the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 16 Jan 2026
The OCEAN ICE hydrography profiles compilation and climatology
Abstract. A compilation of in situ temperature and salinity profiles south of 45° S is assembled, drawing from multiple data centers and sensor sources. This database is then used to create a new Southern Ocean climatology, adopting an interpolation scheme that takes into account ocean depth and mean ocean dynamics, influenced by methods developed for the Southern Ocean Atlas. This interpolation scheme is designed to consider along flow spatial coherency and the distinct dynamic regimes between Antarctic shelf seas and the Southern Ocean. Initial exploration of the profile compilation investigates the type of variability timescales one could reasonably start to analyze in different sectors around Antarctica. A comparison between the climatology product and the World Ocean Atlas climatology, the most used product to date, indicates that the OCEAN ICE climatology provides significant improvements in Antarctic shelf seas, including a more detailed representation of the unique water masses they host. The profile compilation is available in NetCDF format with the SEANOE database at https://doi.org/10.17882/99787, and the climatology product is available at https://doi.org/10.17882/103946. Both the hydrography profiles compilation and the hydrography climatology products are generated under the endorsement of Ocean-Cryosphere Exchanges in ANtarctica: Impacts on Climate and the Earth System (OCEAN ICE) project (https://ocean-ice.eu/) funded by the European Commission and UK Research and Innovation.
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Status: open (until 22 Feb 2026)
- RC1: 'Comment on essd-2025-727', Anonymous Referee #1, 03 Feb 2026 reply
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RC2: 'Comment on essd-2025-727', Anonymous Referee #2, 05 Feb 2026
reply
Overall, the manuscript is of high quality and worthy of prompt publication in ESSD for benefiting the scientific community. However, there are some issues that need to be addressed before publication.
Major comments
I think the most striking benefit of the presented O:I climatology over existing products is its extension to the inner shelf and ice cavities. However, the manuscript at present does not provide performance metrics against the observation data sufficiently to allow readers to evaluate its reproducibility over the shelf. In general, the Antarctic shelves severely suffer from the data paucity, likely requiring the estimated field to be extrapolated over a long distance, especially under the ice shelves. A more thorough, quantitative assessment of interpolation performance over the shelf (e.g., statistics of observation data residuals, mapping with the original scattered data) needs to be included. Caveats for the use of such inner shelf data also need to be explicitly acknowledged, unless low confidence estimations are masked. Furthermore, it is also highly recommended to add evaluation of the interpolation performance in deep waters (below 2,000 m offshore) in comparison to WOA23, which has been widely recognized and utilized. I believe addressing these points will improve the presentation of how this dataset is better than the other product and why it is meanwhile for the scientific community.
Minor comments
L154 “one realization where each quintile is sampled”: Does this mean simply keeping searching until 5 data points are obtained within the search range, or 5 samples are collected continuously assessing if the data values constitute sinusoidal variation? If the former case, how does the method guarantee its sufficiency of capturing their sinusoidal variation? If the latter case, what is the sampling threshold for the variation applied at each grid?
L198 “ellipse of influence”: how is this conceptually different from a correlation scale in the conventional optimal interpolation?
In this relation, after reading the whole manuscript, I could not understand how the adopted interpolation method is compared with the conventional optimal interpolation and why the adopted method is thought to be better. Please explain somewhere.
L214: What is the time period of SSH modelled by SOSE? Does the temporal variation of SSH in SOSE will affect the results? How much?
L224 “The orientation of the ellipse on the continental shelf follows the local topography gradient”: The authors may want to define the ellipse orientation as its major axis direction then correct this sentence to ‘follows the local topography contour’
L228 “The choice of the horizontal resolution is to accommodate the shelf ellipse size”: The shelf ellipse size seems determined by the fixed valued that connects offshore (L221), which is based on the SOSE SSH contours. Assuming the SOSE field had 1/6th degree grids, the chosen grid size of 0.2x0.1 is fairly small and maybe even smaller than the SOSE grid. Overall, I could not understand 1) how the listed values of correlation length scales are determined offshore and 2) how the choice of such small grid size is justified. I suspect there is missing information that required to reproduce these values, maybe something hidden under L219 “In our algorithm”. This point is also relevant to calibration of tuning parameters essential for the best estimation.
L246 “a fast-marching (FM) algorithm is performed to search for and select data beyond the spatial bound defined by ellipses”: Was the FM scheme applied for the entire dataset including offshore? What does “where a simple average metric within ellipses loses meaning” specifically mean?
L286: What is “the weighted standard deviation”? What makes this interpolation error metrics larger; e.g., less data density or wider spread of measured values?
L388 “as noted in Barker and McDougall (2017)” and L389 “a thorough comparison of the two methods tested in this study”: It appears that Barker and McDougall (2017) did not describe the VA method (but Chu and Fan’s CMA) nor cite Wang et al. (2012). Please explain.
Figure 9: “temperature maximum below 100 m” is likely too shallow for upper CDW north of the SACCF.
Temperature: https://woceatlas.tamu.edu/images/printed/jpg/I9_ptm.jpg
Oxygen: https://woceatlas.tamu.edu/images/printed/jpg/I9_oxy.jpg
Figure 10: Although this figure provides how the O:I climatology is different from WOA23, it might be difficult for readers to know which is better in general outside the featured sections.
Summary: I suggest adding a brief explanation about how the presented climatology can be compared with the existing datasets such as WOA23 and Yamazaki et al. and why the present dataset matters for the scientific community.
Citation: https://doi.org/10.5194/essd-2025-727-RC2
Data sets
Southern Ocean (90°S-45°S) conservative temperature and absolute salinity profiles compilation (OCEAN ICE D1.1) Shenjie Zhou et al. https://www.seanoe.org/data/00886/99787/
The OCEAN ICE Southern Ocean Climatology Shenjie Zhou et al. https://www.seanoe.org/data/00928/103946/
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This manuscript presents a new compilation of seal-based, CTD and Argo profiles in the Southern and an associated monthly climatology. A limited exercise of validation is proposed through comparison with the global World Ocean Atlas 2023, a product known for its mediocre quality in the region (e.g. Yamazaki et al 2023).
Much better products than WOA23 exist in the literature (SOSE, Pauthenet et al. 2021, Yamazaki et al 2023), but no meaningful comparisons are provided with this new product. It would be useful to know in what sense this new climatology would improve upon previously published products. This ius particularly true of Yamazaki et al 2023 which shares many similarities with this product in terms of datasets or interpolation method.
I recommend rejection of the manuscript. Judging on the current description, I can not find any added value in the data compilation, and I do not find any salient feature that would make the proposed climatology product superior to other existing products, such as Yamazaki et al 2023.
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