Short-range quantitative precipitation forecasting in Hong Kong

被引:66
作者
Li, PW [1 ]
Lai, EST [1 ]
机构
[1] Hong Kong Observ, Kowloon, Hong Kong, Peoples R China
关键词
quantitative precipitation forecast; nowcasting; numerical weather prediction; rainfall verification;
D O I
10.1016/j.jhydrol.2003.11.034
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
The Hong Kong Observatory has developed a forecasting suite that includes a radar-based nowcasting component, SWIRLS (Short-range Warnings of Intense Rainstorms in Localized Systems), to provide quantitative rainfall guidance up to 3 h ahead and a NWP component that extracts quantified precipitation information from the 24 h forecasts provided by the Observatory's 20 km operational regional spectral model (ORSM). Such operation-critical information is processed and visualized through a combined display for forecasters' ready interpretation. The objective is to establish a mechanism for continuous 24 h QPF monitoring by cross-referencing prognostic information derived from the nowcasting system and the NWP model. The SWIRLS QPF, based on radar and raingauge data analysis and echo movement extrapolation, is quite robust in tracking pre-existing rain systems. Predictions of I and 2 h rainfall distribution patterns for rainstorms of moderate to heavy intensity (30-50 mm/h) are fairly reliable. Although generally less accurate in specific details, the 3 It QPF has nonetheless demonstrated its overall usefulness in operating the Landslip Warning System for the public in Hong Kong. For longer range QPF, ORSM is used. Hourly rainfall information derived from GMS5 digital cloud data and from SWIRLS radar/raingauge analysis is incorporated through a physical initialization (PI) process. Case studies have shown that with PI, QPF in the model is improved. The performance of the QPFs by SWIRLS and ORSM is verified using various skills scores. Verification statistics show that the systems are able to provide useful guidance to forecasters for operational decision-making in heavy rain situations. (C) 2003 Elsevier B.V. All rights reserved.
引用
收藏
页码:189 / 209
页数:21
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