Articles | Volume 18, issue 12
https://doi.org/10.5194/gmd-18-3921-2025
https://doi.org/10.5194/gmd-18-3921-2025
Development and technical paper
 | 
01 Jul 2025
Development and technical paper |  | 01 Jul 2025

Quantifying the oscillatory evolution of simulated boundary-layer cloud fields using Gaussian process regression

Gunho Loren Oh and Philip H. Austin

Viewed

Total article views: 5,389 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
4,259 968 162 5,389 197 269
  • HTML: 4,259
  • PDF: 968
  • XML: 162
  • Total: 5,389
  • BibTeX: 197
  • EndNote: 269
Views and downloads (calculated since 11 Apr 2024)
Cumulative views and downloads (calculated since 11 Apr 2024)

Viewed (geographical distribution)

Total article views: 5,389 (including HTML, PDF, and XML) Thereof 5,325 with geography defined and 64 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 16 Aug 2026
Download
Short summary
It is difficult to study the behaviour of a cloud field due to internal fluctuations and observational noise. We perform a high-resolution simulation of the boundary-layer cloud field and introduce statistical and numerical techniques, including machine-learning models, to study the evolution of the cloud field, which shows a periodic behaviour. We aim to use the numerical techniques to identify the underlying behaviour within noisy observations.
Share