基于集合预报的两种输电线路舞动概率预测方法

利用中国气象局集合预报业务系统GRAPES-EPS（Global/Regional Assimilation and Prediction System Ensemble Prediction System）的15个集合成员预报产品，基于舞动气象模型，分别通过等权重法和集合平均法得到输电线路舞动发生的预测概率，以2016年11月23日和2018年1月4日~6日的电线结冰数据作为实况，检验两种预测方法的效果，结果发现，（1）等权重法和集合平均法预测出的舞动范围均能覆盖实际发生舞动的区域，均可作为舞动发生的客观预测方法；（2）等权重法预测输电线舞动的报对站比例更高而漏报站比例更低，(3)等权重法预测的日最大舞动概率和日平均舞动概率均较集合平均法预测的大；(4) 从空间分布和时间变化来看，等权重法舞动预测的概率值具有一定的连续性，而集合平均法预测的舞动概率值则具有明显的跳跃性，等权重法应用效果较集合平均法更好。

Two Methods of Line Galloping Prediction Based on Ensemble Forecast

Using data of Ensemble Prediction System of Global/Regional Assimilation and Prediction System (GRAPES-EPS), which was the ensemble prediction system of China Meteorology Administration (CMA) and had 15 ensemble members, and in the basis of existing line galloping meteorological model, line galloping was predicted in both November 2016 and January 2018 by using the wire ice data with the relative models, that was, equally-weighted method and ensemble-averaged method. The results show that: (1) both equally-weighted method and ensemble-averaged method could predict the possibility of occurring and developing of line galloping, and the site and time of galloping which are predicted by both two methods are coincided with the observation data; (2) the ratio of stations which are correctly predicted is higher and that of stations which are failed forecasted is lower by using equally-weighted method, by compared with ensemble-averaged method ; (3) from the view of maximum and average of daily line galloping predicted by the two methods, those are predicted by equally-weighted method are larger than that are predicted by ensemble-averaged method; (4) from view of the spatial distribution predicted by the two methods, the line galloping probability predictions have the certain continuity by using equally-weighted method, while the distributions are obviously jumping by using ensemble-averaged method; from the view of time variation, the line galloping predicted by equally-weighted method are changing with time, while the line galloping predicted by ensemble-averaged method are jumping with time variation. That is, in comparison with the galloping predicted by ensemble-averaged method, the line galloping predicted by equally-weighted method is closer to the observation and has better effect in line galloping prediction.