the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
How montane forests shape snow cover dynamics across the central European Alps
Abstract. A substantial fraction of seasonal snow is stored in mid-latitude montane forests, serving as an essential temporal water storage. Across vast areas, snow cover dynamics are the result of processes equally controlled by forest structure, topography, climate, and weather variability. As data availability has limited our ability to disentangle how these four key controls interact across landscapes within complex topography, most forest snow studies have focused on only one or two of the controls. In this study, we employed the process-based FSM2oshd forest snow model framework for an in-depth analysis of the current state of forest snow water resources across the central European Alps. Over the 8 years analysed, forest snow accounted for 20–30 % of the total snow storage in midwinter. In the various effects of existing forest cover on snow, pronounced differences were found depending on elevation, aspect, region, and year. While the presence of forest usually led to a decrease in peak SWE, it decelerated snowmelt, often leading to a later snow disappearance date, particularly on south-facing slopes. However, variability between years and regions was strong enough to shift or even reverse such trends, where snow-scarce years accentuated relative differences in the effects of forests on snow cover. With forest disturbances projected to increase and snow storage to further decline, enhanced complexity of snow cover dynamics in montane forests is to be expected. This places more emphasis on understanding how the effects of key controls such as forest structure, topography, and weather interact.
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RC1: 'Comment on egusphere-2025-3843', Anonymous Referee #1, 06 Nov 2025
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The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2025/egusphere-2025-3843/egusphere-2025-3843-RC1-supplement.pdfReplyCitation: https://doi.org/
10.5194/egusphere-2025-3843-RC1 -
RC2: 'Comment on egusphere-2025-3843', Anonymous Referee #2, 13 Nov 2025
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Dear editors and authors,
Thank you for the opportunity to review this interesting manuscript.
The research studies montane forest snow cover in the Swiss alps using process-based snow model and remote sensing data. The work first goes to test the validity of FSM2oshd model outputs by a novel approach to use PlanetScope RGB images with a manual procedure to assign snow cover extent to specific areas and times. After demonstrating and discussing the model validity, the work moves on to analyse and contrast the simulated snow properties in forested and open regions and how they are influence of terrain and climate. The work reports significant influence of forest cover to snow resources, with pronounces differences caused by in elevation, aspect, and interannual variability.
In my opinion the work is well written and clearly structured, making it a pleasant read. It has novel methodological approach in validating forest snow simulations at a large scale. The process-based snow hydrology analysis is based on simulation output. This is in fact what I like in the study: a process-based model is used to analyse processes in spatial and temporal resolution beyond current measurement capabilities. This is one fundamental use case of environmental models, yet I find models are not very frequently used for this purpose. The process analysis appears valid and well justified and discussed. However, highlighting that findings are based on model simulations could be made more explicit in the abstract and conclusions.
I recommend to publish this work after addressing my minor comments detailed below.
Minor comments
L13: is equally right word here? The controls would have different dominance in different regions
Table 1: where does the data for variables in table one originate from?
L166: excluding images with intercepted snow is not explained. what is the rule for saying there is interception? Would this not create a bias for the analysis, as I’d expect interception to be often present in the mid-winter?
L202: 30 000 grid cells is a lot to verify manually! would you expect any biases there, and con you comment if the process is reproducable
L250-253: the interpretation here having statements like typically and generally is somewhat vague and difficult to verify from figures. Can you give more concrete examples to show the point you are making, as in earlier part of the paragraph.
L259: 13th instead of 14th ?
L263: Perhaps “showed similar patterns” is an overstatement here. Id argue that patterns for sites 2, 4 and 6 are quite different for observed vs simulated.
L289-306: what area do you use to calculate the SWE: the total study area, or the snow covered area for a given time? This will greatly influence the SWE numbers. Furthermore, I’m used to SWE being reported in units of [mm], corresponding kg/m2, i.e. mass per area. Where you talk about SWE in units of mm and km3 interchangeably. I recommend bringing consistency to SWE units here, and elsewhere in the manuscript.
Figure 6: recommend to add letters also to the map next to boxes: dashes and box colors not very obvious indicator
L403-434: figure 10 and associated interpretation is difficult to follow. Even after repeated attempts, I don’t fully understand the logic of the figure, and how it supports the analysis. This might be only me, but think about any simplifications or supporting information that would make this easier to digest. Or is this necessary to include in the first place, as you already have a lot of analysis and results to talk about. Maybe removing altogether would not compromise the main message, but would make the paper more short and concise?
L487-498: one process to discuss further here is how snow unloading from canopy is simulated, and are the unloading routines well validated? Fast unloading means less time for interception sublimation, and less difference between open and forested snow.
L513: also slope can have a big hydrological influence, potentially also soil freezing.
L525: 15 years is not that long ago, I’d say computational snow hydrology in forests dates well beyond that in for example snow interception work.
L540-546: How about edge effects in snow being accumulated at the transition between open areas and forest stands due to changing wind fields. Are they too small scale of a process for your analysis?
L564: You don’t really analyze runoff generation, so this should be written in a more speculative tone. In particular as its part of conclusions chapter.
Citation: https://doi.org/10.5194/egusphere-2025-3843-RC2
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