A Multi-Model Ensemble Pattern Method to Estimate the Refractive Index Structure Parameter Profile and Integrated Astronomical Parameters in the Atmosphere

Round 1

Reviewer 1 Report

A multi-model ensemble pattern method to estimate the refractive index structure parameter profile and integrated astronomical parameters in the atmosphere

 

The manuscript is devoted to an important research topic related to optical turbulence, which leads to perturbations of light waves propagating in the atmosphere. After a detailed analysis of the manuscript, we concluded that the results obtained by authors are significant. We have only a few minor remarks:

 

-First, the authors give statistical characteristics calculated using different models. The authors use rounding to the fourth decimal place after dot. We suggest authors to reduce the number of decimal places after dot in tables because the precisions of R, MAE, BIAS, RMSE are excessive.

 

- We would like to ask what is the Fried parameter from calculations when you use the model Hufnagel-Valley 5/7? The values 5/7 indicate that the Fried parameter should be 5 cm.

 

- Since the values of the Fried parameter and other characteristics of optical turbulence depend on the light wavelength, we recommend that you specify the wavelength of light, for example, for figures 7 – 8.

 

- The calculation results of the refractive index structure parameter Сn2 essentially depend on the model of the outer scale of turbulence. We would like to see what characteristic values and possibly vertical profiles of the outer scale of turbulence you have used. How do you physically interpret the concept of the outer scale of turbulence in the context of calculations of Сn2 .

 

- It is possible to expand the introduction by pointing out the essential importance of the development of this modeling, refinement of empirical dependencies for astronomy. We may recommend to pay attention for the following remote sensing methods and approaches (Slodar, S-Dimm+):

 

- Kovadlo, P.G. et al. Study of the Optical Atmospheric Distortions using Wavefront Sensor Data. Russ Phys J 63, 1952–1958 (2021). https://doi.org/10.1007/s11182-021-02256-y.

- Osborn, J.; Wilson, R.; Butterley, T.; Shephard, H.; Sarazin, M. Profiling the surface layer of optical turbulence with SLODAR. Mon. Not. R. Astron. Soc. 2010, 406, 1405–1408.

-Wang, Z.; Zhang, L.; Kong, L.; Bao, H.; Guo, Y.; Rao, X.; Zhong, L.; Zhu, L.; Rao, C. A modified S-DIMM+: Applying additional height grids for characterizing daytime seeing profiles. Mon. Not. R. Astron. Soc. 2018, 478, 1459–1467.

Author Response

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Author Response File: Author Response.pdf

Reviewer 2 Report

The paper “A multi-model ensemble pattern method to estimate the refractive index structure parameter profile and integrated astronomical parameters in the atmosphere.” by Zhang Hanjiu and others addressed a pathway to estimate the refractive index structure parameter using an ensemble pattern. The authors use routine radiosonde meteorological data combined with a micro-thermometer to verify the proposed method. The authors use different methods, including semiempirical and physical approaches based on the Gladstone relation, or alternatively, apply the Tatarskii formalism. Comprehensive error and correlation analysis were also done about the estimating profiles and the astronomical parameters.

In my opinion, the major takeaways of the paper are that the foundation of a merged pattern estimates the refractive index structure parameter using macroscope meteorological parameters. Moreover, it reduces the dependence on specific parameters of a single method. In previous studies, estimating the refractive index structure parameter accurately is of great difficulty because of the turbulent atmospheric nature. A single approach should be modified along with the sites, seasons, and other factors. It dramatically limits the generalization of these models. Meanwhile, the summary of the existing approaches is of great benefit to relevant researchers. Certainly, there are still lots of approaches that are excluded from the listed approaches, for example, statistical models developed by Vanzandt T.E [1, 2]and Trinquet, H. & J. Vernin [3]. These can serve as references for the authors’ future research.

Consequently, I feel that the paper can be published after minor modifications. After consideration, I recommend a minor revision. My concerns and suggestions about this paper are as below.

 

Concerns:

1. Existing models seem to have a good performance in a specific application in previous practices (results can be seen in your references 16, 25, 26). The authors should not neglect that fact and explain the advantage of the so-called MEP method in the article.
2. Lines 145-146：The authors claim they set alpha=2, beta=6, gamma=4. Are these parameters can be changed? Moreover, what difference will cause as these penalty parameters change?

 

Minors:

1. Lines 1-7: More concert results and evidence can be added in the section abstract—for example, the error and correlation evaluation of two sites, as summarized in section 5.
2. Lines 24 & 79: I advise the authors to unify their statement about the abbreviation MT in one paper, although both statements are used in the literature.
3. Equation 6: There seems to be an extra apostrophe of beta in the denominator. Please check it.
4. Lines 157 & 184: The primary text part seems to have just two profiles.
5. Line 259: You meant ‘different estimating approaches’ in this part. I find this leads to only one research article, and it seems only involved limited methods in this literature. Meanwhile, ample literature exists about atmospheric refractive parameter estimating methods in applications. I think more relevant studies should be added to the reference.
6. Line 279: GPS is the abbreviation of Global Positioning System in the official report. 

 

 

1.            Vanzandt, T. E., K. S. Gage and J. M. Warnock. "An improved model for the calculation of profiles of cn2 and epsilon in the free atmosphere from background profiles of wind, temperature, and humidity." Bulletin of the American Meteorological Society 62 (1981): 924-24. <Go to ISI>://WOS:A1981MH23900182.

2.            Vanzandt, T. E., K. S. Gage and J. M. Warnock. "Statistical-model for probability of turbulence and calculation of vertical profiles of turbulence parameters." Bulletin of the American Meteorological Society 59 (1978): 1230-30. <Go to ISI>://WOS:A1978FV95100025.

3.            Trinquet, H. and J. Vernin. "A statistical model to forecast the profile of the index structure constant c-n(2)." Environmental Fluid Mechanics 7 (2007): 397-407. 10.1007/s10652-007-9031-x. <Go to ISI>://WOS:000250116800005.

Comments for author File: Comments.pdf

Author Response

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Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

I found this study is very interesting and contains  good results. Authors have made corrections. We agree with these corrections and recommend the manuscript for publication. 

Reviewer 2 Report

Accepted