著者
Hsiang-Wen Cheng Shu-Chih Yang Yu-Ching Liou Ching-Sen Chen
出版者
Meteorological Society of Japan
雑誌
SOLA (ISSN:13496476)
巻号頁・発行日
vol.16, pp.97-103, 2020 (Released:2020-06-26)
参考文献数
16
被引用文献数
2

This study investigates the forecast sensitivity of an afternoon thunderstorm in northern Taiwan to the upstream condition associated with the prevailing warm and moist southwesterly winds on 16 June 2008. This event was initiated near noon and lasted for several hours with a maximum hourly precipitation rate of 69 mm hr−1 at 14 LST.Experiments are conducted to assimilate radial velocity only or both radial velocity and reflectivity data from radars at southwestern and southern Taiwan with the WRF-Local Ensemble Transform Kalman Filter Radar assimilation system. Results show that these experiments can predict the rainfall occurrence in northern Taiwan, but the location and rainfall amount is very sensitive to upstream environmental conditions. Assimilating the unfiltered topography-associated reflectivity noise upstream generates unrealistic light rain and cooling, which leads to a great reduction of rainfall in the target area. The precipitation prediction suggests that a careful topography-based quality control performed on the radar data can be essential to restore the necessary environmental conditions for forecasting the afternoon thunderstorm event.
著者
Hsiang-Wen Cheng Shu-Chih Yang Yu-Ching Liou Ching-Sen Chen
出版者
Meteorological Society of Japan
雑誌
SOLA (ISSN:13496476)
巻号頁・発行日
pp.2020-017, (Released:2020-05-12)
被引用文献数
2

This study investigates the forecast sensitivity of an afternoon thunderstorm in northern Taiwan to the upstream condition associated with the prevailing warm and moist southwesterly winds on 16 June 2008. This event was initiated near noon and lasted for several hours with a maximum hourly precipitation rate of 69 mm hr−1 at 14 LST.Experiments are conducted to assimilate radial velocity only or both radial velocity and reflectivity data from radars at southwestern and southern Taiwan with the WRF-Local Ensemble Transform Kalman Filter Radar assimilation system. Results show that these experiments can predict the rainfall occurrence in northern Taiwan, but the location and rainfall amount is very sensitive to upstream environmental conditions. Assimilating the unfiltered topography-associated reflectivity noise upstream generates unrealistic light rain and cooling, which leads to a great reduction of rainfall in the target area. The precipitation prediction suggests that a careful topography-based quality control performed on the radar data can be essential to restore the necessary environmental conditions for forecasting the afternoon thunderstorm event.