登陆台风站点大风预报的人工神经网络方法

The Artificial Neural Network Method on the Station Wind in Landfall Typhoon

利用数值预报格点资料预报登陆台风影响时,沿海地区站点风的预报是各站点的定时二分钟风向风速。通过对MICAPS站点资料进行整合、分析,选取了沿海地区400多个资料比较齐全的站点和海岛站作为预报站点。用NCEP再分析场的格点资料做相关性分析,选定9个预报因子。运用BP网络对每个站点分别建立纬向风和经向风人工神经网络模型,拟合风速的绝对值误差是1.3 m·s^(-1)。独立样本检验,风速绝对误差在2 m·s^(-1)以内。

The grid data of numerical weather prediction（NWP） are used to forecast the 2-min wind velocity and direction at fixed time for the station affected by typhoon.Integrating and analyzing the station data of MICAPS,we select the relatively complete observational materials of more than 400 stations in coastal regions and islands as the raw data for prediction.Meanwhile,the nine suitable forecast factors are fixed by the correlation analysis with the NCEP reanalysis grid data.Based on the back propagation（BP） network, latitudinal and longitudinal artificial neural network models are developed for each station respectively. The absolute error of fitting wind velocity is 1.3 m·s^（-1）.The test of independent samples shows that the absolute error of wind velocity is less than 2.0 m·s^（-1）.This is a statistical interpretation of NWP,and it can pre-estimate the wind velocity effectively in landfall typhoon-affected areas.