Articles | Volume 25, issue 18
https://doi.org/10.5194/acp-25-10773-2025
https://doi.org/10.5194/acp-25-10773-2025
Research article
 | 
19 Sep 2025
Research article |  | 19 Sep 2025

A machine-learning-based perspective on deep convective clouds and their organisation in 3D – Part 1: Influence of deep convective cores on the cloud life cycle

Sarah Brüning and Holger Tost

Data sets

Convective cloud trajectories from 3D radar reflectivities Sarah Brüning https://doi.org/10.5281/zenodo.14724401

Model code and software

Detecting ML-based convective clouds using 3D observational data Sarah Brüning https://doi.org/10.5281/zenodo.14699719

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Short summary
This study analyses the temporal variability and life cycle of 3D convective clouds characteristics in the tropics. We derive the data from a machine-learning-based 3D extrapolation of high-resolution 2D satellite data and an object-based detection algorithm. Cloud properties are not only affected by the surface type. Instead, our findings highlight the impact of convective cores on horizontal and vertical cloud and core properties and a potential prolonging of the cloud life cycle.
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