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Impact of physics parameterization and 3DVAR data assimilation on prediction of tropical cyclones in the Bay of Bengal region

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  • R. Chandrasekar
  • C. Balaji

Abstract

This study focuses on the sensitivity of tropical cyclones (TCs) simulations to physics parametrization scheme for TCs in the Bay of Bengal (BOB). The goal of this study was to arrive at the optimum set of schemes for the BOB region to increase forecast skill. Four TCs, namely Khaimuk, Laila, Jal and Thane have been simulated through the weather research and forecasting (WRF) model with all the physics parametrization schemes available in WRF, and the optimum set of schemes is arrived at. The analysis shows the cumulus, microphysics and planetary boundary layer parameterizations exert a very significant influence on the TC simulations than land surface, short-wave radiation and long-wave radiation parameterizations. With this optimum set of physics schemes, the impact of assimilation of National Centers for Environmental Prediction Automatic Data Processing upper air observations data in the TC simulations has been studied by using three-dimensional variational (3DVAR) data assimilation technique. The control run (without assimilation) and the 3DVAR-simulated tracks and maximum sustained wind speed have been compared with the Joint Typhoon Warning Center observed tracks and wind data. The model-simulated precipitation is validated with Tropical Rainfall Measuring Mission 2A12 surface rain rate and 3B42 daily accumulated rain data. Bias score and equitable threat score have been evaluated for both instantaneous rain rate and 72-h accumulated rain. Copyright Springer Science+Business Media Dordrecht 2016

Suggested Citation

  • R. Chandrasekar & C. Balaji, 2016. "Impact of physics parameterization and 3DVAR data assimilation on prediction of tropical cyclones in the Bay of Bengal region," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 80(1), pages 223-247, January.
    • Handle: RePEc:spr:nathaz:v:80:y:2016:i:1:p:223-247
    DOI: 10.1007/s11069-015-1966-5
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    References listed on IDEAS

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    1. C. Srinivas & V. Yesubabu & K. Hari Prasad & B. Venkatraman & S. Ramakrishna, 2012. "Numerical simulation of cyclonic storms FANOOS, NARGIS with assimilation of conventional and satellite observations using 3-DVAR," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 63(2), pages 867-889, September.
    2. Krishna Osuri & U. Mohanty & A. Routray & Makarand Kulkarni & M. Mohapatra, 2012. "Customization of WRF-ARW model with physical parameterization schemes for the simulation of tropical cyclones over North Indian Ocean," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 63(3), pages 1337-1359, September.
    3. Medha Deshpande & S. Pattnaik & P. Salvekar, 2010. "Impact of physical parameterization schemes on numerical simulation of super cyclone Gonu," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 55(2), pages 211-231, November.
    4. D. Rao & Dasari Prasad, 2007. "Sensitivity of tropical cyclone intensification to boundary layer and convective processes," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 41(3), pages 429-445, June.
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