General comments

The paper, titled “openAMUNDSEN v 0.8.3, an open-source snow-hydrological model for mountain regions”, describes a fully distributed snow-hydrological model optimized for mountain regions. The model provides a detailed simulation of the snow cover's seasonal evolution, including mass and energy balance across the snowpack. It's designed for varied spatial scales (from point scale to thousands of square kilometers) and temporal scales (from single events to climate change scenarios), incorporating features such as spatial interpolation of meteorological data, multi-layer snow simulation, and glacier ice response to climate change. The model's flexibility allows customization for specific applications, backed by a Python codebase and available as an open-source project for public use. The paper is concisely and clearly written, but I believe it requires some revisions. I am convinced that making these revisions will improve the paper. The comments on major revisions are as follows.

• The gridding of meteorological elements through interpolation of weather station data in this paper is conceptually similar to the Micromet model (Liston and Elder, 2006). Therefore, I would like the paper to discuss the advantages of its methodology by comparing it with Micromet. Additionally, please explain the temperature lapse rate with elevation and the elevation dependence of precipitation using equations. I would also like you to describe how these values differ when compared to Micromet.
• The method of determining the Snow Redistribution Factor (SRF) should be explained in figures such as Figure 1 or Figure 3. Furthermore, it seems that calculating SRF requires a fairly detailed DEM, so there should be a discussion on the maximum grid size for which SRF can be calculated. Additionally, expressing how SRF is used in a formula would allow for a better understanding, so I would like you to show the utilization of SRF in an equation.
• I believe the merit of this model lies in the estimation of the spatiotemporal distribution of snow water equivalent (SWE). On the other hand, the validation data consists of snow cover fraction and snow depth, and I think a comparison with SWE is essential to demonstrate the model's validity. I would like you to show the reproducibility of point SWE measurements. By doing so, it would be possible to verify to what extent the model can reproduce the spatiotemporal distribution of SRF and precipitation, so I would like to request additional validation.
• I do not fully understand the meaning of the sentences in lines 355-357, so I would like you to rewrite them more clearly.

AMUNDSEN is a well-known snow model with multiple capabilities and applications, and this description of the open source version is a useful reference. There is little demonstration of model performance, but that is OK in this model description paper, and the model has been extensively evaluated elsewhere. There is no demonstration at all of the method for generating climate scenarios, and I wonder if so much description is warranted when it is not subsequently used in the paper. Otherwise, there are a few places where I would like to see some more detail, and I have noted some minor corrections.

Line 17

“manyfold applications” – many

64

How long are the ”longer time horizons”, and why is lateral snow distribution then especially important?

86

“v0.9” – the title and text otherwise refer to v0.8.3. (what is it going to take to commit to v.1.0?)

Figure 4

It would be useful to see the station locations (the same as Figure 2a?). What is the resolution of the interpolated grid?

271

I guess that Liston and Elder (2006) is used for (the vast majority of) catchments that are less well gauged than Rofental. How does this compare with the dynamic lapse rates?

272

How are the precipitation thresholds chosen?

282

The method for calculating multiple reflections from clouds and slopes is not described. These reflections contribute to measured radiation, so does the model not end up double counting?

353

It is not clear what it means that “different length scales” are used in Figure 5; none are specified.

Figures 5 and 7 (especially 7d)

It is counterintuitive for the areas with more snow to be darker.

The Figure 7 caption does not mention that the pink blobs are clouds (it is not a big problem, but there were better Sentinel-2 views on several other days in June 2019).

422

“orby satellites” – orbital? Or just “satellites” (ones that are not orbital, such as CryoSat-1, are of limited value).

630

I can’t tell what the missing early snowfall event is in Figure 9. 

There are no metrics given, but I might judge from Figures 7 and 9 that the most sophisticated EB + Multi + SRF configuration has the worst performance in comparison with observations.