Accuracy Verification of Satellite Products and Temporal and Spatial Distribution Analysis and Prediction of the CH4 Concentration in China
Round 1
Reviewer 1 Report
The paper “Accuracy verification of satellite products and temporal and spatial distribution analysis and prediction of the CH4 concentration in China” considers problem of orbital spectrometer AIRS products (v. 7) reliability regarding methane concentration. After being compared with ground-based CH4 concentrations AIRS retrieved monthly CH4 product had been used to forecast future methane behavior over China. The problem of satellite data verification and assimilation for prognostic and carbon neutrality goals is very actual and important. In their research authors use up-to-date databases and statistical modeling. The manuscript includes interesting methodology and analyses but, to my opinion, it contains serious shortcomings and can not be accepted for publication.
First, argumentation of AIRS (v. 7) methane product accuracy does not look convincing. 6 ground-based stations located in and around of China are taken for comparison but only 1 is situated in the center of China. It has the worst correlation with satellite retrieved data and smallest number of observations. At the same time it is the central China with its significant anthropogenic emissions that demands careful grounding of orbital spectrometers ability to reproduce variations caused by man-made impact. More convincing proof of AIRS (v. 7) reliability for main China domain (and/or reference to such a comparison from literature carried out just for v. 7) is necessary.
Second (probably, the most important issue), analyses and conclusions are largely based on averaged methane concentration calculated for the whole China or parts of it. Especially strange it looks when average values are taken for the whole considered time-period (2003-2021). China is a great country with huge territory and differences in emissions value and variability. Since 2003 methane has changed (mostly increased) with different (in space and in time) rate. Of course, even such abstract averaged value reflects some real processes but it is strange to talk about its accuracy and forecast of something that does not have physical sense. Apparently, it would be better and more concrete to simulate methane past and future changes for selected stations area. It is also unclear how those averages were calculated.
Third, the manuscript contains serious mistakes and inaccuracies. For instance, even in the abstract it is stated that CH4 concentration over China grows at the average rate of 5,79% per year while the global methane annual growth rate during 2003-2021 did not exceed 1%.
Remarks
Line 18 - “the AIRS data accuracy is higher” – how was this conclusion obtained? I don’t think that it is in general correct to compare accuracy of ground-based observations with AIRS retrievals at height 500 hPa and resolution 1°x1°.
Line 24 - “1890 ppb” – what does this value mean? Is it average value for 2003-2021? I believe this approach incorrect for methane (see remarks to figure 2)
Line 25-26 – annual methane growth can not be so high. Maybe, the growth rate for 2003-2021 is indicated here. It is inappropriate mistake.
Line 28 – the same remark as for the line 24.
Line 30 – what mean “real values” in this case?
Lines 37-38 – First two sentences are poor. It is unnecessarily to mention CO2 often if paper is about CH4. It’s enough to compare the impact of CO2 and CH4 once, for instance like it was done in the 3rd sentence. Beginning should be edited.
Line 42 – I would exclude “in 2021” and insert the reference on 6th IPCC report.
Lines 43-44 - The reference is needed after these 2 sentences
Line 44 – “mainly” is odd word here, should be excluded
Line 46 – it is better to rank sources according to their magnitude. It is not logic to put termites in the beginning.
Line 69 – “at home and abroad” – sounds weird, it is better to edit this
Lines 146-147 – it would be more visual to map those stations.
Table 1 – why is there substantially less data from Shangdianzi station comparatively to other stations? Actually, this station is really important because it is located in the middle of research domain and low correlation of AIRS retrieved data and ground-based data calls into question the validity of the article's conclusions. To correct this shortcoming I would recommend to take other ground-based station located in the central part of the domain (it can be either surface observations or observations of CH4 total column which carried out, for instance, at networks TCCON and NDACC) with more complete dataset and demonstrate availability of particular AIRS v. 7 data (not only of previous versions) for studying surface methane variability in the main China where anthropogenic activity causes its high fluctuations within atmospheric boundary layer which may not always be reliably reflected by orbital spectrometers.
Line 193-195 – this sentence should be edited because of reiteration
Figure 1. - It is enough to place one capture for axis X and Y.
Figure 2. I have not got the idea of this figure. Does it represent average CH4 concentration for 20 year time period? What can this value show taking into account CH4 multiyear trend which furthermore hasn’t been permanent? To my opinion, this figure should be excluded. Instead, it would be more useful to make space distribution of CH4 trends values for 2003-2021. Such figure would reveal unevenness of CH4 temporal changes on the China territory. Moreover, one can present separately the CH4 trend values by time periods – for example, for 2003-2008 and 2009-2022, in order to emphasize methane growth acceleration after 2007.
Figure 5. The name of “d” (probably, winter) is missed in the capture. Generally, see remark to Fig. 2.
Figure 6. The content of this figure is also doubtful (see previous remarks)
Author Response
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Reviewer 2 Report
The paper validated the accuracy of satellite products of CH4 concentration in China and analyzed its temporal and spatial distribution. The subject of the work corresponds to the subject of the journal and can be considered relevant. The work is written in good language, satisfactorily structured, the material is presented consistently and logically. The work is provided with an adequate list of references. The illustrations are simple, but executed with good quality and complement the text well, improving its perception. It was not possible to identify any errors or typos in the text. The material can be published in the journal in the proposed form.
Author Response
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Reviewer 3 Report
Satellite remote sensing can help us improve the understanding the distribution and variation of methane concentration at the regional and even global scale, especially when lacking an effective ground monitoring network at present. This study first validated the AIRS standard methane product by using six WDCCG ground-based stations in and around China. Second, the spatial-temporal characteristics of methane were analyzed, including the annual trend during 2003-2021, the seasonal variation, and the spatial distribution of the three steps in China. Finally, this study predicted the variation trend of methane in the next 10 years based on the SARIMA model. Overall, this manuscript is well written and easy to follow, the illustrations are clear. I think the study is also an important reference for China's “carbon peak and carbon neutrality” policy. I recommend the publication of this article after minor revision. There are some of the amendments as follow.
1. I would recommend revising the language of this article by an English native speaker or a professional party.
2. The main innovative work of this article is not introduced clearly in the abstract. I suggest rewriting the abstract to make it more organized.
3. Introduction: “The seasonal auto-regressive integrated moving average (SARIMA) model is an extension and improvement based on the ARIMA model, considering the seasonality or periodicity of the sequence. Since the CH4 concentration series used in this paper exhibits obvious seasonality and periodicity, the SARIMA model was adopted to predict the future change trend of the CH4 concentration in China.” These sentences should be moved to the method section (Section 2.3).
4. Section 2.1: More details are needed on the data processing of AIRS data, such as the specific parameters used and how to calculate the spatial-temporal means.
5. The name of Y-axis in Figure 1 is repetitive.
6. As far as I know, there are many kinds of geographical distinctions for mainland China. Why use the three steps for analyzing CH4 distribution? More introductions including economy, society，terrain, climate, and other conditions need to be added to this manuscript.
7. Section 3: Authors use a lot of generic knowledge to interpret the analyzed CH4 distribution and trend. The use of more quantitive and accurate evidences is needed. For example, authors may take a look the anthropogenic emissions over the study area. Additionally, authors need to cite more detailed and documented information on relevant evidences, such as energy structure, rice fields, wetlands and other factors closely related to CH4 etc.
8. Section 3.3: “The CH4 concentration difference of the first step was the most obvious, reaching more than 125 ppb and even reaching approximately 170 ppb in some areas.” “Some areas” should be specific.
Author Response
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