Abstract
Tropical cyclones (TCs) are highly disastrous weather phenomena characterised with extreme winds, heavy precipitation and storm surges at landfall along coastal lands. Accurate prediction of the TC formation, movement and intensity is vital for early warning and disaster management. The favourable environmental conditions have been identified as presence of an initial disturbance in the form of incipient lows or tropical easterly waves, high sea surface temperature (SST) (≥26.5 °C) for transport of energy through air–sea fluxes, weak vertical wind shear in the 850–200 hPa layer conducive to large-scale cloud development and divergence in the upper atmosphere to facilitate further surface-level convergence and for overall sustenance of the system (Anthes TCs: their evolution, structure and effects. American Meteorological Society, Science press, Ephrata, p 208, 1982; Gray General characteristics of TCs. In: Roger P,Jr, Roger P, Sr (eds) Storms, vol 1. Routledge, 11 New Fetter Lane, London EC4P4EE. pp 145–163, 2000). The annual average frequency of TCs in the North Indian Ocean (NIO) is about five (Asnani Tropical meteorology, vols. 1 and 2, published by Prof. G.C. Asnani, c/o Indian Institute of Tropical Meteorology, Dr. HomiBhabha Road, Pashan, Pune 411008, India, 1993). Numerical prediction of TCs requires accurate specification of initial conditions that define the characteristics of an incipient storm in terms of its location, radius, central pressure, and tangential and vertical winds.
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References
Anthes, R.A. (1982). TCs: Their Evolution, Structure and Effects. American Meteorological Society, Science press, Ephrata, 208 pp.
Asnani, G.C. (1993). Tropical Meteorology, vols. 1 and 2, published by Prof. G.C. Asnani, c/o Indian Institute of Tropical Meteorology, Dr. HomiBhabha Road, Pashan, Pune 411008, India.
Chen, F. and Dudhia, J. (2001). Coupling an advanced land-surface/hydrology model with the Penn State/NCAR MM5 modeling system. Part I: Model description and implementation. Monthly Weather Review, 129, 569–585.
Courtier, P, Andersson, E, Heckley, W, Pailleux, J, Vasiljevic, D, Hamrud, M, Hollingsworth, A, Rabier, F. and Fisher, M. (1998). The ECMWF implementation of three dimensional variational assimilation (3D-Var). I: Formulation. Quarterly Journal of the Royal Meteorological Society, 124, 1783–1807.
Dudhia, J. (1989). Numerical study of convection observed during winter monsoon experiment using a mesoscale two-dimensional model. Journal of Atmospheric Science, 46, 3077–3107.
Gray, W.M. (2000). General characteristics of TCs. In: Roger, P.Jr, Roger, P. Sr (eds.) Storms vol 1, Routledge, 11 New Fetter Lane, London EC4P4EE. pp. 145–163.
Hong, S.Y, Noh, Y. and Dudhia, J. (2006). A new vertical diffusion package with explicit treatment of entrainment processes. Monthly Weather Review, 134, 2318–2341.
India Meteorological Department (2009). Report on cyclonic disturbances over North Indian Ocean during 2008, RSMC-TC Report No. 1/2009, IMD, New Delhi, India, 108 pp.
India Meteorological Department (2010). Report on cyclonic disturbances over North Indian Ocean during 2009, RSMC-TC Report No. 1/2010, IMD, New Delhi, India, 122 pp.
India Meteorological Department (2011). Report on cyclonic disturbances over North Indian Ocean during 2010, RSMC-TC Report No. 1/2011, IMD, New Delhi, India, 162 pp.
India Meteorological Department (2012). Report on Cyclonic Disturbances over North Indian Ocean during 2011. RSMC-TCs Report No. 02 (2012) IMD, New Delhi, India, 186 pp.
India Meteorological Department (2013). Report on Cyclonic Disturbances over North Indian Ocean during 2012. Met. Monograph No. ESSO/IMD/RSMC-TCs Report No. 01 (2013) IMD, New Delhi, India, 214 pp.
India Meteorological Department (2014). Report on Cyclonic Disturbances over North Indian Ocean during 2013. Met. Monograph No. ESSO/IMD/RSMC-TCs Report No. 01 (2014) IMD, New Delhi, India, 274 pp.
Kain, J.S. (2004). The Kain–Fritsch convective parameterization: An update. Journal of Applied Meteorology, 43, 170–181.
Kalnay, E. (2003). Atmospheric Modeling, Data Assimilation and Predictability. Cambridge University Press, pp. 364.
Knaff, J.A, DeMaria, M, Molenar, D.A, Sampson, C.R. and Seybold, M.G. (2011). An automated objective, multiple-satellite-platform TC surface wind analysis. Journal of Applied Meteorology and Climatology, 50, 2149–2166.
Lin, Y.-L, Farley, R.D. and Orville, H.D. (1983). Bulk parameterization of the snow field in a cloud model. Journal of Climate and Applied Meteorology, 22, 1065–1092.
Liu, H, Crawford, J.H, Pierce, R.B, Norris, P, Platnick, S.E, Chen, G, Longan, J.A, Yantosca, R.M, Evans, M.J, Kittaka, C, Feng, Y. and Tie, X. (2006). Radiative effect of clouds on tropospheric chemistry in a global three-dimensional chemical transport model. Journal of Geophysical Research, 111 , D20303, 1–18.
Mlawer, E.J, Taubman, S.J, Brown, P.D, Iacono, M.J. and Clough, S.A. (1997). Radiative transfer for inhomogeneous atmosphere: RRTM, a validated correlated-k model for the longwave. Journal of Geophysical Research, 102, 16663–16682.
Osuri, K.K, Routray, A, Mohanty, U.C. and Kulkarni, M.A. (2010). Simulation of TCs Over Indian Seas: Data Impact Study Using WRF-Var Assimilation System. In: Charabi, Y. (ed.) Indian Ocean TCs and Climate Change, Springer, Netherlands (Book Chapter), 115–124 pp, doi:10.1007/978-90-481-3109-9_15.
Osuri, K.K, Mohanty, U.C, Routray, A. and Mohapatra, M. (2012). The impact of satellite-derived wind data assimilation on track, intensity and structure of TCs over the North Indian Ocean. International Journal of Remote Sensing, 33, 2012.
Park, S.K. and Zupanski, D. (2003). Four-dimensional variational data assimilation for mesoscale and storm-scale applications. Meteorology and Atmospheric Physics, 82, 173–208.
Prashant, K, Harishkumar, K.P. and Pal, P.K. (2012). Impact of Oceansat-2 Scatterometer Winds and TMI Observations on Phet TC Simulation, doi:10.1109/TGRS.2012.2221720.
Singh, R, Pal, P.K, Kishtawal, C.M. and Joshi, P.C. (2008). The impact of variational assimilation of SSM/I and QuikSCAT Satellite observations on the Numerical Simulation of Indian Ocean TCs. Weather Forecasing, 23, 460–476.
Singh, R, Kishtawal, C.M, Pal, P.K. and Joshi, P.C. (2011). Assimilation of the multisatellite data into the WRF model for track and intensity simulation of the Indian Ocean TCs. Meteorology and Atmospheric Physics, 111, 103–119.
Singh, R, Prashant, K. and Pal, P.K. (2012). Assimilation of Oceansat-2-scatterometer-derived surface winds in the weather research and forecasting model. IEEE Transactions on Geoscience and Remote Sensing, 50, 1015–1021.
Skamarock, W.C, Klemp, J.B, Dudhia, J, Gill, D.O, Barker, D.M, Dudha, M.G, Huang, X, Wang, W. and Powers, Y. (2008). A description of the Advanced Research WRF Ver.30.NCAR Technical Note. NCAR/TN-475 + STR. Mesocale and Microscale Meteorology Davison, National Centre for Atmospheric Research, Boulder Colorado, USA, pp. 113.
Srinivas, C.V, Venkatesan, R, Vesubabu, V. and Nagaraju, C. (2010). Impact of assimilation of conventional and satellite meteorological observations on the numerical simulation of a Bay of Bengal TC of Nov 2008 near Tamilnadu using WRF model. Meteorology and Atmospheric Physics, 110, 19–44.
Srinivas, C.V, BhaskarRao, D.V, Yesubabu, V, Baskaran, R. and Venkatraman, B. (2012). TC predictions over the Bay of Bengal using the high-resolution advanced research weather research and forecasting (ARW) model. Quarterly Journal of the Royal Meteorological Society, doi:10.1002/qj.2064
Xiao, Q, Zhang, X, Davis, C, Tuttle, J, Holland, G. et al. (2009). Experiments of hurricaneinitialization with airborne doppler radar data for the advanced-research hurricane WRF (AHW) Model. Monthly Weather Review, doi: 10.1175/2009MWR2828.1.
Yesubabu, V, Srinivas, C.V, Hariprasad, K.B.R.R. and Baskaran, R. (2013). A study on the impact of observation assimilation on the numerical simulation of TCs Jal and Thane using 3DVAR. Pure and Applied Geophysics, doi:10.1007/s00024-013-0741-3.
Acknowledgements
The authors wish to thank Sri S.A.V. Satya Murthy, Director EIRSG for encouragement and support. The WRF ARW model was obtained from NCAR. The GFS analysis and forecasts used in operational predictions are available from NCEP. The India Meteorological Department is acknowledged for the use of best track and intensity estimates. Authors acknowledge anonymous reviewers for their technical comments that helped to improve the manuscript.
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Srinivas, C.V., Mohan, G.M., Yesubabu, V., Hariprasad, K.B.R.R., Baskaran, R., Venkatraman, B. (2017). Data Assimilation Experiments with ARW–3DVAR for Tropical Cyclone Extreme Weather Predictions Over Bay of Bengal. In: Mohapatra, M., Bandyopadhyay, B., Rathore, L. (eds) Tropical Cyclone Activity over the North Indian Ocean. Springer, Cham. https://doi.org/10.1007/978-3-319-40576-6_22
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