the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 16 Jun 2025
Monitoring the Earth's deformation with the SPOTGINS series
Abstract. A distributed Global Navigation Satellite System analysis center, designated SPOTGINS, has been established by several research groups that utilize the GINS software and the CNES-CLS precise products. Despite the heterogeneity in their research objectives, the SPOTGINS members apply the same configuration and metadata. The computed global ambiguity-fixed precise point positioning time series are fully consistent among the members, and are subsequently published as a single product. This product facilitates a range of research activities, including but not limited to the precise monitoring of the Earth’s deformation and the water vapor content of the troposphere. A comparison of the SPOTGINS series with published series from the Nevada Geodetic Laboratory solution shows no significant difference in quality.
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RC1: 'Comment on essd-2025-223', Matt King, 08 Jul 2025
The authors present a new global GNSS dataset that provides time series of Earth deformation and tropospheric water vapour at locations globally. It is a novel (for GNSS) analysis approach in that it is a cooperative and dsitributed model of data analysis using consistent processing schema. The data products will be useful for many communities interested in Earth deformation studies and water vapour.
The methods employed are state of the art and generally fully described. Assessments of the coordinate time series against those from other solutions are provided, demonstrating a high level of consistency. No comparison is provided for the water vapour products. I could not see how to find the water vapour products on the website. So I suggest water vapour should be removed from the manuscript unless a fuller description is provided.
The data are provided on a web platform but not on a permanent data repository. It does not seem a requirement of ESSD to have the data somewhere permanent. That is ok, but it does raise the issue of versioning, and access to archived versions (I return to that below).
When I downloaded the data in .enu file format the data provide a header file but there does not seem to be any versioning of the datasets. This makes the data prone to erroneous analysis and comparison, and I strongly urge the authors to include versions for the their datasets and a changelog of kinds. The Headers do not include units,s and this should be resolved. The header columns are somewhat obvious to an expert but they are not described (e.g., jjjj.jjjjjjj is meant to refer to decimal Modified Julian Days it seems).
I found the comparison to the NGL solutions helpful, although I am concerned that the comparison to just one station time series is prone to cherry picking. Please include some statistics for a few hundred randomly chosen sites, globally distributed. The 410 IGS sites would be a sensible selection.
Otherwise, I have only a series of more minor comments, but I think most are essential nonetheless.
Abstract: The abstract should mention the temporal sampling of the data and the start date, the present end date of the time series and the number of stations considered at present.
L49 it is not clear if metadata is a part of the dataset described and made available. please clarify this.
L61: capitalise May.
L67: "based on stacked long-term post-fit residuals" is jargon, especially, 'stacked'. It would be useful to know how many stations were involved and how many days/years. or some other guidance. i was surprised that the values are fixed across all sites (but not satellites). it would be interesting to see s vs e plotted in supp material and if this is purely an empirical relationship or if there is a basis for it in physics.
L79 for the present release you should specify the antex file version.
L85 are the orbits in ITRF2020 or is this (as often in GIPSY) a fiducial free orbits and clocks and then a transformation later?
L89 it would be good to tighten up on what is exactly meant by ECMWF reanalysis - is this ERA5 or something else (and please add the reference)
L98 please clarify the origin of these OTL corrections (CM or CF) as consistent with the orbits and clocks (probably reference Fu and Freymueller in J Geodesy).
L101 I hope the full metadata is in the released dataset. please add that here.
Section 2: I did not see any mention on the temporal resolution of the coordinates or clock terms. Please clarify if this is part of a filter of sorts and provide the details on process noise if relevant (plus for tropo and gradients). Also, does the GINS metadata allow for non-north-pointing antennas?
L108 explain the likely wrong metadata more. I presume this is antenna model? NGL use the header so you should be able to be fairly certain. Also, why are the two solutions drifting relative to one another in E and U? please confirm the frame of the NGL solution which I think may be IGS14? The difference in clocks and orbits should also be mentioned.
Figure 4. the low-frequency signal in the scale probably deserves more of a mention, although I guess this pertains to orbits and clocks rather than the dataset being described here.
There are several footnotes in the document but I could not see them linked in the text.
Matt King, July 8 2025
Citation: https://doi.org/10.5194/essd-2025-223-RC1 -
RC2: 'Comment on essd-2025-223', Anna Klos, 15 Jul 2025
The article presents a new time series data set of GNSS permanent station position changes processed and provided under the SPOTGINS initiative. I believe this is a very useful dataset for the geodetic community, and one that researchers in this and other disciplines will certainly benefit from. Below are some comments and suggestions.
1. The dataset was developed consistent with geodetic standards.
2. I have no comments on the text of the publication itself, it is correct and written in a substantive manner.
3. The authors mention that in addition to the position time series, they will also make available the ZTD series. I would advise not to mention this until the ZTD time series are ready and available.
4. I suggest that the article includes more characteristics of the new dataset, such as their comparison with the NGL data, which is shown for one station. It would be good to make comparisons for more stations, not just in the sense of standard deviation. Explaining the similarities and differences, including spatial patterns, would greatly help users understand the quality of the dataset presented.Citation: https://doi.org/10.5194/essd-2025-223-RC2
Data sets
SPOTGINS GNSS position and tropospheric delay series Alvaro Santamaría-Gómez et al. https://doi.org/10.24400/170160/20250414
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