Mesoscale modelling for tropical cyclone forecasting over the North Indian Ocean

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Abstract

The coastal regions of Bay of Bengal (BoB) and Arabian Sea (AS) experience severe damage due to landfalling tropical cyclones (TCs). The synoptic and statistical methods have limitations in predicting the track and intensity beyond 24 hours (Mohanty and Gupta, 1997). However, the numerical forecast using dynamical models can provide better forecast guidance for genesis, intensity and movement of TCs up to 72 hours (Rao and Bhaskar Rao, 2003; Mandal et al., 2004; Osuri et al., 2012a) and helps in the disaster mitigation planning. Hence, it is necessary to evaluate the comprehensive performance of such dynamical models in track and intensity forecasts of TCs. Davis et al. (2008) and Osuri et al. (2012a) showed that real-time TC forecast of ARW (Advanced Research Weather Research and Forecasting) model is generally competitive with, and occasionally superior to, other operational forecasts for track and intensity of landfalling TCs over Atlantic and BoB respectively. Wang et al. (2006) demonstrated that error growth in ARW model forecasts is noticeably slow as the forecast length increases.

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APA

Mohanty, U. C., Osuri, K. K., & Pattanayak, S. (2014). Mesoscale modelling for tropical cyclone forecasting over the North Indian Ocean. In Monitoring and Prediction of Tropical Cyclones in the Indian Ocean and Climate Change (pp. 274–286). Springer Netherlands. https://doi.org/10.1007/978-94-007-7720-0_24

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