Forecasting North Indian Ocean Tropical Cyclone Intensity

India is prone to tropical cyclones annually, originating from the North Indian Ocean basin. Tropical cyclones are destructive and sudden natural occurrences that annually wreak havoc by taking a huge toll on human lives and property. This engenders a need for accurately forecasting the scale of such mass-destructive events, to provide us with enough time to take precautionary measures that can reduce the death toll and minimize costs. Using the CyINSAT dataset, which gives a multimodal and temporal resolution for TCs occurred from 2014 to 2022, this paper employs and compares multiple techniques to solve the wind speed forecasting issue. All models involve recurrent networks along with image feature extractors, which are used together to predict the next wind speeds from a sequence of images. The architectural differences between these models mainly focus on the nuances involved in handling the current wind speed. The proposed architecture gives higher importance to the currently recorded wind speeds and performs significantly better than the baseline models. It successfully obtained an RMSE of 6.31, MAE of 0.093 and MAPE of 4.53.