Maximum Sustained Wind Prediction of Storm Surge in Bay of Bengal

Abstract

Most of the countries around the Bay of Bengal are threatened by storm surges associated with severe tropical cyclones. The destruction along the coastal regions of India, Bangladesh, and Myanmar are serious due to the storm surge. To mitigate the impacts of tropical storm, the prediction of storm surge need to be accurate. Traditional process-based numerical models have the limitation of high computational demands to make timely forecast and deterministic numerical models are strongly dependent on accurate meteorological input to predict storm surge. In this work, a Multilayer perceptron (MLP) and a Radial Basic Function Network (RBFN) used to predict the maximum sustained wind speed in knots (VMAX) of storm in coastal areas of Bay of Bengal. The ANN network model provides fast, real-time storm surge estimates at Bay of Bengal. Simulated and historical storm data are collected for model training and testing, respectively. North India Ocean Best Track Data from Joint Typhoon Warning Center (JTWC) used to perform experiments. The result of MLP is predicted VMAX value closer than in RBFN prediction.