基于GFS预报资料的强对流相似预报研究

An analogy-based method for strong convection forecasts in China using GFS forecast data

本文基于数值模式预报发展了强对流相似预报方法。该方法采用对流参数作为相似预报量,对比当前预报与历史预报的相似物理量场挑选与当前预报最相似的时刻,并利用这些时刻对应的强对流观测权重叠加作为当前预报时刻的强对流预报。以NCEP/GFS预报场资料,对该方法的有效性进行了检验。检验结果表明,该方法对中国地区的强对流有良好预报效果。作为数值预报的有效补充,该方法具有以下几点优势:简便易实现,具有很高的可移植性:以对流参数作为相似预报量,充分利用了模式对温,压,湿,风等基本气象要素预报比较准确的优势;有效避免了对流参数进行强对流预报时的临界值选取问题,考虑了强对流发生的地域性,气候性特点。

This paper describes an analogue-based method for producing strong convection forecasts with conventional outputs from numerical models.The method takes advantage of the good performance of numerical models in predicting synoptic-scale weather situations.It calculates the convective parameters as predictors to detect the favorable-occurrence environment of strong convections.Times in the past when the forecast parameters are most similar to those forecast at the current time are identified by searching a large historical numerical dataset.The observed strong convection situations corresponding to those most similar times are then used to form strong convection forecasts for the current time.The method is applied as a postprocess of the NCEP Global Forecast System(GFS)model.The historical dataset in which the analogous situations are sought comprises two years of summer(June–September)GFS 6-to 48-h forecasts.The strong convection forecast is then generated every 6 h over most regions of China,provided the availability of strong convection observations.The results show that the method performs well in predicting strong convections in different regions of China.Through comparison with another postprocessing strong convection forecast method,it is shown that the convective-parameter threshold problem can be solved by employing the analogy method,which considers the local historical conditions of strong convection occurrence.