This study presents a method for comparing convection-permitting model simulations to radar observations using an innovative object-based approach. The method uses the automated cell-tracking algorithm, Thunderstorm Identification Tracking Analysis and Nowcasting (TITAN), to identify individual convective cells and determine their properties. Cell properties are identified in the same way for model and radar data, facilitating comparison of their statistical distributions. The method is applied to simulations of tropical convection during the Tropical Warm Pool-International Cloud Experiment (TWP-ICE) using the Weather Research and Forecasting Model, and compared to data from a ground-based radar. Simulations with different microphysics and model resolution are also conducted. Among other things, the comparisons between the model and the radar elucidate model errors in the depth and size of convective cells. On average, simulated convective cells reached higher altitudes than the observations. Also, when using a low reflectivity (25 dBZ) threshold to define convective cells, the model underestimates the size of the largest cells in the observed population. Some of these differences are alleviated with a change of microphysics scheme and higher model resolution, demonstrating the utility of this method for assessing model changes.
A clustering algorithm was applied to Frequency with Altitude Diagrams (FADs) derived from 4 yr of hourly radar data to objectively define four tropical precipitation regimes that occur during the wet season over Darwin Australia. The precipitation regimes defined are 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, and regime 2 contains strong convection with relatively small area coverage. Regime 3 is composed 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 all provide insight into the different physical character of the precipitation regimes. Two of the regimes exhibit a diurnal cycle with a peak in the afternoon, while the other two show a peak in their frequency of occurrence in the early morning. The different character of the regimes is also confirmed by the varying contributions that convective and stratiform rainfall make to the overall within-regime precipitation.
Understanding of wintertime precipitation in mountainous regions is central to water resources management in the Murray-Darling Basin. The Great Dividing Range (GDR), which runs along the entire eastern seaboard of the Australian continent, forms the headwaters of all of the major rivers in this agricultural 'breadbasket'. Annual precipitation amounts are up to four times greater in these uplifted regions compared with the lower lying plains to the west (Chubb et al. 2011), and the majority of this precipitation occurs in the cooler months of May-September. A decline of about 15 per cent in cool season precipitation in southern Australia since 1958 has been observed (Nicholls 2010), and links with sealevel pressure changes have been established (Larsen and Nicholls 2009), but the impact on alpine precipitation in this region has not been specifically investigated. Research into the meteorology of mountainous regions has failed to reach the level of interest in Australia that it has
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