Articles | Volume 26, issue 11
https://doi.org/10.5194/acp-26-7949-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-26-7949-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Prognostic modeling of total specific humidity variance induced by shallow convective clouds in a GCM
Louis d'Alençon
CORRESPONDING AUTHOR
LMD/IPSL/Sorbonne Université, CNRS, Paris 75005, France
Frédéric Hourdin
LMD/IPSL/Sorbonne Université, CNRS, Paris 75005, France
Catherine Rio
CNRM, Université de Toulouse, Météo-France, CNRS, Toulouse, France
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Explicit simulations (LES) of cold pools formed by the re-evaporation of convective rainfall are compared with a parameterization developed for a climate model. The study demonstrates the relevance of the parameterization principles. Improvements to the scheme and automatic tuning of free parameters also lead to very good quantitative agreement between the LES and the parameterization.
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Short summary
We develop and implement a prognostic model of the atmospheric humidity variance in a global climate model to improve cloud prediction. Results are systematically compared with a high-resolution model using automatic tuning tools. We show consistency with earlier work performed with a diagnostic model while providing significant improvements in the description and understanding of the atmospheric humidity distribution by highlighting the role of the air detrained from thermals.
We develop and implement a prognostic model of the atmospheric humidity variance in a global...
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