A simple parameterization coupling the convective daytime boundary layer and fair-weather cumuli

A new field experiment, named Boundary Layer Experiment 1996 (BLX96), was conducted to determine the formation of boundary-layer cumuli clouds over heterogeneous land surfaces. The resulting potential temperature (0) and water-vapor mixing ratio (r) observations were compiled into Joint Frequency Distributions (JFDs) that represent the source region from which air rises up as thermals to form cumuli. In order to predict sub-grid boundary-layer cumuli in a climate model, the JFD must be parameterized. Two classical methods to describe JFDs, one based on a statistical fit and another based on surface-layer processes, were found to be inadequate. A new method is devised, where boundary-layer air is divided into one of three groups: updrafts, downdrafts and environment. Separate JFDs are fit to each group and these sub-JFDs are added together to represent the boundary-layer JFD. This method did a good job representing the observed JFDs, but requires many free parameters. A second new method, which needs fewer free parameters, treats the J FD as a mixing diagram. In the absence of advection, the only source regions for air in the mixing diagram are the surface and the entrainment zone. Thus, the tilt of the JFD is caused by various mixtures from these two source regions. The parameterized JFDs can be used with the mean temperature and humidity profile to predict the amount and size distribution of boundary-layer cloud cover. The result is named the Cumulus Potential (CuP) Model. This model considers the diversity of air parcels over a heterogeneous surface, and recognizes that some parcels indeed rise to their lifting condensation level, while others might rise as non-cloud updrafts. This model has several unique features: (1) cloud cover is determined from the boundary-layer JFD of θ vs. r, (2) cloud-base mass flux can be approximated from the mixed-layer JFD, (3) clear and cloudy thermals are allowed to exist at the same altitude, and (4) a range of cloud-base heights, cloud-top heights, and cloud thicknesses are predicted within any one cloud field, as observed. Using data from BLX96, and a model intercomparsion study using Large Eddy Simulation (LES) based on BOMEX , it is shown that the CuP model does a good job predicting cloud-base height and cloud-top height. The model also shows promise in predicting cloud cover, and is found to give better cloud-cover estimates than three classic cumulus parameterizations: one based on relative humidity, the classic statistical scheme proposed by Sommeria and Deardorff (1977), and a slab model proposed by Albrecht (1981).Science, Faculty ofEarth, Ocean and Atmospheric Sciences, Department ofGraduat