Large-eddy simulation of a stratocumulus cloud

Abstract

Stratocumulus clouds form near the surface, covering about 20% of the Earth's surface, and typically appear as a lumpy cloud layer. Stratocumulus have a large effect on the Earth's energy balance because they strongly reflect incoming solar radiation. Climate projections are sensitive to the amount of cloud cover and small variations in the stratocumulus area coverage can produce energy-balance changes comparable to those due to greenhouse gases [1].Large-eddy simulation (LES) can be used to gain insight into the cloud physics and the factors controlling the cloud amount. LES is challenging, requiring very fine grid resolutions because of the sharp inversion (temperature increase) at the cloud top and the fine-scale forcing of buoyant convection that drives the turbulent flow. Turbulence is mainly generated by shear near the surface, (positively) buoyant plumes rising from the surface, and (negatively) buoyant fluid created near the cloud top by radiative cooling.The simulation corresponds to the conditions of the DYCOMS II campaign [2]. The computational domain is 5.12 2 × 1.5 km in the horizontal and vertical directions, and the grid resolution is 1.25 m with 4096 2 × 1200 grid points. The simulation utilizes the buoyancy adjusted stretched-vortex subgrid scale (SGS) model [3]. The LES model and the case details are described in Ref. [4].The images correspond to a snapshot from the LES and show the complex multiscale structure of turbulence in the atmospheric boundary layer. The panels show horizontal (Fig. 1) and vertical ( Fig. 2) cross sections of total water mixing ratio [q t = (mass of water vapor + liquid)/mass of dry atmosphere]. The total water mixing ratio is an active scalar and the main component of buoyancy. Near the surface, shear dominates the turbulence structure with streaks aligned with the mean wind direction. Higher up in the subcloud layer turbulence transitions to the cellularlike structure that is *

Turbulence Structure in a Stratocumulus Cloud

“…Figure 2 shows that cloud cover fraction is nearly 100% with the darker contours corresponding to negligible LWP. High values of LWP correspond to the locations of updrafts that replenish the cloud water, as shown in the total water visualizations of [45]. The LWP contours in Figure 2 are consistent with observations, which also show a highly variable liquid water content (LWC) [40,41,43] suggesting a complex flow where both saturated and clear air regions can be encountered in the cloud layer.…”

A Breakdown in Potential Vorticity Estimation Delineates the Submesoscale‐to‐Turbulence Boundary in Large Eddy Simulations

“…While the Boussinesq equations with buoyancy have been used here in the tradition of oceanic boundary layer LES (e.g., McWilliams et al., 1997), there is no reason why atmospheric boundary layer LES (e.g., Matheou et al., 2017) or cloud‐resolving LES (e.g., Yamaguchi et al., 2017) would not also suffer the same issues with identifying the relevant PV dynamics or energy budgets. Other issues have been identified with PV intended to be used for atmospheric turbulence simulations (Herring et al., 1994), but here the focus is the method for producing the prefiltered PV, why it is the right choice, and its evolution equations.…”

“…This somewhat familiar property of PV has important implications to the study of turbulent fluxes in LES, as will be explained below. Hamlington et al (2014) and describe simulations that are interpreted as either extremely high-resolution submesoscale simulations or extremely large-domain nonhydrostatic LES of boundary layer turbulence, where rotation and stratification become dominant at the largest scales (see also Callies & Ferrari, 2018;Matheou et al, 2017;Pham & Sarkar, 2018;Sullivan & McWilliams, 2018;Skyllingstad & Samelson, 2012;Taylor & Ferrari, 2011;Whitt & Taylor, 2017). Hamlington et al (2014) and describe LES of the spindown of a temperature front in the presence of submesoscale eddies, winds, and waves, and these simulations are analyzed here.…”

“…(2014) and Suzuki et al. (2016) describe simulations that are interpreted as either extremely high‐resolution submesoscale simulations or extremely large‐domain nonhydrostatic LES of boundary layer turbulence, where rotation and stratification become dominant at the largest scales (see also Callies & Ferrari, 2018; Matheou et al., 2017; Pham & Sarkar, 2018; Sullivan & McWilliams, 2018; Skyllingstad & Samelson, 2012; Taylor & Ferrari, 2011; Whitt & Taylor, 2017). Hamlington et al.…”