河南输电线路舞动气象风险的可预报性分析

为了研究基于数值模式的河南输电线路舞动预测的可预报性，本文以数值预报数据和常规舞动气象风险预测模型为基础，通过对河南121个国家气象站的舞动高影响气象要素预报能力的评估，揭示了借助数值预报开展舞动预测的可能性，同时针对河南容易发生输电线路舞动区域进行检验评估，得到以下结论:（1）河南东部平原地区输电线路舞动具有较好的可预报性，而西部山地丘陵地区舞动可预报性相对较低，四个舞动高发区可预报由高到低分别是:东部平原地区、南部山区、西北部山区、西南部盆地。（2）河南地区温度、风速和湿度预报均表现为东部平原地区偏差小、西部山区偏差大的特点；（3）输电线舞动的气象高影响区间的可预报性从大到小依次是风速、温度、湿度，其命中率分别为73.4%、78.4%和67.1%，温度和风速在河南东部的可预报性明显高于河南西部，而湿度在河南南部可预报性高而北部可预报性低；（4）温度、风速和湿度的可预报性区域分布有差异，要提高输电线路舞动预测水平，需要在不同区域针对不同要素进行预报订正和调整。

Analysis of Predictability for Meteorological Risk of Line Galloping Prediction in Henan Province

In order to study the predictability of line galloping in Henan Province, the predictability of meteorological indices was evaluated by using 121 national meteorological stations observation data and NWP (Numerical Weather Prediction) data besides the ordinary line galloping prediction model of meteorological risk in this paper. The basic meteorological variables were examined by using ordinary statistic methods such as error, absolute error, root mean square error and predictabilities of line galloping in four line galloping prone regions. It revealed the possibility of line galloping prediction by using NWP. The results showed that: (1) the predictability of line galloping in the plain areas in the east of Henan Province was high, while it was lower in the mountain areas in the west of Henan Province, the predictabilities of the four galloping prone regions were from high to low were Region No.1 (plain area in the east of Henan Province), Region No.3 (mountain area in the south of Henan Province), Region No.4 (mountain area in the northwest of Henan Province) and Region No.1 (basin area in the southwest of Henan Province); (2) the biases of temperature and wind speed were both small in the plain areas and large in the mountain areas; (3) the predictability of line galloping of meteorological indices from high to low was wind speed, temperature and relative humidity, which the accuracy rates are 73.4%, 78.4%, 67.1% respectively, and the predictability of wind speed and temperature was high in the east and low in the west and the predictability of relative humidity is high in the south and low in the north; (4) in order to improve the level of prediction, it was necessary to correct the different forecast variables in different region for the predictabilities of temperature, wind speed and relative humidity were not totally the same in different areas.