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    Review of 'A simple and quick sensitivity analysis method for methane isotopologues detection with GOSAT-TANSO-FTS'

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    A simple and quick sensitivity analysis method for methane isotopologues detection with GOSAT-TANSO-FTSCrossref
    This article is timely and useful, even for the non-specialist, but it could be enhanced
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    A simple and quick sensitivity analysis method for methane isotopologues detection with GOSAT-TANSO-FTS

     Edward Malina (corresponding) ,  Jan-Peter Muller,  David Walton (2019)
    Measurements of methane isotopologues can differentiate between different source types, be they biogenic (e.g. marsh lands) or abiogenic (e.g. industry). Global measurements of these isotopologues would greatly benefit the current disconnect between top-down (knowledge from Chemistry Transport Models and satellite measurements) and bottom-up (in situ measurement inventories) methane measurements. However, current measurements of these isotopologues are limited to a small number of in situ studies and airborne studies. In this paper we investigate the potential for detecting the second most common isotopologue of methane ( 13 CH 4 ) from space using the Japanese Greenhouse Gases Observation Satellite (GOSAT) applying a quick and simple residual radiance analysis technique. The method allows for a rapid analysis of spectral regions, and can be used to teach University students or advanced school students about radiative transfer analysis. Using this method we find limited sensitivity to 13 CH 4 , with detections limited to total column methane enhancements of >6%, assuming a desert surface albedo of >0.3.
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      Review information

      10.14293/S2199-1006.1.SOR-EARTH.AIH8CJ.v1.RDFXOQ

      This work has been published open access under Creative Commons Attribution License CC BY 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Conditions, terms of use and publishing policy can be found at www.scienceopen.com.

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      Review text

      This is a welcome review of how satellite observations can be used to differentiate between methane from biogenic and industrial sources from the isotope signatures in infra-red absorption. The study is based mainly on the Japanese GOSAT data and it is a good introduction to students about Radiation Transfer Modelling, but with the proviso that the students are already very familiar with infra-red adsorption and light scattering physics.

      The paper would have much wider appeal if there were explanatory diagrams about the mechanisms of light scattering/adsorption in an introductory section. For example a simple diagram to explain what the GOSAT-TANSO-FTS actually measures would make a large difference to the understanding of the work and give this much more general appeal. The data permits detection  of 13CH4, and the ratio of 13 CH­­4 and 12 CH4 known as δ 13 C. This subject has a lot of acronyms, and an explanatory box listing these would also be very helpful.

      Generally the attention to detail about the modelling is clear, but a reader new to the subject would like to know more about the real utility of this approach. For example it would be useful to see if the methodology has been able to pick out geographical regions where the biogenic  methane dominates the industrial methane, so a spatial map of δ 13 C would be useful.

      Finally some comment about the methane released from methane clathrates should be included in the paper. These may assume increasing importance as the Arctic and Antarctic regions warm and release such methane.

      Comments

      Dear Professor Dobson,

       

      Further to our proposed changes, the following changes have been made in our article. We have kept your original text, and answered in line with underlined text.

       

      This is a welcome review of how satellite observations can be used to differentiate between methane from biogenic and industrial sources from the isotope signatures in infra-red absorption. The study is based mainly on the Japanese GOSAT data and it is a good introduction to students about Radiation Transfer Modelling, but with the proviso that the students are already very familiar with infra-red adsorption and light scattering physics.

       

      Thank you for these positive general comments, we expand further below.

       

      The paper would have much wider appeal if there were explanatory diagrams about the mechanisms of light scattering/adsorption in an introductory section. For example a simple diagram to explain what the GOSAT-TANSO-FTS actually measures would make a large difference to the understanding of the work and give this much more general appeal.

       

      Thank you for this point, in order to address this we have taken the following action.

       

      The original ‘Introduction’ section has been split into two, part one discusses the global context of measurements of methane and why it is important we do so. Part two ‘GOSAT and measuring radiance’ provides a brief introduction to the operations of GOSAT-TANSO-FTS with a diagram showing the concept of solar backscatter. The ‘Beer-Lambert’ law is introduced, in order to give an overview of the physics of absorption.

       

      The data permits detection  of 13CH4, and the ratio of 13 CH­­4 and 12 CH4 known as δ 13 C. This subject has a lot of acronyms, and an explanatory box listing these would also be very helpful.

       

      We have added a new section (number 8) titled “Glossary” to identify key terms and acronyms. This section includes Table 6, populated by these terms.

       

      Generally the attention to detail about the modelling is clear, but a reader new to the subject would like to know more about the real utility of this approach. For example it would be useful to see if the methodology has been able to pick out geographical regions where the biogenic  methane dominates the industrial methane, so a spatial map of δ 13 C would be useful.

       

      In order to address this comment we have included a brief section where we apply the data to GOSAT L1B data downloaded from the GOSAT data archive. The following changes have been made.

       

      Section 4.4.3. has been added, describing a method used for matching the simulated spectra with GOSAT-TANSO-FTS L1B data for a short study.

       

      Section 5.4. has been added, indicating the results of the short study proposed in section 4.4.3, with Figure 10 included in this section, generally indicating the challenge of the task with small radiance changes.  

       

      Finally some comment about the methane released from methane clathrates should be included in the paper. These may assume increasing importance as the Arctic and Antarctic regions warm and release such methane.

      Thank you, we have inserted the following section into the introduction in order to address these comments.

       

      Melting of the permafrost is a topic of particular concern, with the Arctic warming faster than any other part of the Earth. The Arctic, currently a minor source of methane could become a major source over the coming century due to this warming (Nisbet et al., 2019). Methane emissions from the Arctic is a particularly complex issue, with up to 33% of the world’s organic carbon stored within the Arctic permafrost (Schuur et al., 2015), and vast reserves of methane stored in crystalline clathrate structures (Myhre et al., 2016). Yet there is no consensus on how and when these carbon reserves will enter the atmosphere; new data and methods are required to address these uncertainties.

       

      With best regards

       

      Ed Malina & co-authors

       

      2020-12-13 21:21 UTC
      +1

      Dear Professor Dobson,

       

      Thank you for reviewing our article.

       

      We agree with the general points you have made in your review, and we propose to make the following changes:

      1) Provide a top-level overview of what GOSAT is measuring, and why this is important.

      2) Add additional context, with a focus on the thawing permafrost in the Arctic regions, highlighting that this is still a highly misunderstood process.

      3) Finally, we will add a section where we use GOSAT L1B data downloaded from the GOSAT webportal to assess the utility of the simulated method proposed in the main body of the article. 

       

      With best regards,

       

      Ed Malina & authors 

      2020-11-03 02:27 UTC
      +1

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