Comment on the reply to the first comment on “ Validation of XCH 4 derived from SWIR spectra of GOSAT TANSO-FTS with aircraft measurement data ”

Abstract. Column-averaged dry-air mole fractions of methane (XCH4), retrieved from Greenhouse gases Observing SATellite (GOSAT) short-wavelength infrared (SWIR) spectra, were validated by using aircraft measurement data from the National Oceanic and Atmospheric Administration (NOAA), the US Department of Energy (DOE), the National Institute for Environmental Studies (NIES), the HIAPER Pole-to-Pole Observations (HIPPO) program, and the GOSAT validation aircraft observation campaign over Japan. In the calculation of XCH4 from aircraft measurements (aircraft-based XCH4), other satellite data were used for the CH4 profiles above the tropopause. We proposed a data-screening scheme for aircraft-based XCH4 for reliable validation of GOSAT XCH4. Further, we examined the impact of GOSAT SWIR column averaging kernels (CAK) on the aircraft-based XCH4 calculation and found that the difference between aircraft-based XCH4 with and without the application of the GOSAT CAK was less than ±9 ppb at maximum, with an average difference of −0.5 ppb. We compared GOSAT XCH4 Ver. 02.00 data retrieved within ±2° or ±5° latitude–longitude boxes centered at each aircraft measurement site with aircraft-based XCH4 measured on a GOSAT overpass day. In general, GOSAT XCH4 was in good agreement with aircraft-based XCH4. However, over land, the GOSAT data showed a positive bias of 1.5 ppb (2.0 ppb) with a standard deviation of 14.9 ppb (16.0 ppb) within the ±2° (±5°) boxes, and over ocean, the average bias was 4.1 ppb (6.5 ppb) with a standard deviation of 9.4 ppb (8.8 ppb) within the ±2° (±5°) boxes. In addition, we obtained similar results when we used an aircraft-based XCH4 time series obtained by curve fitting with temporal interpolation for comparison with GOSAT data.

Comment on the reply to the first comment on "Validation of XCH4 derived from SWIR spectra of GOSAT TANSO-FTS with aircraft measurement data" by M. Inoue et al.
The manuscript becomes clearer.However, I still have some comments.
Dear anonymous referee #1, Thank you very much for your careful reading of our manuscript and valuable comments.
Comment on "Validation of XCH4 derived from SWIR spectra of GOSAT TANSO-FTS with aircraft measurement data" by M. Inoue et al.

General:
This paper describes the validation results of GOSAT XCH4 Ver.02.00 with aircraft measurement data from various projects and sites.The validation of the satellite measurement of greenhouse gases is important to estimate the global and temporal variations of the emission and sink of them.
The paper is well described and it should be published after some revisions.
Comments and questions: 2.2.6 p13, l1 equation (4) Here 'Trend' is a constant value.But year to year variation of growth rate is large for CH4.Are the fitting errors caused by this constant trend small enough for all sites?
We show "Trend" in the equation ( 4) and its fitting error at four sites (PFA, NHA, SGP, CMA) in Table R-1.The fitting error is about 0.7-0.8ppb/year, and we consider that the fitting error caused by the constant trend is small for all sites.In addition to the two sites (SGP and RTA) shown in the manuscript, we examined seasonal dependences of the uncertainties at another two sites (LEF and SGM).
It is better to describe that you examined seasonal dependences of the uncertainties at four sites although you only show for two sites.

2.3
Does 'temporally matched' mean the time difference less than 24 hrs or some shorter time?I guess that the maximum time difference is much shorter than 24 hrs because most of aircraft measurements and GOSAT observations maybe performed during daytime.
"Temporally matched" does not mean the time difference less than 24 hours (or some shorter time).More simply, it means that the GOSAT data and aircraft measurement data are obtained on the same day at each site.The maximum time difference was about 9 hours.
It is also better to describe that the maximum time difference was about 9 hours in the manuscript.

Fig. 7
The differences between aircraft-based XCH4 with CAK and without CAK seem to have seasonal (or some temporal) variations.Can you explain this?
At this point, we do not have sufficient information to explain the seasonal variations you pointed out.However, we consider that since this may be related to the fact that CAK is a function of solar zenith angle, we may have to use aircraft-based XCH4 with CAK when possible.
I see.Could you comment on the possibility of solar zenith angle dependency and it is small enough (or not) compared with other uncertainty?
Table 6 The increasing rate of matched data number is much larger over land than that over ocean.

Do you know why?
We believe that your question means why matched data number becomes much larger over land than that over ocean by expanding the spatial coincidence criteria (from ±2° boxes to ±5° boxes).Most of aircraft sites with much observation data (e.g., SGP, AAO, HIL, LEF) are located in inland.Even if we expand the spatial coincidence criteria, even the ±5° boxes cannot cover ocean regions.It means that expanding to ±5° boxes can lead to much larger matched data over land than ocean.
Sorry for confusing.I mean that the increasing rates of matched data number between direct and curve-fitting are larger over land (43 to 1543: 35.9 times, 102 to 8060: 79 times) than those over ocean (3 to 23: 7.7 times, 10 to 207: 20.7 times).

Table R -
1. Trends of aircraft-based XCH4 and their fitting errors at each site.