Modeling the evolution of the structural anisotropy of snow

Leinss, Silvan; Löwe, Henning; Proksch, Martin; Kontu, Anna

doi:https://doi.org/10.5194/tc-14-51-2020

Articles | Volume 14, issue 1

https://doi.org/10.5194/tc-14-51-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/tc-14-51-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 14, issue 1

Research article

|

14 Jan 2020

Research article |

| 14 Jan 2020

Modeling the evolution of the structural anisotropy of snow

Silvan Leinss, Henning Löwe, Martin Proksch, and Anna Kontu

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Final revised paper (published on 14 Jan 2020)
Supplement to the final revised paper
Preprint (discussion started on 23 Apr 2019)
Supplement to the preprint

Interactive discussion

Status: closed

AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

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- Supplement

RC1: 'Review on "Modeling the Evolution of the Structural Anisotropy of Snow"', Anonymous Referee #1, 21 Jun 2019
- AC1: 'Author final response to comments of Referee #2, tc-2019-63', Silvan Leinss, 23 Aug 2019
- AC2: 'Author final response to comments of Referee #1, tc-2019-63', Silvan Leinss, 23 Aug 2019
RC2: 'Review of tc-2019-63', Anonymous Referee #2, 08 Jul 2019
- AC1: 'Author final response to comments of Referee #2, tc-2019-63', Silvan Leinss, 23 Aug 2019
- AC2: 'Author final response to comments of Referee #1, tc-2019-63', Silvan Leinss, 23 Aug 2019

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision

ED: Publish subject to revisions (further review by editor and referees) (26 Aug 2019) by Guillaume Chambon

AR by Silvan Leinss on behalf of the Authors (07 Oct 2019) Manuscript

ED: Referee Nomination & Report Request started (15 Oct 2019) by Guillaume Chambon

RR by Anonymous Referee #1 (29 Oct 2019)

RR by Anonymous Referee #2 (07 Nov 2019)

Suggestions for revision or reasons for rejection

This paper outlines a new model to track the anisotropic state of the snowpack from non-microstructural parameters commonly available from snowpack models. This model itself is of high importance as it may explain variance in numerous observed macroscale properties, but this paper also contains several additional new findings that merit its immediate publication, namely that settling creates horizontal structures, sample cold storage conditions are adequate and the inequivalence of pc and pex in determining anisotropy

The model provides a good fit to data, and has a clear description of the assumptions used so these are only minor comments:
- Specification of Amin = -0.7. This comes from extrapolation of Figure 5, yet is inconsistent with literature values of -0.3. This discrepancy is not covered in the discussion. Is this to do with the difficulty of measuring depth hoar in the field or something more fundamental in the difference between the way natural snow evolves and TGM growth in the lab? What is the sensitivity of the model to Amin and Amax? If the column Amax from radar measurements is 0.2, values for individual layers could be much higher. It’s not clear how Amax = 0.3 +/- 0.1 was estimated. What is the impact of this estimation?
- I’m not convinced that dividing by a density and a characteristic microstructural length scale in equation 5 on dimensional grounds is the correct thing to do. The orientational dependent part of the equation already indirectly accounts for a difference in size associated with horizontal structure vs size associated with horizontal structure so to then incorporate a size dependent term which is afterwards treated as a constant seems odd. From a physical perspective it seems intuitive that the rate of vapour-solid exchanges is dependent on the effective surface area perpendicular to the thermal gradient i.e. horizontal structures present more surface area for phase changes than vertical structures. I would then argue that you are dividing the flux by something with units of specific surface area but dependent on the anisotropy.
- If empirical correction factor alpha2 is somehow related to the resistance of the bonded ice matrix to compression, would vertical and horizontal structures have the same value?
- Figure 2 – it would be better to have a consistent colour scheme. At the moment red is used for (8) in (a) but (7) in (b).
- Section 3.2. What frequencies / incidence angles are you using? This relates to later section and calculation of standard deviation of A from CPD in section 4.2 – how was this done? Calculated over time / frequency / incidence angle?
- Clearly a lot of work went into derivation of the meteorological data to run SNOWPACK, with associated uncertainties. Why was this approach taken rather than using the Essery https://doi.org/10.5194/gi-5-219-2016 dataset? What could cause the incoming longwave to require a decrease (in processing in this paper) instead of providing an additional thermal contribution due to the trees?
- P19, 2nd paragraph – layers at the base do not always show vertical structures: at the start of the seasons there are only horizontal structures: could this period be used for calibration of Amax? Similarly, could the purely vertical structure profile period in 2010-2011 be used to calibrate Amin?
- P19, L9-10 (begins We think…) this sentence would benefit from some clarity
- P24, L9-10. Missing a discussion about the difference at the bottom (where observations available). The fact that the micro-CT data show vertical structures whereas the model indicates horizontal may be significant depending on application. It would be interesting to discuss possible reasons for this difference. It is also interesting that the model agrees more with A derived from pc rather than pex for this section. What could this mean?
Typos:
P6,L21: should increases -> should increase
P7,L5: alignment, chose -> alignment, we chose
P19,L11: increases to -> increases too
P19,L12: to about -> to be about
P21,L1: r=0.51 c.f. table: r=0.50
P25,L26: seasons -> season
P26,L25: suggested -> suggest
P26,L32: Despite of strong -> Despite strong
P27,L8: dendrits -> dendrites
P27,L32: begin -> beginning
P30,L12: to enhances -> to enhance

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ED: Publish subject to minor revisions (review by editor) (10 Nov 2019) by Guillaume Chambon

AR by Silvan Leinss on behalf of the Authors (20 Nov 2019) Author's response Manuscript

ED: Publish as is (27 Nov 2019) by Guillaume Chambon

AR by Silvan Leinss on behalf of the Authors (06 Dec 2019) Author's response Manuscript

Short summary

The anisotropy of the snow microstructure, given by horizontally aligned ice crystals and vertically interlinked crystal chains, is a key quantity to understand mechanical, dielectric, and thermodynamical properties of snow. We present a model which describes the temporal evolution of the anisotropy. The model is driven by snow temperature, temperature gradient, and the strain rate. The model is calibrated by polarimetric radar data (CPD) and validated by computer tomographic 3-D snow images.