P8       Continuously Cycled Surface and Radar Data Assimilation and its influence on Afternoon Thunderstorm Prediction in Taiwan.

Chen, I-Han, Jing-Shan Hong, and Ya-Ting Tsai, Central Weather Bureau, Taiwan

Taiwan is a relatively small subtropical island (400 km long and 150 km wide) borders the Pacific Ocean and the southeastern coast of China, and has mountains with almost north-south orientation extending above 3000 m [Central Mountain Range (CMR)] within a distance of 50 km. By cause of the geographic location, this area is under the influence of diversified weather phenomena, such as typhoons, southwest monsoons, and frontal systems. Furthermore, the interaction between multiscale weather systems is exclusively pronounced in Taiwan due to its complex topography and apparent land-sea contrast. Hence, the behavior of convective systems here is highly modulated by multiscale weather systems, in particular for afternoon thunderstorms. As stated above, in addition to the small spatial scale and short temporal scale of afternoon thunderstorm systems, the interaction between multiscale weather systems, complex topography and land-sea contrast in Taiwan also render it a challenge to predict the precise location, timing and intensity of afternoon thunderstorms.

The objective of this study is to evaluate the data assimilation strategy and the impact of assimilating surface and radar observations on afternoon thunderstorm prediction in Taiwan. The results show that the cycling strategy improves the model performance in terms of rainfall and surface forecast. Furthermore, assimilating surface observations using update cycle improves the location and intensity of the rainfall system, especially when the strength of sea breeze increased. Besides, assimilating radar observations also improves the rainfall forecast since it provided better first guess, in particular for the three-dimensional wind field due to the better forecast of previous storms. The improvement of rainfall prediction in terms of its location and strength leads to the better prediction of its associated cold pool and outflow boundary, which is quite close to the surface observations.