Sunday, 6 January 2013
Exhibit Hall 3 (Austin Convention Center)
One of the challenges of tropical cyclone prediction is the lack of observations over the ocean. One powerful new source of data is the global positioning system (GPS) radio occultation (RO), which can provide valuable information about moisture distribution over the ocean. In this study we assessed the impact of GPS RO on the prediction of heavy rainfall associated with Typhoon Morakot (2009), a category two typhoon that made landfall on Taiwan, killed 700 people and caused $5.5 billion USD of damage. Two sets of ensemble forecasts were performed using the Weather Research and Forecasting (WRF) model, one with the assimilation of GPS RO data and the other without. The WRF model used triple nests, with grid sizes of 45, 15 and 5 km. The forecasts started at 0000 UTC 6 August 2009, and extended for four days. Our study focused on the third day, the day with maximum rainfall, as well as the four-day total. Several verification scores were used to evaluate the precipitation forecast skill from the two sets of ensemble forecasts. These included: the frequency bias score, the threat score, the Gilbert skill score, the fraction skill score, and image warping. Results from both the scores and image warping indicated that the assimilation of GPS RO data improved the prediction of precipitation. This study used a new method, image warping, which we believe could improve the information provided by verification methods for high resolution forecasts.
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