the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 24 Nov 2023
Investigating the role of typhoon-induced gravity waves and stratospheric hydration in the formation of tropopause cirrus clouds observed during the 2017 Asian monsoon
Abstract. We investigate the formation mechanism of a tropopause cirrus cloud layer observed during the Balloon measurement campaigns of the Asian Tropopause Aerosol Layer (BATAL) over Hyderabad (17.47° N, 78.58° E), India on 23 August 2017. Simultaneous measurements from a backscatter sonde and an optical particle counter onboard a balloon flight revealed the presence of a subvisible cirrus cloud layer (optical thickness ~0.025) at the cold-point tropopause (temperature ~ -86.4 °C, altitude ~17.9 km). Ice crystals in this layer are smaller than 50 microns with a layer-mean ice-crystal number concentration of about 46.79 L-1. Simultaneous backscatter and extinction coefficient measurements allowed us to estimate range-resolved lidar ratio inside this layer with a layer-mean value of about 32.18±6.73 sr which is in good agreement with earlier reported values at similar cirrus cloud temperatures. The formation mechanism responsible for this tropopause cirrus is investigated using a combination of three-dimensional back-trajectories, satellite observations, and ERA5 reanalysis data. Satellite observations revealed that the overshooting convection associated with a category-3 typhoon Hato, which hit Macau and Hong Kong on 23 August 2017 injected ice into the lower stratosphere. This caused a hydration patch that followed the Asian Summer Monsoon anticyclone to subsequently move towards Hyderabad. The presence of tropopause cirrus cloud layers in the cold temperature anomalies and updrafts along the back-trajectories suggested the role of typhoon-induced gravity waves in their formation. This case study highlights the role of typhoons in influencing the formation of tropopause cirrus clouds through stratospheric hydration and gravity waves.
- Preprint
(2438 KB) - Metadata XML
-
Supplement
(1564 KB) - BibTeX
- EndNote
Status: closed
-
RC1: 'Comment on egusphere-2023-2236', Anonymous Referee #2, 13 Dec 2023
The authors present a study case of the formation and characteristics of a cirrus cloud using the combination of multiple observational tools. For the method, they show how the combination of COBALD and Boulder Counter can be used for the estimation of lidar ratio for optically thin cirrus. Their results highlight the role of gravity waves and crystals injection from the typhoon Hato to explain the formation of the cloud. It describes a new method and an observational study case of the observed impacts of the gravity waves which is significant for the understanding of the interplay between small scale dynamics and microphysics. Finally, it thus also highlights the impacts of typhoons on cirrus clouds.
Although the method is interesting and new to my knowledge, the paper is long and would be improved by a more concise writing to improve the understanding of the methods and key findings of the authors. Therefore I recommend a major revision.
Specific comments :
- 1) The paper is quite long and modifications to shorten it a bit might be useful for a better understanding of the study. Here are a few suggestions/ideas to do so :
In the data method part, the authors wrote a short summary of the history/functioning of the instruments COBALD, SOLAIR, CALIOP, CATS, Himawari-8, added to cited literature relative to each one of the instruments (which should be enough). This might be adding details that are not crucial for the understanding of the author's method.
Same comment for the description of ERA5, the justification to use this dataset could be shortened to lines 6,7, and added details such as number of levels available might be added information confusing for the reader (do we need these 37 levels here?)
Overall, this all method section from p4 to p12 would gain to be summed up to improve the understanding of the discussion regarding each result. Maybe a table, with each key variable and the corresponding instrument? This is just a suggestion.
The lidar ratio part (starting p.17) first describes a discussion about different methods to retrieve this variable, when the key message of the paragraph, which is the authors methods and their demonstration of the use of COBALD and Boulder Counter to retrieve it, appears at the end. This paragraph might gain to be restructured/ shortened to guide the reader to its key points.
p30, the paragraph from l12 to line 19 : As it is, it might be added to the introduction. It doesn't comment on the results, but introduces knowledge about literature regarding gravity waves, not directly connected to the author's findings that are described afterwards. Maybe rephrase/shorten it ? The introduction on the other hand is missing some references to existing literature about gravity wave impacts on cirrus clouds, as the authors are demonstrating it in this study.
- 2) The authors present different formulas to calculate the ice water content and efficient coefficient, describe the differences/ similarities then recap all their results in a table page 19. Is there a conclusion regarding the differences between the effective diameters ?
- 3) figure 2 doesn't fit exactly the description in the text :
CL4 is said to have crystals smaller than 40 microns when I don't see the 20 or 25 microns curve (so the crystals are in fact smaller than 20 microns?). Same comment for CL5.
- 4) figure 12 : the symbols for COBALD, CALIOP, CATS are almost indistinguishable on the figure.
- 5) figure 13 and comments from line 14-28 p.31 : The test of MERRA-2 accuracy could be just mentioned, more details would belong to an appendix. I am not sure what figure 13 is adding to the work already presented in the previous parts ? Maybe I am missing something here.
- 6) Figure 14 is in section 3.4.3 which is highlighting the role of gravity waves in the formation of CL5. It describes that temperature anomalies are inferred by subtracting a monthly mean profile to the 23 August profile. I am not sure to understand why choosing a monthly time scale here when gravity waves usually have periods no longer than a few days ?
- typos/formulations
p.13, l17 : extra space between 100 and unit
p.13, l 19, p34 l22 : 'extremely cold temperature'. The 'extremely' is confusing, compared to what ?
Citation: https://doi.org/10.5194/egusphere-2023-2236-RC1 - AC2: 'Reply on RC1', Amit Kumar Pandit, 17 Feb 2024
-
RC2: 'Comment on egusphere-2023-2236', Anonymous Referee #3, 16 Dec 2023
Review of “Investigating the role of typhoon-induced gravity waves and stratospheric hydration in the formation of tropopause cirrus clouds observed during the 2017 Asian monsoon” by Pandit et al.
This study analyzes backscatter sonde and optical particle counter measurements from balloons over Hyderabad, India to characterize properties of subvisible cirrus layer observed near the tropopause. They then investigate the formation mechanism of these cirrus cloud layers near the tropopause using a combination of back trajectories, satellite observations, and ERA5 reanalysis data. They conclude that overshooting convection from a typhoon created a hydration patch which was transported towards Hyderabad and ascended (via gravity waves) to form the cirrus layer. While the analyses of balloon data to characterize the cirrus cloud properties were interesting, the discussion on the formation mechanism of those clouds, particularly its ties to gravity waves, needs further development and clarification. Detailed comments are provided below.
Main Comments:
Although the combined use of various observations is generally a good idea, the frequent comparisons between measurements from different data sources at different locations and times (e.g., Table 2, Fig. 7, 10, 13) were difficult to interpret. This is especially problematic for this study since the phenomena of interest (i.e., overshooting convection, gravity waves) are small scale features that require coincident measurements. I suggest refining and limiting the selection of observations to only those that meet rigorous time and space matching criteria. I would also present the comparisons in a manner that is easily interpretable by the reader.
I also found the discussion of the trajectory results to be somewhat incoherent. If the main purpose of using the backward trajectories is to show the influence from deep convection on cirrus clouds measured by the balloon, the most important quantity to show is the temperature and relative humidity evolution from the convection encounter to the measurement location. Trajectory results should be more concisely presented instead of across multiple figures. I would similarly reorganize other parts of the paper and make the paper more concise overall.
Detailed Comments:
- P4: The temperature impact by tropical storms in Biondi et al. studies is fairly localized, and as such, I would not describe it as “a change in large-scale temperature fields in the TTL”
- P11: Have the authors looked in the effects of trajectory uncertainties on the results? I’m assuming these are kinematic trajectories, whose dispersive nature may be concerning especially when calculating forward trajectories from UTLS levels.
- P12: Is the use of ERA5 cloud cover fraction necessary? Cloud fields in reanalyses are model products (Wright et al., 2020) and vary depending on prescribed boundary conditions, physical parameterizations (e.g., convection), data assimilation approach, and assimilated data. It is likely unsuited as “cloud observations”. Rather, plotting the 100 hPa temperature (or cold point temperature) field may be more reliable.
- P15: What do you mean by running HYSPLIT trajectories from different altitudes of the CL5? Are the trajectories run at multiple altitudes within the ~2 km thick cloud layer estimated from the balloon measurements? And these trajectories intersect the CATS orbit several hours later at the same altitude as the cirrus detected from CATS? Can you be more specific?
- Fig. 5a: Can you explain what is meant by “day fraction (UTC)”? This is confusing to me since the dots are supposedly showing backward trajectories from 23 Aug 2017 at 20 UTC. Time since balloon measurement may be easier to interpret.
- Fig. 5: What is the temperature history of these trajectories? Are the parcels cooling as they reach the balloon measurement point when cirrus clouds were formed? Figs. 11 and 12 are discussed much later, but this is a key parameter to look at as is RH with respect to ice.
- Fig. 5: How are the parcels that descend backward in time between 115-125 degE in panel (a) represented in panel (b)? In the plan view, it looks like they are wrapped in the typhoon at 125-130 degE, which does not seem to be consistent with panel (b)?
- P21: How exactly is the convective anvil top altitude determined from the brightness temperatures to quantify the convective influence? The text mentions that this is discussed in Section 2.4.1, but I don’t see any description of this methodology.
- P21: Pixel resolution certainly impacts temperatures within a convective cloud, but that fact alone is insufficient to claim that “the highest overshooting tops likely exceeded 18 km height”. More concrete evidence of this is needed to make such a claim.
- Table 2: While I understand the attempt to describe the temperature evolution of the parcel sampled, the disparate data sources (radiosonde, GNSS-RO), locations and times of these measurements make it difficult to say anything about the actual temperature evolution/effect, especially since we expect temperature perturbations on small spatial and temporal scales that greatly affect the cirrus cloud formation. It would make more sense to look at the temperatures along the backward trajectories to describe the evolution (like Fig. 11) and see if those agree with temperature observations at matching times and locations.
- Fig. S3: (a) It would be good to include latitude and longitudes. (b) How realistic is the ERA5 water vapor (compared to observations like MLS)? Are you claiming that the wet anomalies are from the typhoon injected water and ice? (c) is x-axis the latitude?
- Fig. S4: Two temperature profiles are compared, but they are again from two different sources at two different locations at two different times. It is overreaching to claim from this figure alone that “tropopause temperature and tropopause altitude might be substantially reduced by the overshooting convection”. Or is this meant to approximate the cold-point tropopause altitude?
- Fig. 6: Do the back trajectory segments shown here exactly match the trajectories in Fig. 5b? It would be better if you could somehow combine these plots into one since they are approximately showing the same information.
- Fig. 7: Where are the MLS observations (track) on the map? It would be helpful to show those to interpret panel (b). Due to the deep averaging kernel of MLS, it is not clear that the 6.5 ppmv water at 82.5 hPa actually represents enhanced water above the CPT as you suggest in p23. They could be contributed from enhanced moisture near the CPT.
- Fig. 9: Is (a) identical to Fig. S4? If so, this needs to be noted (and S4 could be removed). If not, please explain. How do the MLS values compare with the mean ERA5 water vapor shown in (b)? Rather than color coding the dots by the date, consider coloring the dots with the WV mixing ratios?
- Fig. 10: It would better to plot panels (b) to (e) in chronological order to see the decreasing magnitude (or select one representative location and combine the four profiles in one plot).
- P28: Have the authors checked to confirm that supersaturation (and how high of a supersaturation) is achieved along the trajectories to allow for ice nucleation?
- Fig. 12: What resolution analyses are used for these trajectories? Is the resolution high enough to capture gravity waves? I see that the use of MERRA-2 reanalysis data is mentioned later on p31, but this should be discussed earlier along with Fig. 12. Also, how exactly are the vertical wind speeds derived along the trajectories in (b)? I presume the vertical winds are used to compute the kinematic trajectories.
- Fig. 13: The purpose of this figure is unclear. The text seems to suggest that the purpose is to show the cold anomalies using high resolution data (and their impact cirrus), but it is difficult to interpret where and when these measurements are taken in relationship to the balloon measurements and trajectories. The time and lat/lon are noted in the figure caption, that without a map or time series to place them in larger context, it is very difficult to interpret this figure. It is even unclear whether the measurements plotted in one panel are coincident in time and location (they don’t appear to be).
- Fig. 14: Temperatures were anomalously cold at ~17.9 km near the CPT on 23 Aug, but the tropopause altitudes presumably vary across all the profiles used to calculate the mean. Therefore, panel (a) alone is not sufficient to claim that the CPT was unusually cold on that day. It might make more sense to calculate the anomalies in tropopause relative coordinates. I also do not follow the argument that the variations above 15 km are likely due to waves (“wave-like pattern”). Cooling is likely associated with cirrus formation, but the suggested role of waves from Fig. 14 vertical profiles seems circumstantial at best. The authors mention a “Hodograph analysis of radiosonde data” to show evidence of gravity waves and derive their characteristics, but no description of the analysis is provided.
References:
Wright, J. S., Sun, X., Konopka, P., Krüger, K., Legras, B., Molod, A. M., Tegtmeier, S., Zhang, G. J., and Zhao, X.: Differences in tropical high clouds among reanalyses: origins and radiative impacts, Atmos. Chem. Phys., 20, 8989–9030, https://doi.org/10.5194/acp-20-8989-2020, 2020
Citation: https://doi.org/10.5194/egusphere-2023-2236-RC2 - AC3: 'Reply on RC2', Amit Kumar Pandit, 17 Feb 2024
-
RC3: 'Comment on egusphere-2023-2236', Anonymous Referee #1, 24 Dec 2023
-
AC1: 'Reply on RC3', Amit Kumar Pandit, 17 Feb 2024
We thank the referee (Referee #1) for going through our manuscript and providing constructive feedback for its further improvement. We are glad to read the referee’s views on our manuscript. Please find the attached pdf file for our point-by-point response to the referee’s comments.
-
AC1: 'Reply on RC3', Amit Kumar Pandit, 17 Feb 2024
Status: closed
-
RC1: 'Comment on egusphere-2023-2236', Anonymous Referee #2, 13 Dec 2023
The authors present a study case of the formation and characteristics of a cirrus cloud using the combination of multiple observational tools. For the method, they show how the combination of COBALD and Boulder Counter can be used for the estimation of lidar ratio for optically thin cirrus. Their results highlight the role of gravity waves and crystals injection from the typhoon Hato to explain the formation of the cloud. It describes a new method and an observational study case of the observed impacts of the gravity waves which is significant for the understanding of the interplay between small scale dynamics and microphysics. Finally, it thus also highlights the impacts of typhoons on cirrus clouds.
Although the method is interesting and new to my knowledge, the paper is long and would be improved by a more concise writing to improve the understanding of the methods and key findings of the authors. Therefore I recommend a major revision.
Specific comments :
- 1) The paper is quite long and modifications to shorten it a bit might be useful for a better understanding of the study. Here are a few suggestions/ideas to do so :
In the data method part, the authors wrote a short summary of the history/functioning of the instruments COBALD, SOLAIR, CALIOP, CATS, Himawari-8, added to cited literature relative to each one of the instruments (which should be enough). This might be adding details that are not crucial for the understanding of the author's method.
Same comment for the description of ERA5, the justification to use this dataset could be shortened to lines 6,7, and added details such as number of levels available might be added information confusing for the reader (do we need these 37 levels here?)
Overall, this all method section from p4 to p12 would gain to be summed up to improve the understanding of the discussion regarding each result. Maybe a table, with each key variable and the corresponding instrument? This is just a suggestion.
The lidar ratio part (starting p.17) first describes a discussion about different methods to retrieve this variable, when the key message of the paragraph, which is the authors methods and their demonstration of the use of COBALD and Boulder Counter to retrieve it, appears at the end. This paragraph might gain to be restructured/ shortened to guide the reader to its key points.
p30, the paragraph from l12 to line 19 : As it is, it might be added to the introduction. It doesn't comment on the results, but introduces knowledge about literature regarding gravity waves, not directly connected to the author's findings that are described afterwards. Maybe rephrase/shorten it ? The introduction on the other hand is missing some references to existing literature about gravity wave impacts on cirrus clouds, as the authors are demonstrating it in this study.
- 2) The authors present different formulas to calculate the ice water content and efficient coefficient, describe the differences/ similarities then recap all their results in a table page 19. Is there a conclusion regarding the differences between the effective diameters ?
- 3) figure 2 doesn't fit exactly the description in the text :
CL4 is said to have crystals smaller than 40 microns when I don't see the 20 or 25 microns curve (so the crystals are in fact smaller than 20 microns?). Same comment for CL5.
- 4) figure 12 : the symbols for COBALD, CALIOP, CATS are almost indistinguishable on the figure.
- 5) figure 13 and comments from line 14-28 p.31 : The test of MERRA-2 accuracy could be just mentioned, more details would belong to an appendix. I am not sure what figure 13 is adding to the work already presented in the previous parts ? Maybe I am missing something here.
- 6) Figure 14 is in section 3.4.3 which is highlighting the role of gravity waves in the formation of CL5. It describes that temperature anomalies are inferred by subtracting a monthly mean profile to the 23 August profile. I am not sure to understand why choosing a monthly time scale here when gravity waves usually have periods no longer than a few days ?
- typos/formulations
p.13, l17 : extra space between 100 and unit
p.13, l 19, p34 l22 : 'extremely cold temperature'. The 'extremely' is confusing, compared to what ?
Citation: https://doi.org/10.5194/egusphere-2023-2236-RC1 - AC2: 'Reply on RC1', Amit Kumar Pandit, 17 Feb 2024
-
RC2: 'Comment on egusphere-2023-2236', Anonymous Referee #3, 16 Dec 2023
Review of “Investigating the role of typhoon-induced gravity waves and stratospheric hydration in the formation of tropopause cirrus clouds observed during the 2017 Asian monsoon” by Pandit et al.
This study analyzes backscatter sonde and optical particle counter measurements from balloons over Hyderabad, India to characterize properties of subvisible cirrus layer observed near the tropopause. They then investigate the formation mechanism of these cirrus cloud layers near the tropopause using a combination of back trajectories, satellite observations, and ERA5 reanalysis data. They conclude that overshooting convection from a typhoon created a hydration patch which was transported towards Hyderabad and ascended (via gravity waves) to form the cirrus layer. While the analyses of balloon data to characterize the cirrus cloud properties were interesting, the discussion on the formation mechanism of those clouds, particularly its ties to gravity waves, needs further development and clarification. Detailed comments are provided below.
Main Comments:
Although the combined use of various observations is generally a good idea, the frequent comparisons between measurements from different data sources at different locations and times (e.g., Table 2, Fig. 7, 10, 13) were difficult to interpret. This is especially problematic for this study since the phenomena of interest (i.e., overshooting convection, gravity waves) are small scale features that require coincident measurements. I suggest refining and limiting the selection of observations to only those that meet rigorous time and space matching criteria. I would also present the comparisons in a manner that is easily interpretable by the reader.
I also found the discussion of the trajectory results to be somewhat incoherent. If the main purpose of using the backward trajectories is to show the influence from deep convection on cirrus clouds measured by the balloon, the most important quantity to show is the temperature and relative humidity evolution from the convection encounter to the measurement location. Trajectory results should be more concisely presented instead of across multiple figures. I would similarly reorganize other parts of the paper and make the paper more concise overall.
Detailed Comments:
- P4: The temperature impact by tropical storms in Biondi et al. studies is fairly localized, and as such, I would not describe it as “a change in large-scale temperature fields in the TTL”
- P11: Have the authors looked in the effects of trajectory uncertainties on the results? I’m assuming these are kinematic trajectories, whose dispersive nature may be concerning especially when calculating forward trajectories from UTLS levels.
- P12: Is the use of ERA5 cloud cover fraction necessary? Cloud fields in reanalyses are model products (Wright et al., 2020) and vary depending on prescribed boundary conditions, physical parameterizations (e.g., convection), data assimilation approach, and assimilated data. It is likely unsuited as “cloud observations”. Rather, plotting the 100 hPa temperature (or cold point temperature) field may be more reliable.
- P15: What do you mean by running HYSPLIT trajectories from different altitudes of the CL5? Are the trajectories run at multiple altitudes within the ~2 km thick cloud layer estimated from the balloon measurements? And these trajectories intersect the CATS orbit several hours later at the same altitude as the cirrus detected from CATS? Can you be more specific?
- Fig. 5a: Can you explain what is meant by “day fraction (UTC)”? This is confusing to me since the dots are supposedly showing backward trajectories from 23 Aug 2017 at 20 UTC. Time since balloon measurement may be easier to interpret.
- Fig. 5: What is the temperature history of these trajectories? Are the parcels cooling as they reach the balloon measurement point when cirrus clouds were formed? Figs. 11 and 12 are discussed much later, but this is a key parameter to look at as is RH with respect to ice.
- Fig. 5: How are the parcels that descend backward in time between 115-125 degE in panel (a) represented in panel (b)? In the plan view, it looks like they are wrapped in the typhoon at 125-130 degE, which does not seem to be consistent with panel (b)?
- P21: How exactly is the convective anvil top altitude determined from the brightness temperatures to quantify the convective influence? The text mentions that this is discussed in Section 2.4.1, but I don’t see any description of this methodology.
- P21: Pixel resolution certainly impacts temperatures within a convective cloud, but that fact alone is insufficient to claim that “the highest overshooting tops likely exceeded 18 km height”. More concrete evidence of this is needed to make such a claim.
- Table 2: While I understand the attempt to describe the temperature evolution of the parcel sampled, the disparate data sources (radiosonde, GNSS-RO), locations and times of these measurements make it difficult to say anything about the actual temperature evolution/effect, especially since we expect temperature perturbations on small spatial and temporal scales that greatly affect the cirrus cloud formation. It would make more sense to look at the temperatures along the backward trajectories to describe the evolution (like Fig. 11) and see if those agree with temperature observations at matching times and locations.
- Fig. S3: (a) It would be good to include latitude and longitudes. (b) How realistic is the ERA5 water vapor (compared to observations like MLS)? Are you claiming that the wet anomalies are from the typhoon injected water and ice? (c) is x-axis the latitude?
- Fig. S4: Two temperature profiles are compared, but they are again from two different sources at two different locations at two different times. It is overreaching to claim from this figure alone that “tropopause temperature and tropopause altitude might be substantially reduced by the overshooting convection”. Or is this meant to approximate the cold-point tropopause altitude?
- Fig. 6: Do the back trajectory segments shown here exactly match the trajectories in Fig. 5b? It would be better if you could somehow combine these plots into one since they are approximately showing the same information.
- Fig. 7: Where are the MLS observations (track) on the map? It would be helpful to show those to interpret panel (b). Due to the deep averaging kernel of MLS, it is not clear that the 6.5 ppmv water at 82.5 hPa actually represents enhanced water above the CPT as you suggest in p23. They could be contributed from enhanced moisture near the CPT.
- Fig. 9: Is (a) identical to Fig. S4? If so, this needs to be noted (and S4 could be removed). If not, please explain. How do the MLS values compare with the mean ERA5 water vapor shown in (b)? Rather than color coding the dots by the date, consider coloring the dots with the WV mixing ratios?
- Fig. 10: It would better to plot panels (b) to (e) in chronological order to see the decreasing magnitude (or select one representative location and combine the four profiles in one plot).
- P28: Have the authors checked to confirm that supersaturation (and how high of a supersaturation) is achieved along the trajectories to allow for ice nucleation?
- Fig. 12: What resolution analyses are used for these trajectories? Is the resolution high enough to capture gravity waves? I see that the use of MERRA-2 reanalysis data is mentioned later on p31, but this should be discussed earlier along with Fig. 12. Also, how exactly are the vertical wind speeds derived along the trajectories in (b)? I presume the vertical winds are used to compute the kinematic trajectories.
- Fig. 13: The purpose of this figure is unclear. The text seems to suggest that the purpose is to show the cold anomalies using high resolution data (and their impact cirrus), but it is difficult to interpret where and when these measurements are taken in relationship to the balloon measurements and trajectories. The time and lat/lon are noted in the figure caption, that without a map or time series to place them in larger context, it is very difficult to interpret this figure. It is even unclear whether the measurements plotted in one panel are coincident in time and location (they don’t appear to be).
- Fig. 14: Temperatures were anomalously cold at ~17.9 km near the CPT on 23 Aug, but the tropopause altitudes presumably vary across all the profiles used to calculate the mean. Therefore, panel (a) alone is not sufficient to claim that the CPT was unusually cold on that day. It might make more sense to calculate the anomalies in tropopause relative coordinates. I also do not follow the argument that the variations above 15 km are likely due to waves (“wave-like pattern”). Cooling is likely associated with cirrus formation, but the suggested role of waves from Fig. 14 vertical profiles seems circumstantial at best. The authors mention a “Hodograph analysis of radiosonde data” to show evidence of gravity waves and derive their characteristics, but no description of the analysis is provided.
References:
Wright, J. S., Sun, X., Konopka, P., Krüger, K., Legras, B., Molod, A. M., Tegtmeier, S., Zhang, G. J., and Zhao, X.: Differences in tropical high clouds among reanalyses: origins and radiative impacts, Atmos. Chem. Phys., 20, 8989–9030, https://doi.org/10.5194/acp-20-8989-2020, 2020
Citation: https://doi.org/10.5194/egusphere-2023-2236-RC2 - AC3: 'Reply on RC2', Amit Kumar Pandit, 17 Feb 2024
-
RC3: 'Comment on egusphere-2023-2236', Anonymous Referee #1, 24 Dec 2023
-
AC1: 'Reply on RC3', Amit Kumar Pandit, 17 Feb 2024
We thank the referee (Referee #1) for going through our manuscript and providing constructive feedback for its further improvement. We are glad to read the referee’s views on our manuscript. Please find the attached pdf file for our point-by-point response to the referee’s comments.
-
AC1: 'Reply on RC3', Amit Kumar Pandit, 17 Feb 2024
Viewed
| HTML | XML | Total | Supplement | BibTeX | EndNote | |
|---|---|---|---|---|---|---|
| 490 | 159 | 40 | 689 | 57 | 21 | 23 |
- HTML: 490
- PDF: 159
- XML: 40
- Total: 689
- Supplement: 57
- BibTeX: 21
- EndNote: 23
Viewed (geographical distribution)
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1