the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
The effect of partial dissolution on sea-ice chemical transport: a combined model–observational study using poly- and perfluoroalkyl substances (PFAS)
Briana Cate
Jack Garnett
Inga J. Smith
Martin Vancoppenolle
Crispin Halsall
Abstract. We investigate the effect of partial dissolution on the transport of chemicals in sea ice. Physically plausible mechanisms are added to a brine convection model that decouple chemicals from convecting brine. The model is evaluated against a recent observational dataset where a suite of qualitatively similar chemicals (poly- and perfluoroalkyl substances, PFAS) with quantitatively different physico-chemical properties were frozen into growing sea ice. With no decoupling the model performs poorly – failing to reproduce the measured concentrations of high chain-length PFAS. A decoupling scheme where PFAS are decoupled from salinity as a constant fraction, and a scheme where decoupling is proportional to the brine salinity, give better performance and bring the model into reasonable agreement with observations. A scheme where the decoupling is proportional to the internal sea-ice surface area performs poorly. All decoupling schemes capture a general enrichment of longer chained PFAS and can produce concentrations in the uppermost sea-ice layers above that of the underlying water concentration, as observed. Our results show that decoupling from convecting brine can enrich chemical concentrations in growing sea ice and can lead to bulk chemical concentrations greater than that of the liquid from which the sea ice is growing. Brine convection modelling is useful for predicting the dynamics of chemicals with more complex behaviour than sea salt, highlighting the potential of these modelling tools for a range of biogeochemical research.
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Max Thomas et al.
Status: open (until 04 May 2023)
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RC1: 'Comment on tc-2023-37', Anonymous Referee #1, 13 Mar 2023
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Max Thomas et al. determine if and how a 1D parametrization of brine convection can be expanded to reproduce the laboratory PFA measurements of a previous study (Garnett et al. 2021). The paper consists of roughly four parts. In part one, the authors propose four different methods (A,B,C,D). In part two, they tune the free parameters of methods B, C, and D to minimize the absolute bias. In part three, they compare the model against the observed PFA profiles. Finally, in part four, they discuss if their results would apply to longer sea-ice simulations and other chemicals of interest.
The paper's text is clear and the method is clearly formulated (with one small exception) and applied thoroughly. The main conclusions are clearly stated, relevant to the field, and well supported by the results. The plots are mostly legible and not misleading, and the code has been made fully available. The topic of the submitted manuscript fits The Cryosphere. Based on my experience, the quality of the draft is well above average.
However, I found the structure of the paper's second half confusing, and the paper is somewhat ambiguous about its scope. Moreover, the figures could be improved upon, and there are a few minor other issues to address. Accordingly, I recommend accepting the submitted paper, but with minor revisions.
Minor comments in roughly descending importance
- Scope. The introduction clearly states that the paper aims to determine if decoupling can explain the observed properties. However, the methods introduced and the results discussed go beyond that. I feel that one or two paragraphs are missing at the end of the introduction to describe the other main question of the paper, namely if the decoupling is linked to the surface area, brine salinity, or constant. Furthermore, here I feel that the expectations should be clearly stated. From the current draft, I am unsure which methods B, C, and D closest match the known theory.
- Structure. I missed the transitions between results, discussion, and conclusions on my first read. In my view, the tuning of the methods and the analysis of the resulting parameters are the first results. In the current draft, this is a single sentence at the end of 2.2, and is then revisited in Figure 4. Furthermore, I believe the results extend till line 173, and the discussion begins by discussing how general the results are. (I enjoyed the discussion along with the supplementary material.) From lines 129 to 173 I get lost between all the comparisons of B to C to D, and some things are repeated multiple times (e.g. lines 155-159). I recommend breaking down the results into more bite size chunks, answer a question and then move on to the next. One of the questions I would like to see answered is what it means that B and D are so similar. Is there no T dependence in reality? Or, is the data insufficient to distinguish?
- What is the absolute bias |b|? I assume it must be the absolute difference over the vertical sum of the modeled and measured concentrations. But in line 112, it says the difference between the measurements and the co-located model layers, which implies that |b| should only be zero when the model and obs match at all layers. Moreover, how is the absolute bias scaled? What does |b| = 1 mean? Why use the absolute value? Showing b instead could clearly show that the higher alpha is, the higher the total concentration is. It might also make the lines in Subfigure 1b less confusing.
- Figure 1 has many lines that are difficult to distinguish. The readability could be improved by increasing the plots' width to use the paper's full width. The yellow line is also difficult to see; a darker tone would be helpful. There are no subfigure labels (a,b,c), and shifting the legend outside the area of the subfigure would also help. The current version, in which the legend blocks the lines' view and overlaps with the figure borders, is messy.
- Figure 2 has too many lines and markers in too little space. This figure could be separated into two figures for profiles and scatterplots, but at least make full use of the paper width to make columns 1 and 2 twice as wide. This is now a minor detail, but I was initially confused by the axis choice for the right column. Since they share the same observation data, it makes more sense that the observation data be the x-axis—shared data on the shared axis. For example, one could easily compare where the 2.5 measured C12 is in each plot.
- Lines 170 and 172 reference some tests that can be passed or failed. I have searched the submitted manuscript and find no clue what tests these are.
- "was not a useful method" line 155. "useful" is not a well-defined adjective in this context. I recommend stating that C is worse than B and D and better than A.
I am trying to understand why the authors chose the name method A instead of reference or control. It is not a flaw and does not need to change, but I did find it strange that the first "method of decoupling" is "none". Accordingly, there is alpha_B, alpha_C, and alpha_D, but no alpha_A, and so on.
Citation: https://doi.org/10.5194/tc-2023-37-RC1
Max Thomas et al.
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Reproduction capsule for The effect of partial dissolution on sea-ice chemical transport: a combined model--observational study using poly- and perfluoroalkylated substances (PFAS) Max Thomas, Briana Cate, Jack Garnett, Martin Vancoppenolle, Inga J. Smith, and Crispin Halsall https://doi.org/10.24433/CO.6237417.v1
Max Thomas et al.
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