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Composited structure of non-precipitating shallow cumulus clouds

Gu, J.-F. ORCID:, Plant, R. S. ORCID:, Holloway, C. E. ORCID: and Jones, T. R. ORCID: (2021) Composited structure of non-precipitating shallow cumulus clouds. Quarterly Journal of the Royal Meteorological Society. ISSN 1477-870X (In Press)

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To link to this item DOI: 10.1002/qj.4101


The normalized distributions of thermodynamic and dynamical variables both within and outside shallow clouds are investigated through a composite algorithm using large eddy simulations of oceanic and continental cases. The normalized magnitude is maximum near cloud center and decreases outwards. While relative humidity (RH) and cloud liquid water ($q_l$) decrease smoothly to match the environment, the vertical velocity, virtual potential temperature ($\theta_v$) and potential temperature ($\theta$) perturbations have more complicated behaviour towards the cloud boundary. Below the inversion layer, $\theta_v^{'}$ becomes negative before the vertical velocity has turned from updraft to subsiding shell outside the cloud, indicating the presence of a transition zone where the updraft is negatively buoyant. Due to the downdraft outside the cloud and the enhanced horizontal turbulent mixing across the edge, the normalized turbulence kinetic energy (TKE) and horizontal turbulence kinetic energy (HTKE) decrease more slowly from the cloud center outwards than the thermodynamic variables. The distributions all present asymmetric structures in response to the vertical wind shear, with more negatively buoyant air, stronger downdrafts and larger TKE on the downshear side. We discuss several implications of the distributions for theoretical models and parameterizations. Positive buoyancy near cloud base is mostly due to the virtual effect of water vapor, emphasising the role of moisture in triggering. The mean vertical velocity is found to be approximately half the maximum vertical velocity within each cloud, providing a constraint to achieve possible power law distributions for some models. Finally, the normalized distributions for different variables are used to estimate the vertical heat and moisture fluxes within clouds. The results suggest the distributions near cloud edge and the variability of maximum perturbations need careful treatment. The fluxes are underestimated in the inversion layer because the cloud top downdrafts can not be well captured.

Item Type:Article
Divisions:Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
ID Code:98075
Publisher:Royal Meteorological Society

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