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尺度分解技术在定量降水临近预报检验中的应用
Applying Scale Decomposition Method to Verification of Quantitative Precipitation Nowcasts
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摘要: 采用2004年Casati提出的强度尺度检验技术，选取2008年汛期代表不同类型降水（对流云降水、层状云降水、混合云降水）的4个降水过程，从尺度分解角度入手，对“世界气象组织天气研究计划——北京奥运会预报示范项目”（WWRP B08FDP）项目中4个临近预报参加系统（BJANC, GRAPES SWIFT, STEPS, CARDS）的1 h定量降水预报进行时空尺度分解检验，研究降水预报技巧与降水时空尺度和强度之间的关系。结果表明：尽管目前国际先进的临近预报系统的水平分辨率已高达1 2 km，但其有技巧的临近预报能力主要集中于空间尺度大于32 km、时间尺度大于1 h的降水系统，而对小于这些尺度的降水系统预报能力仍非常有限；在不同时空尺度的临近预报降水误差中，60%以上的误差来自于空间尺度小于8 km的降水，85%以上的误差来自于时间尺度小于1 h的降水，传统的外推技术不能满足这些较小时空尺度降水预报的需求，要发展有效的预报方法来提高较小时空尺度降水的预报能力。将基于外推的临近预报和基于稠密观测资料、快速更新的数值预报的潜势预报相结合可能是一条有效的解决途径。Abstract: Verification of quantitative precipitation forecast has always been a challenge due to the high discontinuity of rainfall in spatial and temporal scales. Conventional methods (TS and MSE score, etc.) cannot meet the need for verification of high resolution (1—2 km) forecasts. In recent years, several new spatial verification approaches which can give more information about the complex spatial structure of forecast field have been developed, such as the intensity-scale verification method, the feather based (or object-oriented) verification method, neighborhood (or fuzzy) verification method and field deformation approaches etc. The attempt to use the intensity scale technique is introduced by Casati et al. to assess radar based 1 hour quantitative precipitation forecasts for 4 different nowcasting systems (BJANC, GRAPES SWIFT, STEPS, and CARDS) which attended the World Weather Research Program for the Beijing 2008 Olympic Games (WWRP B08FDP). The intensity-scale verification approach accounts for the spatial structure of the forecast field and allows the skill score to be diagnosed as a function of the spatial scale of the forecast error and intensity of the precipitation events. Different precipitation types (convective, stratiform and mixed type) during B08FDP demo period are selected to get representative results, it shows that these nowcasting systems exhibit forecasting skills only when the precipitation system is above 32 km spatial scale and last longer than 1 hour despite the using of most advanced systems in the world with the high resolution of 1 to 2 km. For spatial scale lower than that, the forecasting ability is very limited, which indicates that product performance characterized at different spatial scale should be considered in the applying of nowcasting products. When analyzing the forecasting errors with different spatial and temporal scales, it's found that more than 60% and more than 85% of the forecasting error come from spatial scales smaller than 8 km and time scales smaller than 1 hour respectively. Improvements in smaller scales precipitation forecasts are important. Most nowcasting systems explore the linear extrapolation technique to make 0 to 2 hours nowcasts, yet the valid extrapolation time is very limited, especially for smaller scale (less than 1 hour) convective systems, which is mainly caused by the nonlinear development of the convections. Therefore, more information about the circulation which has close relation to the movement and development of the storm should be considered. So far, the most popular way is to blend the radar based extrapolation with the dense observations and numerical model based potential forecast.
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图 2 检验区域示意图 (覆盖北京及其周边地区512km×512km的范围)
Fig. 2 Schematic figure of verification region (512 km×512 km cover Beijing area)
图 3 2008年B08FDP示范期间6个主要降水个例在不同空间尺度 (a) 和时间尺度 (b) 上1h降水的特征能量 (用母小波的平方表示) 与所有尺度上总能量比率分布图 (尺度分解图中每个个例都取其过程平均值)
Fig. 3 1-hour precipitation energy (Wml2) ratio of different spatial scale (a) and temporal scale (b) to the whole scales (from analysis fields) for 6 cases during B08FDP demo period
图 4 2008年7月14日09:00—7月15日09:00(a), 8月8日19:00—8月9日12:00(b), 8月14日11:00—22:00(c), 8月21日12:00—8月22日07:00(d) 临近预报系统 (4个系统平均)1 h定量降水预报技巧同降水的空间尺度和阈值强度之间的变化关系 (每个个例都取其过程平均值)
Fig. 4 Skill score distribution of 1-hour precipitation forecast (average of 4 systems) with precipitation spatial scale and intensity for 4 cases (taking the process average for every case) in 2008 (a) 09:00 14 July—09:00 15 July, (b) 19:00 8 August—12:00 9 August, (c) 11:00—22:00 14 August, (d) 12:00 21 August—07:00 22 August
图 5 2008年7月14日09:00—7月15日09:00 (a), 8月8日19:00—8月9日12:00 (b), 8月14日11:00—22:00 (c), 8月21日12:00—8月22日07:00临近预报系统在不同降水阈值､不同特征尺度上的1h定量降水预报误差与所有尺度总体误差的比率分布 (每个个例都取其过程平均值)
Fig. 5 Error contribution of 1-hour precipitation forecast (average of 4 systems) on each scale to that of the sum of whole scales for 4 casesin 2008 (taking the process average for every case) (a) 09:00 14 July—09:00 15 July, (b) 19:00 8 August—12:00 9 August, (c) 11:00—22:00 14 August, (d) 12:00 21 August—07:00 22 August
图 6 2008年7月14日09:00—7月15日09:00 (a), 8月8日19:00—8月9日12:00 (b), 8月14日11:00—22:00(c), 8月21日12:00—8月22日07:00(d) 临近预报系统1h定量降水预报技巧同降水的时间尺度和阈值强度之间的变化关系
Fig. 6 Skill score distribution of 1-hour precipitation forecast with precipitation temporal scale and intensity for 4 casesin 2008 (a) 09:00 14 July—09:00 15 July, (b) 19:00 8 August—12:00 9 August, (c) 11:00—22:00 14 August, (d) 12:00 21 August—07:00 22 August
图 7 2008年7月14日09:00—7月15日09:00(a), 8月8日19:00—8月9日12:00(b), 8月14日11:00—22:00(c), 8月21日12:00—8月22日07:00(d) 临近预报系统在不同降水阈值､不同时间尺度上1h定量降水预报误差与所有尺度总误差的比率
Fig. 7 Error contribution of 1-hour precipitation forecast (average of 4 systems) on each temporal scale to that of the sum of whole scale for 4 cases in 2008 (a) 09:00 14July— 09:00 15 July, (b) 19:00 8 August—12:00 9 August, (c) 11:00—22:00 14 August, (d) 12:00 21 August—07:00 22 August
表 1 事件A的概率分布表
Table 1 Probability distribution of event A
表 2 随机事件B的后验概率分布表
Table 2 Posterior probability distribution of event B
表 3 2008年主要降水过程
Table 3 List of main rainfall processes in 2008
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