ISSN 1000-0526
CN 11-2282/P
CN 11-2282/P
Archive > Volume 47 Issue 8 > 2021,47(8):919-931. DOI:10.7519/j.issn.1000-0526.2021.08.002 Prev Next
A Downburst Nowcasting Method Based on Observations of S-Band New Generation Weather Radar
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Abstract:
Downburst is the most common weather phenomenon of convective storm, and forecasting its initial outbreak is one of the most challenging contents in severe convective storm forecasting. In this paper, a downburst nowcasting algorithm based on radar and radiosonde observation data was proposed. On the basis of ground clutter suppression and radial velocity dealiasing of radar base data and processing of sounding data to obtain 0℃, -20℃ and minimum equivalent potential temperature heights, the algorithm first identifies and tracks storm cells and calculates the hail indexes, then identifies the mid-level radial convergence characteristics and mesocyclone, making them associated with the identified storm cell. After that, many radar characteristics of storm cells are extracted. After statistical analysis of downburst and non-downburst cases, nine radar precursor factors of downburst were selected as the input of fuzzy logic method, and the nowcasting equation of downburst was established. The algorithm was tested with a downburst case which occurred in Jianli of Hubei Province on 1 June 2015, responsible for the “Oriental Star” cruise ship capsizing. The results show that the algorithm has predicted 8 times in 20:41-21:21 BT that the storm cell having caused the shipwreck will produce downburst. The first prediction time is 47 minutes earlier than that of the cruise ship capsizing at 21:28 BT. In addition, the effectiveness of the downburst nowcasting algorithm was evaluated by using all thunderstorm gales in Hubei Province from June to August 2019. The results show that the hit rate of downburst is 86.4%, and the average forecast time is 39 min. According to the echo pattern, the hit rates of downburst nowcasting for squall line, linear convection and non-linear convection are 93.2%, 90.5% and 75.6%, respectively. Actually, the algorithm module has been integrated into the automatic identification and warning system of classified severe convective weather developed by Wuhan Institute of Heavy Rain of CMA, and has been put into operation since 2019. The algorithm will be continuously optimized in the forecasting operation application in the future.
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