Friday, 13 November 2009: 8:55 AM
The tropical cyclone (i.e., hurricane) is one of the greatest natural hazards on the Earth. The forecast of hurricane, however, lack the skill due to many factors including the scarcity of observations over oceans. Data sparseness degrades the initial condition for numerical modeling, which results in a forecast with errors. The abundances of satellite data, on the other hand, provide a potential to improve model initial conditions by applying method such as Three Dimensional Variational Assimilation (3DVAR). In this study, Weather Forecast and Research (WRF) model with its 3DVAR package was utilized to investigate the influence of Quick Scatterometer (QuikSCAT) observations on the prediction of Hurricane Ike (2008) for both track and intensity. The sensitivity runs were conducted separately with QuikSCAT wind vectors for comparison purpose. Incorporation of QuikSCAT winds was found to improve the initial condition resulting in the improvement of simulated intensity and track.
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