Prediction of Landfall Intensity, Location, and Time of a Tropical Cyclone

TC is characterised by warm core, and a low and availability of huge data, new models using Artificial pressure system with a large vortex in the atmosphere. TC Neural Networks (ANNs) have been increasingly used to brings strong winds, heavy precipitation and high tides in forecast track and intensity of cyclones (Leroux et al. 2018; coastal areas and resulted in huge economic and human loss. Alemany et al. 2018; Giffard-Roisin et al. 2020; Moradi Kordmahalleh, Over the years, many destructive TCs have originated in the Gorji Sefidmazgi, and Homaifar 2016). North Indian Ocean (NIO), consisting of the Bay of Bengal The most important prediction about a TC is its arrival at and the Arabian Sea. In 2008, Nargis, one of the disastrous land, known as landfall of a cyclone. The accurate prediction TC in recent times, originated in the Bay of Bengal and resulted about the location and time of the landfall, and intensity of in 13,800 casualties alone in Myanmar and caused the cyclone at the landfall will hugely help authorities to take US$15.4 billion economic loss (Fritz et al. 2009). In 2018, preventive measures and reduce material and human loss. In Fani cyclone caused 89 causalities in India and Bangladesh, this work, we attempt to predict intensity, location, and time and US$9.1 billion economic loss (Kumar, Lal, and Kumar of the landfall of a TC at any instance of time during the 2020).