Model simulations of atmospheric methane (1997–2016) and their evaluation using NOAA and AGAGE surface and IAGOS-CARIBIC aircraft observations

Zimmermann, Peter H.; Brenninkmeijer, Carl A. M.; Pozzer, Andrea; Jöckel, Patrick; Winterstein, Franziska; Zahn, Andreas; Houweling, Sander; Lelieveld, Jos

doi:https://doi.org/10.5194/acp-20-5787-2020

Articles | Volume 20, issue 9

https://doi.org/10.5194/acp-20-5787-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Special issue:

The Modular Earth Submodel System (MESSy) (ACP/GMD inter-journal...

https://doi.org/10.5194/acp-20-5787-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 20, issue 9

Research article

|

14 May 2020

Research article |

| 14 May 2020

Model simulations of atmospheric methane (1997–2016) and their evaluation using NOAA and AGAGE surface and IAGOS-CARIBIC aircraft observations

Peter H. Zimmermann, Carl A. M. Brenninkmeijer, Andrea Pozzer, Patrick Jöckel, Franziska Winterstein, Andreas Zahn, Sander Houweling, and Jos Lelieveld

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Final revised paper (published on 14 May 2020)
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Preprint (discussion started on 15 Feb 2018)
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Interactive discussion

Status: closed

AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

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RC1: 'Review of discussion paper "Model simulations of atmospheric methane and their evaluation using AGAGE/NOAA surface- and IAGOS-CARIBIC aircraft observations, 1997-2014" by P. Zimmermann et al.', Anonymous Referee #1, 06 Apr 2018
- AC2: 'reply to referee#1', Peter Zimmermann, 31 Jan 2019
RC2: 'Review of manuscript ``Model simulations of atmospheric methane and their evaluation using AGAGE/NOAA surface- and IAGOS-CARIBIC aircraft observations, 1997--2014'' by Peter H. Zimmermann et al.', Anonymous Referee #2, 17 Apr 2018
- AC1: 'Reply to referee#2's comments', Peter Zimmermann, 15 Jan 2019

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision

AR by Peter Zimmermann on behalf of the Authors (27 Mar 2019) Author's response Manuscript

ED: Referee Nomination & Report Request started (29 Mar 2019) by Maria Kanakidou

RR by Anonymous Referee #1 (09 Apr 2019)

Suggestions for revision or reasons for rejection

Re-Review of revised manuscript "Model simulations of atmospheric methane 1997-2016 and their evaluation using NOAA and AGAGE surface- and IAGOS-CARIBIC aircraft observations" by Zimmermann et al.

The revised manuscript of Zimmermann et al. presents an updated analysis of the global CH4 budget (and trends), using now 17 global monitoring stations instead of only 6 stations in the initial discussion paper, while leaving out coastal stations (used in the initial discussion paper), which cannot be well reproduced by the EMAC model. Therefore the authors addressed the general comments (1) and (2) of my previous review.

However, the authors did not address at all my previous comment (3) and still analyze only one hypothesis for the global CH4 increase, namely the combined increase of CH4 emissions from shale gas in North America and from tropical wetlands. Given the large number of hypotheses discussed in the literature, I find it very unsatisfactory that the analysis of the paper is still limited just to this single scenario. In addition, the authors do not even make any attempt to motivate the choice of this particular scenario. While there is some evidence from several studies that agricultural CH4 emissions from ruminants have increased (a scenario which unfortunately is not further analyzed in the paper), a persistent increase of tropical wetland CH4 emissions over the whole 2007-2016 period remains very speculative. The authors only briefly state in section 4.2 (lines 399-400): "Enhanced precipitation in the regional summer season (Nisbet et al., 2016; Bergamaschi et al., 2013) may be a possible cause of growing tropical wetland emissions". However, none of the 2 cited papers analyzed in any detail the tropical precipitation patterns, nor do Zimmermann et al. present any own meteorological analyses. While some studies in the literature found some correlations between tropical wetland CH4 emissions and ENSO induced anomalies in precipitation [e.g. Pandey at al., 2017], the reported anomalies appear directly related to the ENSO patterns (with a typical duration in the order of 1 year) - but to my knowledge do not support any persistent increase over the entire 2007-2016 period.

Given the restriction of the paper to a single scenario (which - in my view - is not the most likely one) the added value of the paper to the analysis of the global CH4 trends remains very limited.
Furthermore, the presentation of the paper is not satisfactory - in the following just some examples:

(a) Introduction, page 3 (lines 84-86): "In other words, it was found by both authors that the combined fossil CH4 sources (1985-2002) must have been much stronger (factor of 2), at the expense of microbial sources." This conclusion was drawn only by Schwietzke et al. (2016), but not by Schaefer et al (2016). Then the authors continue: "Further, it was concluded that fossil fuel related sources had decreased." This was indeed concluded in both studies. However then the text continues: "Although the findings of the two articles are not necessarily in conflict...." As the studies have first been presented to give the same conclusions (which I think is not correct regarding the first statement): why should they then be in conflict?

(b) Presentation of results: The first 1.5 pages of the results section ("4 Simulation results" and "4.1 The period 1997 through 2006" largely discuss again the model setup, especially the use of the tagged tracers (repeating 3 times the finding that the sum of the tagged methane tracers is equal to the "reference tracer" with all emission sources - a finding which is basically trivial, since the system is setup as linear system).

(c) apart from the restriction of the analysis to a single scenario (see my general comment above) the discussion of this single scenario is only very limited. At the end of section 4.2.1 the authors state:
"Kirschke et al. (2013) and Turner et al. (2016), however, found that an increase by 17-22 Tg/y could explain the renewed methane growth and 30-60% of this could be attributed to increasing U.S. anthropogenic methane emissions, which supports our results with 20.70 Tg/y emission increase including 8.38 Tg/y", but do not mention that the results of Turner et al. (2016) have been questioned by Bruhwiler et al [2017], highlighting in particular several methodical issues in the Turner et al. (2016) paper. In general the discussion of the results should be put much more in context with the existing literature.

(d) the presentation of the conclusions and outlook should better summarize the real conclusions (and limitations) of the study. E.g. the discussion of the "2nd order polynomial extrapolation predicts steady state after 13 years" seems rather hypothetical and the statement " NOAA/AGAGE station methane data are updated annually so further updates are expected" rather trivial.

A further issue of the paper is that the applied optimization technique is rather simple. In principle such simple techniques (with a very limited number of parameters) can be useful for quick analyses and for illustrative purposes. However, this should be put into context with more sophisticated inverse modelling techniques and should include a discussion of the limitations of these simple techniques. The optimization technique used in this study is rather similar to simple synthesis inversion techniques, typically used ~20 year ago (e.g. [Hein et al., 1997]) - using fixed global spatial and temporal emission distribution patterns. A very critical issue of these synthesis inversions, however, is that they are prone to the so-called aggregation error [Kaminkski et al., 2001].

Given the discussed limitations of the revised paper, I cannot recommend the paper for publication in ACP.

References

Bruhwiler, L. M., et al., U.S. CH4 emissions from oil and gas production: Have recent large increases been detected?, J. Geophys. Res.-Atmos., 122(7), 4070-4083, 2017.

Hein, R., P. J. Crutzen, and M. Heimann, An inverse modeling approach to investigate the global atmospheric methane cycle, Global Biogeochem. Cycles, 11, 43-76, 1997.

Kaminski, T., P. J. Rayner, M. Heimann, and I. G. Enting, On aggregation errors in atmospheric transport inversions, J. Geophys. Res., 106(D5), 4703-4715, 2001.

Pandey et al., Enhanced methane emissions from tropical wetlands during the 2011 La Niña, Scientific Reports volume 7, Article number: 45759, 2017.

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ED: Reconsider after major revisions (11 Apr 2019) by Maria Kanakidou

AR by Peter Zimmermann on behalf of the Authors (19 Jul 2019)

ED: Referee Nomination & Report Request started (23 Jul 2019) by Maria Kanakidou

RR by Anonymous Referee #2 (06 Sep 2019)

Suggestions for revision or reasons for rejection

The manuscript by Zimmermann et al. presents findings of a modeling study trying to identify the source strength of CH4 from different sectors, so that the ECHAM5/EMAC/MESSy modelling system properly reproduces the measured CH4 concentrations throughout a 20 year period.

In the manuscript the model setup is explained and the results are presented, supported by an abundance of figures.

There are a few minor points that I would like to see addressed before final publication on ACP:

1 - The authors should mention a reason why they are not using information for the inter-annual variability of CH4 emissions. It is clearly stated that inter-annually constant natural and anthropogenic emissions are used, when there have been regional - and global, changes within the period they are simulating (e.g. see "Global trends of methane emissions and their impacts on ozone concentrations" (doi:10.2760/820175)). The do give an explanation on why they do not use inter-annually changing OH concentrations, supported by references, but not for the emissions. If they choose not to include these changes there should be a short assessment explaining how they believe this affects the results.

2 - The sentence in lines 139-141 is repeated 10 lines later (149-151). One of the two should be changed/removed.

3 - P4 L152: The authors state that the model properly represented the years 1997-2006 after multiple spin-ups. Up to this point in the manuscript there is no mention of any kind of emission optimizing. This means that the model, with inter-annually constant emissions, without any emission optimization taking place, captured both the increasing concentrations of the years 1997-2000, and the stagnated period of 2000-2006. If this is the case, I would assume that the model was not yet in equilibrium, since there should be a linear relation between emissions and CH4 concentrations.

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ED: Reconsider after major revisions (11 Sep 2019) by Maria Kanakidou

AR by Peter Zimmermann on behalf of the Authors (18 Dec 2019) Author's response Manuscript

ED: Referee Nomination & Report Request started (18 Jan 2020) by Maria Kanakidou

RR by Anonymous Referee #2 (28 Jan 2020)

ED: Publish subject to minor revisions (review by editor) (09 Feb 2020) by Maria Kanakidou

Thank you very much for the large effort you made to restructure the manuscript. This now reads nicely and is very informative. However, there are a few small improvements needed before this is published in ACP.
Some of them are mentioned by the reviewer.
A few more corrections are listed here-below. Please make all appropriate corrections to the manuscript and submit a revised track changes document that will go through editor review.
1. Please define the spin up time for the EMAC simulation.
2. L 22-23: rephrase for clarity : what the interhemispheric difference the model calculates and what is observed
3. Section 3.4 page 6: At the end of the section you need to clearly spell out how the posteriori CH4 EMAC simulation is made. For instance something like: After optimizing the source strengths, the CH4 EMAC distribution has been simulated as the sum of the tagged methane tracers corresponding to the posteriori emissions. Because if I understand it correctly you did not re-run the full EMAC with the posteriori emissions.
4. Line 250: remove ‘and’
5. Line 288: In Table 1 I read sum of emissions: a priori 580, posteriori 577 Tg/yr. 577 should be corrected to 578 but even with this correction the difference is 2 and about 0.3%. Do I read something wrong? Obviously it has to do with the rounding of the numbers but please make consistent.
6. Lines 296-297: The sentence does not read well – please rephrase.
7. Lines 298-301: The sentence does not read well: what is the 131.1 nmol/mol and what the 133.3 nmol/mol. Please rephrase.
8. Lines 305-306: The sentence starting by ‘A shorter…’ does not read well. Do you mean: For the same source strength, the atmospheric abundance is lower at a longer than a shorter distance from the source. Please rephrase.
9. line 319: I think you refer to Table 2 here and not 3
10. line 330: I would remove ‘the graphs of’
11. line 333, remove the text between comma ‘ according to the definition in Sect. 3.2 (Fig.2b)’
12. line 334: add after ‘sampling regions’ ‘defined in Sect 3.2 (Fig 2b)’
13. line 393: confirm

Figure 1 provide units in the figure caption
Figure 2 caption: line 740, please provide time frame for these flights routes (1996 to present?)
Figure 6: correct caption for clarity: Annual zonal mean OH mixing ratios in pmol/mol.
Figures 7, 9b and 16: Increasing the size of the y-axis would be beneficial for the reader to see the differences.
Figure 8 caption: explain which is each region and provide y and x axis explanations
Figure 9b caption: same for … Please rephrase the caption.
Figure 10 caption: move the second sentence in the beginning of the caption.
Figure 12 caption: move ‘2007 through 2016’ after ‘stations’
Line 800: from 2007 through 2014
Figure S16: explain in the caption what the x axis is representing.

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AR by Peter Zimmermann on behalf of the Authors (21 Feb 2020) Author's response Manuscript

ED: Publish as is (04 Mar 2020) by Maria Kanakidou

AR by Peter Zimmermann on behalf of the Authors (27 Mar 2020)

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Short summary

The atmospheric abundance of the greenhouse gas methane is determined by interacting emission sources and sinks in a dynamic global environment. In this study, its global budget from 1997 to 2016 is simulated with a general circulation model using emission estimates of 11 source categories. The model results are evaluated against 17 ground station and 320 intercontinental flight observation series. Deviations are used to re-scale the emission quantities with the aim of matching observations.