The classification and simulation of precipitating convective regimes over Darwin, Australia

Tropical convective clouds come in many different forms, making improved understanding, simulation or parameterization difficult. There are arguably infinite possible variations in the meteorological conditions that can lead to an infinite variation in cloud types. Yet, in most cases these differences are likely not important to our understanding of gross behaviour and features of tropical clouds or our ability to make accurate and useful numerical predictions. The challenge is to know when differences between clouds are important and when they are superficial. This talk will outline how the natural complexity of tropical convection can be simplified into a discrete and manageable number of regimes, and how the regimes can be used to evaluate a numerical model.

Four regimes were created by applying a clustering algorithm to Frequency with Altitude Diagrams (FAD's) derived from four years of hourly radar data obtained from the Gunn Point radar in Darwin Australia (wet season only). The precipitation regimes were found to be distinguished in terms of convective intensity, presence of stratiform precipitation and precipitation coverage. Regime 1 consists of patchy convection of medium intensity and low area coverage. Regime 2 contains strong convection with relatively small area coverage. Regime 3 is comprised of weak convection with large area coverage and large stratiform regions and regime 4 contains strong convection with large area coverage and large stratiform regions. Analysis of the seasonal cycle, diurnal cycle and regime occurrence as a function of monsoon activity indicate that regimes 1 and 2 are characteristic of continental convection, while regimes 3 and 4 are characteristic of maritime convection.

After the physical nature of each regime was established, the Weather Researching and Forecasting (WRF) model was employed to determine if the regimes could be used to evaluate a numerical model simulating tropical convection. To compare model simulations with the radar derived regimes, the model microphysical data was converted into simulated radar reflectivities, and model derived FADs were created. The final part of the presentation will outline how the radar FADs, the radar regimes and the simulated reflectivity data can be used to provide an objective assessment how the model performs at simulating the observed precipitation structure under different synoptic conditions.