Intensity Prediction of Tropical Cyclones using Long Short-Term Memory Network

The weather-related forecast is one of the difficult problems to solve due to the complex interplay between various cause factors. Accurate tropical cyclone intensity prediction is one such problem that has huge importance due to its vast social and economic impact. Cyclones are one of the devastating natural phenomena that frequently occur in tropical regions. Being a tropical region, Indian coastal regions are frequently affected by tropical cyclones [1] that originate into the Arabian Sea (AS) and Bay of Bengal (BOB), which are parts of the North Indian Ocean (NIO). With the increasing frequency of cyclones in NIO [2], it becomes more crucial to develop a model that can forecast the intensity of a cyclone for a longer period of time by observing the cyclone only for a small period of time. Various statistical and numerical methods have been developed to predict the intensity of cyclones [3-7] but all these methods lack effectiveness in terms of accuracy and computation time.