Modeling Coastally Trapped Wind Surges over Southeastern Australia. Part I: Timing and Speed of Propagation
- 1 February 1999
- journal article
- Published by American Meteorological Society in Weather and Forecasting
- Vol. 14 (1) , 53-66
- https://doi.org/10.1175/1520-0434(1999)014<0053:mctwso>2.0.co;2
Abstract
During the spring and summer months, the southeast coast of Australia often experiences abrupt southerly wind changes, the leading edge being known locally as a “southerly buster.” The main characteristic of this phenomenon is the sudden shift in wind direction, usually from north or northwesterly to southerly. Associated with this wind surge is a significant temperature drop and sea level pressure rise. A severe southerly buster has wind speeds exceeding gale force (17 m s−1) and poses a threat to human safety. Southerly busters have been the subject of a number of studies over several decades. These have focused on the development and propagation of the wind surge. The aims of this study are quite different, namely, to assess the ability of a real-time, high-resolution, numerical weather prediction (NWP) model to simulate some of the key features of the southerly buster, notably the time of passage and strength at various locations along the southeast coast and at two inland stations. A large number (20) of case studies of southerly wind changes along the east coast of New South Wales has been selected to verify 40 simulations from the numerical model. The focus of the case studies was on quantifying the skill of the model in simulating the timing and speed of propagation of the southerly buster. The measure of skill adopted here was one based on a direct comparison of model predictions with observations. It was found that the performance of the model was good overall but was highly case dependent, particularly according to season and time of day, with some poor and some excellent simulations. This ability of the NWP model to provide predictions within an acceptable error has positive implications as a useful tool in real-time forecasting.Keywords
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