Assessment of Different Boundary Layer Parameterization Schemes in Numerical Simulations of Typhoon Nida (2016) Based on Aircraft Observations

Round 1

Reviewer 1 Report

Comments for author File: Comments.pdf

Author Response

Response: Thank you for the very constructive review. We have enjoyed the discussions that emerged following your comments. In accordance with your suggestions, we have clarified the descriptions, improved the quality of the figures, and revised the entire manuscript to enhance its readability. Our point-by-point responses to your specific comments are given in the following.

Major comments

1. Response: In this paper, the aircraft observations obtained in Cartesian coordinates are used to analyze and discuss the simulation. Bao et al. (2020; 2022) in a cylindrical polar coordinate framework discussed the results of Hurricane Weather Research and Forecast system Numerical simulation. It can directly examine the critical radially inflowing and tangential winds. To further study the typhoon of the critical radially inflowing and tangential winds and the mean wind profiles, we will convert the observations to a cylindrical polar coordinate in future. The above discussion is included in Lines 475–481.

2. Response: According to your suggestion, we have clarified all the figure captions. Please find the captions of the figures for more detail.

Specific comments

1. Response: The present study mainly focuses on the typhoon boundary layer structure, especially the strong convective cloud tower, and compares the simulation results of several parametric schemes, so it does not compare the central intensity, and we choose the two comparisons of figure3. This is clarified in Lines 169–172.

2. Response: According to your suggestion, we have revised the Figure 4. We have added a subfigure (Figure 4b), where the distribution of sea level pressure, 10-m winds, and the intensity of typhoon were shown. The related description of this figure was added to Lines 179–184.

3. Response: The possible reason is that the spatial distribution of low layer divergence, one of the important factors of precipitation, was modified by the changed winds. This should be further studied and analyzed in the future. It is also clarified in Lines 201–205.

4. Response: The observation data comes from aircraft observation, which is only one layer of data, and we show it in Figure 15–16, and compared in Table 3. We illustrate the comparison of the results in the text. According to your comment, we have clarified the statement (Lines 242–243): “In this section, we compared the numerical simulations (Figures 9–16) to the observations (Figures 15–16 and Table 3) as following.”

5. Response: It is "easterly jet area". According to your comment, we have corrected this term in the full text (Lines 256–267, 284, and 286).

6. Response: Based on your suggestion, we have clarified the “ideal typhoon model” in Lines 252–254: “Here, the ideal typhoon model means the vertical typhoon structure analyzed in Emanuel et al. (1986) [26], Chen et al. (2019) [20] and Fei et al. (2021) [28], the eye area sinks and both sides of the eye area rises.”  

Author Response File: Author Response.docx

Reviewer 2 Report

General comments: Targeting at revealing the influence of boundary layer parameterization schemes on a simulated typhoon case, the authors performed a series of high-resolution numerical experiments, and compared the results to various observations.  The structure of the paper is clear, and its potential conclusions could be a useful guidance for others.  However, the writing needs a substantial improvement.  As a result, major revision is suggested in its current form.  All the specific comments are listed below.

Major comment: I think there is no “best” PBL parameterizations in any general sense.  However, there could be one in a specific case study, through choosing several observational quantities to validate such scheme.  So, I guess the authors should link such “best” choice to the environment (South China Sea) they focused on: why this choice is the “best” over this region and not so over the other regions.  Do their conclusions apply only to the South China Sea, or only to the specific typhoon case?  This is more useful than reporting all the simulation details and results here.

Below are more specific ones.

Comment 1: Lines 63-65.  Selected references are needed for this statement.

Comment 2: Lines 69-70.  How does the BL characteristics over the South China Sea affect the choice of PBL scheme?  See major comment 1.

Comment 3: Lines 72-73.  Please define NCEP, FNL, and GPM before using abbreviations.  Check related problems throughout the paper.

Comment 4: Line 86.  “improved by 20-30%” -> “was improved by 20-30%”

Comment 5: Lines 87-88.  What is the meaning of “limit the data layer analysis”?  “when the altitude was below 1000m” the altitude of what you are referring to?

Comment 6: Fig 1.  The caption is not clear enough.  Detection track should be flight track?  Unit of precipitation should be added (please check all figures).  The color of TC track is the same as that of the flight track.  Please add more lat-lon labels (check all the plots).

Comment 7: Line 93.  “Generated” is not precise, unless a threshold of wind or pressure is specified.  I guess here is the first record in best-track dataset.  So “typhoon was generated” is not correct here as it is only a depression.

Comment 8: Line 103.  Define IMERG, CPM before abbreviation.

Comment 9: Line 105-106.  This sentence has repeated meanings of a maximum 30 mm/h.  Also, the minimum should be zero, based on Fig. 1.

Comment 10: Line 125.  What is “Pattern design”?

Comment 11: Fig 2.  Please be more specific to the caption.  Three domains? Nested? Resolutions for each?  A track (also its intensity like in Fig. 1) of the TC should be added so that readers know which part you are focusing on.

Comment 12: Table 1. “Resolution ratio” -> “Resolution”

Comment 13: Line 144. What is “half-levels”?

Comment 14: Line 145. “for the duration” -> “at the time”

Comment 15: Line 146. “under … grids” is not proper.

Comment 16: Line 150.  “Simulation Deviation Analysis” -> “Simulated deviation analysis”

Comment 17: Line 152.  The purpose of examining the “periodic changes” is inconsistent with the focus of rapid intensification stated later.

Comment 18: Fig 3. There are at least five things in a sentence (TC, wind, radius, simulation, and results).  Which is the subjective?  The radius of TC’s maximum wind simulated at (a) and (b) should be better?

Comment 19: Line 161.  “We divided Typhoon into four areas” is improper.  You only chose four subregions of the typhoon where flight observations are taken.

Comment 20: Fig 4.  What is the difference between Fig. 4 and Fig. 1a?  Please remove redundant information.  Regions can be defined also in Fig. 1 or 2.

Comment 21: Fig 5.  “simulated by each parameterization” -> “simulated using each parameterization” (check this throughout the paper)

Comment 22: Fig 6.  “path deviation” -> “track errors”  “pressure deviation” -> “pressure differences”

Comment 23: Fig 8.  Caption should be “Simulated precipitations (mm) using different parameterization schemes”

Comment 24: Line 216.  “The … schemes were … similar to … the model” is an improper description.  Schemes are not model.

Comment 25: Line 219.  “rapids” -> “jet”?

Comment 26: Figs 9-14.  “Analysis of … component space profile in area …” -> “Vertical cross section of … component of velocity in area …”

Comment 27: Table 3.  “Parametric” -> “parameterization” (check this throughout the paper); “Simtlated” is incorrectly spelled.

Comment 28: Figs 15-16.  Captions should be “Comparison of simulated U/V/W with observation for area …”.

Comment 29: Fig 17.  How to define the mean and turbulent part of velocity for TKE?  Azimuthal-mean or time mean?

Comment 30: Line 394. Unclear subjective (eye? Area? U wind? Schemes?)  Which is similar to observations and model?

Comment 31: Line 397.  Hard to follow the meaning.

I think more corrections to the writing should be done by some native speakers, in addition to the above listed ones.

I think more corrections to the writing should be done by some native speakers, in addition to my listed ones.

Author Response

General Comment

Response: Thank you for the very constructive review. We have enjoyed the discussions that emerged following your comments. In accordance with your suggestions, we have clarified the descriptions, improved some of the figures, and revised the entire manuscript to enhance its readability. Our point-by-point responses to your specific comments are given in the following.

Major Comment

Response: We agree that there is no “best” choice of PBL schemes. In the present study, we tried to link such “best” choice to South China Sea. Because previous studies are mostly based on ground observations in the Atlantic, Pacific, or coastal areas (Nelson et al., 2022; Pradhan et al., 2018, 2019; Shen and Du, 2023), with only a few focused on the South China Sea. The boundary layer characteristics of typhoons in the South China Sea are different from those in other sea areas, such as shallow interocean circulation, turbulence characteristics, and helical rolls in the tropical cyclone boundary layer (Fang et al., 2005; Tang et al., 2021; Zhao et al., 2020). Because different parameterization schemes for the boundary layer refers to different physical process (Alam, 2020), the different physical features in the South China Sea possibly affect the choice of boundary layer schemes. Thus, we studied Typhoon Nida, a typhoon case in the South China Sea, which boundary features was observed by the aircraft, based on numerical simulations. The above discussions were included in Lines 64–75.

References

Alam, M. Sensitivity Study of Planetary Boundary Layer Parameterization Schemes for the Simulation of Tropical Cyclone ‘Fani’ Over the Bay of Bengal Using High Resolution Wrf-Arw Model. Journal of Engineering Science. 2020, 11(2), 1–18. DOI: 10.3329/jes.v11i2.50893. 
Fang, G. H.; Susanto, D.; Soesilo, I.; Zheng, Q.A.; Qiao, F.L.; Q.; Wei, Z.X. A note on the South China Sea shallow interocean circulation. Adv. Atmos. Sci. 2005, 22(6), 946–954. DOI: 10.1007/BF02918693.
Nelson, M. A.; Conry, P.; Costigan, K. R; Brown, M. J.; Meech, S.; Zajic, D.; Bieringer, P. E.; Annunzio A.; Bieberbach, G. A Case Study of the Weather Research and Forecasting Model Applied to the Joint Urban 2003 Tracer Field Experiment. Part III: Boundary-Layer Parametrizations. Bound.-Lay. Meteorol. 2022, 183(3), 381-405. DOI: 10.1007/s10546-022-00696-8.
Pradhan, P. K.; Liberato, M. L. R.; Ferreira, J. A.; Dasamsetti, S.; Rao, S. V. B. Characteristics of different convective parame-terization schemes on the simulation of intensity and track of severe extratropical cyclones over North Atlantic. Atmos. Res. 2018, 199, 128-144. DOI: 10.1016/j.atmosres.2017.09.007.
Pradhan, P. K.; Liberato, M. L. R.; Kumar, V., Rao, S. V. B.; Ferreira, J.; Sinha, T. Simulation of mid-latitude winter storms over the North Atlantic Ocean: impact of boundary layer parameterization schemes. Clim. Dym. 2019, 53(11), 6785-6814. DOI: 10.1007/s00382-019-04962-3.
Shen, Y.; Du, Y. Sensitivity of boundary layer parameterization schemes in a marine boundary layer jet and associated pre-cipitation during a coastal warm-sector heavy rainfall event. Front. Earth Sci. 2023, 10. DOI：10.3389/FEART.2022.1085136.
Tang, J.; Zhang, J. A.; Chan, P.; Hon, K.; Lei, X.; Wang, Y.A. direct aircraft observation of helical rolls in the tropical cyclone boundary layer. Sci. Rep. 2021, 11(1), 18771. DOI: 10.1038/s41598-021-97766-7.
Zhao, Z.; Chan, P.W.; Wu, N.; Zhang, J.A.; Hon, K.K. Aircraft observations of turbulence characteristics in the tropical cyclone boundary layer. Bound.-Lay. Meteorol. 2020, 174, 493–511.DOI: 0.1007/s10546-019-00487-8.

Specific Concerns

1. Response: According to your suggestion, we have added the references as following. Please find Line 64–66 for more detail. 

References

Nelson, M. A.; Conry, P.; Costigan, K. R; Brown, M. J.; Meech, S.; Zajic, D.; Bieringer, P. E.; Annunzio A.; Bieberbach, G. A Case Study of the Weather Research and Forecasting Model Applied to the Joint Urban 2003 Tracer Field Experiment. Part III: Boundary-Layer Parametrizations. Bound.-Lay. Meteorol. 2022, 183(3), 381-405. DOI: 10.1007/s10546-022-00696-8.
Pradhan, P. K.; Liberato, M. L. R.; Ferreira, J. A.; Dasamsetti, S.; Rao, S. V. B. Characteristics of different convective parame-terization schemes on the simulation of intensity and track of severe extratropical cyclones over North Atlantic. Atmos. Res. 2018, 199, 128-144. DOI: 10.1016/j.atmosres.2017.09.007.
Pradhan, P. K.; Liberato, M. L. R.; Kumar, V., Rao, S. V. B.; Ferreira, J.; Sinha, T. Simulation of mid-latitude winter storms over the North Atlantic Ocean: impact of boundary layer parameterization schemes. Clim. Dym. 2019, 53(11), 6785-6814. DOI: 10.1007/s00382-019-04962-3.
Shen, Y.; Du, Y. Sensitivity of boundary layer parameterization schemes in a marine boundary layer jet and associated pre-cipitation during a coastal warm-sector heavy rainfall event. Front. Earth Sci. 2023, 10. DOI：10.3389/FEART.2022.1085136.

2. Response: The boundary layer characteristics of typhoons in the South China Sea are different from those in other sea areas, such as shallow interocean circulation, turbulence characteristics, and helical rolls in the tropical cyclone boundary layer (Fang et al., 2005; Tang et al., 2021; Zhao et al., 2020). Because different parameterization schemes for the boundary layer refers to different physical process (Alam, 2020), the different physical features in the South China Sea possibly affect the choice of boundary layer schemes. The above discussion was added in Lines 70–75. 

References

Alam, M. Sensitivity Study of Planetary Boundary Layer Parameterization Schemes for the Simulation of Tropical Cyclone ‘Fani’ Over the Bay of Bengal Using High Resolution Wrf-Arw Model. Journal of Engineering Science. 2020, 11(2), 1–18. DOI: 10.3329/jes.v11i2.50893. 
Fang, G. H.; Susanto, D.; Soesilo, I.; Zheng, Q.A.; Qiao, F.L.; Q.; Wei, Z.X. A note on the South China Sea shallow interocean circulation. Adv. Atmos. Sci. 2005, 22(6), 946–954. DOI: 10.1007/BF02918693.
Tang, J.; Zhang, J. A.; Chan, P.; Hon, K.; Lei, X.; Wang, Y.A. direct aircraft observation of helical rolls in the tropical cyclone boundary layer. Sci. Rep. 2021, 11(1), 18771. DOI: 10.1038/s41598-021-97766-7.
Zhao, Z.; Chan, P.W.; Wu, N.; Zhang, J.A.; Hon, K.K. Aircraft observations of turbulence characteristics in the tropical cyclone boundary layer. Bound.-Lay. Meteorol. 2020, 174, 493–511.DOI: 0.1007/s10546-019-00487-8.

3. Response: Revised per your suggestion. The abbreviations were defined at Lines 77–81. We have also corrected the related problems throughout the manuscript.

4. Response: Revised per your suggestion. Please see Line 93.

5. Response: Aircraft observations are mainly focused on the boundary layer, with an altitude of 1000m approaching the boundary layer. On the other hand, for research purposes, we selected data from the plane's level flight period. This is also clarified at Lines 94–96.

6. Response: Revised per your suggestion. Please see the revised figures and its captions caption of Figure 1 (Lines 99–104) for detail.

7. Response: Nida was generated at 6:00 on July 30, 2016 (UTC), when its intensity was enhanced to a tropical storm. This was also revised in Lines 106–109.

8. Response: Based on your suggestion, we clarified the definition of “IMERG” and “GPM” in Lines 78–79.

9. Response: Revised per your suggestion. Please see Lines 118–119 for detail. 

10. Response: Based on your suggestion we have revised it to “Model design” (Line 142).

11. Response: Based on your suggestion, we have revised the Figure 2 and the related captions. Please see Lines 150–151 for detail.

12. Response: Revised per your suggestion. Please see Lines 153–154 for detail.

13. Response: It is “levels”. This has been modified in Line 161.

14. Response: Revised per your suggestion. Please see Line 162 for detail.

15. Response: Based on your comment, we have revised the sentence to “to simulate the turbulence in high-resolution, …”. Please see Line 163 for more detail.

16. Response: Revised per your suggestion. Please see Line 167 for detail.

17. Response: According to your suggestion, we have revised this sentence in Lines 169–173.

18. Response: According to your suggestion, we have revised the caption of Figure 3 (Lines 177–178).

19. Response: The definition of the analysis areas was based on the track of aircraft observation, and eyewall structure based on the distribution of precipitation, sea level pressure and low layer winds. Based on your suggestion, we have clarified the definition (Lines 179–184), and revised Figure 4 to show more TC features (Lines 206–214).

20. Response: The purpose of Figure 1 is to show the general features of Typhoon Nida and aircraft observation. The Figure 4 is to introduce the definition of the analysis areas. According to your suggestion, we have clarified the definition of the analysis areas in Lines 179–184, and revised Figure 4 in Lines 206–214.

21. Response: Revised per your suggestion. Please see the captions of Figure 5 (Lines 217–218).

22. Response: Revised per your suggestion. Please see the captions of Figure 6 (Line 220).

23. Response: Revised per your suggestion. Please see the captions of Figure 8 (Lines 227–229).

24. Response: According to your suggestion, the sentence was revised to (Lines 250–252): “Compared to other boundary schemes, the U-wind simulations in eye area of YSU and MYNN schemes were more similar with the observation/results of ideal typhoon model”.

25. Response: Revised per your suggestion. Please see Line 256 for detail.

26. Response: Revised per your suggestion. Please see the captions of Figures 9–14 for detail.

27. Response: The Table 3 was revised per your suggestion. And the spelling was checked throughout the manuscript. 

28. Response: The captions of Figures 15–16 were revised per your suggestion.

29. Response: According to your comments, We have added a new Section 2.3 to introduce TKE; please see Lines 138–140. The average value is a spatial average, which is consistent with the aircraft observation path for easy comparative analysis (clarified in Lines 421–422).

30. Response: According to your comments, we have clarified the sentence to (Lines 443-444): “In the eye area, the simulation results of the YSU and MYNN schemes were relatively close to those of aircraft observations and ideal typhoon model.” 

31. According to your comments, we have clarified the sentence to (Lines 445-446): “The interface of north-south wind has a clear leftward inclination from low to high level.”

Response: The manuscript has been revised by native speakers before initial submission. And we have double checked the grammar and spelling carefully before revision.

Author Response File: Author Response.docx

Round 2

Reviewer 2 Report

The authors have revised the manuscript accordingly and therefore I am suggesting the paper being accepted for publication.

No further comments.