Annual Cycle of Tropical Convective Clouds from 20-Year MODIS Observations with an Improved Convective Cloud Detection

Abstract This study utilizes a 20-yr (2003–22) dataset of tropical deep convective clouds (DCCs) from MODIS wide-swath observations with a new detection method to characterize the annual cycle of tropical DCCs, focusing on global patterns, regional variations, and day/night differences. Tropical mean daytime DCC occurrence peaks in December (1.90%) and reaches a minimum in May (1.55%). Notable features include the double ITCZ over the eastern Pacific in March–April and alternating northwest–southeast bands of day/night differences over the Amazon. Regional analyses across six tropical regions, using four DCC size classes (class 1 “small” to class 4 “giant”), reveal distinct behaviors: The western Pacific has the highest DCC occurrences, driven primarily by giant clusters; the eastern Pacific shows similar seasonal trends across all classes; the equatorial Atlantic lacks growth of class 4 clusters; Africa consistently shows larger nighttime cluster sizes; and the Amazon features an alternating day/night dominance in DCC occurrences, with larger nighttime occurrences from May to August but smaller values from October to December. Distributions of normalized DCC cluster number density and occurrence as a function of cluster size show that larger clusters (>10 4 km 2 ) dominate total convective area, despite the numerical dominance of smaller clusters (<10 3 km 2 ). Oceanic regions exhibit unique patterns of day/night differences, characterized by fewer clusters smaller than 10 2.5 km 2 and larger than 10 5 km 2 , but more clusters in the intermediate range during nighttime. These findings provide valuable information for model evaluations, highlighting the importance of resolving DCC cluster size variability in climate models.

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Publication Details

Journal
Journal of Climate
Published
2025-08-25
DOI
https://doi.org/10.1175/jcli-d-25-0007.1
Citations
1
Primary Topic
Atmospheric aerosols and clouds
Type
article
Field-Weighted Citation Impact
1.11
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article

Annual Cycle of Tropical Convective Clouds from 20-Year MODIS Observations with an Improved Convective Cloud Detection

Zhien Wang, Kang Yang, Min Deng
1 citations
Journal of Climate
Atmospheric aerosols and clouds
1.11
article

Annual Cycle of Tropical Convective Clouds from 20-Year MODIS Observations with an Improved Convective Cloud Detection

Zhien Wang, Kang Yang, Min Deng
article en
1 citations

Abstract

Abstract This study utilizes a 20-yr (2003–22) dataset of tropical deep convective clouds (DCCs) from MODIS wide-swath observations with a new detection method to characterize the annual cycle of tropical DCCs, focusing on global patterns, regional variations, and day/night differences. Tropical mean daytime DCC occurrence peaks in December (1.90%) and reaches a minimum in May (1.55%). Notable features include the double ITCZ over the eastern Pacific in March–April and alternating northwest–southeast bands of day/night differences over the Amazon. Regional analyses across six tropical regions, using four DCC size classes (class 1 “small” to class 4 “giant”), reveal distinct behaviors: The western Pacific has the highest DCC occurrences, driven primarily by giant clusters; the eastern Pacific shows similar seasonal trends across all classes; the equatorial Atlantic lacks growth of class 4 clusters; Africa consistently shows larger nighttime cluster sizes; and the Amazon features an alternating day/night dominance in DCC occurrences, with larger nighttime occurrences from May to August but smaller values from October to December. Distributions of normalized DCC cluster number density and occurrence as a function of cluster size show that larger clusters (>10 4 km 2 ) dominate total convective area, despite the numerical dominance of smaller clusters (<10 3 km 2 ). Oceanic regions exhibit unique patterns of day/night differences, characterized by fewer clusters smaller than 10 2.5 km 2 and larger than 10 5 km 2 , but more clusters in the intermediate range during nighttime. These findings provide valuable information for model evaluations, highlighting the importance of resolving DCC cluster size variability in climate models.

Journal of ClimateVol. 38(21)
State University of New York (US), Brookhaven National Laboratory (US), Stony Brook University (US)
Openalex Percentile: Top 20%
Atmospheric aerosols and clouds
1.11
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