Global Aerosol Classification Based on Aerosol Robotic Network (AERONET) and Satellite Observation

Round 1

Reviewer 1 Report

Title: Global aerosol classification based on Aerosol Robotic Network (AERONET) and satellite observation

Manuscript ID : remotesensing-1112732

 

Revision of the paper

 

Anonymous Referee

 

Comments:

This paper is judged to be the paper that classified the types of atmospheric aerosols into four types using AERONET data and identified the characteristics of major aerosol sources. In addition, the effectiveness of the developed classification method was also applied to satellite data analysis.

From the analyzed data, data on the major aerosol types and scattering and absorption properties in each region can be identified. It is judged as a good research result and can be published in “Remote Sensing”.

However, the content of the research is too focused on confirming the facts and the scientific interpretation seems insufficient. And, the conclusion part is missing.

 

Major Comments

1. Please add “Conclusion” part.
2. Add scientific findings from this research.

 

Minor Comments

1. Line 213. “The value of δ1 and δ2 are preseted by 0.02 and 0.3 empirically”. The values of δ1 and δ2 are different according to the region. Please check values of δ2. The paper “On the spectral depolarisation and lidar ratio of mineral dust provided in the AERONET version 3 inversion product. Atmospheric Chemistry and Physics, 2018” can be helpful.

Author Response

Thank for your review, the response are shown in the file below.

Author Response File: Author Response.docx

Reviewer 2 Report

Please, read the attached document.

Comments for author File: Comments.pdf

Author Response

Thank you for your pdf, the responses are shown below.

Author Response File: Author Response.docx

Reviewer 3 Report

Title: Global aerosol classification based on Aerosol Robotic Network (AERONET) and satellite observation

Overall recommendation:

Recommends for publication after revisions.

Major comments:

1. Figure 10, 4^th panel- why Karachi has more of a close aggregation than the other three panels/ places?
2. The paper is well written in terms of language, however the content felt long. Maybe that’s only me, but I like to suggest the authors to shorten the manuscript if at all possible. While I understand that having ten figures doesn’t make it easier to cut down, supporting information files are an option. Also, authors tend to have some level of explanation/ discussion at the result section, I suggest combined result and discussion section might make it easier to follow. Then, have a strong conclusion section, or keep it as the last paragraph (as is now).

Minor comments:

1. Line 223: Inspired, fixed the typo
2. Table 1: Why some of the stations have very small # of valid datapoints? Do they follow different seasonal timelines/ stay off for a certain time?

Comments for author File: Comments.pdf

Author Response

Thank you for your suggestions, the responses are shown below.

Author Response File: Author Response.docx

Round 2

Reviewer 1 Report

I think it is possible to publish it as it is.

Author Response

Thank you for your suggestion.

Reviewer 2 Report

Please, consider my new recommendations (pdf file).

Comments for author File: Comments.pdf

Author Response

Thank you for your suggestions in pdf file. I have corrected the mistakes.

Author Response File: Author Response.docx

Reviewer 3 Report

I like the responses, thank you for clarifying and making necessary changes.

Author Response

It is my pleasure, thank you for your suggestion.