the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
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
Angel Liduvino Vara-Vela
Christoffer Karoff
Noelia Rojas Benavente
Janaina Nascimento
Abstract. Methane is the second most important greenhouse gas after carbon dioxide, and accounts for around 10 % of total European Union greenhouse gases emissions. Given that the atmospheric methane budget over a region depends on its terrestrial and aquatic methane sources, inverse modeling techniques appear as a powerful tools for identifying critical areas that can later be submitted to emission mitigation strategies. In this regard, an inverse modeling system of methane emissions for Europe is being implemented based on the Weather Research and Forecasting (WRF) model: the Aarhus University Methane Inversion Algorithm (AUMIA) v1.0. The forward modeling component of AUMIA consists of the WRF model coupled to a multipurpose global database of methane anthropogenic emissions. To assure transport consistency during the inversion process, the backward modeling component will be based on the WRF model coupled to a lagrangian particle dispersion module. A description of the modeling tools, input data sets and one-year forward modeling evaluation from April 01, 2018 to March 31, 2019 is provided in this paper. The a posteriori methane emission estimates, including a more focused inverse modeling for Denmark, will be provided in a second paper. A good general agreement is found between the modeling results and observations based on the TROPOspheric Monitoring Instrument (TROPOMI) onboard the Sentinel-5 Precursor satellite. Model-observation discrepancies for summer peak season are in line with previous studies conducted over urban areas in central Europe, with relative differences between simulated concentrations and observational data in this study ranging from study ranging from 1 to 2 %. Domain-wide correlation coefficients and root-mean-square-errors for summer months ranged from 0.4 to 0.5 and from 27 to 30 ppb, respectively. For winter months, otherwise, model-observation discrepancies show a significant overestimation of anthropogenic emissions over the study region, with relative differences ranging from 2 to 3 %. Domain-wide correlation coefficients and root-mean-square-errors in this case ranged from 0.1 to 0.4 and from 33 to 50 ppb, respectively, indicating that a more refined inverse analysis assessment will be required for this season. According to modeling results, the methane enhancement above the background concentrations came almost entirely from anthropogenic sources; however, these sources contributed with only up to 2 % to the methane total column concentration. Contributions from natural sources (wetlands and termites) and biomass burning were not relevant during the study period. 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.
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Angel Liduvino Vara-Vela et al.
Status: final response (author comments only)
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CEC1: 'Comment on gmd-2023-9', Juan Antonio Añel, 05 May 2023
Dear authors,
Unfortunately, after checking your manuscript, it has come to our attention that it does not comply with our "Code and Data Policy".https://www.geoscientific-model-development.net/policies/code_and_data_policy.htmlYou have archived your code and data on UCAR servers and GitHub. However, these are not suitable repositories for scientific publication. GitHub itself instructs authors to use other alternatives for long-term archival and publishing, such as Zenodo. Therefore, please, publish your code in one of the appropriate repositories, and reply to this comment with the relevant information (link and DOI) as soon as possible, as it should be available for the Discussions stage. Also, please, include the relevant primary input/output data.In this way, if you do not fix this problem, we will have to reject your manuscript for publication in our journal. I should note that, actually, your manuscript should not have been accepted in Discussions, given this lack of compliance with our policy. Therefore, the current situation with your manuscript is irregular.Also, you must include in a potentially reviewed version of your manuscript the modified 'Code and Data Availability' section, the DOI of the code (and another DOI for the dataset if necessary). Moreover, in the GitHub repository for AUMIA there is no license listed. If you do not include a license, the code is not free-libre open-source software (FLOSS); it continues to be your property. Therefore, when uploading the model's code to the repository of your choice compliant with our policy, you could want to choose a FLOSS license. We recommend the GPLv3. You only need to include the file 'https://www.gnu.org/licenses/gpl-3.0.txt' as LICENSE.txt with your code. Also, you can choose other options that Zenodo provides: GPLv2, Apache License, MIT License, etc.Juan A. AñelGeosci. Model Dev. Exec. EditorCitation: https://doi.org/10.5194/gmd-2023-9-CEC1 -
AC1: 'Reply on CEC1', Angel Liduvino Vara-Vela, 05 May 2023
Dear Juan Antonio,
Thank you for the comment
We have just created a zenodo repository to archive all relevant files to replicate the modeling results we present in the manuscript. Below are the link and DOI as required
Link: https://doi.org/10.5281/zenodo.7899895
DOI: 10.5281/zenodo.7899895
Do I need to upload here a new version of the manuscript including this information?
Citation: https://doi.org/10.5194/gmd-2023-9-AC1 -
EC1: 'Reply on AC1', Fiona O'Connor, 05 May 2023
Dear Angel,
Thank you for setting up a zenodo repository. This will be helpful to the reviewers and the final acceptance of your manuscript will depend on ensuring that these details are in the revised manuscript.
Regards,
Fiona O'Connor
Citation: https://doi.org/10.5194/gmd-2023-9-EC1 -
AC2: 'Reply on EC1', Angel Liduvino Vara-Vela, 06 May 2023
Dear Fiona,
It remains unclear to me whether I have to upload here a new version of the manuscript including the repository details, please confirm it
Angel
Citation: https://doi.org/10.5194/gmd-2023-9-AC2 -
CEC2: 'Reply on AC2', Juan Antonio Añel, 10 May 2023
Dear authors,
It is not necessary that you upload a new version of the manuscript at this point. The necessary information is now published in this thread in Discussions. If, eventually, the handling topical editor considers that your manuscript is acceptable for publication or if revisions are requested, then you should include the necessary amendments to the text in the future new version.
Regards,
Juan A. Añel
Geosci. Model Dev. Executive Editor
Citation: https://doi.org/10.5194/gmd-2023-9-CEC2
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CEC2: 'Reply on AC2', Juan Antonio Añel, 10 May 2023
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AC2: 'Reply on EC1', Angel Liduvino Vara-Vela, 06 May 2023
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EC1: 'Reply on AC1', Fiona O'Connor, 05 May 2023
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AC1: 'Reply on CEC1', Angel Liduvino Vara-Vela, 05 May 2023
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RC1: 'Comment on gmd-2023-9', Anonymous Referee #1, 12 May 2023
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.
Citation: https://doi.org/10.5194/gmd-2023-9-RC1 -
AC3: 'Reply on RC1', Angel Liduvino Vara-Vela, 25 May 2023
Dear referee,
We would like to thank you for the appropriate and constructive comments. A point-by-point response file is attached, and when the discussion period ends we will post a revised version of the manuscript with all the suggestions included.
Best regards,
The authors
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AC3: 'Reply on RC1', Angel Liduvino Vara-Vela, 25 May 2023
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RC2: 'Comment on gmd-2023-9', Anonymous Referee #2, 01 Jun 2023
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.
Citation: https://doi.org/10.5194/gmd-2023-9-RC2 -
AC4: 'Reply on RC2', Angel Liduvino Vara-Vela, 08 Jun 2023
Dear referee,
We would like to thank you for the appropriate and constructive comments and suggestions. A point-by-point response file is attached, and when the discussion period ends we will post a revised version of the manuscript with all the suggestions included.
Best regards,
The authors
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AC4: 'Reply on RC2', Angel Liduvino Vara-Vela, 08 Jun 2023
Angel Liduvino Vara-Vela et al.
Angel Liduvino Vara-Vela et al.
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