Response to Referee # 2 ' Comments MS No . : amt-2021-92 MS type : Research article Title : Atmospheric Carbon Dioxide Measurement from Aircraft and Comparison with OCO-2 and Carbon Tracker Model Data

Dear Professor, Thank you very much for spending your valuable time in reviewing our research paper and providing the list of comments/suggestions. You have put forward detailed and specific modification suggestions for the article, including the layout of the article, the citation of references, the interpretation of formula parameters, etc. We have responded to your modification suggestions one by one and made corresponding modifications to the manuscript. The amendments are mentioned below. Your valuable comments play a very important role in improving the article. Thank you again for your valuable comments

Where, is the point number of the pulse, and represent the mean and standard deviation.
is the value of each point on the pulse, and is the standard deviation of each point. Hence, the SNR of the sum can be written as Therefore, we can choose the number of points on the pulse to improve the SNR of each pulse.

OCO-2 Measurement Results
During this flight experiment, the OCO-2 passed over the flight area on March 16 and the observations over the study area are shown in Figure 18.  Figure 18(b) shows the XCO2 results detected by  shows the corresponding standard deviation production of OCO-2. As can be seen from Figure 18(a), OCO-2 observations covered both ocean and land surfaces. Due to the fast flight speed of the satellite, the data time period falling in the study area was from 12:57:25 to 12:57:38 UTC. A quality flag was applied to the satellite dataset and the cloud-contaminated retrievals were removed. In the flight area, there is little difference between the values of XCO2 measured by OCO-2 over land and ocean areas. The average value of XCO2 over land area is 414.28 ± 0.81 ppm and that over ocean area is 414.23 ± 0.55 ppm. However, due to the uneven distribution of CO2 volume mixing ratio in the land area, the standard deviation of XCO2 products over the land area is larger than that over the ocean. The XCO2 measured by OCO-2 varied from 401.66 ppm to 418.80 ppm, with an average of 414.25 ± 0.62 ppm.

Vertical Profile Comparison of CO2 Concentration
The measurement results of the airborne greenhouse gas analyzer were compared with those of OCO-2 inversion and Carbon Tracker model, which is a global carbon cycle data assimilation system. The comparison results are shown in Figure 19. km, the CO2 concentration is almost constant. This might be due to the stability of the atmosphere above.

Specific
Point 1: Line 143ff: "two-way nested chemistry-transport model Tracer Model 5'' (see also  Line 154: CarbonTracker is an inverse model framework developed by . Point 2: I suppose the trace gas is CO2 here, i.e., online means on a CO2 line. If yes please say so. Response 2: We are thankful to the reviewer for the valuable suggestion. We have replaced " trace gas " by "CO2". Relevant changes have been made in the revised version of the manuscript at: Line 162: The laser pulse of the online wavelength was strongly attenuated because it was absorbed by the CO2 molecules while propagating through the atmosphere.
Point 3: "hard target": is that the surface or the cloudtop? Please be more precise here. Response 3: We are thankful to the reviewer for the valuable suggestion. "hard target": is the surface, we have revised the mistake. Relevant changes have been made in the revised version of the manuscript at: Line 170: is the height of the surface above sea level.
where ℜ (V/W) represents the voltage response rate of the APD detector, is the power of echo signal, is the voltage.
Line 176: where Δ 2 is the differential absorption cross section of the online and offline wavelengths, 2 is the molecular density of the CO2. and are pressure and temperature profiles.
Line 189: where is the Avogadro's constant, is the gas constant, ( ) and ( ) are the pressure and temperature profiles, respectively. 2 is the dry-air ratio of water vapor, represents the integral weight function.
Point 5: Section 3.1: Please improve text for the non-expert reader. Response 5: We are thankful to the reviewer for the valuable suggestion. We have improved text about section 3.1. We highlighted the revised/modified text with red font. Relevant changes have been made in the revised version of the manuscript at: Line 209: The performance of the ACDL system was evaluated by comparing the original echo signals over three different surface types, including the ocean, the mountain, and the urban residential surface types. The original signals of the ACDL over the ocean, urban residential, and mountainous areas are shown in Figures 4, 5, and 6, respectively. Including local amplification of each signal. The amplification signals from left to right are online monitor signal, online echo signal, offline monitor signal and offline echo signal. In each group of original echo signals, the online and offline monitor signals are fixed at the same position but the echo signals appear in different positions due to the different heights of the ground surface. The original signals were filtered before using, and the signals whose pulse peak values were not in the linear region of APD were discarded. The echo signals in the ocean area were significantly smaller than those over the residential and the mountain areas. This might be due to the low reflectivity of the ocean, which leads to the reduction of the signal noise ratio (SNR) over the ocean. Point 6: Section 3.2: I suppose Eq. 7 describes the signal and Eq.8 the noise, if yes please write that (see also reviewer #1). Please correct misleading sentences. What is on the abscissa of panel a of Figs. 7-9 (with units)? Response 6: We are thankful to the reviewer for the valuable suggestion. Eq. 7 and Eq. 8 have been explained in detail, and the abscissa of Figs. 7-9 is marked. We highlighted the revised/modified text with red font. Relevant changes have been made in the revised version of the manuscript at: Line 197: In this study, the PIM uses the integrated value of the points on the pulse to calculate DAOD.
In our experiment, the random noise followed Gaussian distribution. When the points on the pulse are superposed, the sum continues following the Gaussian distribution of ( , ( ) Where, is the point number of the pulse, and represent the mean and standard deviation.
is the value of each point on the pulse, and is the standard deviation of each point. Hence, the empirical estimate of the SNR of the equivalent measurement on the whole averaging window can be Therefore, we can choose the number of points on the pulse to improve the SNR of each pulse.
Line 526:   Line 244: Figure 14 shows the comparison of the XCO2 calculated from the ACDL measurements with the dry-air mole fraction of CO2 measured using the UGGA. Both of the datasets show a good agreement by exhibiting a similar variation trend. The results from the two datasets also show that the volume mixing ratio of the atmospheric CO2 is highest over the residential area and the lowest over ocean surface. In this study, the in-situ observations measured using the UGGA were also analysed for several days.
The vertical profiles of the atmospheric CO2 were measured using the UGGA during spiral and the descent of the aircraft and the results are shown in figure 15. The data recorded below 0.5 km were discarded because of sudden spikes due to slowing down of the aircraft and the associated sudden pressure changes. Figure 15 shows that the atmospheric CO2 volume mixing ratio is largest near the ground, and it decreases gradually with the progression in the altitude. This might be due to the weak photosynthesis as the plants are in dormant stage during winter in northeast China (Mustafa et al., 2021).
Moreover, northeast China is also a source of carbon due to heating and industrial activities, which also contributes significantly to the atmospheric CO2 (Shan et al., 1997). In addition, the CO2 concentration at different altitudes were the highest on 18 March. This could be caused by the weather conditions and pollution levels. Table 3 shows the weather report released by the Qinhuangdao meteorological station on each day of the flight. The AOD values measured using various instruments on each flight day are shown Figure Fig.19. Response 8: We are thankful to the reviewer for the valuable suggestion. We have supplemented the contents of Section 3.4 and added the results of standard deviation, including the results of adding standard deviation in Figure 18 (b). Combined with the comment of reviewer #1, we revised the last sentence of section 3.5. We highlighted the revised/modified text with red font. Relevant changes have been made in the revised version of the manuscript at:  Figure 18(b) shows the XCO2 results detected by OCO-2. Figure 18(c) shows the corresponding standard deviation production of OCO-2. As can be seen from Figure 18(

Technical corrections
Additional to the remarks of reviewer #1 there are the following issues: Point 10: Line 64: Don't create fantasy names for existing institutes. The correct name is 'German Aerospace Center (DLR)'. Line 143: Typo in citation.