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Simulation Of Land Falling Tropical Cyclones Over The Bay Of Bengal Using Weather Research And Forecasting (WRF) Model | 4464
ISSN: 2157-7625

Journal of Ecosystem & Ecography
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Simulation of land falling tropical cyclones over the Bay of Bengal using Weather Research and Forecasting (WRF) model

International Conference onBiodiversity & Sustainable Energy Development

Kuvar Satya Singh

Posters: J Ecosyst Ecogr

DOI: 10.4172/2157-7625.S1.009

Abstract
This study examines the real-time prediction of three land-falling tropical cyclones (Aila, Laila and Jal) over the Bay of Bengal using the Advanced Research core of Weather Research and Forecasting (WRF) (ARW) model. Coupling of the ARW model to a simple mixed layer ocean model, derived from the WRF model is also investigated. A sensitivity study is conducted with two planetary boundary layer (PBL) parameterization schemes (Yonsei University (YSU), and Mellor-Yamada Nakanishi and Niino closure 2.5 (MYNN)) with and without one-dimensional mixed layer ocean model. Four numerical experiments are conducted for each cyclone case to evaluate performance of the model on the simulated track and intensity of Bay of Bengal cyclones. The model is integrated with two-way nested domains with horizontal resolution at 27 Km and 9 Km. The meteorological parameters for the initial and lateral boundary conditions are derived from the National Centers for Environmental Prediction (NCEP) Final analysis(FNL) at 1?x1? resolutions. Sea surface temperatures are derived from the high-resolution real-time global sea surface temperature (RTG_SST) at 0.083?x0.083? resolution analyses from NCEP. The results indicate that the simulations are sensitive to the choice of PBL parameterization schemes in both with and without one-dimensional mixed layer model. It is found that the Mellor-Yamada Nakanishi and Niino (MYNN) PBL scheme provides a better prediction of intensity, track, and rainfall consistently using one-dimensional mixed layer ocean model. The average root mean square error (RMSE) of intensity (8 hPa in CSLP and 7 m/s in surface wind), mean track, and landfall errors is found to be least with MYNN PBL schemes. The intensity and distribution of rainfall are well simulated by the model as well as comparable with the TRMM estimates.
Biography
Kuvar Satya Singh is a Ph.D. student from Indian Institute of Technology Kharagpur at the Centre of Oceans, Atmosphere and Land Sciences (CORAL). His broad area of research is mesoscale modeling of tropical cyclones over Bay of Bengal using weather research and forecasting (WRF) model
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