ALBERT

Description:    In this paper, impact of Indian Doppler Weather Radar (DWR) data, i.e., reflectivity ( Z ), radial velocity (Vr) data individually and in combination has been examined for simulation of mesoscale features of a land-falling cyclone with Advance Regional Prediction System (ARPS) Model at 9-km horizontal resolution. The radial velocity and reflectivity observations from DWR station, Chennai (lat. 13.0°N and long. 80.0°E), are assimilated using the ARPS Data Assimilation System (ADAS) and cloud analysis scheme of the model. The case selected for this study is the Bay of Bengal tropical cyclone NISHA of 27–28 November 2008. The study shows that the ARPS model with the assimilation of radial wind and reflectivity observations of DWR, Chennai, could simulate mesoscale characteristics, such as number of cells, spiral rain band structure, location of the center and strengthening of the lower tropospheric winds associated with the land-falling cyclone NISHA. The evolution of 850 hPa wind field super-imposed vorticity reveals that the forecast is improved in terms of the magnitude and direction of lower tropospheric wind, time, and location of cyclone in the experiment when both radial wind and reflectivity observations are used. With the assimilation of both radial wind and reflectivity observations, model could reproduce the rainfall pattern in a more realistic way. The results of this study are found to be very promising toward improving the short-range mesoscale forecasts. Content Type Journal Article Pages 1-17 DOI 10.1007/s11069-011-9835-3 Authors Kuldeep Srivastava, India Meteorological Department, Lodi Road, New Delhi, 110003 India Rashmi Bhardwaj, Guru Gobind Singh Indraprastha University, Kashmere Gate, Delhi, 110403 India S. K. Roy Bhowmik, India Meteorological Department, Lodi Road, New Delhi, 110003 India Journal Natural Hazards Online ISSN 1573-0840 Print ISSN 0921-030X