Evaluating a 1D Kain-Fritsch Convective Parameterization Scheme Using Observationally-Derived Trigger Function Variables

A convective parameterization scheme (CPS) as used in numerical weather prediction (NWP) models accounts for subgrid scale vertical transports of energy and mass, reduces thermodynamic instability, and redistributes temperature and moisture in a model grid cell. These parameterizations are often used in coarse resolution (~10 km) NWP simulations to resolve deep convective storms. Most CPSs have a trigger function, which is used to determine if conditions are met for the possibility of convection to occur in a model grid cell. One of the most well-known CPSs is the Kain-Fritsch. The Kain-Fritsch CPS is a mass flux scheme, in which ensembles of clouds will have a cumulative effect on the environment. In addition, these mass flux schemes explicitly calculate updrafts/downdrafts and entrainment/detrainment rates. The trigger function in the Kain-Fritsch CPS is the temperature perturbation term (δT), which has two crucial variables which are cloud base height (CBH) and cloud base vertical velocity (CBVV).

From Haliczer et al. (2024), 83 case dates were analyzed in and surrounding the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) region that exhibited mostly shallow cumulus clouds. In Haliczer et al. (2024), satellite data from the Visible Infrared Imaging Radiometer Suite (VIIRS) coupled with ground instruments from the ARM SGP site were used in a unique and novel approach for retrieving both cloud base height (CBH) and cloud base vertical velocity (CBVV) across a domain that spans around 2° in longitude and latitude. Both CBH and CBVV were derived from the observations, and the trigger function values were calculated. In the present study, these observationally derived trigger functions are compared against those generated in a 1D version of the Kain-Fritsch CPS model, where the input is a sounding profile of temperature and moisture. This 1D model was run over 12 case SGP dates, with analyses of both observations and model derived values performed. This study will also use a variety of sounding profiles to understand the behavior of the trigger function, and evaluate when this parameter is activated. Furthermore, values of CBH and CBVV are then calculated for the aforementioned case dates and are used within the 1D model to assess the sensitivity of this CPS to these observation-based parameters.