Data Assimilation and Simulation of Mesoscale Convective Systems Associated with Squalls
Mohan Kumar Das1,2, Md. Abdul Mannan Chowdhury
2 and Someshwar Das
3, (1)SAARC Meteorological Research Centre (SMRC), Dhaka, Bangladesh, (2)Jahangirnagar University, Savar, Bangladesh, (3)India Meteorological Department, New Delhi, India
Contact First Author: Mohan Kumar Das; mohan28feb@yahoo.com
English Abstract:
Improving the simulation of the squall events is important as such events routinely result in strong gusty wind, hails, rain and significant loss of life and property over Bangladesh, Indian eastern, northeastern region and neighbourhood. Performance of the mesoscale models is sensitive to the quality of initial conditions. This study deals the improvement of numerical simulation of squall events during pre-monsoon season with improved initial condition through mesoscale data assimilation system. Advanced Research Weather Research and Forecasting model (WRF ARW) along with three dimensional variational (3DVar) data assimilation (DA) technique are used to improve the simulation of these intense events. Pre-monsoon squalls and tornado are studied employing observations from ground based radar, TRMM and synoptic stations. Subsequently, an attempt is made to simulate the storms using WRF model at 4 km and 1 km horizontal resolution, and 40 vertical levels.
Several sensitivity experiments were conducted with different combinations of cloud microphysics schemes, planetary boundary layer schemes and cumulus parameterization schemes to examine the RMSE of forecasts.
The event Brahmanbaria tornado of 22 March 2013 is simulated by using the WRF model at 1 km horizontal resolution based on 6 hourly FNL re-analysis data and boundary conditions of NCEP. Results show that while there are differences of 30 minutes to 1 hour between the observed and simulated time of the storm.
In this study, DWR observations (radial winds and reflectivity) of Bangladesh Meteorological Department are used for the squall events in order to update the initial and boundary conditions through 3DVar technique within the WRF ARW. The intensity of the events, generated from the simulations is also compared with the available meteorological observations in order to evaluate the model performance.
The intensity and location of the MCSs are well represented in model initial time as well as in simulations after assimilation of DWR data. The time series of minimum SLP and maximum surface wind show the intensity and structure of the MCSs are better simulated due to DWR DA. The assimilation experiments are able to capture the location and amount of rainfall over Bangladesh reasonably well as compared to without mesoscale DA simulations.
