the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
SnowPappus v1.0, a blowing-snow model for large-scale applications of Crocus snow scheme
Matthieu Baron
Ange Haddjeri
Matthieu Lafaysse
Louis Le Toumelin
Vincent Vionnet
Mathieu Fructus
Abstract. Wind-induced snow transport has a strong influence on snow spatial variability especially at spatial scales between 1 and 500 m in alpine environments. Thus, the evolution of snow modelling systems towards 100–500 m resolutions requires representing this process. We developed SnowPappus, a parsimonious blowing snow model coupled to the Crocus state-of-the-art snow model, able to be operated over large domains and entire snow seasons. SnowPappus simulates blowing snow occurrence, horizontal transport flux and sublimation rate on each grid cell as a function of 2D atmospheric forcing and snow surface properties. Then, it computes a mass balance using an upwind scheme to provide eroded or accumulated snow amounts to Crocus. Parameterizations used to represent the different processes are described in detail and discussed against existing literature. A point-scale evaluation of blowing snow fluxes was conducted, mainly at the Col du Lac Blanc observatory in French Alps. Blowing snow occurrence evaluation showed SnowPappus performs as well as a currently operational scheme. Evaluation of the simulated suspension fluxes highlighted a strong sensitivity to the suspended particles terminal fall speed. Proper calibrations allows the model to reproduce the correct order of magnitude of the mass flux in the suspension layer. Numerical performances of gridded simulations of Crocus coupled with SnowPappus were assessed, showing the feasibility of using it for operational snow forecast at the scale of the entire French Alps.
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Matthieu Baron et al.
Status: final response (author comments only)
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RC1: 'Comment on gmd-2023-43', Anonymous Referee #1, 07 Jun 2023
There are many 1D models of blowing snow, several 2D models (operating on decametre grid scales as far back as the 1990s), and even 3D coupled snow-atmosphere models. An operational model that can be run on large scales is certainly of interest. The authors give a fair summary of previous work and a nearly complete description of the model being introduced. The paper is very long, however, for the amount of original material being presented; some of this is due to repetition and poor organization of material. Having said that “Blowing snow occurrence evaluation showed SnowPappus performs as well as a currently operational scheme” in the abstract, there needs to be a statement about the need and benefits for SnowPappus. There is no evaluation of the model in large-scale applications beyond demonstrating its computational feasibility. But the main problem is that this manuscript requires major copy editing for clarity and concision, beyond what can be achieved in review.
I will expect to have more scientific comments on an easier to read revision, but here are a few corrections that I have noted:
There is, I think, a u* missing in equation 13
For reproducibility, quoting the values of F(T), A and B in equations 25 and 26 would save the reader some cross referencing. \mu_{satc} and Rh_i are essentially the same thing. Some signposting would help anyone hoping to find the SnowPappus code in the extensive SURFEX repository.
Wind is measured at Huez and Chambon, so why no simulations forced by observed wind speed in figure 10?
Red points masked by the legend in figure 12a appear pink. Move the legend.
Vincent Vionnet is a co-author of this paper, so it should not be necessary to be so speculative about differences from Vionnet et al. (2018) in section 5.1.Citation: https://doi.org/10.5194/gmd-2023-43-RC1 - AC1: 'Reply on RC1', Matthieu Baron, 30 Aug 2023
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RC2: 'Comment on gmd-2023-43', Anonymous Referee #2, 12 Jun 2023
The manuscript “SnowPappus v1.0, a blowing-snow model for large-scale applications of Crocus snow scheme“ by Baron et al., presents a model development for the Crocus snow model to include drifting snow processes. Given the operational applications of Crocus, it potentially is an important step forward. This would warrant publication in a journal like GMD. However, having said that, I think that the major drawback of the current manuscript is that the goal (which is somewhat implicitly stated in the introduction) is not corroborated by the right validation data to determine if the model developments regarding the drifting snow module are actually an improvement. In other words, I interpret the goal of the model development to be to better capture the spatial distribution of snow (l.23-28). However, the actual goal stated by the authors in the Introduction is vague (l.51): “to carry out simulations at the scale of the French Alps.” One would expect here to read something like: “to carry out simulations that improve the spatial distribution of snow depth at the scale of the French alps”. The only validation data presented are the blowing snow measurements, which are point measurements. This kind of point validation data makes it hard to justify if the spatially explicit, 2D treatment of drifting snow is in fact useful. However, if the only goal is to represent drifting snow mass fluxes, it would be necessary to evaluate if a 2D/3D approach is really necessary, or if simply the 1D approach, calculating mass fluxes based on snow cover properties and wind speed is sufficient (i.e, applying Eq. 22) to reproduce that.
I also would like to stress here that I think that for operational applications, there should also be a demand by the operational users for any validation of model output that is going to be used in an operational product. How would an operational team judge simulated spatial patterns of snow depth when they cannot be certain how well the model reproduces those? Observed blowing snow fluxes at only three points in the domain hardly provide confidence that spatial patterns of snow deposition are in fact correctly reproduced.
Note that drifting snow also impacts the snow microstructure and density profiles by forming wind slabs. This did not seem to be the focus of the authors, but it would require snow pits to validate the results. In any case, the Introduction should discuss this snow microstructural aspect in more depth, I think.
So unfortunately, I think that this is a more serious flaw of the study that makes it hard to further judge the study for possible publication. If I were to recommend major revisions, I would need to see a path forward for how revisions, including new analysis or simulations, could better support the conclusions. But since to me it is not clear at this point what the goal of the model development is, it is very hard to judge what is needed and if it can be deemed feasible. I think either the focus needs to be on the concentration profiles at 1D simulations, and compare those with observations. Or include observations of spatial patterns of snow depth to investigate to what extent the model reproduces those patterns. However, all these options require major redesign of the study and a big overhaul of the manuscript.
Another major concern is the length of the paper, which I think is mainly a result of insufficient organization and logic. On occasion there is too much detail given, and some discussion is too spread out. For example, Section 2.2.1 treats "Theoretical background", but section 2.3.2 also reads like theoretical background. So while reading, the manuscript is jumping back and forth between theoretical considerations, and implementation details, which makes it somewhat cumbersome to read and follow. But the manuscript would need to be shortened massively and bring its length more in line with the amount of unique content and validation data. Otherwise, a lot of detail is provided which is not helpful to interpret the results. For example, the discussion on sublimation stand all by itself. It is not clear at all how it impacts the simulations.
l.76-77: "The ability of Crocus to distinguish different snow types at the surface may be an opportunity for the simulation of snow transport (Guyomarc’h and Mérindol, 1998; Lehning et al., 2000)." is vague. Do authors aim to validate this in their study or not?
On a final note, given that Vincent Vionnet is listed as co-author, it is actually very strange to read:
L.790-791: “precise temporal window within the year of Vionnet et al. (2018) which was not given in their article and may differ from ours” and l.792: “We could retrieve the original simulation outputs of Vionnet et al. (2018)”. It shouldn’t have been so problematic to resolve these issues, since Vincent Vionnet is co-author. In fact, given his co-authorship, a much more solid discussion of the SnowPappus results with his earlier work is expected at this point.
Citation: https://doi.org/10.5194/gmd-2023-43-RC2 - AC2: 'Reply on RC2', Matthieu Baron, 30 Aug 2023
Matthieu Baron et al.
Data sets
supplementary to "SnowPappus v1.0, a blowing-snow model for large-scale applications of Crocus snow scheme" , 2D wind forcing Matthieu Baron, Ange Haddjeri, Matthieu Lafaysse, Louis le Toumelin, Vincent Vionnet, and Mathieu Fructus https://doi.org/10.5281/zenodo.7681661
Supplementary material to "SnowPappus v1.0, a blowing-snow model for large-scale applications of Crocus snow scheme" Matthieu Baron, Ange Haddjeri, Matthieu Lafaysse, Louis le Toumelin, Vincent Vionnet, and Mathieu Fructus https://doi.org/10.5281/zenodo.7681551
Model code and software
Supplementary to "SnowPappus v1.0, a blowing-snow model for large-scale applications of Crocus snow scheme" : SURFEX codes and dependancies Matthieu Baron, Ange Haddjeri, Matthieu Lafaysse, Louis le Toumelin, Vincent Vionnet, and Mathieu Fructus https://doi.org/10.5281/zenodo.7687821
Matthieu Baron et al.
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