Modeling coastally trapped wind surges over southeastern Australia. Part I: Timing and speed of propagation

Citation
Hj. Reid et Lm. Leslie, Modeling coastally trapped wind surges over southeastern Australia. Part I: Timing and speed of propagation, WEATHER FOR, 14(1), 1999, pp. 53-66
Citations number
17
Categorie Soggetti
Earth Sciences
Journal title
WEATHER AND FORECASTING
ISSN journal
08828156 → ACNP
Volume
14
Issue
1
Year of publication
1999
Pages
53 - 66
Database
ISI
SICI code
0882-8156(199902)14:1<53:MCTWSO>2.0.ZU;2-Z
Abstract
During the spring and summer months, the southeast coast of Australia often experiences abrupt southerly wind changes, the leading edge being known lo cally as a "southerly buster." The main characteristic of this phenomenon i s the sudden shift in wind direction, usually from north or northwesterly t o southerly. Associated with this wind surge is a significant temperature d rop 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 a bility 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 eas t 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 s kill 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 dire ct comparison of model predictions with observations. It was found that the performance of the model was good overall but was highly case dependent, p articularly according to season and time of day, with some poor and some ex cellent simulations, This ability of the NWP model to provide predictions w ithin an acceptable error has positive implications as a useful tool in rea l-time forecasting.