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Sensitivity of tropical cyclone intensification to boundary layer and convective processes

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  • D. Rao
  • Dasari Prasad

Abstract

This study examines the role of the parameterization of convection, planetary boundary layer (PBL) and explicit moisture processes on tropical cyclone intensification. A high-resolution mesoscale model, National Center for Atmospheric Research (NCAR) model MM5, with two interactive nested domains at resolutions 90 km and 30 km was used to simulate the Orissa Super cyclone, the most intense Indian cyclone of the past century. The initial fields and time-varying boundary variables and sea surface temperatures were taken from the National Centers for Environmental Prediction (NCEP) (FNL) one-degree data set. Three categories of sensitivity experiments were conducted to examine the various schemes of PBL, convection and explicit moisture processes. The results show that the PBL processes play crucial roles in determining the intensity of the cyclone and that the scheme of Mellor-Yamada (MY) produces the strongest cyclone. The combination of the parameterization schemes of MY for planetary boundary layer, Kain-Fritsch2 for convection and Mixed-Phase for explicit moisture produced the best simulation in terms of intensity and track. The simulated cyclone produced a minimum sea level pressure of 930 hPa and a maximum wind of 65 m s −1 as well as all of the characteristics of a mature tropical cyclone with an eye and eye-wall along with a warm core structure. The model-simulated precipitation intensity and distribution were in good agreement with the observations. The ensemble mean of all 12 experiments produced reasonable intensity and the best track. Copyright Springer Science+Business Media, Inc. 2007

Suggested Citation

  • 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.
  • Handle: RePEc:spr:nathaz:v:41:y:2007:i:3:p:429-445
    DOI: 10.1007/s11069-006-9052-7
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    Citations

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    Cited by:

    1. 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.
    2. S. Fadnavis & Medha Deshpande & Sachin Ghude & P. Ernest Raj, 2014. "Simulation of severe thunder storm event: a case study over Pune, India," 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. 72(2), pages 927-943, June.
    3. V. Yesubabu & C. Srinivas & S. Ramakrishna & K. Hari Prasad, 2014. "Impact of period and timescale of FDDA analysis nudging on the numerical simulation of tropical cyclones in the Bay of Bengal," 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. 74(3), pages 2109-2128, December.
    4. Shumin Chen & Yu-Kun Qian & Shiqiu Peng, 2015. "Effects of various combinations of boundary layer schemes and microphysics schemes on the track forecasts of tropical cyclones over the South China Sea," 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. 78(1), pages 61-74, August.
    5. D. Bala Subrahamanyam & Radhika Ramachandran & K. Nalini & Freddy P. Paul & S. Roshny, 2019. "Performance evaluation of COSMO numerical weather prediction model in prediction of OCKHI: one of the rarest very severe cyclonic storms over the Arabian Sea—a case study," 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. 96(1), pages 431-459, March.
    6. P. Raju & Jayaraman Potty & U. Mohanty, 2012. "Prediction of severe tropical cyclones over the Bay of Bengal during 2007–2010 using high-resolution mesoscale model," 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 1361-1374, September.
    7. 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.
    8. C. Srinivas & V. Yesubabu & K. Hariprasad & S. Ramakrishna & B. Venkatraman, 2013. "Real-time prediction of a severe cyclone ‘Jal’ over Bay of Bengal using a high-resolution mesoscale model WRF (ARW)," 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. 65(1), pages 331-357, January.
    9. 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.
    10. Saji Mohandas & Raghavendra Ashrit, 2014. "Sensitivity of different convective parameterization schemes on tropical cyclone prediction using a mesoscale model," 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. 73(2), pages 213-235, September.
    11. 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.
    12. Dodla Rao & Desamsetti Srinivas, 2014. "Multi-Physics ensemble prediction of tropical cyclone movement over Bay of Bengal," 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. 70(1), pages 883-902, January.
    13. Sanjeev Singh & C. Kishtawal & P. Pal, 2012. "Track prediction of Indian Ocean cyclones using Lagrangian advection model," 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. 62(3), pages 745-778, July.

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