J9.3 Simulation of boundary layer clouds with double-moment microphysics and microphysics-oriented subgrid-scale modeling

Tuesday, 25 January 2011: 4:15 PM
605/610 (Washington State Convention Center)
Dorota Jarecka, University of Warsaw, Warsaw, Poland; and W. W. Grabowski, H. Morrison, and H. Pawlowska

Mixing of cloud with dry environmental air changes the cloud droplet spectrum and crucially affects optical properties of clouds. This effect is still poorly understood (Brenguier and Grabowski 1993, Burnet and Brenguier 2007, Chosson et al. 2004, 2007) and it is a significant source of uncertainty in aerosol indirect effects. In a nutshell, the issue is whether the mixing results in the reduction of only the droplet size (as in the homogeneous mixing), only the droplet concentration (as in the extremely inhomogeneous mixing), or both the concentration and the size (as in the inhomogeneous mixing). On theoretical grounds, homogeneity of mixing depends on the relative magnitude of the time scales of droplet evaporation and of turbulent homogenization. Results from direct numerical simulations suggest that a simple relationship exists between the ratio of the time scales and the slope of the mixing line on the diagram representing the relative change of the droplet concentration versus the change of the droplet radius cubed (Andrejczuk et al. 2009). In that study, the time scale for droplet evaporation was calculated as a function of the droplet size and the subsaturation predicted by the model. The time scale for turbulent homogenization was derived as a function of the turbulent kinetic energy and the simulated mean scale of cloudy filaments.

In a LES model applying a double-moment microphysics scheme (i.e., when the droplet concentration as well as the mixing ratio are predicted) the mixing scenario is determined by a single parameter (see Eq. 11 in Morrison and Grabowski 2008). However, no approach is available to guide the selection of this parameter during model simulations. In other words, currently the parameter can only be assumed constant in space and time during the simulation. We will present a consistent approach to predict this parameter (and thus the homogeneity of mixing) during model simulations. This involves addition of two model variables to predict the evolution of small-scale turbulent stirring toward the microscale homogenization following an approach described in Grabowski (2007) and Jarecka et al. (2009) and based on ideas put forward by Broadwell and Breidenthal (1982). Using such a relatively sophisticated subgrid-scale model, the mixing scenario can be predicted locally at each model time step as a function of local conditions.

Double-moment LES model EULAG with the new subgrid scale mixing scheme was used to simulate shallow convective clouds from BOMEX experiment and stratocumulus clouds observed during EUCAARI-IMPACT campaign. Results for the shallow convective clouds show that a wide range of mixing scenarios typically exists in cumuli. In agreement with observational analysis of Small et al. (2010), extremely inhomogeneous mixing seems to take place near cloud edges. There is also a large number of points where mixing is more homogeneous, and the homogeneity of mixing for these points tends to shift toward more homogeneous mixing in the upper parts of the cloud field. The latter is consistent with the simulated increase of the subgrid-scale turbulent kinetic energy and the mean droplet radius with height, both favoring the shift toward homogeneous mixing. Simulations of EUCAARI-IMPACT stratiform clouds are currently under preparation and their results will be presented at the meeting.


Andrejczuk, M., W. W. Grabowski, S. P. Malinowski, and P. K.Smolarkiewicz, 2009: Numerical simulation of cloud-clear air interfacial mixing: homogeneous versus inhomogeneous mixing. J. Atmos. Sci., 66, 2493-2500.

Brenguier, J.-L. and V. W. Grabowski, 1993: Cumulus entrainment and cloud droplet spectra: A numerical model within a two-dimensional dynamical framework. J. Atmos. Sci., 50, 120-136.

Broadwell, J. E., and R. E. Breidenthal, 1982: A simple model of mixing and chemical reaction in turbulent shear layer. J. Fluid. Mech., 125, 397-410.

Burnet, F. and J. L. Brenguier, 2007: Observational study of the entrainment-mixing process in warm convective clouds. J. Atmos. Sci., 64, 1995-2011. Chosson, F., J.-L. Brenguier, and M. Schroeder, 2004: Radiative impact of mixing processes in boundary layer clouds. Proceedings of the International Conference on Clouds and Precipitation, Bologna, Italy, 371-374.

Chosson, F., J.-L. Brenguier, and L. Schueller, 2007: Entrainment-mixing and radiative transfer simulation in boundary-layer clouds. J. Atmos. Sci., 64, 2670-2682.

Grabowski, W. W., 2007: Representation of turbulent mixing and buoyancy reversal in bulk cloud models. {\it J. Atmos. Sci.}, {\bf 64}, 3666-3680.

Jarecka, D., W. W. Grabowski, H. Pawlowska, 2009: Modeling of subgrid scale mixing in large-eddy simulation of shallow convective, J. Atmos. Sci., 66, 2125-2133

Morrison, H., and W. W. Grabowski, 2008: Modeling supersaturation and subgrid-scale mixing with two-moment bulk warm microphysics. J. Atmos. Sci., 65, 792-812.

Small, J. D., and P. Y. Chuang , 2010: An analysis of entrainment mixing processes in warm cumulus. 13th Conference on Cloud Physics, Portland, USA.

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