Modifications to the CLASS Boundary Layer Model for Improved Interaction Between the Mixed Layer and Clouds

The impact of clouds on the mixed layer (ML) is critical for understanding the evolution of boundary layer humidity and temperature over the course of a day. We found that accounting for moistening of the cloud layer (CL) by humidity originating in the ML dramatically alters the interaction between the ML and the CL in a one-dimensional cloud-topped boundary layer model: Chemistry Land-surface Atmosphere Soil Slab (CLASS) (Vil & agrave;-Guerau de Arellano et al., 2015, ). We demonstrate that enabling CLASS to moisten the lower CL improves the prediction of humidity (and the flux of humidity) both above and below the ML top (h). To account for this moistening, we propose a length scale, L, above h, over which mixing of mass fluxes into the environment occurs. The mass fluxes are assumed to decrease linearly from h to a height L meters above h, analogous to a convective plume detraining into the environment at a height-independent rate. Accounting for this process is accomplished by modifying the differential equations representing the growth of the jumps (sharp changes in humidity and temperature) at h. From analysis of a large number of diurnal Large Eddy simulations (covering approximately 11,000 different early morning initial conditions), we provide a regression model for parameterizing L from early morning weather variables. With the regression-based estimate of L, the modified model (CLASS-L) accounts for moistening the lower CL, and as a result, yields improved humidity dynamics, humidity flux profiles, and cloud growth under a broad range of conditions. This study improved the representation of clouds above the mixed layer (ML) top in a simplified cloud-topped atmospheric boundary layer model, Chemistry Land-surface Atmosphere Soil Slab (CLASS) (Vil & agrave;-Guerau de Arellano et al., 2015, ). The CLASS model does not moisten the lower cloud layer (CL) when moisture originating from the ML reaches the CL. To address this, we propose a mixing length scale, L, above the ML top over which moisture originating from the ML is mixed into the environment, and name this model CLASS-L. A power-law regression is used to estimate L with regression coefficients based on a large set of daytime diurnal simulations (covering approximately 11,000 different initial conditions) using CLASS-L and state-of-the-art, three-dimensional Large Eddy Simulation. With this simple enhancement to CLASS, CLASS-L dramatically improved humidity dynamics, cloud growth, and humidity flux profiles both above and within the ML under a very broad range of initial conditions. We enhance land-atmosphere-cloud interactions in a simplified model (Vil & agrave;-Guerau de Arellano et al., 2015, ) We propose an empirically determined length scale above the mixed layer over which mixing of humidity mass flux with the environment occurs The modifications (Chemistry Land-surface Atmosphere Soil Slab-L) dramatically alter the state and flux profiles in cloudy conditions, in agreement with Large Eddy Simulations