Review of Roccetti et al., “Development of a HAMSTER: Hyperspectral Albedo Maps dataset with high Spatial and Temporal Resolution”

Here, the authors detail an effort towards generating hyperspectral global albedo maps based on MODIS albedo estimates combined with laboratory-measured spectra for various surface types. The need for this type of study is sound, and the dataset could well be of interest to ESM modelers in particular.

Regarding the execution of the study, the manuscript is of good writing quality and mostly of logical structure. However, there are still numerous choices made in the analysis which require further clarification and/or justification until publishable quality may be reached. Therefore, at this stage a major revision of the manuscript is required to address the issues listed below:

Major issues

Choice of MODIS data: The MCD product user manuals quite clearly state that “We recommend that users use the MCD43D 30 arcsecond products (or the 30 arcsecond MCD43GF gapfilled products) instead of the MCD43C products as much as possible, since the MCD43C products merely represent averages of the direct BRDF retrievals obtained with the MCD43D processing. The averaged MCD43C products thus necessarily include various QA flags within each pixel, and are therefore less rigorously high quality than the MCD43D products.” Yet, the authors have chosen to base their analysis on MCD43C3. Why?

Reference spectra: One is tempted to ask about the geographical distribution of the soil and vegetation spectra used here. For example, boreal forests are and behave quite differently from African rainforests – how well are the various regions of the Earth represented in the data? Do you have any means of assessing the uncertainty that is potentially related to misrepresented vegetation in particular, as the soil-vegetation references appeared to be heavily weighed towards soil sampling? What is the overall uncertainty of the HAMSTER data layers?

Treatment of snow within the HAMSTER maps: The reference spectra did not seem to contain snow and there was no mention of simulating snow spectra with snow models. How then did you achieve the PCA deconstruction over snow? What about mixed pixels with fractional snow cover and fractional vegetation cover, how are those handled?

Structure: Inclusion of HAMSTER validation in section on data and methods is confusing, as these are clearly results and not source data or its processing. Recommend revising the structure to start section 3 with the validation, and then proceeding towards analysis of features in HAMSTER data.

Gap filling on multiple layers: There are 5 different layers of gap filling needed – what are the respective percentages of global MODIS grid that are filled out at each of these steps? Do I understand correctly that in step 2, albedo values spanning to +/-40 (5x8) days of target date may be selected to fill the gap? 40 days during snowmelt or vegetation greenup could result in dramatically different gap-filled albedos relative to what was actually on the ground, what is the justification for this wide search window?

Minor issues (line# or element)

130 – I was under the impression that MCD products do not contain sea ice albedo or sea ice cover? Certainly the result figures show no Arctic sea ice, so why is sea ice referenced here and again in section 3? This also refers to the major issue on snow treatment – sea ice albedo is even more complex than snow, and I haven’t seen anything in the manuscript about its treatment?

Fig 7 – TROPOMI coverage extends elsewhere from Africa, why only focus the comparison there?

Section 3 – the PCA-interpolated spectral albedos appear reasonable for most land surfaces, certainly. But I question the validity of the urban areas’ spectra, there did not seem to be any reference spectra on man-made structures in the study? And how would PCA handle the extremely nonlinear shifts in land cover and surface material that are common to urban areas? Since the overall quality of MODIS albedos over cities has not been quantitatively assessed and the validity of the RossThick-LiSparse retrieval is uncertain over them, I would be very careful of highlighting those areas in particular unless the authors can prove that their spectra are valid.

The paper discusses the development of a dataset called HAMSTER (Hyperspectral Albedo Maps with high Spatial and TEmporal Resolution). The researchers aim to improve the accuracy of radiative transfer simulations of Earth’s system by providing a more detailed representation of surface albedo, a key parameter in calculating the planet’s energy budget.

The manuscript is well-structured and comprehensive, but there are some major and minor comments that need to be addressed before publication.

Major:

M1. For the seven climatology calculation steps, you need to specify/quantify how many missing pixels remain before/after each step, preferably as a percentage.

M2. In light of Figure 3 and 4, it becomes evident that the employed method did not successfully generate accurate albedo representations for spectral bands not covered by the input dataset. The primary objective of this study is to construct an almost continuous albedo dataset using a limited number of input bands. While the direct comparison for the 1640 nm band exhibits strong agreement, the 810 nm band—outside the MODIS bands—shows the poorest comparison. However, it is precisely in the bands excluded from MODIS that the value of the HAMSTER product becomes apparent. Am I missing something here? 

M3. In Figures 5 and 6, the comparison is limited to only two specific days. While the separation into winter and summer is understandable, it raises the question of why a more extensive set of days was not utilised for potentially robust comparisons. Given the availability of numerous days, it would be beneficial to assess whether these two selected days are truly representative of broader trends. 

Minor:

L32: The word “the” is missing between “compared” and “Moderate”

L34: Which specific land surface products are being referred to?

L42: Please define the acronym VIS upon first use.

L52: I would argue that radiative transfer simulations do not demand all wavelengths, but only the representative ones. The simulations likely does benefit from higher resolution. Could you support your statement with a reference?

L60: Not sure what you mean by extrapolated in time, could you describe it a bit more.

L70: Consider adding a sentence to differentiate your work on hyperspectral albedo maps from that of Braghiere et al., emphasising any novel aspects.

L96-100: Could you provide a clearer description or explanation for the content in lines 96-100? It was challenging to grasp.

L124: Could you explain the rationale behind assuming no atmosphere in this part?

L335-336: Please verify the parentheses in this section to ensure correctness.

L347: Could you provide additional context or highlight the substantial increase mentioned?

L408: Please specify the number of principal components obtained in your analysis.

L419: Include the range here.

L432: Consider adding a statement explaining that performance deteriorates as wavelengths move farther away from the MODIS input bands (as mentioned in comment M2).