Turbulence in Marine Convective Boundary Layer Clouds.

Turbulence is a key transport mechanism responsible for many cloud processes. As a primary mechanism of cloud evolution, it drives entrainment and mixing, influences cloud microphysics. Experimental information on turbulence gathered during measurement campaigns is, however, mostly used to estimate turbulent fluxes or statistical moments of vertical velocity for the purpose of LES simulations. As a consequence, information on turbulence within, between and below clouds, based on in situ airborne measurements is scarce and incomplete.

In this study we perform metaanalysis of airborne turbulence measurements collected in the course of five research campaigns (POST, DYCOMS-II, ASTEX, RICO and EPIC) in order to provide a synthesized description of turbulence in marine boundary layer with clouds. These various measurement campaigns, performed at different location and different time allow to obtain some universal statistical characteristics of turbulence in the marine stratocumulus (Sc) and cumulus (Cu) boundary layers.

In the first part of the analysis we present characteristics of Turbulence Kinetic Energy (TKE) such as vertical distribution and scale-depending anisotropy inside, outside and below clouds.

In the second part of the analysis we present similar characteristics of TKE dissipation rate ε. We apply standard methods to estimate ε, based on TKE spectra and structure functions of velocity fluctuations, as well as the novel zero-crossing methods introduced and tested recently by Waclawczyk et al.( 2017).

Finally, we discuss the results, comparing them to large eddy simulations of marine cloudy boundary layers. This allows us to point out the key issues to be solved in order to better understand cloud properties.

Wacławczyk, M., Ma, Y.-F., Kopeć, J. M., and Malinowski, S. P.: Novel approaches to estimating the turbulent kinetic energy dissipation rate from low- and moderate-resolution velocity fluctuation time series, Atmos. Meas. Tech., 10, 4573-4585, https://doi.org/10.5194/amt-10-4573-2017, 2017.