定量降水预报技术进展

采用ECMWF interim再分析资料、ECMWF集合预报资料、自动站降水资料，运用“集合异常预报法”和“EFI（Extreme Forecast Index）阈值法”对浙江东部一次台风远距离极端降水的成因和可预报性进行探讨，结果表明：（1）台风倒槽长期存在，在北侧冷空气入侵作用下在浙江沿海地区引起锋生，并在倒槽顶端诱生低压环流，是造成浙江东北部大暴雨的主要原因。（2）36 h时效的集合预报显示，大气可降水量、850 hPa南风分量、925 hPa水汽通量和200 hPa辐散都超过气候平均值3~4个标准差，且超过3个标准差的概率也达到了70%~90%，表明浙江沿海有优越的动力和充沛的水汽条件，异常强烈的天气信号，预示发生极端降水为高概率事件。（3）随着预报时效的延长，各物理量异常概率会明显减小，因此在判断极端天气发生可能性时应降低预警的概率阈值。（4）不同时效降水的EFI对95%和99%百分位事件的预报效果均很好，可以比确定性预报提前3~4 d提供极端降水信号。EFI指数所反映的极端降水信息较确定性模式更加可靠且稳定，在决策服务中具有更高的参考价值。（5）“集合异常预报法”可以获得与极端天气相关的形势场和物理量的异常概率，而EFI在长时效的预报更具优势，两者结合、优势互补，可以为预报员提供更全面的极端天气信号。

The value of probabilistic prediction

In this study, the mechanism and predictability of a remote typhoon heavy rainfall in eastern Zhejiang Province are investigated by ensemble anomaly forecasting, with ECMWF reanalysis data, ECMWF ensemble prediction data, and automatic weather station precipitation data. Results show that: (1) Under the intrusion of cold air from the north side of the typhoon inverse which existed for a long time, it caused frontal formation in the coastal area of Zhejiang, and induced a low pressure circulation at the top of the inverse trough, was the main reason for the heavy rainfall in the northeast of Zhejiang. (2) The ensemble forecast with 36-hour prediction valid shows that precipitable water vapor, south wind component on 850 hPa, water vapor flux on 925 hPa and divergence of 200 hPa all exceed 3~4 standard deviations of climate average, and the probability of standard deviation exceeding 3 reaches 70%~90%. These factors indicate that great dynamic condition and abundant water vapor exist along the coast of Zhejiang. Strong anomalous signals predict high probability of an extreme heavy rainfall event. (3) With the extension of the forecast lead time, the anomalous probability of each physical quantity is significantly reduced. Therefore, the threshold of anomalous probability should be reduced for the early warning of extreme weather. (4) The EFIs (Extreme Forecast Index) with different forecast lead time have good prediction results for 95% and 99% percentile precipitation events, and it can provide extreme precipitation signals 3~4 days earlier than deterministic forecasts. The information for extreme rainfall events provided by ensemble prediction EFI index is more reliable and stable than deterministic forecast, and has higher reference value in decision-making services. (5) Ensemble anomaly forecasting method quantitatively measures the abnormal probability of synoptic scale pattern and physical quantities. EFI shows advantage in longer-time scale forecast. The combination of these two forecast methods could provide more comprehensive signal for extreme weather event.