the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
A new dataset of Mesoscale Convective Complexes (MCC) derived from FY-2G satellite data
Abstract. Mesoscale Convective Complexes (MCCs) are major convective weather systems occurring in midlatitude regions, typically associated with significant weather phenomena such as heavy rainfall, thunderstorms, strong winds, and hail. Based on the cloud-top temperature (CTT) data of the FY-2G satellite, and through multi-threshold screening combined with morphological analysis, an automated algorithm for MCC identification and tracking was developed. The algorithm is then applied to generate an hourly dataset of MCC variables over mainland China from June 2015 to December 2024. The dataset encompasses variables describing the spatial extent of the cold-core region (CTT < -52 °C) of MCCs, the minimum cloud-top temperature within the cold cloud shields, and the geographic coordinates (longitude and latitude) of the centroids of the cold cloud shields. This work also conducts a preliminary analysis of the spatial and temporal distribution characteristics of MCCs over mainland China based on the dataset. Results indicate that MCCs occur more frequently in Southwest China than in other regions of the country, and over 70 % of MCC events occur in summer both in Southwest China and mainland China. Moreover, MCC frequency in Southwest China exhibits significant interannual variability.
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Status: open (until 25 Feb 2026)
- RC1: 'Comment on essd-2025-652', Anonymous Referee #1, 07 Feb 2026 reply
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RC2: 'Comment on essd-2025-652', Anonymous Referee #2, 08 Feb 2026
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This paper developed an automated algorithm for MCC identification and tracking based on the FY-2G satellite data. Such a dataset is valuable for various applications, such as climate change research and disaster risk reduction. The algorithm is proved to be physically sound and can effectively capture MCC occurrence and movement over mainland China. In general, the paper is well written: the method is clearly described, the analysis and discussions are thorough and comprehensible. However, there are some places that either need more clarification or should be revised before it is published. These are listed in the following specific comments and questions.
Question about the method:
- In the north China, cases that are “nealy cloud-free or covered by thin cloud” could be miss-identified as MCC (around line 185) . Can this happen for other seasons and in other regions? If so, how can we justify the correctness of the identified MCCs by simply eliminate the winter season?
Specific comments and corrections:
- Line 23: “both in South China and mainland China”. People may misunderstand these as two separate regions of China. Maybe it’s better to say “both in South China and mainland China as a whole”.
- Line 35: “region of major topographic features” is an ambiguous expression. Do you mean region of large-scale plateau?
- Line 39: The hyphens here should be em-dashes.
- Lines 96-97 and lines 100-102: These sentences described how manual census reveals the problem of using the original parameters from Maddox (1980) in China. It’s better to conjunct these sentences properly to increase the logic fluency and coherence.
- Line 102: please give proper references to the criteria stated here (i.e., CTT<=-52℃with an area >=50000 km2). And does the 40000 km2 criteria brought from previous studies or randomly set in this study?
- Table 1: Both TBB and CTT are used in this table. Are they different variables? Or just two different expressions of the same variable? If the latter, it’s better to use the same expression.
- Lines 129-130: the hyphen here should be em-dash.
- Equation 1: The equation and text are inconsistent. The equation actually calculated the total clutter area Si, rather than “the individual pixel area” as stated in lines 141-142.
- Lines 180-181: this sentence is confusing. a better expression may be “comparative analysis was conducted between two typical algorithm-identified cases, one from this region and the other from southern China, with the latter manually confirmed.”
- Line 182: “the CTT” should be “The CTT”. Additionally, please refer to the explicit figure on basis of which the discussion is made.
- Lines 198-199: Are this statement addressed from figure 5? If so, it's better to move it below to appropriate places, perhaps after line 205.
- Line 202: The title could be “Data Output”, to avoid confusion with the title of section 4.
- Section 3.4: It is recommended to provide a table here to summarize the key information of the dataset, for instance the variables, dimensions, attributes.
- Line 230: The phrase “cumulative MCC” is confusing. Are there other types of MCC?
- Line 235: The phrase “extremely large” is ambiguous. Could give a quantitative number?
- Line 243: It’s unclear where the southwest China here refers to. Please consider illustrating the area in the figure, or providing an exact depiction of its extension in the text.
- Lines 245-248: Please mention figure 7 here when doing description based on the figure.
- Line 251: “Zhang, 2025” should be “Zhang et al., 2025”. “in Figs. 7 and 8” should be “in Figure 7”.
- Line 260: Perhaps “The coherence of the peak in 2020 across...” can be “The coherence of the peak in 2020, as well as the periodicity, across...”
- Line 281: “2015-2014” should be “2015-2024”.
- Line 282-283:”where cold surface conditions can lead to ” perhaps is better to be ”where cold surface conditions and thin very high clouds can lead to ”?
Citation: https://doi.org/10.5194/essd-2025-652-RC2
Data sets
A new dataset of MCC derived from FY-2G satellite data Ke Xu https://doi.org/10.5281/zenodo.17349888
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Main comments:
This work developed an automated algorithm for mesoscale convective complex (MCC) identification and tracking, and then composed a long-term dataset of MCC variables over mainland China, based on the FY-2G cloud-top temperature data. MCC is an important type of convective system, often bringing about persistent heavy rain and secondary geologic disasters. Thus, this work has the potential in promoting the monitoring and research on the occurrence of MCC, and helping in disaster alleviation over the region. In general, the algorithm is described clearly, the manuscript is well-organized, and the dataset can be actually downloaded. However, there are some places (see specific comments) that need to be revised before it can be accepted for publication.
Specific comments: