Prediction of Low-level Wind Shear for the Winter in the Jeju Area using Recurrent Neural Network
Ensemble verification and prediction of low-level wind shear (LLWS) are an important matter for airplane landing and management. In this study, we compared the prediction performance of LLWS forecasts of ensemble mean, multiple regression model and long short-term memory (LSTM), which belong to the family of recurrent neural network based on the grid points over the Jeju area. The prediction skills of methods were compared by mean absolute error. We found that the prediction skills of forecasts of LSTM were better than the bias-corrected forecasts in terms of deterministic prediction.