Title: A Deep Convective Systems Database Derived from the Intercalibrated Meteorological Geostationary Satellite Fleet and the TOOCAN algorithm (2012-2020)

Author(s): Thomas Fiolleau and Remy Roca

MS No.: essd-2024-36

MS type: Data description paper[

Review Comments: General Comment.

This manuscript describes the database derived from the intercalibrated geostationary satellite constellation (GEOring), processed by the TOOCAN algorithm to produce a historical dataset of the trajectories and characteristics of the mesoscale convective system over the 9 years from 2012 to 2020. The dataset is composed of two databases, the TOOCAN, describing the trajectories, including the radiative and morphological characteristics of the MCS with a 30-minute time step, and the CACATOES, a 1°x1° global monthly file describing the spatial distribution of the DCS density over the tropical belt. This is a very rich dataset and the manuscript describes in detail the procedures used, presents some results and shows some examples. I consider the manuscript suitable for publication in the ESSD after some minor corrections.

Specific Comments:

• Line 40 – Rewrite the sentence – difficult to understand the meaning, as well as the verb agreement.
• Line 43 – “MCS for a family of deep convective systems with horizontal scales larger than 100 km”. When you mention 100 km horizontal scale, it corresponds to an MCS of roughly with 10000 km². However, you start to look MCS from an area larger than 635 km². Please clarify and justify the choice.
• Line 47-50. Please rewrite for better clarity.
• Line 53 – Infirm?
• Line 57 – Please correct - algorithms…
• Line 57 – The justification is not appropriate now, in nowadays, there are the ISCCP H series, the MERGIR, among others.
• Line 62 – “ A deep convective system then corresponds to a succession of convective clusters “ Should be in the other way round ?, and why only deep convective, stratiform clouds also is part of MCS.
• Line 85 – There is a new paper (Km‐Scale Simulations of Mesoscale Convective Systems Over South America—A Feature Tracker Intercomparison - 10.1029/2023JD040254). This is study is very complementary to the discussions on this manuscript.
• Line 88 – I think it is important to define what the author calls a cluster of pixels. Later in the text I noticed that you are looking at the 4 neighbouring pixels and the diagonal pixels. It should be clearly defined what you are tracking. I also suggest talking about the RDT algorithm, which also uses a variable threshold to follow the MCS structure. What are the basic differences between the two methods? Also, I see some similarities of the TOOCAN with the Fortracc, is the TOOCAN based in this tracking with the variable threshold?
• Line 113 - Sometime the split is a natural characteristic of the MCS, as for instance the supercells that regularly split in two different systems.
• Line 120 – “MCS shield growth rate has been carried out (Elsaesser et al. 2022)” . Several other papers earlier discussed the growth rate, one example is the Machado and Laurent 2004 (https://doi.org/10.1175/1520-0493(2004)132<0714:TCSAEO>2.0.CO;2.).
• Table I – correct Feng etal.
• Page 145 – “This paper presents a such DCS database” – rewrite the sentence.
• Page 185 – “The decrease of the ScaRaB data availability does not impact the quality of the corrections from the end of 2018”. If there is no effect, why not apply the correction once a month to have a more homogeneous dataset?
• Page 188 – Authors should discuss the larger Bias of Meteosat-7.
• Page 197 – How does the interpolation take into account differences in satellite resolution? How is the change in resolution with latitude zenith angle taken into account? How do you deal with missing data, are they extrapolated? How does the different resolution affect the size of the MCS? Is the 55N to 55S window too large for an acceptable satellite viewing angle?
• Figure 2 – “…in the range [180 K-235 K] between 2012 and 2020” why the range is different from the SCARAB correction [180 K-240 K]
• Line 225 – “The arrivals of GOES-16” – replace by launched;
• Line 250 - Could you explain why the cloud cluster associated with the tropical cyclone was dropped from the track? Several times the MCS evolved from a tropical storm to a hurricane. In this case, does TOOCAN consider the MCS dissipated?
• Line 278 - There is an almost linear relationship between size (the threshold) and lifecycle. Your methodology uses the 1.5-hour lifecycle for the different thresholds. For 190K, 1.5 hours is a high requirement, but for 235K it is common.
• Line 280 - How do you deal with semi-transparent clouds? For pixels where the Tir does not correspond exactly to the cloud top, the 3D threshold procedure will not work correctly because it contradicts the basic principle of the 3D threshold? Wouldn't it be better to follow the corrected cloud top?
• Line 282 – “to resolve the unphysical split and merge issues.” There are split and merge in real life – Explain what do you consider unphysical?
• Line 287 – How the algorithm handles missing images. With overlapping, you would normally have to use image extrapolation or a dynamic overlap threshold. How does TOOCAN use the overlap threshold and what value is used?
• Line 304 - Maybe I didn't understand correctly, but this is not a good example to show, because the advanced feature of TOOCAN is the 3D threshold to avoid splits and merges. However, looking at system A, it seems to be a unique MCS, but TOOCAN produced several MCS that merge (you said there was no merge) at 1200. Also, B appears to be a single MCS, but it changes to C. Could you provide a better explanation for these merges and splits we see in this image? It seems that TOOCAN solves many split and merge situations, but it continues to have split and merge in smaller numbers.
• Figure 7 - I did not understand how a missing image could increase the bias in the number population of short lived MCS. It is also interesting to see that the 2 hour missing image has the largest bias and 4 hours no bias, for short lived MCS. I fully understand this for systems larger than about 8 hours, but for shorter lifetimes I don't.
• Line 365 – Perhaps it was in this part of the manuscript that I understood the above problem. Actually, this is not a missing image, it is the replication of the same image. So it is not really a missing image, it represents that the MCS was frozen. Please clarify.
• Line 402 – “propagated distance, cold cloud maximum extent…)” – please do not use … and add all variables – maybe in a table – it is an important information to the users.
• Line 405 – “thresholds, eccentricity, instantaneous velocity…)” Same comment.
• Line 407 – “. A quality flag lower than 11110 is a good compromise to keep DCS little impacted by imagery issues”. Please clarify what 11110 means.
• Figure 10 - It would be more appropriate to present this figure on the basis of the whole year, since not including the missing months, mainly during the dry season, will have an impact on the number of MCS/day..
• Line 532 – “The CACATOES 1°x1°-1day global monthly files” please clarify what is 1day in this sentence.
• Line 535 – Is the TOOCAN algorithm available? It will be important for the user to have access to the algorithm that produced the dataset.

The manuscript introduces two novel datasets about deep convective systems over the intertropical belt: TOOCAN and CACATOES. The TOOCAN dataset contains the tracking of deep convective systems from 2012 to 2020, which is generated using a 3-D tracking algorithm and a homogenized geostationary infrared brightness temperature archive. The CACATOES dataset is derived from the TOOCAN dataset by projecting the morphological characteristics of each deep convective system onto 1-degree x 1-degree grids. Overall, the manuscript is written and organized well. The authors clearly describe the source datasets and explain how to generate the target datasets. Furthermore, the authors discuss the uncertainties of the datasets and briefly compare them with other existing datasets. I recommend the publication of the manuscript if the authors can correct minor language errors.

Minor comments

Line 40: “the various the phases” to “the various phases”? “its evolution is” to “its evolution in”?

Line 47: Are all DCS events initiated from several individual deep convective cells? Why can’t deep convection be initiated from a single deep convective cell?

Line 53: “infirm”? Do you mean “weaken”?

Line 90: “then” to “the”?

Line 97: Correct the citation format of Endlich and Wolf 1981.

Line 110: “multi-thresolding” to “multi-thresholding”?

Lines 117-120: Please rewrite this sentence.

Line 182: “zenithal” to “zenith”.

Line 186: Delete “a”?

Lines 223-224: Delete “making the processes easier”?

Line 237: “the all” to ”all the”.

Lines 281-282: Please rewrite the sentence.

Line 344: Delete “a”

Lines 362-365: If consecutive images are deleted during other hours, how about the results?

Line 437: What do you mean by the total cold cloudiness? Cold cloudiness area?

Line 453: “Similarly, to” to “Similar to”.

Line 455: Add “in“ before “Fig. 9c”.

Lines 481: Correct the sentence!