The study focuses on quantifying the evolution of albedo in the accumulation zone of the WSS (Austria). By combining in situ measurements with satellite observations, the authors demonstrate a good agreement between these approaches, enabling a detailed analysis of the spatiotemporal variability of albedo. On this glacier, as on many other Alpine glaciers, accumulation zones are progressively shrinking, exposing not only firn from previous years but also an increasing proportion of exposed bare ice at the surface, leading to a significant decrease in albedo. Based on seven years of observations, the authors highlight a pronounced decline in albedo within the accumulation zone, where ice exposure at the surface has become more frequent, particularly since 2022. Due to the positive feedback of albedo, this phenomenon further enhances glacier melt, a process the authors quantified in this study. Despite its critical role in glacier mass balance evolution, this mechanism remains relatively understudied, particularly in terms of its spatial variability. Results presented in this study thus provide valuable insights for the glaciological community.

I thoroughly enjoyed reading this paper, which is clear, well-written, and well-structured, presenting novel and valuable findings. I particularly appreciated the discussion section, especially sections 4.3 and 4.4. The introduction is also well-written and clear; however, the list of cited references is often not exhaustive. It would be beneficial to either expand the references or, at a minimum, indicate their non-exhaustive nature using "e.g." (e.g., lines 1, 20, 26, 31, 36...). The methodology section is well-structured and engaging, but data availability (e.g., time period, resolution, etc.) remains somewhat unclear at times. Given that numerous measurements and observations were conducted over different periods and at varying temporal and spatial resolutions, a more visual representation (such as a figure or table) summarizing the measurement periods, resolution, uncertainties, etc., could significantly improve readability. Finally, before publication, I believe it would be valuable to clarify the (not major) points outlined below.

Incertitudes

It seems important to better clarify and quantify uncertainties, particularly to improve the discussion and comparison between the two methods.

1) Regarding the AWS observations, I appreciate the effort to quantify uncertainty presented in the appendix, but some questions remain: What is the sensor accuracy (line 137)? Where does the 14% uncertainty come from (e.g., Figure 4 and S5)? The uncertainty related to surface roughness could be mentioned (e.g. line 131)

2) The S2 images provide high-resolution spatially distributed albedo data, which is highly relevant. However, uncertainties associated with this method are not quantified and should be reported in the study (e.g., Figure 4).

Additionally, for this method, it is unclear whether and how the solar zenith angle at the time of image acquisition is accounted for in the albedo calculation. Could this have a significant impact on the albedo from S2?

Thus, the comparison between AWS and S2 approaches (e.g., bias, RMSE, Section 3.1.2) could be further discussed in relation to their respective uncertainties.

Spatial variability and albedo

1) The study of the spatial variability of albedo is both interesting and innovative and could be better illustrated. For example, lines 243–244 and Section 3.2 could be accompanied by a spatially distributed albedo map, as this information is not clearly visible in Figure 5.

2) The interpretation of the relationship between albedo and SMB is valuable; however, the effect of temperature is not discussed. Years with low albedo values (e.g., 2022–2024) are also among the warmest, making it difficult to disentangle the impact of albedo feedback on melt from that of high temperatures. This aspect could be further explored or at least mentioned. Additionally, temperature data are reported in Figure 7b, but this panel is not discussed when analyzing the summer of 2022.

3) Furthermore, regarding the results presented in Figure 12, it seems important to mention that the satellite images for 2023 and 2024 were acquired in September, a period when the glacier’s albedo is likely not at its lowest (see Figure 2). Could the comparison of glacier-wide albedo between years be somewhat biased by the late acquisition dates in these two years (e.g., line 343)? This point could be addressed.

Simulations

Although the authors mention that the model validation exercise seems to be outside the scope of the study, the fact that they quantify the impact of albedo on melt using this method and highlight it in the results (e.g., lines 324-327, Figure 11), and also in the discussion, conclusion, and abstract makes it, in my opinion, difficult to avoid an precise evaluation of the model. If this precise quantification is a result the authors wish to emphasize, I strongly encourage them to properly evaluate the model. Otherwise, I suggest they focus solely on relative comparisons from sensitivity tests.

Some suggestions for model evaluation : The simulated vs. observed snow-to-ice transition could be quantified using a delta day (line 201) ; Fig 9 could be evaluated using the SR50 (although the SR50 was used to force the model with snowfall, there is no precipitation during the period presented); ice temperature sensor measurements could be compared with the model simulations.

Additionally, some clarifications on the simulation parameterizations seem important, particularly regarding model calibration and initial conditions (e.g., in the appendix). Finally, is the surface in the simulations in Figure 11 still ice? This should be specified. If so, is an albedo of 0.6 realistic for ice?

Line by line comments:

Lines 27-31: long sentence difficult to understand. Please reformulate.

Line 80 to 88: What is the measurement period for the AWS (in relation to the above comment) and other sensors, and what is the temporal resolution? The same applies for the ice temperature sensors and the camera.

Line 83: Ice temperature sensor: Is it used in this study?

Line 85-86: It took me some time to understand that we are in the accumulation zone, but with exposed ice (which is uncommon for an accumulation area). A clearer description here could help, especially since Figure 1 shows only snow.

Line 105: "Ice flow is not apparent" – Please specify: "Ice flow is lower than..."

Line 139 and throughout the document: "Low" and "very low" refer to specific values (i.e., 0.2 and 0.4) as indicated here. These terms are used throughout the document, sometimes with quotation marks and sometimes without. Conversely, "low albedo" is sometimes mentioned without explicitly referring to these values, making the text harder to follow. Please ensure that quotation marks are consistently used when referring to these specific values, or alternatively, use a uniform notation (e.g., alb < 0.2).

Line 145: Could you provide further details, such as the spatial resolution of the S2 images, the number of images, and the period covered?

Line 182: "Albedo as input" – do you mean albedo from the AWS?

Line 216: Unclear where the value of 0.3 comes from. Could you clarify?

Line 234, 238: "Generally coincide or occur" – This statement could be quantified (e.g., using delta day) to add more weight to the comparison.

Line 248 and throughout the paper: Be consistent with units: mm w.e. should be accompanied by a time period (e.g., mm w.e. yr⁻¹) (e.g., line 248, line 323, line 396, etc.).

Line 246 to 251: To give more weight to the different ablation values, you could mention the percentage they represent relative to the mean, especially for 2022.

Line 252: Specify that this refers to albedo from S2.

Line 419: While I find this discussion relevant and convincing, wouldn’t the primary effect of darkening at the glacier scale be more related to the expansion of the accumulation zone?

Line 459-460: Also, the firn.

Figures and Sup. Mat.

General: Many figures should be larger because they are sometimes difficult to read.

Figure 1b: Glacier outlines and 50m contours are barely visible (green and blue lines).

Figure 5: Difficult to read. Consider splitting it into two panels: one with AWS-in situ and AWS-S2 (to show the comparison) and another with S2 at the stakes (to show spatial variability).

Figure 7: It is difficult to differentiate the colors specific to each stake. Add (a) and (b) directly on the figure. 

Figure 12h: The contours are hard to see, especially the green ones. Could they be made larger or changed to a different color?

Sup. Mat.: The order of references to the supplementary material is not always chronological (e.g., Line 90: referenced as 2 in the supplementary material but should be 1). Additionally, some references to the supplementary material could be more specific (e.g., Line 186: which figure does this correspond to?).