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In-Depth Information
Assimilation of Doppler Weather
Radar Data in WRF Model for
Numerical Simulation of Structure
of Cyclone Aila (2009) of the Bay of
Bengal at the Time of Landfall
Kuldeep Srivastava*, Rashmi Bhardwaj 1
and S.K. Roy Bhowmik
India Meteorological Department, Lodi Road, New Delhi - 110003, India
1 Guru Gobind Singh Indraprastha University, Dwarka, New Delhi
*e-mail: kuldeep.nhac@gmail.com
1. Introduction
For effective forecasting of tropical cyclone (TC) it is very important to have
accurate initial structure of cyclone in numerical models. Assimilation of local
data such as Doppler Weather Radar (DWR) data in numerical weather
prediction (NWP) models has potential to improve the initial and boundary
condition for the prediction of land falling cyclones. Xiao et al. (2005, 2007)
carried out study on the assimilation of DWR radial wind and reflectivity into
NWP model using the 3-dimensional variational data assimilation (3DVAR)
system for the heavy rainfall events. A number of case studies on the positive
impact of DWR radial wind and reflectivity observations in the assimilation
cycle of Advanced Regional Prediction System (ARPS) were documented by
Xue et al. (2003). Kun Zhao and Ming Xue (2009) studied the impact of radar
data on the analysis and prediction of the structure, intensity and track of land
falling Hurricane Ike-2008, at a cloud-resolving resolution. The hurricane
landfall, intensification and weakening during the simulation period are well
captured by assimilating both airborne Doppler radar reflectivity and wind
data (Zhaoxia et al., 2009). The Bratseth successive correction technique and
cloud analysis are part of ARPS Model developed by Center for Analysis and
Prediction of Storms (CAPS), Oklahoma University, USA (Bratseth, 1986;
Brewster, 1996). The ARPS data assimilation system (ADAS) and cloud
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