The influence of environmental factors on the intensity of typhoon Mirinae in the South China Sea and its forecast analysis

Abstract

The rapidly intensifying typhoon Mirinae (1603) originated in the South China Sea (SCS) has been selected to analyze the high and low level circulations, vertical wind shear (VWS) and ocean conditions in and around the SCS when Mirinae was strengthening. Further, the fuzzy neural network (FNN) ensemble model has been developed for 24-hour intensity prediction based on climatology and persistence factors and dynamic factors of numerical prediction products as potential predictors. The underlying conditions were favorable for Mirinae, however, it did not be intensified to a strong typhoon because of the weak high and low level circulations and strong VWS. For the FNN ensemble prediction model input, predictors were selected by employing both a novel stepwise variable selection algorithm based on the k-nearest mutual information estimation and Laplacian Eigenmaps of manifold learning, and then the main prediction information hidden in high dimensional data set was extracted with low-dimensional structure. Results show that, the predictions of the new model are stable and reliable, and the forecast accuracy is high, providing a new forecasting tool and modeling method for the objective forecast of typhoon intensity.