the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 04 Mar 2024
A Global land snow scheme (GLASS) v1.0 for the GFDL Earth System Model: Formulation and evaluation at instrumented sites
Abstract. Snowpack modulates water storage over extended land regions, and at the same time plays a central role in the surface albedo feedback, impacting the climate system energy balance. Despite the complexity of snow processes and their importance for both land hydrology and global climate, several state-of-the-art land surface models and Earth System Models still employ relatively simple descriptions of snowpack dynamics. In this study we present a newly-developed snow scheme tailored to the Geophysical Fluid Dynamics Laboratory (GFDL) Land Model version 4.1. This new snowpack model, named GLASS ("Global LAnd-Snow Scheme"), includes a refined and dynamical vertical layering snow structure which allows us to track in each snow layer the temporal evolution of snow grain properties, while at the same time limiting the model computational expense, as necessary for a model suited to global-scale climate simulations. In GLASS, the evolution of snow grain size and shape is explicitly resolved, with implications for predicted bulk snow properties, as they directly impact snow depth, snow thermal conductivity and optical properties. Here we describe the physical processes in GLASS and their implementation, as well as the interactions with other surface processes and the land-atmosphere coupling in the GFDL Earth System Model. The performance of GLASS is tested over 10 experimental sites, where in-situ observations allow for a comprehensive model evaluation. We find that, when compared to previous version of GFDL snow model, GLASS improves predictions of seasonal snow water equivalent and soil temperature under the snowpack.
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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
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Status: closed
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CEC1: 'Comment on egusphere-2024-506', Juan Antonio Añel, 28 Mar 2024
Dear authors,
Unfortunately, after checking your manuscript, it has come to our attention that it does not comply with our "Code and Data Policy".
https://www.geoscientific-model-development.net/policies/code_and_data_policy.htmlFirst, the "Code and Data Availability" section in your manuscript points out two Git repositories. Git repositories are not valid for scientific publication. This is clearly stated in our policy. Moreover, the links that you provide to the repositories do not work. At least the repositories do not load when writing this comment.
You have included a Zenodo repository in the information for your manuscript. However, this is not visible or available for readers and anyone who would like to comment on your manuscript during the Discussions stage, therefore impeding a proper evaluation of it by the community members. To partially solve this issue, I publish here the information for the repository containing code and data here:Code for the Global Land Snow Scheme (GLASS) v1.0.0: https://zenodo.org/records/10681526
However, in any potentially reviewed version of your work, you must include the Zenodo repository information (link and DOI) in the "Code and Data Availability" section and remove the links to the Git repositories.
Secondly, you have developed a snowpack model run as part of the GFDL ESM 4.1. Therefore, it is only possible to replicate your work with the complete GFDL ESM 4.1 code, as your code is run as part of it. This means that you must include a new repository (e.g., again Zenodo - or any other acceptable according to our policy) and its DOI in the "Code and Data Availability" section with your work. Therefore, please publish your code in one of the appropriate repositories and reply to this comment with the relevant information (link and DOI) as soon as possible, as it should be available before the Discussions stage. Later, if your manuscript is accepted for publication or goes through a new round of reviews, you must include the information in the text of the manuscript.
If you do not fix this problem and promptly reply to this comment with the requested information, we will have to reject your manuscript for publication in our journal. I should note that, given this lack of compliance with our policy, your manuscript should not have been accepted in Discussions. Therefore, the current situation with your manuscript is irregular.Juan A. Añel
Geosci. Model Dev. Executive EditorCitation: https://doi.org/10.5194/egusphere-2024-506-CEC1 -
AC1: 'Reply on CEC1', Enrico Zorzetto, 01 Apr 2024
Dear Editor,
Thank you for your comment regarding our manuscript.
About the first point raised in the comment: We would like to note that the Zenodo repository with our model software and data is already reported in the manuscript in the "code and data availability" statement at line 745, which reads:
"Code and data availability. The source code of GLASS v1.0 as well as the input data and model output are shared in a public repository:https://zenodo.org/records/10681526"
The mention of the two git repositories at line 675 of the manuscript is erroneous and should have been removed in the final version of the manuscript. They do not contain any additional information with respect to the Zenodo repository and were used only as a placeholder before submitting our software and data to the Zenodo repository. We will be sure to remove mention of these git repositories in any updated version of the manuscript, and hope readers and reviewers will refer to the existing code and data availability statement at line 745 of the current manuscript, which contains a link to the Zenodo repository with data and software. The same DOI is reported in the online assets.
About the second point raised in the comment, concerning the model code of GLASS v1.0 within ESM4.1: The snow model we developed is indeed a component of ESM4.1. We did not include the entire ESM4.1 source code in our repository as this is a published software appropriately referenced in the manuscript. The Zenodo repository mentioned in the manuscript contains the new code component as well as new input data developed as part of this work.
As requested, we have now submitted a new version of our software on Zenodo which, in addition to the snow model GLASS developed in our work, includes the entire land model (LM4) used in our work. This new repository includes the entire codebase used in our study, as well as the input data used. The DOI of this updated repository, which we will include in any revised version of the manuscript, is reported here:
https://zenodo.org/records/10901373Please let me know whether this answer is satisfactory and whether any additional clarification may be needed.
Enrico Zorzetto,
On behalf of all authors
Citation: https://doi.org/10.5194/egusphere-2024-506-AC1 -
CEC2: 'Reply on AC1', Juan Antonio Añel, 01 Apr 2024
Dear authors,
Thanks for your reply. Indeed, it is quite unfortunate that you have included erroneously two "Code and Data Availability" sections in your manuscript. To clarify it, the correct place for this section is where in the preprint is currently the information about the Git repositories, not at the bottom of the manuscript.
Regarding the ESM4.1 code, unfortunately, your reply does not comply with our policy. It is my understanding that the land model is run as a module of the full model, and that it is what you have used for your work. Therefore, you have to deposit in the repository the full model, not only the land component. That is, the repository must contain all the software that you have used to perform your work.
Juan A. Añel
Geosci. Model Dev. Executive Editor
Citation: https://doi.org/10.5194/egusphere-2024-506-CEC2 -
AC2: 'Reply on CEC2', Enrico Zorzetto, 01 Apr 2024
With respect to the content of the repository:
The code we provide in the revised repository (the entire land model of ESM4.1 including the snow model GLASS) is exactly the source code we compile and run to obtain the results in the paper. There is no additional source code required to replicate our results. As mentioned in the paper and in the documentation of the Zenodo repository, what we present in the manuscript is the result of a standalone land model simulation. The atmospheric forcing is observed rather than modeled, and we include the input atmospheric data we used for this purpose as part of the code and data release. We will make sure to further clarify this point in the revised manuscript.
Enrico Zorzetto,
on behalf of all authors
Citation: https://doi.org/10.5194/egusphere-2024-506-AC2 -
CEC3: 'Reply on AC2', Juan Antonio Añel, 02 Apr 2024
Dear authros,
Thanks for the clarification. Not being the topical editor handling your manuscript, I had not read it thoroughly and was unaware that the atmosphere was observed data. This way, we can consider your manuscript in compliance with our journal code policy.
Regards,
Juan A. Añel
Geosci. Model Dev. Executive Editor
Citation: https://doi.org/10.5194/egusphere-2024-506-CEC3
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CEC3: 'Reply on AC2', Juan Antonio Añel, 02 Apr 2024
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AC2: 'Reply on CEC2', Enrico Zorzetto, 01 Apr 2024
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CEC2: 'Reply on AC1', Juan Antonio Añel, 01 Apr 2024
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AC1: 'Reply on CEC1', Enrico Zorzetto, 01 Apr 2024
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RC1: 'Comment on egusphere-2024-506', Anonymous Referee #1, 30 Apr 2024
General comments
This paper presented a refined snow model (GLASS) and its implementation in the GFDL Earth system model. The GLASS model provides a detailed representation of the snowpack structure to track the evolution of snow grain properties in each snow layer. Testing cases were conducted using a reference dataset to evaluate the model performance. The results show that this new model improves the estimation of the soil temperature and have a better representation of SWE and daily snow albedo. The contribution of this work is worthy of publication, but it requires additional edits. Please see the detailed comments below.
Detailed comments
- Pg 2 line 27: In the sentence “ranging from and watershed-scale ….”, remove “and”.
- Pg 2 line 53-54: Please change the sentence as “It not only impacts the hydrological response but also interacts with the atmosphere through surface temperature and reflectivity.”
- Section 3: Please enhance the notation used for the functions shown in this section. Some terms within the functions are not provided with full names and units when they first appear in this paper. The comments below only listed several places that need edits. So please review each function in this paper and make sure clear information is provided. This will help readers to understand and/or incorporate those functions into their model implementations.
- Pg 7 line 179-185: Is the method for optimizing the vertical layers developed by the authors, or is it adapted from existing research? If it is developed by the authors, please provide the rationale behind the presented method. Specifically, why does it need to first define an optimal distribution of the snow layer and then compare it with the actual snow layers for adjustment? What’s the benefits or reasons for it? Also, please explain why the optimal distribution of snow layers is defined as indicated in line 180-182. While the text describes how the optimal layers are defined, it lacks an explanation for why these specific numbers/parameters were chosen. Is there any scientific support for them?
- Pg 11 function 13: please specify what “TF”, “cl” and “λ” means.
- Pg 11 function 14: please specify what “L0” means.
- Pg 11 function 15: please specify what “cs” means.
- Pg 11 function 16: please specify what “Lvap” means.
- Pg 11 function 17: please specify what “Isn,s” means. Also, does this term need to be shown in the Figure 1?
- Pg 17 line 450: remove “)” before the first comma.
- Pg 17 line 451: change “byJordan” as “by Jordan”.
- Pg 19 line 494: please spell the full name for “GSWP3” and add citation or URL link for this dataset (if available).
- Pg 25 line 575: please reference Figure 10 at the end of the first sentence in this paragraph.
- Pg 27 line 591: please change “Figure 10” as “Figure 11”.
- Pg 32 line 637: In the paper citation, remove “?” or add the correct citation.
- Pg 33 line 660: add “than” in the sentence. (“temperature predictions were on average higher *than* those obtained…”).
Citation: https://doi.org/10.5194/egusphere-2024-506-RC1 -
AC3: 'Reply on RC1', Enrico Zorzetto, 25 Jun 2024
We thank the reviewer for the comments on the manuscript. We will provide a point-by-point response to these comments with our revised manuscript submission.
Citation: https://doi.org/10.5194/egusphere-2024-506-AC3
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RC2: 'Comment on egusphere-2024-506', Anonymous Referee #2, 18 Jun 2024
The manuscript: “A Global land snow scheme (GLASS) v1.0 for the GFDL Earth System Model: Formulation and evaluation at instrumented sites” by Zorzetto et al. describes a new, physics-based snow scheme to be used in land surface schemes. The scheme includes many physics-based snow processes like heat conduction, compaction and liquid water flow, which improve the performance in some key metrics like SWE, snow depth, etc. The model is validated on a high quality dataset of snow sites across the globe, in different climate regimes. Those testing sites include both canopy and non-canopy sites. The tests thus are extensive. I think the manuscript suits the journal well, and could be published. But there are quite a few issues that need attention. Mostly to improve clarity, but there are also a few occasions where the source of parameterizations is not really clear, as I'll point out below.
Major points:
- Abstract: The abstract (as well as the conclusions for that matter) could benefit from some more quantitative measures of the improvements found. The only conclusion of what the improvements bring is the one line at the end: “We find that, when compared to previous version of GFDL snow model, GLASS improves predictions of seasonal snow water equivalent and soil temperature under the snowpack.” I think this needs to be expanded on with some quantitative results. Similarly for the conclusions.
- Section 3.2: I have read the section multiple times, but I didn’t manage to comprehend the differences between implicit and explicit melt. I would expect dB/dT_g, the denominator in Eq. 6 to be 0 when the surface is in melting conditions. The sentence in L235/236: “The new temperature … heat diffusion process.” I did not understand how this works. The terms are not included in Eq. 12 for example. I think that this section needs some attention and rewriting, to improve clarity.
- Section 3.3: Also here, I think some improvements can be made. Eq. 14 is supposed to represent Eq. 5, as per the line preceding the equation. But then G in eq. 5 is not included, while the heat advection from liquid water is included in Eq. 14, which is not listed in Eq. 5. I assume that in Eq. 5, this term would take the role of energy advected in rain water. In fact Eq. 16 is basically Eq. 5, just with the term G on the left hand side, and including the energy from rain. Eq. 14 and Eq. 15 then seem superfluous. I think this all needs to be made more consistent, for clarity.
- Section 3.7: It is written: “Therefore, this nonlinear interaction between heat diffusion and heat flux due to sublimating snow is accounted for by correcting the layer’s temperature to ensure that energy is conserved when both processes are considered to occur simultaneously.”
This sounds like the model is accounting for the energy associated with latent heat twice. If it is included in the surface energy balance (Eq. 5), then the only thing that sublimation would need to take care of, is the mass transfer that is associated with the latent heat exchange. There is no need to additionally modify the temperature of the layer. That was already taken care of via the latent heat flux in the upper boundary condition.
- Generally speaking, I think publications on model schemes should report on the mass and energy balance error they achieve. Thus, summing up all surface and soil energy fluxes, and comparing with the internal energy change of the snow cover. Similarly, summing up all mass fluxes at the upper and lower boundary, and comparing with the change in SWE in the model. This generally gives a good insight in the numerical quality of the model. I know it can be a lot of work to set up, but I think it’s almost mandatory when discussing a numerical scheme.
- Lastly, the scheme is only evaluated on the point scale, while its intended use is for the large scale (global) simulations. For the manuscript, this is fine, and a bit of discussion is provided here, but it feels too short. Is the additional computational and memory consumption from the GLASS scheme acceptable for large-scale simulations? For example, it is risky to have a variable number of snow layers without an upper bound, since that makes it hard to control memory usage in large models with many grid points. In the Conclusions, it is briefly mentioned that it is within computation constraints, but what constraints were set here for the model development?
Minor comments
- Generally, a few language corrections are required. For example, articles seem to be often missing. For example L1: “Snowpack modulates”. I think this should be “The snowpack modulates” or “Snowpacks modulate”. Similar errors are present throughout. Also some wrongly placed parentheses for citations are present, like for example L306: “the parameterization by (Yen, 1981)” → “the parameterization by Yen (1981)”
- L49 “it has been recognized”: a phrasing like that calls for appropriate citations. Please add some.
- L151: “Design of snow layers” is unclear, please rephrase.
- L194-200: This part is very hard to follow. Any chance to rephrase?
- Fig. 1 caption “solid contributions to runoff”: not sure what is meant here, how can snow or ice runoff?
- L212: This is a bit confusing. In Section 3.7, it is argued that “we assume that the entire water vapor flux comes from sublimation”. However, in Eq. 5, latent heat is associated with Lg, which is defined as the latent heat of evaporation. I would argue that if only sublimation is considered, this must be the latent heat of sublimation. Furthermore, one could argue that in reality, evaporation takes precedence over sublimation, because of the smaller latent heat associated with it. Why is liquid water evaporation neglected?
- L341-343: Please try to find alternative wording. I just don’t comprehend the issue that is being described. Which temperature difference is this about?
- L389: “look-up” table: how is this constructed, and where can it be found?
- Eq. 35-38: Where do these equations come from? And why are Eq. 37 and 38 the same? Generally, sphericity and dendricity change in opposite directions, so both change rates having the same sign is unusual.
- Eq. 39: how are the coefficients b0, b1, b2 determined? Are these related to snow properties, as described in L433-436? This is not so clear.
- Eq. 40: R0 doesn’t seem to be defined? How determined?
- Section 3.13: I like the flow chart, but the readability of this section could be improved if the different elements in the flow chart are numbered or labeled (i), (ii), (iii) for example, such that the processes in the text can be assigned those labels or numbers to. This allows the text to be more precisely linked to the figure.
- L477: “Finally, we re-layer …” I don’t think this is shown in Fig. 2, but I think it should.
- L505-508: I suggest this sentence, it’s hard to follow now.
- L498-500: This is somewhat poorly phrased. At Col de Porte, the measurements are done at a constant height above the snow surface. Thus, the correction is done at the data level. For the other sites, the model doesn’t correct the height of the measurements for the presence of a snowcover, when calculating heat fluxes. I think the phrasing should be more along the lines of this.
- L532-535: It’s somewhat confusingly written. The sentence: “For example, for the swa site with some of the largest differences between the two models, the BRDF albedo scheme used in LM-CM leads to a significant underestimation of daily albedo (Fig. 5A).” Could be followed by “This underestimation is not present in the GLASS albedo scheme.”
Then, the sentence: “For the three BERMS forested sites (ojp, obs, and oas), where the model simulates the effects of multi-layer canopy on radiative fluxes, the SWE predictions of the two models are much closer (Fig. 5B). However, in this case modelled and observed albedo values differ significantly.” Could be added “differ significantly in both GLASS and CM”.
- L549: I would avoid the term “snow amount”, because it can cause confusion if it’s about snow height or SWE.
- Fig. 5 & 7 / Section 5.2: In the discussion on albedo, it’s striking that when there is no snow, the model has a consistent bias compared to observations (looking at the summer months in Fig. 5). I know that it is discussed in the manuscript, but maybe it’s better to restrict comparing albedo to the months with snow cover only in panel 7C. The GLASS model modifications seem to impact only snow physics, and not soil physics. Thus, the summer months are less relevant for the manuscript.
- L567-573: The discussion in L584-589 needs to be moved closer to L567-573. It could be mentioned more explicitly that an underestimation of surface temperature can also result from an underestimation in near surface density.
- L637: seems to be missing a citation at the “?”
Citation: https://doi.org/10.5194/egusphere-2024-506-RC2 -
AC4: 'Reply on RC2', Enrico Zorzetto, 25 Jun 2024
We thank the reviewer for the comments on the manuscript. We will provide a point-by-point response to these comments with our revised manuscript submission.
Citation: https://doi.org/10.5194/egusphere-2024-506-AC4
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AC4: 'Reply on RC2', Enrico Zorzetto, 25 Jun 2024
Interactive discussion
Status: closed
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CEC1: 'Comment on egusphere-2024-506', Juan Antonio Añel, 28 Mar 2024
Dear authors,
Unfortunately, after checking your manuscript, it has come to our attention that it does not comply with our "Code and Data Policy".
https://www.geoscientific-model-development.net/policies/code_and_data_policy.htmlFirst, the "Code and Data Availability" section in your manuscript points out two Git repositories. Git repositories are not valid for scientific publication. This is clearly stated in our policy. Moreover, the links that you provide to the repositories do not work. At least the repositories do not load when writing this comment.
You have included a Zenodo repository in the information for your manuscript. However, this is not visible or available for readers and anyone who would like to comment on your manuscript during the Discussions stage, therefore impeding a proper evaluation of it by the community members. To partially solve this issue, I publish here the information for the repository containing code and data here:Code for the Global Land Snow Scheme (GLASS) v1.0.0: https://zenodo.org/records/10681526
However, in any potentially reviewed version of your work, you must include the Zenodo repository information (link and DOI) in the "Code and Data Availability" section and remove the links to the Git repositories.
Secondly, you have developed a snowpack model run as part of the GFDL ESM 4.1. Therefore, it is only possible to replicate your work with the complete GFDL ESM 4.1 code, as your code is run as part of it. This means that you must include a new repository (e.g., again Zenodo - or any other acceptable according to our policy) and its DOI in the "Code and Data Availability" section with your work. Therefore, please publish your code in one of the appropriate repositories and reply to this comment with the relevant information (link and DOI) as soon as possible, as it should be available before the Discussions stage. Later, if your manuscript is accepted for publication or goes through a new round of reviews, you must include the information in the text of the manuscript.
If you do not fix this problem and promptly reply to this comment with the requested information, we will have to reject your manuscript for publication in our journal. I should note that, given this lack of compliance with our policy, your manuscript should not have been accepted in Discussions. Therefore, the current situation with your manuscript is irregular.Juan A. Añel
Geosci. Model Dev. Executive EditorCitation: https://doi.org/10.5194/egusphere-2024-506-CEC1 -
AC1: 'Reply on CEC1', Enrico Zorzetto, 01 Apr 2024
Dear Editor,
Thank you for your comment regarding our manuscript.
About the first point raised in the comment: We would like to note that the Zenodo repository with our model software and data is already reported in the manuscript in the "code and data availability" statement at line 745, which reads:
"Code and data availability. The source code of GLASS v1.0 as well as the input data and model output are shared in a public repository:https://zenodo.org/records/10681526"
The mention of the two git repositories at line 675 of the manuscript is erroneous and should have been removed in the final version of the manuscript. They do not contain any additional information with respect to the Zenodo repository and were used only as a placeholder before submitting our software and data to the Zenodo repository. We will be sure to remove mention of these git repositories in any updated version of the manuscript, and hope readers and reviewers will refer to the existing code and data availability statement at line 745 of the current manuscript, which contains a link to the Zenodo repository with data and software. The same DOI is reported in the online assets.
About the second point raised in the comment, concerning the model code of GLASS v1.0 within ESM4.1: The snow model we developed is indeed a component of ESM4.1. We did not include the entire ESM4.1 source code in our repository as this is a published software appropriately referenced in the manuscript. The Zenodo repository mentioned in the manuscript contains the new code component as well as new input data developed as part of this work.
As requested, we have now submitted a new version of our software on Zenodo which, in addition to the snow model GLASS developed in our work, includes the entire land model (LM4) used in our work. This new repository includes the entire codebase used in our study, as well as the input data used. The DOI of this updated repository, which we will include in any revised version of the manuscript, is reported here:
https://zenodo.org/records/10901373Please let me know whether this answer is satisfactory and whether any additional clarification may be needed.
Enrico Zorzetto,
On behalf of all authors
Citation: https://doi.org/10.5194/egusphere-2024-506-AC1 -
CEC2: 'Reply on AC1', Juan Antonio Añel, 01 Apr 2024
Dear authors,
Thanks for your reply. Indeed, it is quite unfortunate that you have included erroneously two "Code and Data Availability" sections in your manuscript. To clarify it, the correct place for this section is where in the preprint is currently the information about the Git repositories, not at the bottom of the manuscript.
Regarding the ESM4.1 code, unfortunately, your reply does not comply with our policy. It is my understanding that the land model is run as a module of the full model, and that it is what you have used for your work. Therefore, you have to deposit in the repository the full model, not only the land component. That is, the repository must contain all the software that you have used to perform your work.
Juan A. Añel
Geosci. Model Dev. Executive Editor
Citation: https://doi.org/10.5194/egusphere-2024-506-CEC2 -
AC2: 'Reply on CEC2', Enrico Zorzetto, 01 Apr 2024
With respect to the content of the repository:
The code we provide in the revised repository (the entire land model of ESM4.1 including the snow model GLASS) is exactly the source code we compile and run to obtain the results in the paper. There is no additional source code required to replicate our results. As mentioned in the paper and in the documentation of the Zenodo repository, what we present in the manuscript is the result of a standalone land model simulation. The atmospheric forcing is observed rather than modeled, and we include the input atmospheric data we used for this purpose as part of the code and data release. We will make sure to further clarify this point in the revised manuscript.
Enrico Zorzetto,
on behalf of all authors
Citation: https://doi.org/10.5194/egusphere-2024-506-AC2 -
CEC3: 'Reply on AC2', Juan Antonio Añel, 02 Apr 2024
Dear authros,
Thanks for the clarification. Not being the topical editor handling your manuscript, I had not read it thoroughly and was unaware that the atmosphere was observed data. This way, we can consider your manuscript in compliance with our journal code policy.
Regards,
Juan A. Añel
Geosci. Model Dev. Executive Editor
Citation: https://doi.org/10.5194/egusphere-2024-506-CEC3
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CEC3: 'Reply on AC2', Juan Antonio Añel, 02 Apr 2024
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AC2: 'Reply on CEC2', Enrico Zorzetto, 01 Apr 2024
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CEC2: 'Reply on AC1', Juan Antonio Añel, 01 Apr 2024
-
AC1: 'Reply on CEC1', Enrico Zorzetto, 01 Apr 2024
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RC1: 'Comment on egusphere-2024-506', Anonymous Referee #1, 30 Apr 2024
General comments
This paper presented a refined snow model (GLASS) and its implementation in the GFDL Earth system model. The GLASS model provides a detailed representation of the snowpack structure to track the evolution of snow grain properties in each snow layer. Testing cases were conducted using a reference dataset to evaluate the model performance. The results show that this new model improves the estimation of the soil temperature and have a better representation of SWE and daily snow albedo. The contribution of this work is worthy of publication, but it requires additional edits. Please see the detailed comments below.
Detailed comments
- Pg 2 line 27: In the sentence “ranging from and watershed-scale ….”, remove “and”.
- Pg 2 line 53-54: Please change the sentence as “It not only impacts the hydrological response but also interacts with the atmosphere through surface temperature and reflectivity.”
- Section 3: Please enhance the notation used for the functions shown in this section. Some terms within the functions are not provided with full names and units when they first appear in this paper. The comments below only listed several places that need edits. So please review each function in this paper and make sure clear information is provided. This will help readers to understand and/or incorporate those functions into their model implementations.
- Pg 7 line 179-185: Is the method for optimizing the vertical layers developed by the authors, or is it adapted from existing research? If it is developed by the authors, please provide the rationale behind the presented method. Specifically, why does it need to first define an optimal distribution of the snow layer and then compare it with the actual snow layers for adjustment? What’s the benefits or reasons for it? Also, please explain why the optimal distribution of snow layers is defined as indicated in line 180-182. While the text describes how the optimal layers are defined, it lacks an explanation for why these specific numbers/parameters were chosen. Is there any scientific support for them?
- Pg 11 function 13: please specify what “TF”, “cl” and “λ” means.
- Pg 11 function 14: please specify what “L0” means.
- Pg 11 function 15: please specify what “cs” means.
- Pg 11 function 16: please specify what “Lvap” means.
- Pg 11 function 17: please specify what “Isn,s” means. Also, does this term need to be shown in the Figure 1?
- Pg 17 line 450: remove “)” before the first comma.
- Pg 17 line 451: change “byJordan” as “by Jordan”.
- Pg 19 line 494: please spell the full name for “GSWP3” and add citation or URL link for this dataset (if available).
- Pg 25 line 575: please reference Figure 10 at the end of the first sentence in this paragraph.
- Pg 27 line 591: please change “Figure 10” as “Figure 11”.
- Pg 32 line 637: In the paper citation, remove “?” or add the correct citation.
- Pg 33 line 660: add “than” in the sentence. (“temperature predictions were on average higher *than* those obtained…”).
Citation: https://doi.org/10.5194/egusphere-2024-506-RC1 -
AC3: 'Reply on RC1', Enrico Zorzetto, 25 Jun 2024
We thank the reviewer for the comments on the manuscript. We will provide a point-by-point response to these comments with our revised manuscript submission.
Citation: https://doi.org/10.5194/egusphere-2024-506-AC3
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RC2: 'Comment on egusphere-2024-506', Anonymous Referee #2, 18 Jun 2024
The manuscript: “A Global land snow scheme (GLASS) v1.0 for the GFDL Earth System Model: Formulation and evaluation at instrumented sites” by Zorzetto et al. describes a new, physics-based snow scheme to be used in land surface schemes. The scheme includes many physics-based snow processes like heat conduction, compaction and liquid water flow, which improve the performance in some key metrics like SWE, snow depth, etc. The model is validated on a high quality dataset of snow sites across the globe, in different climate regimes. Those testing sites include both canopy and non-canopy sites. The tests thus are extensive. I think the manuscript suits the journal well, and could be published. But there are quite a few issues that need attention. Mostly to improve clarity, but there are also a few occasions where the source of parameterizations is not really clear, as I'll point out below.
Major points:
- Abstract: The abstract (as well as the conclusions for that matter) could benefit from some more quantitative measures of the improvements found. The only conclusion of what the improvements bring is the one line at the end: “We find that, when compared to previous version of GFDL snow model, GLASS improves predictions of seasonal snow water equivalent and soil temperature under the snowpack.” I think this needs to be expanded on with some quantitative results. Similarly for the conclusions.
- Section 3.2: I have read the section multiple times, but I didn’t manage to comprehend the differences between implicit and explicit melt. I would expect dB/dT_g, the denominator in Eq. 6 to be 0 when the surface is in melting conditions. The sentence in L235/236: “The new temperature … heat diffusion process.” I did not understand how this works. The terms are not included in Eq. 12 for example. I think that this section needs some attention and rewriting, to improve clarity.
- Section 3.3: Also here, I think some improvements can be made. Eq. 14 is supposed to represent Eq. 5, as per the line preceding the equation. But then G in eq. 5 is not included, while the heat advection from liquid water is included in Eq. 14, which is not listed in Eq. 5. I assume that in Eq. 5, this term would take the role of energy advected in rain water. In fact Eq. 16 is basically Eq. 5, just with the term G on the left hand side, and including the energy from rain. Eq. 14 and Eq. 15 then seem superfluous. I think this all needs to be made more consistent, for clarity.
- Section 3.7: It is written: “Therefore, this nonlinear interaction between heat diffusion and heat flux due to sublimating snow is accounted for by correcting the layer’s temperature to ensure that energy is conserved when both processes are considered to occur simultaneously.”
This sounds like the model is accounting for the energy associated with latent heat twice. If it is included in the surface energy balance (Eq. 5), then the only thing that sublimation would need to take care of, is the mass transfer that is associated with the latent heat exchange. There is no need to additionally modify the temperature of the layer. That was already taken care of via the latent heat flux in the upper boundary condition.
- Generally speaking, I think publications on model schemes should report on the mass and energy balance error they achieve. Thus, summing up all surface and soil energy fluxes, and comparing with the internal energy change of the snow cover. Similarly, summing up all mass fluxes at the upper and lower boundary, and comparing with the change in SWE in the model. This generally gives a good insight in the numerical quality of the model. I know it can be a lot of work to set up, but I think it’s almost mandatory when discussing a numerical scheme.
- Lastly, the scheme is only evaluated on the point scale, while its intended use is for the large scale (global) simulations. For the manuscript, this is fine, and a bit of discussion is provided here, but it feels too short. Is the additional computational and memory consumption from the GLASS scheme acceptable for large-scale simulations? For example, it is risky to have a variable number of snow layers without an upper bound, since that makes it hard to control memory usage in large models with many grid points. In the Conclusions, it is briefly mentioned that it is within computation constraints, but what constraints were set here for the model development?
Minor comments
- Generally, a few language corrections are required. For example, articles seem to be often missing. For example L1: “Snowpack modulates”. I think this should be “The snowpack modulates” or “Snowpacks modulate”. Similar errors are present throughout. Also some wrongly placed parentheses for citations are present, like for example L306: “the parameterization by (Yen, 1981)” → “the parameterization by Yen (1981)”
- L49 “it has been recognized”: a phrasing like that calls for appropriate citations. Please add some.
- L151: “Design of snow layers” is unclear, please rephrase.
- L194-200: This part is very hard to follow. Any chance to rephrase?
- Fig. 1 caption “solid contributions to runoff”: not sure what is meant here, how can snow or ice runoff?
- L212: This is a bit confusing. In Section 3.7, it is argued that “we assume that the entire water vapor flux comes from sublimation”. However, in Eq. 5, latent heat is associated with Lg, which is defined as the latent heat of evaporation. I would argue that if only sublimation is considered, this must be the latent heat of sublimation. Furthermore, one could argue that in reality, evaporation takes precedence over sublimation, because of the smaller latent heat associated with it. Why is liquid water evaporation neglected?
- L341-343: Please try to find alternative wording. I just don’t comprehend the issue that is being described. Which temperature difference is this about?
- L389: “look-up” table: how is this constructed, and where can it be found?
- Eq. 35-38: Where do these equations come from? And why are Eq. 37 and 38 the same? Generally, sphericity and dendricity change in opposite directions, so both change rates having the same sign is unusual.
- Eq. 39: how are the coefficients b0, b1, b2 determined? Are these related to snow properties, as described in L433-436? This is not so clear.
- Eq. 40: R0 doesn’t seem to be defined? How determined?
- Section 3.13: I like the flow chart, but the readability of this section could be improved if the different elements in the flow chart are numbered or labeled (i), (ii), (iii) for example, such that the processes in the text can be assigned those labels or numbers to. This allows the text to be more precisely linked to the figure.
- L477: “Finally, we re-layer …” I don’t think this is shown in Fig. 2, but I think it should.
- L505-508: I suggest this sentence, it’s hard to follow now.
- L498-500: This is somewhat poorly phrased. At Col de Porte, the measurements are done at a constant height above the snow surface. Thus, the correction is done at the data level. For the other sites, the model doesn’t correct the height of the measurements for the presence of a snowcover, when calculating heat fluxes. I think the phrasing should be more along the lines of this.
- L532-535: It’s somewhat confusingly written. The sentence: “For example, for the swa site with some of the largest differences between the two models, the BRDF albedo scheme used in LM-CM leads to a significant underestimation of daily albedo (Fig. 5A).” Could be followed by “This underestimation is not present in the GLASS albedo scheme.”
Then, the sentence: “For the three BERMS forested sites (ojp, obs, and oas), where the model simulates the effects of multi-layer canopy on radiative fluxes, the SWE predictions of the two models are much closer (Fig. 5B). However, in this case modelled and observed albedo values differ significantly.” Could be added “differ significantly in both GLASS and CM”.
- L549: I would avoid the term “snow amount”, because it can cause confusion if it’s about snow height or SWE.
- Fig. 5 & 7 / Section 5.2: In the discussion on albedo, it’s striking that when there is no snow, the model has a consistent bias compared to observations (looking at the summer months in Fig. 5). I know that it is discussed in the manuscript, but maybe it’s better to restrict comparing albedo to the months with snow cover only in panel 7C. The GLASS model modifications seem to impact only snow physics, and not soil physics. Thus, the summer months are less relevant for the manuscript.
- L567-573: The discussion in L584-589 needs to be moved closer to L567-573. It could be mentioned more explicitly that an underestimation of surface temperature can also result from an underestimation in near surface density.
- L637: seems to be missing a citation at the “?”
Citation: https://doi.org/10.5194/egusphere-2024-506-RC2 -
AC4: 'Reply on RC2', Enrico Zorzetto, 25 Jun 2024
We thank the reviewer for the comments on the manuscript. We will provide a point-by-point response to these comments with our revised manuscript submission.
Citation: https://doi.org/10.5194/egusphere-2024-506-AC4
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AC4: 'Reply on RC2', Enrico Zorzetto, 25 Jun 2024
Peer review completion
Journal article(s) based on this preprint
Data sets
A Global Land Snow Scheme (GLASS) v1.0.0 Enrico Zorzetto https://zenodo.org/records/10681526
Model code and software
A Global Land Snow Scheme (GLASS) v1.0.0 Enrico Zorzetto https://zenodo.org/records/10681526
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Sergey Malyshev
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Elena Shevliakova
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
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