A Study on Simulation of Heavy Rainfall Events Over Indian Region with ARW-3DVAR Modeling System |
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| Authors: | U C Mohanty A Routray Krishna K Osuri S Kiran Prasad |
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| Institution: | (1) Centre for Atmospheric Sciences, Indian Institute of Technology Delhi, Hauz Khas, New Delhi, 110016, India;(2) National Centre for Medium Range Weather Forecasting, A-50, Sector-62, Noida, India |
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| Abstract: | An attempt is made to evaluate the impact of the three dimensional variational (3DVAR) data assimilation within the Weather
Research Forecasting (WRF) modeling system to simulate two heavy rainfall events which occured on 26–27 July 2005 and 27–30
July 2006. During the 26–27 July 2005 event, the unprecedented localized intense rainfall 90–100 cm was recorded over the
northeast parts of Mumbai city; however, southern parts received only 10 cm. Model simulation with the data assimilation experiment
is reasonably well predicted for the rainfall intensity (800 mm) in 24 h and with accurate location over Mumbai agreeing with
observation. Divergence, vorticity, vertical velocity and moisture parameters are evaluated during the various stages of the
event. It is noticed that maximum convergence and vorticity during the mature stage; at the same time the vertical velocity
also follows a similar trend during the period in the assimilation experiment. Vorticity budget terms over the location of
heavy rainfall revealed that the contribution of the positive tilting term produced positive vorticity which triggered the
convection and negative contribution to vorticity from the tilting term to precede the dissipation of the system. Model simulations
from the second rain event, the off-shore trough at sea level along the west coast of India, is well represented after assimilation
of observations during day-1 and day-2 as compared to the control simulations; the orientation of the off-shore trough is
well matched with that of the observed. The intensity and spatial distribution of the rainfall has considerably improved in
the assimilation simulation. The statistical skill scores also revealed that the precipitation forecast during the period
has appreciably improved due to assimilation of observations. The results of this study indicate a positive impact of the
3DVAR assimilation on the simulation of heavy rainfall events. |
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