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During recent years, an increase in the intensity of pre‐monsoon tropical cyclones (TCs) is observed over the Arabian Sea. This study suggests that this increase is due to epochal variability in the intensity of TCs and is associated with epochal variability in the storm‐ambient vertical wind shear and tropical cyclone heat potential (TCHP). There is a significant increase (0.53 kJ cm−2 year−1) of TCHP during recent years. The warmer upper ocean helps TCs to sustain or increase their intensity by an uninterrupted supply of sensible and latent heat fluxes from the ocean surface to the atmosphere.
A soft‐computing cyclone intensity prediction scheme (SCIPS) is introduced using an artificial neural network (ANN) approach and adding ocean heat content, as an additional predictor to the normally used atmospheric parameters, to predict tropical cyclone intensity change in the western north Pacific Ocean. We used 1997–2004 data to develop and validate this scheme. The ANN‐based estimations have been compared with observations and estimations using the multiple linear regression (MLR). SCIPS performance improves upon MLR as the lead hour increases from 12 to 120 h and also for high intensifying cyclones.
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