the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 15 Jan 2026
GRACE and GRACE-FO Mascons for Ocean Dynamic Applications
Abstract. A new series of mascons are made from GRACE and GRACE-FO data, specifically designed for use by oceanographers interested in studying variations in ocean mass transport and circulation. This series has pre-removed those changes in ocean mass distribution caused by barystatic gravity, rotation, and deformation (GRD) signals, as well as the non-oceanographic signals caused by four major oceanic earthquakes, neither of which impact circulation. Subtle changes in the processing and regularization schemes also help reduce the visibility of instrument/orbital errors in the ocean signal, particularly in the arctic and near the sites of the removed earthquakes. The primary benefit of this data set is increased ease of use for researchers interested in ocean dynamics, as the product is designed to be used "off the shelf" with no additional corrections required, even by those less familiar with GRACE data usage. The complete dataset is available at https://doi.org/10.18738/T8/3VUPEW (Pie et al., 2025).
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Status: open (until 13 Mar 2026)
- RC1: 'Comment on essd-2025-718', Anonymous Referee #1, 26 Feb 2026 reply
Data sets
CSR GRACE & GRACE-FO Dynamic Ocean Mascons RL06.2DO Nadège Pie et al. https://doi.org/10.18738/T8/3VUPEW
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- 1
The paper describes a new ocean bottom pressure product based on GRACE/FO data, which includes corrections for four major earthquakes and for gravitation, rotation and deformation (GRD) effects related to land water and ice changes. These so-called dynamic ocean mascons (DOM) include additional changes in data processing that lead to better representation of ocean bottom pressure signals around Franz Josef Land. The new dataset is timely and fills a major need when using GRACE/FO data products for studies of ocean dynamics. The methodology is well developed and clearly described in section 2. The statistical evaluation of the DOM product is basically fine but a couple of improvements to the dataset would seem essential, as elaborated below.
I find the lack of treatment of GRD effects from atmospheric mass changes over land a major shortcoming of this dataset. It is unclear why these effects are not included. They are clearly important around Eurasia and Antarctica at the annual time scale, judging from previous works including the cited paper by Tamisiea et al. (2010). Just because they are not provided in other GRD calculations, as stated in lines 363-364, is not a good justification for leaving those potentially important effects out of this dataset. Quite the contrary! An implementation of such a correction could use surface atmospheric fields from the AOD model or some other atmospheric reanalysis product of choice. I strongly recommend that the authors update their dataset with this extra correction.
Another important issue is the characterization of uncertainty for the newly applied corrections or in some sense the remaining GRD and earthquake signals after correction. In this regard, a number of other similar products, dealing with these corrections, have been recently made available (e.g., Landerer and Wiese, https://doi.org/10.5067/HMOGD-4JM01; Dahle et al. 2025, https://doi.org/10.5194/essd-17-611-2025). Discussion of the new dataset in the context of other similar products would be very useful. Moreover, comparisons with these other corrections, particularly for the case of GRD, could provide a measure of uncertainty. The only quantitative discussion of uncertainty refers to the DOM fields and is based on crude comparisons with ECCO (lines 437-441). Any measure of uncertainty for the corrections provided would be useful when applying the DOM fields to ocean circulation and data assimilation studies.
A final concern is the DOM evaluations performed using comparisons with ECCOv4r4. First, such comparisons need to acknowledge that the ECCOv4r4 solution is itself constrained by GRACE data (in that case JPL mascons). Thus, interpreting similarities between GRACE and ECCOv4r4 as a sign of the quality of DOM derived in the paper (e.g., lines 425-429) is at best ambiguous. Second, perhaps more important is to show quantitatively whether DOM estimates are more or less consistent with the ECCO fields than the regular (uncorrected) mascons. Similar attempts are reported by Ponte et al. (2024, https://doi.org/10.1029/2024EA003661) for the seasonal cycle. See also comment on Figure 11 below.
MINOR ISSUES (listed with line numbers)
8/ Capitalize “arctic” here and elsewhere when referring to region, ocean, etc.
50/ Sounds too “assertive”. You have tried to remove non-oceanographic signals from earthquakes, but not all earthquakes. Moreover, there are possibly other non-oceanographic signals (e.g., Mandea et al. 2015; https://doi.org/10.1002/2015JB012048) that are ignored in this work. While outside the scope of this paper, these signals could be mentioned to provide broader context.
52/ Define mascon at first mention (line 36?).
80/ Define ECCOv4r4.
118-119/ This statement also seems too assertive (see comment on line 50).
139/ Define ellipsoid correction.
135/ What “idea across”? Too colloquial? It would be more informative to say that the approximation is good to within some percentage number or something equivalent.
346-347/ Could be written more clearly.
355/ Imprecise phrasing: pressure variations do not arise from geostrophic balance, instead they lead to geostrophic balance as currents driven by those pressure variations feel the Coriolis force in a rotating planet.
356/ “Because internal pressure variations should average out to zero,…”
Figure 7/ It is not easy to see the subtle differences in these panels. Perhaps showing a difference of trends and amplitudes can provide a better quantitative assessment of the importance of a spatially varying GRD vs spatially constant correction. The differences in annual amplitude can also miss possible differences coming from changes in phase. If differences in phase are important, showing the root-mean-square difference of the annual cycles might be a better alternative.
397/ Effects of GRD and comparisons with ECCO are also discussed by Ponte et al. (2024; https://doi.org/10.1029/2024EA003661) in the context of the seasonal cycle. A discussion of how the current results relate to their findings would be useful to add in section 3.
420-421/Remaining earthquake signals can be seen in side lobes away from the epicenter in both trend and rms plots (figure 6b,d). Is a linear trend the best model to remove? Some more insight into this would be useful for the user, including some discussion of why the current models seem to miss significant parts of the earthquake signal.
428/ Define f/H.
Figure 11/ Do the DOM behave differently compared to the regular mascons? The focus should be on what improvements are brought by the DOM and this figure and its discussion do not address the key reason for the analysis.
459-463/ The Argentine basin issue has been noted and discussed before in several papers. Moreover, the DOM dataset does not bring anything new to this issue, as far as I can grasp from this brief discussion. I suggest deleting this text.
512/ “…and the effect of global atmospheric pressure”
516/ The text here reads “mascons are designed to be comparable to ocean models” but two lines below we have “mascons should not be compared to…models of ocean bottom pressure”. Please rewrite more clearly.
Appendix/ Substantial text in the appendix is basically a repetition word for word of the main text. This is a bad practice and really unnecessary. All repeated text should be deleted.
References/ Please double check your list for completeness. I could not find Pie et al. (2025), Ponte et al. (2018), Save (2019), Sun et al. (2016).