Review of Vara-Vela et al., “Implementation of a Satellite-Based Tool for the Quantification of CH4 emissions over Europe (AUMIA v1.0) – Part 1: Forward Modeling Evaluation against Near-Surface and Satellite Data”

My main concern with this work is that it intends to introduce a new inversion framework for TROPOMI CH4 data, itself somewhat incremental, but the authors have decided to split the paper in to 2 parts. With this first part only concerning the forward model, it is difficult to assess and explain the differences compared to observations. The forward model fails to capture the variability observed by the ground-based ICOS network and also fails to match the satellite total column observations. The issues may be with the prior as the authors suggest (and which would be demonstrated by actually showing the inversion results) but when the authors apply the averaging kernels (as should be done), this “smoothing” effect leads to much poorer comparisons and there’s not a sufficient explanation for this.

Unfortunately I believe that the attempt to split the paper into two has led to this first part being particularly weak and lacking. There’s clearly significant work that has gone in to this study but I would recommend that the authors consider publishing it as a whole, therefore being able to back up their speculation with quantitative inversion results.

Specific Comments:

Abstract: The authors appear to very strongly oversell their work with the statement that “The results found in this study contribute with a new model evaluation of methane concentrations over  Europe, and demonstrate a huge and under explored potential for methane inverse modeling using improved TROPOMI products in large-scale applications.” Inverse modelling of methane is a very active area with a strong track record from a number of European groups. Many groups have published inversion results using TROPOMI data and indeed, there are large European projects in this area.

L65 – This ignores some of the TIR instruments that measure CH4, IASI being maybe the most relevant here. Some mention of these should be made and then an explanation on why the focus is on the SWIR instruments.

L74: Tsuruta et al. (2023) would appear to be a very relevant reference, given it involves TROPOMI inversions over Europe, that is omitted. Some discussion of how this work relates/compares to that should be undertaken.

L98: “carefully selected” – How? Why? What criteria?

L100: I think there needs to be a strong justification for doing this as a 2-part paper and I’m struggling to see why it needed to be split. Can the authors please expand upon the rationale for this.

L170: Do these “agricultural” fluxes include rice production? This is usually separate and somewhat complex given the overlap with naturally inundated areas.

L213: Is Sitch 2003 the correct reference? It makes no mention of methane nor wetlands… More details are needed here as to how the wetland CH4 fluxes are derived.

L220: It would be good to see a map of these biogenic fluxes, comparable to Figure 2. Are they sensible? Has the WRF-GHG soil moisture/temperature been evaluated?

L235: This is lacking detail. What were the test permutations for the parameterisations? What was the final configuration?

L338: What are the implications of this regridding? What was the approach taken for the averaging kernel and a priori information? More details are needed.

Figure 3: Missing units. A single colourbar could be used (it’s just repeated).

Figure 3: The ICOS data all looks to have similar values throughout the year with very little variability compared to the simulations.

L394: I don’t believe this is true (but I could be wrong). Specifically I’m thinking of Tsuruta et al. (2023) who state “Anthropogenic fluxes, such as those from agriculture, landfills and production and use of oil, gas and coal, are taken from the EDGAR v6.0 inventory”.

L495: This comes back to why this time period specifically was selected and also the point earlier about how some of the fluxes were calculated (e.g. wetland emissions).

L519: The modelled stratosphere can play a significant role and I don’t see a mention of that. Has any attempt been made to assess how well the modelled stratosphere performs (e.g. by comparison to profile observations or other sources)?

Figure 6 – Caption: I think the “respectively” needs to be moved outside of the brackets as I think it also applies to panels a/e.

Figure 6: Panels C/G – This difference is dominated by the offset and there’s very little spatial structure visisble (i.e. it’s all light red or all light blue). It may be more informative to centre the colourbar around the average and lessen the range to enahcne spatial details.

The manuscript describes the first part of the AUMIA system, which focuses on the forward modelling with WRF-GHG and its evaluation using TROPOMI and ICOS observations. The major concern is that without the inverse modelling part of the work, this first paper does not include much of a model development but focuses on forward modelling evaluation. In addition, there are several methodological descriptions missing, that should be clarified, that I listed below. Other than these aspects, the manuscript is well-written and easy to follow and understand. However, before being suitable for publishing in GMD, the below comments need to be addressed and implemented.

Comments:

Lines 34-36. This last sentence sounds like an overstatement as there are previous studies using TROPOMI observations.

Line 98-99: How are these periods selected? This should be better described.

Line 119: What are these flux models and how do they work? More information is needed here.

Table 1 can be considered to be moved to the supplement.

Lines 235-237: More information is needed for these sensitivity simulations.

Lines 244-250: This section and Table 2 are identical, just keep one of them.

ICOS stations in Figures 3-5 seem to not change, should be double-checked.

Editorial comments:

Line 15: Remove “a” before powerful tools.

Line 28: Remove “otherwise” and add “On the other hand” in the beginning of the sentence.

Line 39: Add a reference after the first sentence.

Figures 3-5. Units are missing in the figures and/or the figure caption.