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Large-eddy simulations of EUCLIPSE–GASS Lagrangian stratocumulus-to-cumulus transitions: Mean State, turbulence, and decoupling

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Stevens,  Björn
Director’s Research Group AES, The Atmosphere in the Earth System, MPI for Meteorology, Max Planck Society;

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Citation

De Roode, S. R., Sandu, I., van der Dussen, J. J., Ackerman, A. S., Blossey, P., Jarecka, D., et al. (2016). Large-eddy simulations of EUCLIPSE–GASS Lagrangian stratocumulus-to-cumulus transitions: Mean State, turbulence, and decoupling. Journal of the Atmospheric Sciences, 73, 2485-2508. doi:10.1175/JAS-D-15-0215.1.


Cite as: https://hdl.handle.net/11858/00-001M-0000-0027-D35E-E
Abstract
Results of four Lagrangian stratocumulus-to-shallow-cumulus transition cases as obtained from six different large-eddy simulation models are presented. The model output is remarkably consistent in terms of the representation of the evolution of the mean state, which is characterized by a stratocumulus cloud layer that rises with time and that warms and dries relative to the subcloud layer. Also, the effect of the diurnal insolation on cloud-top entrainment and the moisture flux at the top of the subcloud layer are consistently captured by the models. For some cases, the models diverge in terms of the liquid water path (LWP) during nighttime, which can be explained from the difference in the sign of the buoyancy flux at cloud base. If the subcloud buoyancy fluxes are positive, turbulence sustains a vertically well-mixed layer, causing a cloud layer that is relatively cold and moist and consequently has a high LWP. After some simulation time, all cases exhibit subcloud-layer dynamics that appear to be similar to those of the dry convective boundary layer. The humidity flux from the subcloud layer toward the stratocumulus cloud layer, which is one of the major sources of stratocumulus cloud liquid water, is larger during the night than during the day. The sensible heat flux becomes constant in time, whereas the latent heat flux tends to increase during the transition. These findings are explained from a budget analysis of the subcloud layer.