Simulation of tropical cyclones over the Bay of Bengal during 1999-2013 : Impact of physical parameterization schemes

Abstract

Tropical Cyclone (TC) is one of the most devastating and deadly weather phenomena and causes loss of life and property. The Bay of Bengal (BoB) is a potentially energetic region for the development of cyclonic storms, accounting about 6% of the global annual total number of cyclonic storms. Accurate prediction of these storms is essential to avoid loss of lives and damage to properties. In this regard, the reduction of errors associated with the track and intensity forecast of the TCs is an important aspect to disseminate more reliable information to the disaster management. The present study examined the performance of Advanced Research Weather Research and Forecasting (WRF-ARW) model for the simulation of track and intensity of TCs over BoB during 1999-2013. The numerical simulations were carried out for 38-cyclones (during 1999-2013) using different microphysical parameterization (MP), cumulus parameterization (CP) and planetary boundary layer (PBL) schemes of the WRF-ARW model. The total 1133 simulations were performed by using 11 combinations with four MPs [Lin et al. (LIN), Ferrier (new Eta) (FERR), WSM 6-class Scheme graupel scheme (WSM6) and Thompson (THOMP)], four CPs [Kain-Fritsch (KF), Betts-Miller-Janjic (BMJ), Grell-Devenyi (GD) and New Grell Scheme (NG)] and three PBLs (Yonsei University scheme (YSU), Mellor-Yamada-Janjic (Eta) TKE (MYJ) and Asymmetrical Convective Model version 2 (ACM2)] to identify the best logical combination of these schemes to predict the track and intensity of TCs over BoB. The best combination of CP and PBL schemes were more influenced the simulations of intensity and track of the cyclones compared to the MP schemes. Further, the simulations were conducted for intense storms with different initial conditions and suggested that the combination of KF + LIN + YSU provided better simulations of the storms for 72h over the BoB and also observed the decreased track error from 1999 to 2013 cyclones. This clearly indicated that the improvement in the initial conditions and parameterization schemes of the WRF-ARW model. This study is very useful for the cyclone warning centers, disaster management centers, real-time governance system and researchers to provide better management for coastal community during the cyclone events.