A Dynamical Statistical Model for Prediction of a Tropical Cyclone

Abstract

A dynamical statistical method is applied for operational forecasting of the Bay of Bengal tropical cyclone "Nargis" of April-May 2008. The method consists of three forecast components, namely (a) analysis of Genesis Potential Parameter (GPP) and maximum potential intensity, (b) track prediction, and (c) 12 hourly intensity prediction for forecasts up to 72 hours. The results of the study showed that GPP could provide necessary predictive signal at early stages of development on the further intensification of the low pressure system into a tropical cyclone. The landfall forecast position errors by different operational numerical models (NWP) showed landfall position errors ranging from 10 km to 150 km and landfall time error ranges from 6 hours early to 6 hours delay. The dynamical statistical model is capable to provide 12 hourly nearly realistic intensity forecasts up to 60 hours of forecast.

Real-Time Track Prediction of Tropical Cyclones over the North Indian Ocean Using the ARW Model

“…The current TC operational model in use at the India Meteorological Department (IMD), New Delhi, is the Quasi-Lagrangian Model (QLM), apart from global and regional models like the Global Forecast System (GFS) and the ARW. The QLM has shown little skill over the NIO Basin because it runs at 40-km horizontal resolution with 16 vertical levels (see online at http://www.imd.gov.in/section/ nhac/dynamic/RSMC-2011.pdf; Roy Bhowmik and Kotal 2010;Kotal and Roy Bhowmik 2011). As compared with other operational centers, NCEP in the United States uses the high-resolution hurricane WRF (HWRF) model, which is based on the NMM dynamical core of WRF; operating at cloud-permitting (3 km) resolution, it has achieved significant skill in hurricane track and intensity forecasts (Gopalakrishnan et al 2006(Gopalakrishnan et al , 2012Tallapragada et al 2008) over the Atlantic and Pacific Ocean basins.…”