Characteristic Scales of Tropical Convection Based on the Japanese Advanced Himawari-8 Imager Observations
Round 1
Reviewer 1 Report
Any reason to choose such a time period, specifically? You should explain that.
The same to explain why the first 60 PCs in particular.
Author Response
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Reviewer 2 Report
Generally, I have not too many comments on the article. But I have some questions or suggestions for the authors. 1. This is an exciting but not so exciting article. Because PCA & FFT methods use widely in some fields (Ex: climate) the authors use these methods to analyze AHI data to do scale analysis is ok. At least we know satellite data has similar characteristics to the reanalysis data. 2. Based on the results presented in the article, is it possible authors put one or two figures and paragraphs showing the DA result? It would be good to let readers know how the scale analysis impacts the DA system. And would increase the value of this article. 3. Follow (2), the authors show even different times (Day & Night, Fig9-10), the 1st PCA shows a very similar pattern because of the low propagation frequency. The importance of the meso- or micro-scale system is how those fast change systems impact the DA? Sometimes, high-frequency systems will treat as noise signals in the DA or NWP model. Again, it would be good to show one or two figures or results from DA to present the different scale impacts to the numerical systems.Author Response
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Reviewer 3 Report
The authors propose a paper that investigates the characteristic scales of convection, a method combining a principal component (PC) analysis with Fourier decomposition is applied to brightness temperature observations from Advanced Himawari-8 Imager (AHI). the results show that the first 60 PCA components capture not only the macro-scale but also the meso-scale features of convective activities, with strong repercussions not only in the context of satellite analysis, but also in the study of tropical precipitation on a synoptic scale with future model and numerical implications, such as data assimilation on a local and global scale.
Starting from my limited experience on this subject and these technologies, I find the work very interesting, well structured and mature enough for publication.
In general, I suggest that the authors introduce the problem studied not only from the perspective of remote sensing, but also from a more general atmospheric science point of view. I suggest broadening the introduction starting from the criticalities that this study wants to fill and implications with other areas of atmospheric science.
Despite the data representation appearing very solid, some figures are not very representative and hardly understandable:
1) Figure 2,3,6,9 increase the size of the panels, even if this should increase the number of figures. The important thing is that the figure is legible and representative of the data. It is currently extremely difficult to intertwine.
2) For all the figures I suggest to choose color scales and ranges, which are more readable and less saturated.
3) The bibliography can be extended, it is currently on average short.
Author Response
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Author Response File: Author Response.docx
