S B Thampi
Articles written in Journal of Earth System Science
Volume 116 Issue 4 August 2007 pp 275-304
Obtaining an accurate initial state is recognized as one of the biggest challenges in accurate model prediction of convective events. This work is the first attempt in utilizing the India Meteorological Department (IMD) Doppler radar data in a numerical model for the prediction of mesoscale convective complexes around Chennai and Kolkata. Three strong convective events both over Chennai and Kolkata have been considered for the present study. The simulation experiments have been carried out using fifth-generation Pennsylvania State University–National Center for Atmospheric Research (PSU–NCAR) mesoscale model (MM5) version 3.5.6. The variational data assimilation approach is one of the most promising tools available for directly assimilating the mesoscale observations in order to improve the initial state. The horizontal wind derived from the DWR has been used alongwith other conventional and non-conventional data in the assimilation system. The preliminary results from the three dimensional variational (3DVAR) experiments are encouraging. The simulated rainfall has also been compared with that derived from the Tropical Rainfall Measuring Mission (TRMM) satellite. The encouraging result from this study can be the basis for further investigation of the direct assimilation of radar reflectivity data in 3DVAR system. The present study indicates that Doppler radar data assimilation improves the initial field and enhances the Quantitative Precipitation Forecasting (QPF) skill.
Volume 119 Issue 2 April 2010 pp 183-199
In this paper, we describe offline analysis of Indian Doppler Weather Radar (DWR) data from cyclone Ogni using a suite of radar algorithms as implemented on NEXRAD and the advanced algorithms developed jointly by the National Severe Storms Laboratory (NSSL) and the University of Oklahoma. We demonstrate the applicability of the various algorithms to Indian radar data, the improvement in the quality control and evaluate the benefit of nowcasting capabilities in Indian conditions. New information about the tropical cyclone structure, as derived from application of the algorithms is also discussed in this study.
Finally, we suggest improvements that could be made to the Indian data collection strategies, networking and real-time analysis. Since this is the first study of its kind to process and utilize DWR data in a tropical climate, the suggestions on real-time analysis and data collection strategies made in this paper, would in many cases, be beneficial to other countries embarking on DWR network modernization programs.