Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 18, issue 12
Articles | Volume 18, issue 12
https://doi.org/10.5194/gmd-18-3921-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-18-3921-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 18, issue 12
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

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Latest update: 05 Sep 2026
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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.
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