Impact of Variational Data Assimilation for Simulating Tropical Cyclones over Bay of Bengal Using WRF-ARW

Abstract

Tropical cyclones, one of the most destructive of all the natural disasters, are capable of causing loss of life and extensive damage to property. The Bay of Bengal is a potentially energetic region for the development of cyclonic storms and about 7% of the global annual tropical storms form over this region with two cyclone seasons in a year. Tropical cyclones have great socio-economic concern for the Indian subcontinent. Precise forecasting of tropical cyclone intensity and track are important for the countries bordering the Bay of Bengal, especially India, Bangladesh and Myanmar due to significant socio-economic impact. There has been remarkable improvement in forecasting of the tropical cyclones with the development of high resolution atmospheric models and the global forecasting systems such as the National Centers for Environmental Predictions (NCEP) Global Forecasting System (GFS). Assimilation of available observations has been considered to be very important for accurate description of initial conditions in numerical models (Park and Zupanski, 2003; Navon, 2009; Pu et al., 2009). In particular, assimilation methods like variational approach has the additional advantage of assimilating observations by satisfying model dynamic and thermodynamic constraints through a set of independent balance equations (in 3DVAR) (Courtier et al., 1998).