The manuscript presents a dataset that makes an attempt to bridge the gap between land cover maps (from ESA CCI) and the requirement of users (i.e. Regional Climate Models or RCMs), namely maps of Plant Functional Types (PFTs). Arguably, the solution from ESA CCI LC to do so, based on the standard cross walking table (CWT) of Poulter et al. (2015), can be improved. The main idea of this study is that these CWT can be regionalized by climate zones (the Holdridge Life Zones or HLZ) to be better tailored to the needs of RCMs, at least over Europe. The authors further go to do a validation based on a new point based dataset (GT-SUR).

I think the overall rationale for the paper is there. However, I find several issues which would preclude publication in the present form. Hopefully the authors will be able to tackle them and present a revised version that addresses these issues.

One first issue is based on the style. The document does not read super well, partly because it is being very descriptive on a case by case basis with respect to the classes. The text is too long in this respect and many of the details are not so relevant. The results were each class in analyzed separately with respect to filtering (e.g. figures 6, 8, 10-14 and related text) are very tedious. I suggest this should be condensed in some form or another, if not removed and relegated to annexes. There are other issues too that make the reading difficult (not in terms of language, but style), some of which I detail in the remarks further below.

Another major issue I have is that the validation based on GT-SUR is done only on the LANDMATE PFT map, and not on the baseline ESA CCI LC map, nor on the ESA CCI LC map transformant to PFT with the standard CWT. This makes it impossible to judge on the improvement in quality provided by the present study. It may very well be that all the accuracy with respect to GT-SUR is from the correct classification of the LC in the first place, and not at all by the added value provided by the study. I suppose this is not the case, but it is not proven by the study. In fact, readers might think the authors are misleading the audience by claiming accuracy when none is due. To defend themselves from this, I strongly suggest that the authors engage in making the same comparison with GT-SUR with some baseline reference before they apply their contribution (and I would suggest to do it both for the LC, and for the PFTs with the default CWT). In that way, they will be able to isolate and quantify the added-value of their contribution

Another point that I think needs improvement is the whole part on the ‘filtering’. It is not fully clear to me what is being done or why. It needs to be explained better and probably simplified. Also, all this part (along with the results) occupy a very substantial part of the manuscript and it is not fully clear why. Also, why are things aggregated at 2.5 dd instead of done at the 0.1dd? I fully understand that there are mismatches between the samples at point level and grid level, but I am not convinced by what is done here. I probably misunderstood something, but again, it should be crystal clear why things are done

Last major point is that I do not see why the dataset is done only for 2015. Especially since the ESA CCI LC maps are done for 1992-2020 now, and that they had been designed to be consistent in time. I think most users would expect you to exploit this info and provide not just a single date basemap but also a set of consistent maps for the observation period.

The rest of my remarks are here below:

L7: “to achieve the *best* possible representation”? Arguing it is the best is perhaps exaggerating. Unless you prove that cannot be anything better.

L31: I think it may be misleading that the concept of PFTs in increasingly used. It has been used for a long while now, and it is unclear if there is a trend in using it more. Some models are perhaps drifting away from it, or at least evolving in a bit of a different way… see: https://doi.org/10.1111/gcb.13910 and https://doi.org/10.1029/2018MS001453

L38: as it seems clear the CWPs will be a key concept in the rest of the paper, it would be good to describe here a bit more what it is. The more general reader would not necessarily understand why a specific “procedure” is needed for “translating” LULC to PFT. I would further recommend to spend more time explaining the fundamental difference between LULC and PFTs. Thirdly, I would go forward and cite studies that have actually employed a CWP in practice (https://doi.org/10.1038/s41467-021-24551-5 and https://doi.org/10.1038/s41467-017-02810-8 come to mind, there must be others). A separate dedicated paragraph in the intro on all of this would be warranted.

L48: is it specific for the RCM community? Could it not be applied more generally to the ESM (Earth System Modelling) community, irrespective of whether it is region or global?

L75: While I understand the logic of having a general workflow sub-section first to present an overview, the way it is it actually complicates the understanding. For instance, you talk about the HLZ map (L84) without saying before what it is (or rather describing what it is). It feels that maybe this section is not so useful as it is… if you want to keep it, it should be made much more generic so that it does not depend on what you will explain after.

L87: Not clear here (even if it may become clearer after) why an individual CWT is needed for each LULC class. The idea of a CWT would (a priori) be that you have one table for all.

L117: This simplified downscaling by bilinear interpolation will probably lead to problems in mountain areas. Any way to mitigate this? Could you comment on the possible consequences?

L127: typo on “merged”

Figure 2: There a logical inconsistency in the colour gradients you use. To be consistent, please always keep “deserts” as either the lighter or darker colour in each scale

Table 3 is a bit pointless as a table, as it only has one field (the number is not very meaningful in the context of this paper) and thus is just a list. If you keep this as a table, could you please add more fields with info (e.g. description)

L149: It is not clear enough where the information to make the C3/C4 distinction comes from. This separation is very important for modellers, yet the CCI LC product (and standard CWT) does not provide any way to do the distinction. This suggests it is difficult to do. Claiming that here you can do it would require more details on how it is done and some validation that is it done correctly. Furthermore, could you also clarify in what ways this is better than using the Still maps  commonly used  by modelers (e.g. https://doi.org/10.1029/2001GB001807)

L174: I don’t quite follow. You say six, but the title says 8. Not directly clear why you say “at the expense of two shrub-PFTs”. Probably better to rephrase (this and other parts of the paragraph) by being more exhaustive at first (i.e. there are 6 tree classes and 2 shrubs classes. The reason why is … )

L185: typo in class 61

L192: Again, the C4/C3 is not clear enough to me, from the text itself. Furthermore, is what Wei et al. did really an accepted way?

L200: you have not clearly stated what the actual “translation” is?

L202: specify that this is only for the European domain considered here

L205: what about C4 crops? According to the authors, the main point of the study is to make a map that reveals traits more than LC, but the C4 vs C3 is perhaps one of the most important ones for vegetation models. So one would expect a proper C4 crop PFT.

L210: more info on what the actual translation means would be needed

L217: Do you mean, with respect to Siebert et al?

L223: I have the impression that the same could have been decided for C4 plants. It seems that the level of scrutiny in this irrigated class is not the same as the one applied for C4/C3. In both cases, an external product could be used, but in C4/C3 it was and not for irrigated.   

L229: Are bare classes fully ‘non-vegetated’, or do they contain residual vegetation? If so, any idea of how much?

L232-236: I do not see what LANDMATE PFT brings specifically here. The distinction between urban and bare is done by the underlying land cover map, so here the credit goes to the LC cover map and not the present study.

L239: what about inland water, i.e. rivers and small lakes? Are these also set as NA? are the RCM land-sea-mask covering such areas?

L282-285: why bring this issue of cost and size here? Here you have a very large amount of records for free… (ie. You do not need to collect them), so these phrases seem irrelevant.

Table 6: I do not understand what these numbers represent exactly. Samples? Correct samples (i.e. where GT-SUR and LANDMATE match)?

Table 7: why not put this as a graph instead of a table? It would be more informative with a single glance

Figure 6 (and others): personally, I find the shadow of the points distractive.

Figure 9: should be “Bucharest”

Format of results is not optimal for understanding. IT should be done in a more condensed way, and not class by class, with a large plot for each. Try to be more synthetic.

L447: Why in LANDMATE PFT only made available for Europe 2015? The ESA CCI LC is available from 1992 to 2020. The transition from LC to PFT seems relatively straightforward. Why would you not produce the time series?  The users would surely expect it.

L450: this link does not lead anywhere…  at least for me…

L457: “For each ESA-CCI land cover class, an individual CWT is developed…”. This does not make sense to me like. The standard way to use the CCI CWT is that it applies weights to each land cover class, and the CWT is the matrix of these weights (rows = LC, cols = PFT). If you apply a CWT to each LC class (to each row), you are just setting the weights for that class.  Now I understand that what you  are actually doing is to set an extra dimension, that of the HLZ. So you need to be more specific, and say that the CWT is decomposed by different HLZ for every LC.

Overall, the paper seems to represent an advance in land-cover/ plant functional type (PFT) modeling that informs regional climate models (RCM). I think the paper could be improved by adding more detail about the cross-walk procedure and, in particular, providing a rich example of how the linkage to the Holdridge Life Zones (HLZ) allows for future updates to the land-cover classification in response to environmental change. I gather that, in an RCM, climate changes that push a location out of one HLZ and into another would prompt an update to the corresponding PFT at that location; i.e., the vegetation canopy would be allowed to change and therefore the RCM model state would change in advance of the next time step. This is very interesting and potentially powerful, given that it allows some of the complexity of a dynamic vegetation model to be represented more simply, but it should be made more explicit.

There are also a couple of key technical issues with the paper. The crosswalk procedure should be explained in much more detail; the tables in Appendix A are deceptively rich in detail but they really don't make sense without more explication in Section 3. I also think Figure 2 may have the colors for each HLZ mislabeled, as some of the map regions' displayed HLZ classes do not make sense (e.g., desert in Scotland). There are also additional analyses referred to by the authors (ca. Line 487, "The additional comparison with a high resolution dataset

(WSF2015) showed that not only large but also small agglomerations of urban areas are represented well in LANDMATE PFT.") that are completely undescribed in the paper.

Specific comments:

Lines 12-13: The authors write: "A suitable evaluation method has been developed and applied to assess the quality of the new PFT dataset." This is a little vague. Perhaps the authors could be more specific about the type of evaluation method, or remove this sentence from the Abstract?

Lines 88-95 and Appendix A: I find the crosswalk tables in Appendix A, and the crosswalk procedure as described, to be confusing. The row sums for every crosswalk table in Appendix A are 100, which seems to imply they are percentages. However, using Table A4 as an example, it's not clear to me how the ESA-CCI LC class (number 30 in this example) is converted to the LANDMATE PFT based on the HLZ. Typically, a cross-walk table would describe how two uniquely identified, intersecting spatial units are resolved into mutually conflicting classifications. But neither the HLZ nor the ESA-CCI LC class are uniquely identified (i.e., two widely separated locations might have the same HLZ). Is this a probabilistic approach? If the pixel with ESA-CCI LC class 30 is in Holdridge Life Zones 1-6, it has a 20% chance of being classified as Tundra, 20 percent change of being classified as Swamp, and 60 percent chance of being classified as Crops? The authors should be much more explicit about this somewhere in Section 3.

Lines 93-94: The authors write: "This revision of the CWTs is supported by reference data and visual satellite image interpretation." Is this described somewhere? Please add a reference to the appropriate section of the paper (Section 3?).

Figure 2: I think the colors may not be labeled correctly... It seems that much of Italy and Spain are "Rain Forest" and "Wet Forest" variously in the "Warm Temperate" or "Boreal" climate zones while much of Scotland and Ireland appear to be "Desert scrub" or Desert" (Warm temperate climate zone).

Section 3: I think the authors should add a table of their final PFT classification. It is confusing to have Table 3, which is specific to the validation dataset, but not a table of the PFT classification for this new data product. For instance, on Line 204, a reference is made to Table 3, which is the validation dataset's PFT table, during a discussion of the new product's PFT classification.

Line 174: Related to the previous comment... The authors write that the target set of PFT classes for trees and shrubs "was done at the expense of two shrub-PFTs." I interpret "at the expense of" as meaning that something was sacrificed, i.e., removed. I look at Figure 3 and see that there are, in fact, two shrub PFTs. Perhaps the authors could revise this sentence?

Line 315: I think the inline equation is missing an equal sign, i.e., the symbol "n_{i+}" should be followed by an equal sign.

Lines 487-488: The authors write: "The additional comparison with a high resolution dataset

(WSF2015) showed that not only large but also small agglomerations of urban areas are represented well in LANDMATE PFT." This is the first time this analysis and this dataset (WSF2015) are mentioned. The authors should describe this analysis as part of the paper (Section 4).

Technical corrections:

- Line 20: "was declared an" should be "were declared"

- Line 30: "as realistic" should be "as realistically"

- Line 44: "origin" should probably be "originate"

- Line 127: "are mereged" should be "are merged"

- Line 185: "lass 61" should probably be "Class 61"

- Line 216: A space is missing between the end of one sentence ("2005).") and the start of the next: "Although the ESA-CCI LC..."

- Line 428: I think Figure 7g needs to be reference along with Figure 7i.

- Line 489: "and despite of the" should probably be "and despite"