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Chennai, India

Thampi S.B.,Cyclone Detection Radar | Reddy Y.K.,Meteorological Centres | Venkateswarlu S.,Cyclone Detection Radar
Meteorology and Atmospheric Physics

This paper demonstrates the usefulness of Indian Doppler Weather Radar (DWR) data for nowcasting applications, and assimilation into a mesoscale Numerical Weather Prediction (NWP) model. Warning Decision Support System Integrated Information (WDSS-II) developed by National Severe Storm Laboratory (NSSL) and Advanced Regional Prediction System (ARPS) developed at the Centre for Analysis and Prediction, University of Oklahoma are used for this purpose. The study reveals that the WDSS-II software is capable of detecting and removing anomalous propagation echoes from the Indian DWR data. The software can be used to track storm cells and mesocyclones through successive scans. Radar reflectivity mosaics are created for a land-falling tropical cyclone-Khaimuk of 14 November 2008 over the Bay of Bengal using observations from three DWR stations, namely, Visakhapatnam, Machilipatnam and Chennai. Assimilation of the quality-controlled radar data (DWR, Chennai) of the WDSS-II software in a very high-resolution NWP model (ARPS) has a positive impact for improving mesoscale prediction. This has been demonstrated for a land-falling tropical cyclone Nisha of 27 November 2008 of Tamil Nadu coast. This paper also discusses the optimum scan strategy and networking considerations. This work illustrates an important step of transforming research to operation. © 2011 Springer-Verlag. Source

Srivastava K.,Lodi Road | Roy Bhowmik S.K.,Lodi Road | Sen Roy S.,Lodi Road | Thampi S.B.,Cyclone Detection Radar | Reddy Y.K.,Cyclone Detection Radar

In this paper, impact of assimilation of Indian Doppler Weather Radar (DWR) data has been assessed by numerical weather prediction system (ARPS) at 9 km horizontal resolution. The radial velocity and reflectivity observations from two DWR stations namely, Chennai (Lat. 13.0° N and Long. 80.0° E) and Machilipatnam (Lat. 16.5° N and Long. 81.3° E) are assimilated using the ARPS Data Assimilation System (ADAS) and cloud analysis scheme of the model. Two case studies selected are 1) Bay of Bengal Tropical Cyclone Ogni of October 2006 and 2) A local thunderstorm event of 5 June 2009 over the southeast parts of India. The study shows that the model at 9 km resolution with the assimilation of DWR observations (Chennai) could simulate mesoscale features such as: number of cells, spiral rain band structure, location of the center, strengthening of the lower tropospheric winds and northerly movement of the small size cyclonic storm in the analysis as well as in the forecasts. The model with DWR assimilation could retain the intensity of the cyclone up to 6 hours of forecasts. Thereafter the cyclone showed a weakening trend when it was drifting away from the radar site. In case of thunderstorm, the model with the DWR assimilation could capture the convective precipitation in the right location. The DWR assimilation could realistically reproduce the development process and south-westward movement of thunderstorm cells. Source

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