Evaluation of a new parameterization for fair-weather cumulus

A new parameterization for boundary layer cumulus clouds, called the cumulus potential (CuP) scheme, is introduced. This scheme uses joint probability density functions (JPDFs) of virtual potential temperature and water-vapor mixing ratio, as well as the mean vertical profiles of virtual potential temperature, to predict the amount and size distribution of boundary layer cloud cover. This model considers the diversity of air parcels over a heterogeneous surface, and recognizes that some parcels rise above their lifting condensation level to become cumulus, while other parcels might rise as clear updrafts. This model has several unique features: 1) surface heterogeneity is represented using the boundary layer JPDF of virtual potential temperature versus water-vapor mixing ratio, 2) clear and cloudy thermals are allowed to coexist at the same altitude, and 3) a range of cloud-base heights, cloud-top heights, and cloud thicknesses are predicted within any one cloud field, as observed.

Using data from Boundary Layer Experiment 1996 and a model intercomparsion study using large eddy simulation (LES) based on Barbados Oceanographic and Meteorological Experiment (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 other cumulus parameterizations: one based on relative humidity, a statistical scheme based on the saturation deficit, and a slab model.