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.
- Preprint
(1782 KB) -
Supplement
(1340 KB) - BibTeX
- EndNote
Max Thomas et al.
Status: final response (author comments only)
-
RC1: 'Comment on tc-2023-37', Anonymous Referee #1, 13 Mar 2023
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 - AC1: 'Reply on RC1', Max Thomas, 25 May 2023
-
RC2: 'Comment on tc-2023-37', Anonymous Referee #2, 04 May 2023
Overall comments
This paper investigates the transport and evolution of chemical species through sea ice by comparing lab experiments with theoretical modelling work. The paper shows that simply assuming that PFAS evolve in the same way as salinity does not match observations. Three possible alternative models are tested, with two seeming plausible representations of this process. The rationales for some of these models could have been explained more and there are important presentational areas for improvement. But I think that the paper is a very good contribution, containing novel results of interest to the Cryosphere readership. Thus, it should be published subject to the minor corrections.
Minor (general) comments:
The presentation of results could be improved, both the in terms of the figures and the text. I make detailed line-by-line comments below, but I think the heart of the issue is that the figures may be in a sub-optimal order. The following is only a suggestion but may improve the readability of the paper.
Figure 3 is by far the easiest to understand, so I suggest it should go first, possibly with a second panel showing an example with a short chained PFAS as a contrast.
Then figure 1 could go second (or even by moved an appendix/supplement, which might allow for the model fitting to be explained in more detail). At present, it is not clear why the absolute value of b is plotted (or even the precise definition of b, which should be more clearly stated). Plotting b would make the sign of the bias apparent. The figure is far too small with very many lines (the choice of which is not precisely stated in the caption). One solution might be having a single panel (larger) in the main text explaining the calibration of a single example in greater detail, then move all the other calibrations to a supplement.
Then figure 2 (which was good) would move next, and finally figure 4. The latter could potentially be expanded to plot more of the correlations implicit in table 1. E.g., it could have a separate panel with N_c as the independent variable and alpha_{B,C,D} as dependent variables, normalized appropriately.
The reordering of the figures may also help the writing by making the ideas easier to visualize.
The other structural writing issue is the overlap between sections 3 and section 4. I think more of the detail should go into section 3 and then section 4 should be more summative (rather than restating the detail in section 3).
Technical line-by-line comments:
- L5: could mention direction of bias (although this is clear later in the abstract)
- L6: “as a constant fraction” a bit vague (fraction of what, especially when it is being contrasted with “proportional to the brine salinity” which also has a constant proportionality coefficient)
- L7: consider putting the other poorly performing scheme earlier (before the good ones)
- L34: this was interesting, it looked like none of the models would have been able to reproduce this?
- L50: will the sampling bias be the same for salt vs PFAS? If the idea that some of the PFAS is stuck on the solid, then you might think there is a greater sampling bias for salt vs PFAS. Might be worth discussing
- Table 1: could give a definition/formula for K_OW.
- A more general point is that the terms ‘decoupling,’ ‘partitioning,’ ‘fractionation’ are being used for the same type of process. It may be worth spelling this out explicitly in the introduction.
- Eq. (1): could explain that diffusion is assumed to be slow on these timescales
- L80: I would write out this formula. I would also make it more explicitly clear that c_br=c_si/phi (or similar expression using S for salinity).
- In equation (2), the meaning of this formula is not very clear. The usual lever rule for bulk concentration is c_si=c_br*phi+c_s*(1-phi), but this does not appear to be equivalent to equation (2).
- Relating to equation (3), subject to the comments about equation (2), it is possible to combine equations (2) and (3) to relate c_s to c_br, in which case the proportionality constant would be called a partition coefficient.
- L104-105: could add a reference for this claim. Are there any independent experimental estimates of the strength of this effect?
- L122 add “(WLS)” as the acronym appears in figure legend but is otherwise undefined.
- L144: the differences are quite marginal
- L165: needs a paragraph break (but also see general comments on rearranging sections 3 and 4).
- L207: presumably, how to handle the decoupling will vary between these distinct types of chemicals?
Citation: https://doi.org/10.5194/tc-2023-37-RC2 - AC2: 'Reply on RC2', Max Thomas, 25 May 2023
Max Thomas et al.
Data sets
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.
Viewed
| HTML | XML | Total | Supplement | BibTeX | EndNote | |
|---|---|---|---|---|---|---|
| 210 | 76 | 14 | 300 | 25 | 4 | 4 |
- HTML: 210
- PDF: 76
- XML: 14
- Total: 300
- Supplement: 25
- BibTeX: 4
- EndNote: 4
Viewed (geographical distribution)
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1