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

Viewed

Total article views: 645 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
533 83 29 645 29 45
  • HTML: 533
  • PDF: 83
  • XML: 29
  • Total: 645
  • BibTeX: 29
  • EndNote: 45
Views and downloads (calculated since 05 Feb 2025)
Cumulative views and downloads (calculated since 05 Feb 2025)

Viewed (geographical distribution)

Total article views: 645 (including HTML, PDF, and XML) Thereof 645 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 19 Sep 2025
Download
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.
Share
Altmetrics
Final-revised paper
Preprint