Prediction of Track of Super Cyclone Amphan using WRF-ARW Model
DOI:
https://doi.org/10.3329/dujees.v10i2.57513Keywords:
Cyclone track, Bay of Bengal, Prediction, WRF-ARW, Landfall time, Landfall positionAbstract
An attempt has been made to study the prediction of the track of Super Cyclone (SuC) Amphan that formed on 13 May over Southeast Bay of Bengal (BoB) and made landfall to West Bengal-Bangladesh Coast on 20 May 2020 using Advanced Research WRF (ARW) dynamics of Weather Research and Forecasting (WRF) model. Model integration has been carried out using two-way interactive nesting domains with resolutions of 27 km for domain 1 and 9 km for domain 2 respectively covering the Bay of Bengal. Simulations are performed at an interval of 6 hours with ICs using the National Centre for Environmental Prediction (NCEP) global forecast system (GFS) 0.25° analysis and forecasts. To understand the applicability of the model in predicting the track along with landfall position and landfall time, nine real-time numerical forecasts have been carried out with model simulation starting at 00 UTC of 13 May, 14 May, 15 May, 16 May, 17 May, 18 May, 19 May, 20 May and 21 May 2020. The experiments with initial time on 16 May, 17 May, 18 May, 19 May, and 20 May 2020 have produced the best performance for the track and intensity prediction which are comparable to those provided by Bangladesh Meteorological Department (BMD) and Regional Specialized Meteorological Centre (RSMC). The tracks are produced based on the distribution of sea level pressure and vorticity. The model shows that the track prediction accuracy increases as the lead time decreases with the updated ICs. The results obtained from the model are in good agreement with the reported data. The experiment of SuCAmphan produced better track and intensity predictions with lead-time of 144, 120, 96, 48, and 24 hours. The results demonstrate that the model is capable to produce the track of SuCAmphan with reasonable accuracy.
The Dhaka University Journal of Earth and Environmental Sciences, Vol. 10(2), 2021, P 35-42
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