the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 27 May 2026
Accurate assessment of surface mass balance based on stake observations and model correction at Dome A, East Antarctica
Abstract. Accurate quantification of surface mass balance (SMB) in the Antarctic interior underpins ice sheet mass budget assessments and ice core interpretation. Stake measurements, however, systematically underestimate SMB because firn densification causes surface lowering unrelated to mass change. Here, we simulate firn compaction with a firn densification model and correct stake records from 2008-2024 at Dome Argus (Dome A), East Antarctica, thereby refining SMB estimates and their spatial variability. The mean annual corrected SMB is 24.14 kg m-2 yr-1, 8.8 % higher than the uncorrected value (22.19 kg m-2 yr-1). Over the stake array, the RACMO2.4p1 regional model yields lower and more spatially uniform SMB (17.50 kg m-2 yr-1). Using automatic weather station observations, we estimate annual sublimation of 2.34 mm w.e yr-1. and hoar deposition of 0.87 mm w.e. yr-1, indicating that the net vapor flux is equivalent to 5.7 % of the total mass input. This framework reduces densification induced bias in stake-derived SMB, provides an observational benchmark for evaluating regional climate models, and supports accurate dating of ice core climate records from Dome A.
Competing interests: At least one of the (co-)authors is a member of the editorial board of The Cryosphere.
Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this paper. While Copernicus Publications makes every effort to include appropriate place names, the final responsibility lies with the authors. Views expressed in the text are those of the authors and do not necessarily reflect the views of the publisher.- Preprint
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RC1: 'Comment on egusphere-2026-2150', Anonymous Referee #1, 15 Jul 2026
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The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2026/egusphere-2026-2150/egusphere-2026-2150-RC1-supplement.pdfReplyCitation: https://doi.org/
10.5194/egusphere-2026-2150-RC1 -
RC2: 'Comment on egusphere-2026-2150', Anonymous Referee #2, 05 Aug 2026
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This article presents a refined estimate of the surface mass balance (SMB) at Dome A on the Antarctic plateau, defined as precipitation minus sublimation in this dry region. The SMB is quantified using a 7×7 array of stakes spaced 5 km apart, covering an area of 30 km by 30 km. A key strength of this article is that it accounts for firn compaction caused by densification, using a densification model calibrated against a locally measured density profile, and that it estimates the contribution of sublimation to the total SMB from an automatic weather station (AWS).
The accurate estimation of the net snow accumulation at Dome A is valuable for evaluating models and improving our understanding of the SMB of the Antarctic plateau. The article is clearly written, and although the methods are standard, they are clearly explained, and the results are well illustrated. However, it seems to me that this article would be better suited to a journal publishing observational data (e.g., ESSD) rather than The Cryosphere, as the scope of the study is limited to Dome A. I leave it to the editor to decide whether this article is well suited to the journal The Cryosphere. Beyond this remark, the article appears scientifically sound and I recommend its publication after the following major and minor comments have been addressed.
Major comments
- I recommend adding a discussion of the uncertainty associated with stake measurements: what is the spatial variability of accumulation at the kilometer scale? What is the uncertainty on each stake's observation with respect to the surrounding 5 km × 5 km area? If no local observations allow this uncertainty to be estimated, I suggest using other existing observations from the Antarctic plateau to estimate it, as this is a crucial point for interpreting the SMB observations.
- Section 3.2: I did not understand the purpose of this paragraph. I recommend clarifying it by clearly distinguishing between subsidence due to snow accumulation and subsidence due to sub-surface densification.
- Section 3.4.2: I feel this section would benefit from more thorough treatment, notably by including the uncertainty on the stake measurements. In addition, L289–292 state that the discrepancy arises because RACMO has a resolution of 11 km: I suggest to aggregate the stake measurements over one or several RACMO grid cells to check whether the larger-scale spatial patterns are well represented in RACMO or not, independently of sub-grid spatial variability.
Minor comments- I would suggest adjusting the number of significant figures throughout the manuscript. In my view, one decimal place would be sufficient for SMB values (e.g., XX.X kg m⁻² yr⁻¹ instead of the current XX.XX kg m⁻² yr⁻¹).
- Use a consistent unit for SMB throughout the manuscript: kg m⁻² yr⁻¹ (the text sometimes uses m yr⁻¹ w.e., cm a⁻¹, mm yr⁻¹ w.e.)
- L35: 131 Gt yr⁻¹ for which period?
- L60–61: How much is 15.1 cm a⁻¹ as a percentage of the mean accumulation at Summit?
- L90: How many stake measurements are excluded?
- Section 2.1.2: Details on the instrumental setup of the AWS are missing, notably how subsurface temperature is measured, whether the height of the instruments above the ground surface is measured, and how this height has evolved over the observation period.
- L105: Add an evaluation of ERA5 against the AWS for the common period, for all variables used in the article.
- Throughout the article, but particularly in Section 2.4.1, units are missing for many variables. For every variable introduced, the corresponding unit should be given, even when it is an SI unit. Example, L133–140: units for H, A, ρ_sf, V_fc, ρ_i, V_ice, B. This is just one example, as units are missing for a large proportion of the variables introduced in the manuscript.
- Equation (4): It seems to me that the t_z inside the integral should be replaced with t.
- L171: "consistent with the temporal resolution of the ERA5 forcing data" — ERA5 is available at hourly resolution, so I do not understand this justification for working at a monthly time step.
- Section 2.5: A justification is missing for the choice of bulk transfer coefficients, along with an estimate of how this choice, together with the simplified flux formulation adopted, may affect the estimated condensation and sublimation fluxes.
- L278–279: It is wind divergence over ridges and convergence in valleys that causes erosion on ridges and deposition in valleys.
- Figure 5: If you wish to keep the divergent blue/red colormap, I would suggest using 24 kg m⁻² yr⁻¹ (your mean SMB estimate) as the central value of the colorbar, and stating this in the figure caption, as divergent colormaps require a meaningful central value. Alternatively, if you would prefer not to center the colorbar on 24 kg m⁻² yr⁻¹, I would recommend using a continuous (non-divergent) colormap for SMB, such as 'viridis' or 'YlGnBu' in Python, for example.
- L301–302: I think that using daily values instead of hourly values may introduce substantial biases in the flux estimates. The error resulting from this assumption should be estimated using the days for which hourly data are available.
- Section 3.5: An evaluation of the RACMO sublimation flux should be added to complete the study.
- L321: I find "critical" too strong a term; I suggest replacing it with the actual value (~9%).
Citation: https://doi.org/10.5194/egusphere-2026-2150-RC2
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