Satellite-derived products of solar and longwave irradiances  used for snowpack modelling in mountainous terrain

Quéno, Louis; Karbou, Fatima; Vionnet, Vincent; Dombrowski-Etchevers, Ingrid

doi:https://doi.org/10.5194/hess-24-2083-2020

Articles | Volume 24, issue 4

https://doi.org/10.5194/hess-24-2083-2020

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

https://doi.org/10.5194/hess-24-2083-2020

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

Articles | Volume 24, issue 4

Research article

|

28 Apr 2020

Research article |

| 28 Apr 2020

Satellite-derived products of solar and longwave irradiances used for snowpack modelling in mountainous terrain

Louis Quéno, Fatima Karbou, Vincent Vionnet, and Ingrid Dombrowski-Etchevers

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Final revised paper (published on 28 Apr 2020)
Preprint (discussion started on 19 Sep 2017)

Interactive discussion

Status: closed

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

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RC1: 'Referee Comment', Anonymous Referee #1, 14 Nov 2017
- AC2: 'Response to Referee#1', Louis Quéno, 26 Oct 2018
RC2: 'Referee comment', Anonymous Referee #2, 14 Apr 2018
- AC1: 'Missing document', Louis Quéno, 29 Sep 2018
- AC3: 'Response to Referee#2', Louis Quéno, 26 Oct 2018
AC4: 'Revised manuscript', Louis Quéno, 30 Oct 2018

Peer-review completion

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

ED: Reconsider after major revisions (further review by editor and referees) (15 Mar 2019) by Harrie-Jan Hendricks Franssen

AR by Louis Quéno on behalf of the Authors (20 Mar 2019) Author's response Manuscript

ED: Referee Nomination & Report Request started (21 Mar 2019) by Harrie-Jan Hendricks Franssen

RR by Anonymous Referee #3 (26 Aug 2019)

RR by Anonymous Referee #4 (18 Feb 2020)

Suggestions for revision or reasons for rejection

Review of the Article hess-2017-573

Satellite products of incoming solar and longwave radiations used for snowpack modelling in
mountainous terrain

by Louis Quéno1, Fatima Karbou, Vincent Vionnet, and Ingrid Dombrowski-Etchevers

This paper compares different products for estimating incoming solar and longwave radiations to be used for snowpack modelling in mountainous terrain using the CROCUS snow model, at the scale of an entire mountain range.

General comments:

The accuracy of incoming solar radiation is one of the key source of errors for snowpack modelling. This is particularly true in in mountainous terrain, because complex topography. For this reason, the topic of the paper is relevant. However, this paper seems to be a very technical review of existing products and it adds very little novelty to the science on this topic. I expected indications that are more concrete on how to improve existing products or propose new, better products. Even if the paper is quite boring to read, the analysis is accurate and the discussion is quite interesting. The results part is instead very boring with many technical details, which are not interesting for the general reader. I suggest making this part much more compact, eventually leaving details on the comparison for a supplementary material section. I have some methodological observations on how complex topography has been taken in account in processing the radiation data and on the role of uncertainties in precipitation data (see specific comments).
Nevertheless, I would recommend publication after a careful revision, since the paper could provide useful guidelines on how to interpret remote sensing radiation observations in Alpine regions.

Specific comments:

1. Introduction

The major source of uncertainty in snow models is likely to be the correct estimation of precipitation and of the rain/snow limit. Then, especially during the melting season, radiation and snow surface radiative properties, and this is the focus of the paper. However, precipitation remains the first uncertainty reason (Günther et al, 2019; Engel et al., 2017).

2. Methods

In all the compared products, are precipitation and other meteorological variables the same, besides radiation? Otherwise, the comparison could be biased by other sources of errors.

3. Evaluation of radiation products

Line 255. You justify the fact that the effect of slope and aspect were not taken in account because the evaluation were made over flat terrain. However being in the mountains, sky view factor should be taken in account. The sky view factor reduces the amount of diffuse shortwave radiation and can affect the longwave radiation balance (i.e. Corripio, 2003; Rigon et al. 2006, eq.5). Was this effect taken in account while evaluating with ground observations?

3. Impact of products on snowpack simulations

Line 363. Please clarify immediately the meaning of A-Cro, AL-Cro, AS-Cro.

Line 366. A-Cro overestimates the snow depth … this can be due different reasons. This should be already clearly stated here. (I´ve seen that later in the discussion this point is addressed).

5. Discussion

Line 477. Which are the reasons of A-Cro overestimation? Why you state that there is not overestimation of snow accumulation? What about precipitation or snow/rain limits? Figure 8 seems to suggest that the model´s overestimation is mainly due to an overestimation of the snow precipitation in the accumulation season (or to wind erosion in the snow observations …). In Figures 8 and 10 it seems also that there are already during the accumulation season differences in the modelled scenarios. Do have all scenarios the same solid precipitation input? Are the differences only caused by the different radiation input?

Line 482. Underestimation of the turbulent fluxes can be related to a variety of reasons: surface roughness length, atmospheric stability parametrization, air humidity, temperature and wind biases. Is it possible to discriminate among the different reasons?

Line 484. This is a key point for snow modelling. See also the recent work of Günther et al, 2019.

References

Corripio, J.: Vectorial algebra algorithms for calculating terrain parameters from DEMs and solar radiation modelling in mountainous terrain, Int. J. Geogr. Inf. Sci., 17, 1–24, 2003.

Engel, M., Notarnicola, C., Endrizzi, S., Bertoldi, G., 2017. Snow model sensitivity analysis to understand spatial and temporal snow dynamics in a high-elevation catchment. Hydrol. Process. 31, 4151–4168. https://doi.org/10.1002/hyp.11314

Günther, D., Marke, T., Essery, R., & Strasser, U. ( 2019). Uncertainties in snowpack simulations—Assessing the impact of model structure, parameter choice, and forcing data error on point‐scale energy balance snow model performance. Water Resources Research, 55, 2779– 2800. https://doi.org/10.1029/2018WR023403

Rigon, R., Bertoldi, G., Over, T.M.T.M.M., 2006. GEOtop: A Distributed Hydrological Model with Coupled Water and Energy Budgets. J. Hydrometeorol. 7, 371–388. https://doi.org/10.1175/JHM497.1

Referee Report: PDF

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ED: Publish subject to minor revisions (review by editor) (24 Feb 2020) by Harrie-Jan Hendricks Franssen

AR by Louis Quéno on behalf of the Authors (13 Mar 2020) Author's response Manuscript

ED: Publish subject to technical corrections (25 Mar 2020) by Harrie-Jan Hendricks Franssen

AR by Louis Quéno on behalf of the Authors (25 Mar 2020) Author's response Manuscript

Short summary

In mountainous terrain, the snowpack is strongly affected by incoming shortwave and longwave radiation. Satellite-derived products of incoming radiation were assessed in the French Alps and the Pyrenees and compared to meteorological forecasts, reanalyses and in situ measurements. We showed their good quality in mountains. The different radiation datasets were used as radiative forcing for snowpack simulations with the detailed model Crocus. Their impact on the snowpack evolution was explored.