velocity estimates in presence of offsets, but not the parametric methods (e.g. least squares adjustment).
More downloads and information can be found at the Nevada Geodetic Laboratory website.
For the time series:
Blewitt G., W. C. Hammond, C. Kreemer (2018). Harnessing the GPS data explosion for interdisciplinary science. Eos, 99, doi:10.1029/2018EO104623.
For the velocities:
Blewitt G., C. Kreemer, W.C. Hammond, J. Gazeaux (2016). MIDAS robust trend estimator for accurate GPS station velocities without step detection. Journal of Geophysical Research, 121, 2054-2068, doi:10.1002/2015JB012552.
The GNSS solution named ’JPL14’ is produced by the Jet Propulsion Laboratory (JPL) group using a Precise Point Positioning (PPP) data analysis strategy. JPL’s GipsyX software is employed to produce daily position time series for over 2,000 globally distributed stations using JPL satellite orbits and clock products expressed in the IGS14 reference frame. The data set covers the period January 1994 to December 2019.
This GNSS data analysis strategy complies with the standards (models, corrections,...) of the International GNSS Service (IGS) reanalysis (reprocessing) campaigns ; hence the Sixteenth session of the Group of Experts for the Global Sea Level Observing System (GLOSS), held in Busan (Republic of Korea), 11-13 April 2019, tasked the SONEL data assembly centre to consider including the JPL solution (position time series and velocities) for the subset of GNSS stations nearby tide gauges. Among the more than 2,000 stations processed by JPL, as many as 328 have actually been identified as co-located, or nearby, tide gauges.
The GNSS velocities, provided here for 367 stations (nearby tide gauges and reference frame stations included) with a minimum record length of 3 years and data gaps not exceeding 30%, are also produced by JPL.
More details about the GNSS data analysis strategy can be found here.
Estimated (robust) velocities: | 367 |
CGPS@TG | 276 |
Average of formal errors: | 0.62 mm/yr |
Median of formal errors: | 0.47 mm/yr |
Vertical velocities table
The JPL14_Vertical-Velocities_Table provides the vertical GPS velocities and uncertainties from the 422 stations fulfilling the criteria of 3 years of minimum length and data gaps not exceeding 30%, estimated by the JPL group.
Daily time series
The JPL14.zip file contains individual station data files of daily residual position time series in ITRF2014 with respect to the position at the epoche 2020-01-01. These positions are expressed in meters in the local frame (North, East, and Up). The reference position and the 3D velocity in the local coordinate system (East, North, Up) are provided in the header of each file.
Position discontinuities
The JPL14_discontinuities_Table.txt file provides the position offsets that have been estimated by the JPL group.
More information and data sets useful for other applications can be found at the JPL website.
Heflin, M., Moore, A., Murphy, D., Desai, S., Bertiger, W., Haines, B., Kuang, D., Sibthorpe, A., Sibois, A., Ries, P., Hemberger, D., Dietrich, A. (2019), Introduction to JPL’s GNSS Time Series.
In briefest terms, the approach consists in differencing the sea level time series from a tide gauge with an equivalent time series from satellite altimetry. To the extent that both instruments measure identical ocean signals, their difference is a proxy for the vertical position of the tide gauge. Assuming that the instrumental drifts are negligible, the time series of the sea level differences will then be dominated by vertical land motion at the tide gauge. This is illustrated in the figure on the right (click on the image to enlarge).
It is essential that the processing of both data types be as consistent as possible too. For instance, since an atmospheric correction is typically applied to satellite altimetry data, we applied the identical correction to the tide-gauge data. This correction is referred to as SLP (Sea Level Pressure) correction in the header of the t-files, but it comprises the static and dynamic effects of the atmosphere. The corrections were provided by AVISO under the name Dynamic Atmospheric Correction (DAC). However, the details of the atmospheric corrections and their accuracies are not relevant here, since common errors will cancel in the differentiation. It is the consistency of models and corrections applied to both datasets that must be ensured.
Tide gauge data:
All tide gauge data used in our calculations are from the Revised Local Reference (or ’RLR’) dataset of the PSMSL. We selected tide gauges with more than 15 years and a minimum of 70% of valid monthly mean sea levels over the satellite altimetry period, starting in 1993.0.
Satellite altimetry data:
We used time series of satellite altimetry mean sea level anomalies (SLA), i.e., sea surface heights with respect to an arbitrary temporal mean (it can be different from one provider to the other), whose primary raison d’être is to avoid large numerical values (decametric ellipsoidal heights with regard to the expected centimeter level changes in mean sea levels). Note that we considered satellite altimetry data from several data suppliers.
Here, we are dealing with the data set identified as Global MSLA heights in delayed time ("all sat merged") from the Archiving, Validation, and Interpretation of Satellite Oceanographic data (AVISO; http://www.aviso.altimetry.fr/en/data.html). The temporal sampling was homogenized to time series of monthly data.
Sea level differences:
Time series of sea level differences (SLD) between monthly tide gauge and satellite altimetry data were built using three variants of satellite SLA time series, namely the closest grid point, the most correlated grid point, and the average within a 1° radius from the tide gauge location. However, since the differences between these variants were negligible, we adopted the SLA averaged within a radius of 1° around the tide gauge location.
Once computed, the time series of sea level differences (SLD) were checked visually to discard those that displayed clear non linear behaviour, i.e., for which vertical land motion would not be adequately modelled by a linear trend. We then estimated the linear trend of the de-seasoned and de-trended SLD time series. All quoted uncertainties represent 1-sigma standard errors.
Future updates:
We plan to update the calculations of the sea level differences on a yearly basis, because as the time series lengthen and the satellite providers improve their products (new models, corrections, algorithms...), some level of improved precision is expected. However, there can be real differences between sea levels measured by a tide gauge at the coast and that measured off-shore by a satellite altimeter, due to the ocean processes which occur between the two points. This could be interesting to investigate and monitor. By contrast, for most open ocean locations, there is usually a high degree of correlation between variability in the two types of sea level. In this case, the vertical land motion can be estimated, provided the instrumental drifts are negligible. If there are (drifts), it enables tide gauge data to be used as a check on the satellite altimeter information and its stability and, conversely, it enables gross errors in tide gauge datum to be identified.
The web map enables the users to navigate from one site (station) to another, and click on a specific site in the map to see its attributes. By clicking further, an individual web page for the site can be accessed, where details on the data and meta-data are displayed for that site. The user can then get some additional statistics and download files with the associated time series (sea level differences...). Here, we provide a more comprehensive means to download the data from all the sites.
Table of linear trends of sea level differences
The vertical_velocities_ALTG_AVISO.txt provides the vertical velocities and uncertainties for the 478 stations for which we computed the monthly sea level differences (satellite altimetry minus tide gauge data) and derived a linear trend (see About).
Time series of monthly sea level differences
The useries_aviso.zip archive (.zip file) contains the 478 individual files of monthly sea level differences (satellite altimetry minus tide gauge data) time series. The format of the individual files is rather straightforward. The values are expressed in millimetres with respect to an arbitrary datum. The choice of the datum was arbitrary to avoid negative values (a constant of about 7000 mm was added to the differences).
G. Wöppelmannn & M. Marcos (2016) : Vertical land motion as a key to understanding sea level change and variability. Reviews of Geophysics, 54, pp. 64-92.
Work in progress...
Work in progress...