基于集合匹配尺度的邻域集合概率法及其在梅雨锋暴雨预报中的适用性

Neighborhood Ensemble Probability Method Based on Ensemble Agreement Scale and Its Application on Quantitative Probability Forecast of Meiyu Frontal Heavy Rainfall

概率预报是由集合预报衍生、包含不确定性信息的客观产品,对业务决策服务有重要的参考价值。传统的邻域集合概率法中,邻域半径固定不变,不符合实际天气过程中牵涉甚广的尺度谱。为此引入基于集合匹配尺度的邻域集合概率法(Neighborhood Ensemble Probability based on Ensemble Agreement Scale,EAS_NEP),并在中国南方典型的梅雨锋暴雨中开展准确性和预报技巧的定量检验评估,以期验证该方法在此类过程中的适用性,并促进其在实际业务中的推广使用。联合扰动初始场、侧边界和物理过程所得到的集合预报能较好地表征实际的预报不确定性,进一步在此基础上比较了格点概率法、不同半径的邻域集合概率法以及EAS_NEP的优劣。试验结果表明,EAS_NEP能根据集合成员间的一致性程度,自适应地调整邻域半径,其在集中型降水中所确定的邻域半径通常大于分散型降水。动态调整的邻域半径既避免了半径过大时的过度平滑与关键信息丢失,又消除了半径较小所带来的奇异点,其空间分布呈阶梯型,空间连续性更优。此外,BS(布莱尔评分)、FSS(分数技巧评分)和ROC曲线(相对作用特征曲线)等定量评估结果也体现出EAS_NEP相比传统方法正的预报技巧,尤其是在分散型降水和高阈值检验时优势更明显。以上结果表明,EAS_NEP在梅雨锋暴雨的预报中具有较好的应用前景,运用在业务中能有效提升概率预报质量。

Probability forecast is an objective product derived from ensemble forecasts and contains information of uncertainty,which has important reference value for operational decision-making services.In the traditional neighborhood ensemble probability method(NEP),the neighborhood radius is always a constant and does not conform to the scale spectrum involved in the practical weather events.Therefore,the Neighborhood Ensemble Probability based on Ensemble Agreement Scale(EAS_NEP)was introduced,and comprehensive evaluations were conducted for two Meiyu frontal heavy rainfall events in southern China,in order to verify the applicability of this method in such events and promote its popularization in practical operation.The ensemble forecasts obtained by combining the initial condition,lateral boundary and physical process of perturbations can better represent the practical prediction uncertainty.Based on this,the Grid-to-grid Probability(GP),NEP with different radii and EAS_NEP were compared for accuracy,forecast skill and other aspects of performance.The results showed that EAS_NEP can adjust the neighborhood radius adaptively according to the agreement between ensemble members and its radii tend to be lager for concentrated precipitation than dispersed precipitation.These dynamically adjusted radii not only avoid excessive smoothing and key information loss when the neighborhood radius is too large,but also eliminate the singular points caused by small radius and possess stepped spatial distribution with better continuity.In addition,quantitative evaluation results such as BS,FSS and ROC curves also confirm that EAS_NEP has improved forecasting skills compared to traditional methods,especially in the case of dispersed precipitation and high threshold situation.The results suggest that EAS_NEP has a good application prospect in the Meiyu frontal heavy rainfall events and can effectively improve the quality of probability forecast.