Unlocking the Potential of Melting Calorimetry: A Field Protocol for Liquid Water Content Measurement in Snow

Barella, Riccardo; Bavay, Mathias; Carletti, Francesca; Ciapponi, Nicola; Premier, Valentina; Marin, Carlo

doi:https://doi.org/10.5194/egusphere-2023-2892

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https://doi.org/10.5194/egusphere-2023-2892

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02 Jan 2024

| 02 Jan 2024

Unlocking the Potential of Melting Calorimetry: A Field Protocol for Liquid Water Content Measurement in Snow

Riccardo Barella, Mathias Bavay, Francesca Carletti, Nicola Ciapponi, Valentina Premier, and Carlo Marin

Abstract. Melting calorimetry, a classic experiment conducted in high school chemistry laboratories using calorimeters made from coffee cups, holds untapped potential beyond its educational context. Despite the fact that in the past this technique has been successfully used to measure the liquid water content in snow, its widespread adoption was impeded as it is often unjustly associated with generating large measurement errors. This paper shows how this technique can be incorporated in a rigorous field protocol to measure the liquid water content in the snow providing also a quantification of the uncertainty associated to the measurements. The results presented here encourage the use of melting calorimetry in all cases where liquid water content of the snow has to be quantified.

Received: 01 Dec 2023 – Discussion started: 02 Jan 2024

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Riccardo Barella, Mathias Bavay, Francesca Carletti, Nicola Ciapponi, Valentina Premier, and Carlo Marin

Status: closed

RC1:
'Comment on egusphere-2023-2892', Ryan Webb, 11 Jan 2024
The manuscript by Barella et al. describes a detailed analysis of errors in melt calorimetry for snow liquid water content (LWC) calculations. They compare this to that of freezing calorimetry and additionally conduct experiments to determine some of the random user uncertainties associated with the method. The authors present some melt calorimetry field protocol and conduct field investigations to show the utility of the methods.
Overall, I really like the concept of this study. I agree that melt calorimetry has been overlooked in recent years as I have recently published a paper using this method myself (Webb et al., 2021). Furthermore, with field instrumentation advancing in the past couple of decades the improved error estimates have been greatly reduced compared to those of the past, as this manuscript shows. However, the current state of the manuscript needs major revisions to be publishable. I was on the boundary between major revisions and reject because my comments below require a lot of work. I also think it may be a better fit as a technical note similar to my 2021 paper. I would like to emphasize that I really like the project and that these comments are meant to be constructive and helpful in producing a more readable and impactful final paper.
I also chose not to be anonymous partly because I reference some of my own papers. I try not to reference my own work in reviews, but the LWC in snow and melt calorimetry sub-discipline is quite small and I do believe my papers are objectively relevant.
Reference: Webb et al., 2021: https://www.mdpi.com/2072-4292/13/22/4617
Major Comments:
The authors seem to push for the take home message to be the field protocol that they produce within this work. However, there seems to be very little added from the protocol outlined in Kawashima et al. (1998). While they do cite this paper, it is not acknowledged that they made only minor adjustments to this older protocol. Therefore, I do not think this should be the main point of the paper. I think the more important contribution is the error calculations.

The manuscript seems to have a lack of focus. There is a lot going on and the writing jumps around quite a bit. I think it would be helpful to just focus on the uncertainty of melt calorimetry for snow LWC and how to keep that to a minimum. To do this, the authors could remove the detailed comparison to freezing calorimetry and offer a brief comparison of uncertainty with citations. The math in this manuscript is solid and I think should be the focus followed by a brief update to the Kawashima et al. (1998) protocol, and lastly a brief overview of the case studies showing the reliability of the method. Re-writing and organizing as detailed below would further help the focus stand out better.

I think that the manuscript needs to be re-organized for readability. In the current form, the writing is difficult to interpret what is methods, results, or discussion/interpretation. The manuscript would benefit from having distinct Methods, Results, and Discussion sections. As it is currently written, the manuscript bounces around quite a bit and is hard to follow.

The manuscript is also quite long for this type of study. I think re-organizing the text may help to reduce some of the redundancy in in the writing. The re-writing will also help catch some of the typos and inconsistencies (I point out a few in the minor comments).
The introduction is missing quite a bit of background information. There is a short paragraph that states broadly why LWC in snow is important, followed by multiple paragraphs detailing calorimetry. The in-depth discussion of calorimetry could be shortened since it is an established scientific method. I think a lot more background information could be offered on the ways that LWC is often measured in the field and why calorimetry is useful. For example, there are GPR methods that have been used for LWC in snow from the plot to the small catchment scale (Webb et al., 2018, 2022), drones and TDRs have been used (Valence et al., 2022), and hyperspectral imaging (Donahue et al., 2022). However, calorimetry is a great way to make more direct observations/calculations of LWC to compare and improve these empirically based methods (Webb et al., 2021). Lastly, Some more citations could be given for the importance of LWC for hydrology (Eiriksson et al., 2013; Leroux et al., 2020) and avalanches (Schlumpf et al., 2024) from other research groups globally. This is further reflected in the manuscript being 23 pages long, plus 2 appendices, but only 24 references.

References
Webb et al., 2018: https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2018wr022680
Webb et al., 2022: https://onlinelibrary.wiley.com/doi/full/10.1002/hyp.14541
Valence et al., 2022: https://tc.copernicus.org/articles/16/3843/2022/
Donahue et al., 2022: https://tc.copernicus.org/articles/16/43/2022/
Eiriksson et al., 2013: https://onlinelibrary.wiley.com/doi/10.1002/hyp.9666
Leroux et al., 2020: https://doi.org/10.1029/2020WR027466
Schlumpf et al., 2024: https://www.sciencedirect.com/science/article/pii/S0165232X23002872

Minor Comments (with line numbers for reference):
96-97: Please choose either theta or LWC and be consistent throughout. I think given all the equations in this manuscript theta is the better option.
97: I agree that volumetric is the best way to discuss LWC, but you go back to by mass in section 3.3 and then to volumetric again. This can be confusing to readers not familiar with the major differences, especially looking at the error in figures 5 and 6. By volume gives essentially ml of water per volume while mass LWC really is dependent on the snow density and can have a huge difference in the actual amount of water in the sample.
102: “in EQ.(1) is shown the energy balance equation” please re-write.
105: no need for comma after “where”
106: L, rho_w, and E don’t actually appear in equation 1 so should not be defined here.
121: “This imply accounting” please correct typo, though this sentence may not be necessary.
122-124: I do not agree that radiation is negligible. During my development of my own melt calorimetry protocol I had some prototype calorimeters and found the temperature did not settle out very well when in the sun. Sometimes it is difficult to keep the calorimeter shaded in a shallow prairie snowpack, so I think this point could be better emphasized. I found myself having to remind others about this necessary step when in the field as it is easy to forget when not in a deeper pit. My experiences may have been because it was a cheaper prototype calorimeter prior to the one I developed and currently use, but I still think shading is an important step for these types of measurements for readers to know about.
138-146: This paragraph seems unnecessary. A general outline of the paper was given earlier, but an outline paragraph for every section unnecessarily lengthens the manuscript. I think the headings and sub-headings do a good job of telling me what is to come.
140: “reveling”
178: “Colbeck” should be outside of the parentheses the way this sentence is written.
179: Why assuming 200 cc? I understand it is because of the box cutter sampler, but please state this.
181: why 366 kg/m3? This seems like an odd choice for an arbitrary number in evaluating equations.
185: These are very precise measurements. While I agree that these are needed for accurate calorimetry, it would be nice to also show how inaccurate calorimetry becomes when scale precision is 1.0 g and T is 1.0 deg_C as this is what many researchers could have in standard pit kits. This may drive home the point that specific instruments are necessary for calorimetry.
187: 2 cc translates to 1% which is not supported by any studies, as mentioned. I agree that this level of accuracy can likely be achieved in nice uniform layers. However, in some fresh snow, depth hoar, or where an ice lens or melt-freeze crust is present this level of accuracy will be difficult to achieve. I think something more like 5% or maybe more. It will also certainly depend on the experience level of the user.
192: “notable practical advantages” Yes! I completely agree and this is why I use this method, too.
209-210: I don’t think the discussion about artificially introducing LWC to snow is necessary here.
218: How do you know the temperature of the ice cubes? This seems like a pretty critical part of this experiment and it is not clear how it is known or what range of ice cube temperatures were used.
237-242: This is one example of discussion points being made in the middle of methods that can make it difficult to follow. It also makes it difficult to find specifics of the methods if I want to go back as it unnecessarily lengthens the methods.
244: What was the windspeed from the fan that produced this much error?
250-251: So, it was snow samples and not ice cubes? This is confusing as equation 22 is for an ice cube. This part of the manuscript is unclear on what is being done. How does this specifically translate to error in LWC?
268: source or sources?
287-288: “water saturation on top of ice layers” could use a citation.
291: would this 18 cm depth be inserted horizontally or vertically? In my experiences, horizontal measurements of LWC on pit faces may overestimate/underestimate the LWC of some layers because water kept above a barrier that is destroyed by digging the pit will then freely drain down the pit face. This is often a very difficult process to notice unless very careful attention to this specific process is made.
305: “a particular attention”
317: it seems overly redundant to use LWC theta.
317: early on in the manuscript the authors mentioned that theta would be kept at volumetric. Now it switches back to by mass. By mass is more dependent upon snow density, so volumetric can be better to use for LWC analyses. Either way, please be consistent.
321: please specify box cutter here.
321: “18 cm^3” should probably be just cm correct?
322-323: is one of the dimensions only filled to 2 cm depth or is it 2 cm short? This statement is confusing here. Also, this further supports an increased uncertainty in volume estimates since a 10% error in volume results in only 0.1% error in LWC. However, this 0.1% error is by mass LWC instead of volumetric LWC? Please also explain and quantify how the volume error translates into a snow density error that propagates into the volumetric LWC error?
325: Why would the mass be off by a few grams? In wind it was only off by 1.5 grams, correct?
Figures 5 and 6: Please convert to volumetric water content as the error shown here would change for different densities of snow.
352: Please specify that you developed these values yourself as it currently reads like they are available from the manufacturer, which they are not.
354: What make and model of thermometer did you use?
355: what make and model of scale did you use?
361: Why must the shape and size of the sampler match the calorimeter? Didn’t you use a box cutter sampler with a round calorimeter bottle? As long as the sampler is smaller than the opening for the calorimeter you should be able to easily and quickly get the sample into the calorimeter.
363: As mentioned earlier, please further emphasize the need for protection from solar radiation.
371-372: This 200 g of water is assuming a relatively high snow density of 500 kg/m^2, correct? I think a more general statement could be made where this will depend on the expected or measured density of the snow layer. For a density of 330 kg/m^3, which is not unreasonable to expect, this would result in an R value of 3. Lesser densities of upper layers or fresh snow would then increase to even higher R values where you mention we should try to avoid.
Figure 7 caption: “the insulated container where heat exchange occurs” – why not just say calorimeter. Also, the site and denoth meter have not been introduced in the text yet.
368-383: These procedures do not appear to be much different from Kawashima et al., 1998. Some specific volumes or masses are different, but the procedure is essentially identical when combined with a standard snow pit procedures.
388: “accuracy” was not really tested, and I don’t think that it can be. “reliability” or consistency with other methods was testes qualitatively, though.
405: How did you shield things from the sun and wind in a 50 cm snowpack? I imagine that completely shading the calorimeter was difficult at these depths, or at least that is what I have found to be the case.
406: This doesn't add up. June 16 is 123 days after Feb. 14 which would be at least 60 measurements if performed every second day. Is it every 3 or 4 days, basically twice a week?
408: What does SSA add to this study? It seems to only be distracting and adding length to an already long manuscript.
421: similar comment about NIR. While the images are cool, I think the crystal type is more informative/valuable to the story of this study.
431-432: Depends on what you mean by retention capacity. Many studies assume a value of 0.02 retention as the retained after naturally drained (certainly with 0.04 or 0.05 as the maximum), but I am not sure if that is what you mean here since the term is not defined and can mean different things in different disciplines. Maybe remove this comment.
451: What is meant by “the air temperature stood at 1.8 cm”?
458: “loose and coarse” so I assume you are referring to depth hoar. This is an example of what I mention earlier about increasing the error of snow volumetric sampling for certain crystal forms.
Figure 10 caption: confusing phrase “in the end it is reported a scheme of the profile” but I really like the addition of crystal form over NIR.
Appendix A: When you found the properties of your calorimeter, did you use a set of standard methods to determine material properties that you could cite?
Again, I would like to emphasize that I really like this study and these comments are meant to be constructive.
I am happy to discuss any of these points in the public forum or privately. Feel free to reach out with any questions: Ryan.Webb@uwyo.edu
-Ryan Webb
Citation: https://doi.org/10.5194/egusphere-2023-2892-RC1
RC2: 'Comment on egusphere-2023-2892', Jeff Dozier, 23 Jan 2024

Review of Barella et al., “Unlocking the potential of melting calorimetry: a field protocol for liquid water content measurement in snow”
I’m in agreement with the other referee’s (Ryan Webb) remarks.
Measurement of the liquid water content in snow is important because of the myriad of ways that water affects snow’s electromagnetic and geophysical properties. Mostly now, field researchers use an electromagnetic approach, measuring snow permittivity and applying the Maxwell-Garnett mixing rule of water in dry snow for an assumed prolate spheroidal shape for the water inclusions. Although this electromagnetic method enables rapid sampling, a direct measurement is still useful for validation, especially in the field.
This paper by Barella et al. makes a case that melting calorimetry is comparable in accuracy and convenience to freezing calorimetry. However, the contribution of the paper to what we already know is rather modest. It mostly reinforces the analysis by Colbeck (1978), although it disputes Colbeck’s conclusion that melting calorimetry is too inaccurate to use in the field. The paper also emphasizes the importance of accounting for heat transfer from the calorimeter itself, but again that knowledge was previously articulated by Fasani et al. (2023).
Therefore, this paper’s contribution is perhaps too marginal to warrant publication. The described experiment with untrained users (to identify and perhaps anticipate errors in field measurements) is compromised by using ice cubes instead of snow, whereas part of the likely error in the field involves the handling of the snow sample.
As a review paper, the shortcoming is that it only compares the melting and freezing calorimetric methods, whereas the dilution method described by Davis et al. (1985) would appear to take advantage of the analysis throughout the process being done at 0°C. In contrast, both melting and freezing calorimetry require fluids that are much warmer or colder than the snow sample (i.e., ±40°C) thereby needing much care to protect the analysis from heat transfer between the calorimeter and the environment. As a review paper, therefore, the analysis should include other direct methods of measuring liquid water content in snow (Davis et al., 1985; Fisk, 1986).
The paper needs substantial rewriting. The Abstract for example reads as a teaser exclaiming the benefits of melting calorimetry but not providing evidence about accuracy and uncertainty. The paper itself has some of this information, but the Abstract should provide more than a headline.
Finally, the E term (calorimeter constant) appears in Equations (2) and (4), but not in the driving Equations (1) and (3). Thus the linkages from (1) to (2) or from (3) to (4) are not clear.
Citations in the review
Colbeck, S. C.: The difficulties of measuring the water saturation and porosity of snow, Journal of Glaciology, 20, 189-201, https://doi.org/10.3189/S0022143000198089, 1978.
Davis, R. E., Dozier, J., LaChapelle, E. R., and Perla, R.: Field and laboratory measurements of snow liquid water by dilution, Water Resources Research, 21, 1415-1420, https://doi.org/10.1029/WR021i009p01415, 1985.
Fasani, D., Cernuschi, F., and Colombo, L. P. M.: Calorimetric determination of wet snow liquid water content: The effect of test conditions on the calorimeter constant and its impact on the measurement uncertainty, Cold Regions Science and Technology, 214, 103959, https://doi.org/10.1016/j.coldregions.2023.103959, 2023.
Fisk, D.: Method of measuring liquid water mass fraction of snow by alcohol solution, Journal of Glaciology, 32, 538-539, https://doi.org/10.3189/S0022143000012272, 1986.

Citation: https://doi.org/10.5194/egusphere-2023-2892-RC2

Status: closed

RC1:
'Comment on egusphere-2023-2892', Ryan Webb, 11 Jan 2024
The manuscript by Barella et al. describes a detailed analysis of errors in melt calorimetry for snow liquid water content (LWC) calculations. They compare this to that of freezing calorimetry and additionally conduct experiments to determine some of the random user uncertainties associated with the method. The authors present some melt calorimetry field protocol and conduct field investigations to show the utility of the methods.
Overall, I really like the concept of this study. I agree that melt calorimetry has been overlooked in recent years as I have recently published a paper using this method myself (Webb et al., 2021). Furthermore, with field instrumentation advancing in the past couple of decades the improved error estimates have been greatly reduced compared to those of the past, as this manuscript shows. However, the current state of the manuscript needs major revisions to be publishable. I was on the boundary between major revisions and reject because my comments below require a lot of work. I also think it may be a better fit as a technical note similar to my 2021 paper. I would like to emphasize that I really like the project and that these comments are meant to be constructive and helpful in producing a more readable and impactful final paper.
I also chose not to be anonymous partly because I reference some of my own papers. I try not to reference my own work in reviews, but the LWC in snow and melt calorimetry sub-discipline is quite small and I do believe my papers are objectively relevant.
Reference: Webb et al., 2021: https://www.mdpi.com/2072-4292/13/22/4617
Major Comments:
The authors seem to push for the take home message to be the field protocol that they produce within this work. However, there seems to be very little added from the protocol outlined in Kawashima et al. (1998). While they do cite this paper, it is not acknowledged that they made only minor adjustments to this older protocol. Therefore, I do not think this should be the main point of the paper. I think the more important contribution is the error calculations.

The manuscript seems to have a lack of focus. There is a lot going on and the writing jumps around quite a bit. I think it would be helpful to just focus on the uncertainty of melt calorimetry for snow LWC and how to keep that to a minimum. To do this, the authors could remove the detailed comparison to freezing calorimetry and offer a brief comparison of uncertainty with citations. The math in this manuscript is solid and I think should be the focus followed by a brief update to the Kawashima et al. (1998) protocol, and lastly a brief overview of the case studies showing the reliability of the method. Re-writing and organizing as detailed below would further help the focus stand out better.

I think that the manuscript needs to be re-organized for readability. In the current form, the writing is difficult to interpret what is methods, results, or discussion/interpretation. The manuscript would benefit from having distinct Methods, Results, and Discussion sections. As it is currently written, the manuscript bounces around quite a bit and is hard to follow.

The manuscript is also quite long for this type of study. I think re-organizing the text may help to reduce some of the redundancy in in the writing. The re-writing will also help catch some of the typos and inconsistencies (I point out a few in the minor comments).
The introduction is missing quite a bit of background information. There is a short paragraph that states broadly why LWC in snow is important, followed by multiple paragraphs detailing calorimetry. The in-depth discussion of calorimetry could be shortened since it is an established scientific method. I think a lot more background information could be offered on the ways that LWC is often measured in the field and why calorimetry is useful. For example, there are GPR methods that have been used for LWC in snow from the plot to the small catchment scale (Webb et al., 2018, 2022), drones and TDRs have been used (Valence et al., 2022), and hyperspectral imaging (Donahue et al., 2022). However, calorimetry is a great way to make more direct observations/calculations of LWC to compare and improve these empirically based methods (Webb et al., 2021). Lastly, Some more citations could be given for the importance of LWC for hydrology (Eiriksson et al., 2013; Leroux et al., 2020) and avalanches (Schlumpf et al., 2024) from other research groups globally. This is further reflected in the manuscript being 23 pages long, plus 2 appendices, but only 24 references.

References
Webb et al., 2018: https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2018wr022680
Webb et al., 2022: https://onlinelibrary.wiley.com/doi/full/10.1002/hyp.14541
Valence et al., 2022: https://tc.copernicus.org/articles/16/3843/2022/
Donahue et al., 2022: https://tc.copernicus.org/articles/16/43/2022/
Eiriksson et al., 2013: https://onlinelibrary.wiley.com/doi/10.1002/hyp.9666
Leroux et al., 2020: https://doi.org/10.1029/2020WR027466
Schlumpf et al., 2024: https://www.sciencedirect.com/science/article/pii/S0165232X23002872

Minor Comments (with line numbers for reference):
96-97: Please choose either theta or LWC and be consistent throughout. I think given all the equations in this manuscript theta is the better option.
97: I agree that volumetric is the best way to discuss LWC, but you go back to by mass in section 3.3 and then to volumetric again. This can be confusing to readers not familiar with the major differences, especially looking at the error in figures 5 and 6. By volume gives essentially ml of water per volume while mass LWC really is dependent on the snow density and can have a huge difference in the actual amount of water in the sample.
102: “in EQ.(1) is shown the energy balance equation” please re-write.
105: no need for comma after “where”
106: L, rho_w, and E don’t actually appear in equation 1 so should not be defined here.
121: “This imply accounting” please correct typo, though this sentence may not be necessary.
122-124: I do not agree that radiation is negligible. During my development of my own melt calorimetry protocol I had some prototype calorimeters and found the temperature did not settle out very well when in the sun. Sometimes it is difficult to keep the calorimeter shaded in a shallow prairie snowpack, so I think this point could be better emphasized. I found myself having to remind others about this necessary step when in the field as it is easy to forget when not in a deeper pit. My experiences may have been because it was a cheaper prototype calorimeter prior to the one I developed and currently use, but I still think shading is an important step for these types of measurements for readers to know about.
138-146: This paragraph seems unnecessary. A general outline of the paper was given earlier, but an outline paragraph for every section unnecessarily lengthens the manuscript. I think the headings and sub-headings do a good job of telling me what is to come.
140: “reveling”
178: “Colbeck” should be outside of the parentheses the way this sentence is written.
179: Why assuming 200 cc? I understand it is because of the box cutter sampler, but please state this.
181: why 366 kg/m3? This seems like an odd choice for an arbitrary number in evaluating equations.
185: These are very precise measurements. While I agree that these are needed for accurate calorimetry, it would be nice to also show how inaccurate calorimetry becomes when scale precision is 1.0 g and T is 1.0 deg_C as this is what many researchers could have in standard pit kits. This may drive home the point that specific instruments are necessary for calorimetry.
187: 2 cc translates to 1% which is not supported by any studies, as mentioned. I agree that this level of accuracy can likely be achieved in nice uniform layers. However, in some fresh snow, depth hoar, or where an ice lens or melt-freeze crust is present this level of accuracy will be difficult to achieve. I think something more like 5% or maybe more. It will also certainly depend on the experience level of the user.
192: “notable practical advantages” Yes! I completely agree and this is why I use this method, too.
209-210: I don’t think the discussion about artificially introducing LWC to snow is necessary here.
218: How do you know the temperature of the ice cubes? This seems like a pretty critical part of this experiment and it is not clear how it is known or what range of ice cube temperatures were used.
237-242: This is one example of discussion points being made in the middle of methods that can make it difficult to follow. It also makes it difficult to find specifics of the methods if I want to go back as it unnecessarily lengthens the methods.
244: What was the windspeed from the fan that produced this much error?
250-251: So, it was snow samples and not ice cubes? This is confusing as equation 22 is for an ice cube. This part of the manuscript is unclear on what is being done. How does this specifically translate to error in LWC?
268: source or sources?
287-288: “water saturation on top of ice layers” could use a citation.
291: would this 18 cm depth be inserted horizontally or vertically? In my experiences, horizontal measurements of LWC on pit faces may overestimate/underestimate the LWC of some layers because water kept above a barrier that is destroyed by digging the pit will then freely drain down the pit face. This is often a very difficult process to notice unless very careful attention to this specific process is made.
305: “a particular attention”
317: it seems overly redundant to use LWC theta.
317: early on in the manuscript the authors mentioned that theta would be kept at volumetric. Now it switches back to by mass. By mass is more dependent upon snow density, so volumetric can be better to use for LWC analyses. Either way, please be consistent.
321: please specify box cutter here.
321: “18 cm^3” should probably be just cm correct?
322-323: is one of the dimensions only filled to 2 cm depth or is it 2 cm short? This statement is confusing here. Also, this further supports an increased uncertainty in volume estimates since a 10% error in volume results in only 0.1% error in LWC. However, this 0.1% error is by mass LWC instead of volumetric LWC? Please also explain and quantify how the volume error translates into a snow density error that propagates into the volumetric LWC error?
325: Why would the mass be off by a few grams? In wind it was only off by 1.5 grams, correct?
Figures 5 and 6: Please convert to volumetric water content as the error shown here would change for different densities of snow.
352: Please specify that you developed these values yourself as it currently reads like they are available from the manufacturer, which they are not.
354: What make and model of thermometer did you use?
355: what make and model of scale did you use?
361: Why must the shape and size of the sampler match the calorimeter? Didn’t you use a box cutter sampler with a round calorimeter bottle? As long as the sampler is smaller than the opening for the calorimeter you should be able to easily and quickly get the sample into the calorimeter.
363: As mentioned earlier, please further emphasize the need for protection from solar radiation.
371-372: This 200 g of water is assuming a relatively high snow density of 500 kg/m^2, correct? I think a more general statement could be made where this will depend on the expected or measured density of the snow layer. For a density of 330 kg/m^3, which is not unreasonable to expect, this would result in an R value of 3. Lesser densities of upper layers or fresh snow would then increase to even higher R values where you mention we should try to avoid.
Figure 7 caption: “the insulated container where heat exchange occurs” – why not just say calorimeter. Also, the site and denoth meter have not been introduced in the text yet.
368-383: These procedures do not appear to be much different from Kawashima et al., 1998. Some specific volumes or masses are different, but the procedure is essentially identical when combined with a standard snow pit procedures.
388: “accuracy” was not really tested, and I don’t think that it can be. “reliability” or consistency with other methods was testes qualitatively, though.
405: How did you shield things from the sun and wind in a 50 cm snowpack? I imagine that completely shading the calorimeter was difficult at these depths, or at least that is what I have found to be the case.
406: This doesn't add up. June 16 is 123 days after Feb. 14 which would be at least 60 measurements if performed every second day. Is it every 3 or 4 days, basically twice a week?
408: What does SSA add to this study? It seems to only be distracting and adding length to an already long manuscript.
421: similar comment about NIR. While the images are cool, I think the crystal type is more informative/valuable to the story of this study.
431-432: Depends on what you mean by retention capacity. Many studies assume a value of 0.02 retention as the retained after naturally drained (certainly with 0.04 or 0.05 as the maximum), but I am not sure if that is what you mean here since the term is not defined and can mean different things in different disciplines. Maybe remove this comment.
451: What is meant by “the air temperature stood at 1.8 cm”?
458: “loose and coarse” so I assume you are referring to depth hoar. This is an example of what I mention earlier about increasing the error of snow volumetric sampling for certain crystal forms.
Figure 10 caption: confusing phrase “in the end it is reported a scheme of the profile” but I really like the addition of crystal form over NIR.
Appendix A: When you found the properties of your calorimeter, did you use a set of standard methods to determine material properties that you could cite?
Again, I would like to emphasize that I really like this study and these comments are meant to be constructive.
I am happy to discuss any of these points in the public forum or privately. Feel free to reach out with any questions: Ryan.Webb@uwyo.edu
-Ryan Webb
Citation: https://doi.org/10.5194/egusphere-2023-2892-RC1
RC2: 'Comment on egusphere-2023-2892', Jeff Dozier, 23 Jan 2024

Review of Barella et al., “Unlocking the potential of melting calorimetry: a field protocol for liquid water content measurement in snow”
I’m in agreement with the other referee’s (Ryan Webb) remarks.
Measurement of the liquid water content in snow is important because of the myriad of ways that water affects snow’s electromagnetic and geophysical properties. Mostly now, field researchers use an electromagnetic approach, measuring snow permittivity and applying the Maxwell-Garnett mixing rule of water in dry snow for an assumed prolate spheroidal shape for the water inclusions. Although this electromagnetic method enables rapid sampling, a direct measurement is still useful for validation, especially in the field.
This paper by Barella et al. makes a case that melting calorimetry is comparable in accuracy and convenience to freezing calorimetry. However, the contribution of the paper to what we already know is rather modest. It mostly reinforces the analysis by Colbeck (1978), although it disputes Colbeck’s conclusion that melting calorimetry is too inaccurate to use in the field. The paper also emphasizes the importance of accounting for heat transfer from the calorimeter itself, but again that knowledge was previously articulated by Fasani et al. (2023).
Therefore, this paper’s contribution is perhaps too marginal to warrant publication. The described experiment with untrained users (to identify and perhaps anticipate errors in field measurements) is compromised by using ice cubes instead of snow, whereas part of the likely error in the field involves the handling of the snow sample.
As a review paper, the shortcoming is that it only compares the melting and freezing calorimetric methods, whereas the dilution method described by Davis et al. (1985) would appear to take advantage of the analysis throughout the process being done at 0°C. In contrast, both melting and freezing calorimetry require fluids that are much warmer or colder than the snow sample (i.e., ±40°C) thereby needing much care to protect the analysis from heat transfer between the calorimeter and the environment. As a review paper, therefore, the analysis should include other direct methods of measuring liquid water content in snow (Davis et al., 1985; Fisk, 1986).
The paper needs substantial rewriting. The Abstract for example reads as a teaser exclaiming the benefits of melting calorimetry but not providing evidence about accuracy and uncertainty. The paper itself has some of this information, but the Abstract should provide more than a headline.
Finally, the E term (calorimeter constant) appears in Equations (2) and (4), but not in the driving Equations (1) and (3). Thus the linkages from (1) to (2) or from (3) to (4) are not clear.
Citations in the review
Colbeck, S. C.: The difficulties of measuring the water saturation and porosity of snow, Journal of Glaciology, 20, 189-201, https://doi.org/10.3189/S0022143000198089, 1978.
Davis, R. E., Dozier, J., LaChapelle, E. R., and Perla, R.: Field and laboratory measurements of snow liquid water by dilution, Water Resources Research, 21, 1415-1420, https://doi.org/10.1029/WR021i009p01415, 1985.
Fasani, D., Cernuschi, F., and Colombo, L. P. M.: Calorimetric determination of wet snow liquid water content: The effect of test conditions on the calorimeter constant and its impact on the measurement uncertainty, Cold Regions Science and Technology, 214, 103959, https://doi.org/10.1016/j.coldregions.2023.103959, 2023.
Fisk, D.: Method of measuring liquid water mass fraction of snow by alcohol solution, Journal of Glaciology, 32, 538-539, https://doi.org/10.3189/S0022143000012272, 1986.

Citation: https://doi.org/10.5194/egusphere-2023-2892-RC2

Riccardo Barella, Mathias Bavay, Francesca Carletti, Nicola Ciapponi, Valentina Premier, and Carlo Marin

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Short summary

Unlocking the potential of melting calorimetry, traditionally confined to school labs, this paper demonstrates its application in the field for accurate measurement of liquid water content in snow. Dispelling misconceptions about measurement uncertainty, it provide a robust protocol and quantifies associated uncertainties. The findings endorse the broader adoption of melting calorimetry for quantification of snow liquid water content in operational context.


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