Using Doppler LIDAR data,three methods are implemented to forecast the wind field around Hong Kong International Airport（HKIA）.The methods are grey theory,BP neural network and triple exponential smoothing.On one hand,PPI scan data which could roughly represent the wind conditions near the arrival and departure corridors are employed to forecast the wind velocity of every point in the whole wind field.On the other hand,glide scan data are employed to obtain precise forecast of the headwind profiles,which could vividly illustrate the transient and sporadic nature of terrain-induced wind-shear.With the forecasting results of wind field,pilots can get wind-shear alert in advance,so they will have more time to deal with it.Experimental results show that:（1） the performance of triple exponential smoothing degenerates with prolonging time;（2） both grey theory and BP neural network can adapt to wind forecasting with long period,even if the wind field fluctuates fast;（3） the forecasting precision of grey theory is better than that of BP neural network.