Abstract
The objective of the present study is to investigate in detail the sensitivity of cumulus parameterization (CP), planetary boundary layer (PBL) parameterization, microphysics parameterization (MP) on the numerical simulation of severe cyclone LAILA over Bay of Bengal using Weather Research & Forecasting (WRF) model. The initial and boundary conditions are supplied from GFS data of 1° × 1° resolution and the model is integrated in three ‘twoway’ interactive nested domains at resolutions of 60 km, 20 km and 6.6 km. Total three sets of experiments are performed. First set of experiments include sensitivity of Cumulus Parameterization (CP) schemes, while second and third set of experiments is carried out to check the sensitivity of different PBL and Microphysics Parameterization (MP) schemes. The fourth set contains initial condition sensitivity experiments. For first three sets of experiments, 0000 UTC 17 May 2010 is used as initial condition. In CP sensitivity experiments, the track and intensity is well simulated by Betts-Miller-Janjic (BMJ) schemes. The track and intensity of LAILA is very sensitive to the representation of large scale environmental flow in CP scheme as well as to the initial vertical wind shear values. The intensity of the cyclone is well simulated by YSU scheme and it depends upon the mixing treatment in and above PBL. Concentration of frozen hydrometeors, such as graupel in WSM6 MP scheme and latent heat released during auto conversion of hydrometeors may be responsible for storm intensity. An additional set of experiments with different initial vortex intensity shows that, small differences in the initial wind fields have profound impact on both track and intensity of the cyclone. The representation of the mid-tropospheric heating in WSM6 is mainly controlled by amount of graupel hydrometeor and thus might be one of the possible causes in modulating the storm’s intensity.
Article PDF
Similar content being viewed by others
Avoid common mistakes on your manuscript.
References
Anthes, R. A., Y. Kuo, S. Benjamin, and Y. F. Li, 1982: The evolution of the mesoscale environment of severe local storms: preliminary modeling results. Mon. wea. Rev., 110, 1187–1213.
Arpe, K., A. Hollingsworth, M. S. Tracton, A. C. Lorenc, S. Uppala, and P. Kallberg, 1985: The response of numerical weather prediction systems on the FGGE level IIb data. Part 2: Forecast verifications and implications for predictability. Quart. J. Roy. Meteor. Soc., 111, 67–101.
Betts, A. K., 1986: A new convective adjustment scheme Part I: Observational and theoretical basis. Quart. J. Roy. Meteor. Soc., 112, 677–691.
Betts, A. K., and M. J. Miller, 1986: A new convective adjustment scheme Part II: Single column tests using GATE wave, BOMEX, and arctic air mass data sets. Quart. J. Roy. Meteor. Soc., 112, 693–709.
Bhaskar Rao, D. V., and D. Hari Prasad, 2006: Numerical prediction of the Orissa super cyclone (1999): Sensitivity to the parameterization of convection, boundary layer and explicit moisture processes. Mausam, 57, 61–78.
Bhaskar Rao, D. V., and D. Hari Prasad, 2007: Sensitivity of tropical cyclone intensication to boundary layer and convective processes. Nat. Hazards, 41, 429–445.
Bhaskar Rao, D. V., D. Hari Prasad, and D. Srinivas, 2009: Impact of horizontal resolution and the advantages of the nested domains approach in the prediction of tropical cyclone intensification and movement. J. Geophys. Res., 114, D11106, 1–24.
Cacciamani, C., D. Cesari, F. Grazzini, T. Paccagnella, and M. Pantone, 2000: Numerical simulation of intense precipitation events south of the Alps: Sensitivity to initial conditions and horizontal resolution. Meteor. Atmos. Phys., 72, 147–159.
Charney, J. G., and A. Eliassen, 1964: On the growth of the hurricane depression. J. Atmos. Sci., 21, 68–75.
Deshpande, M., S. Pattanaik, and P. S. Salvekar, 2010: Impact of physical parameterization schemes on numerical simulation of super cyclone Gonu. Nat. Hazards, 55, 211–231.
Deshpande, M., S. Pattanaik, and P. S. Salvekar, 2012: Impact of cloud parameterization on the numerical simulation of a super cyclone. Ann. Geophys., 30, 775–795.
Dudhia, J., 1989: Numerical study of convection observed during the winter monsoon experiment using a mesoscale two-dimensional model. J. Atmos. Sci., 46, 3077–3107.
Dudhia, J., S.-Y. Hong, and K. S. Lim, 2008: A new method for representing mixed-phase particle fall speeds in bulk microphysics parameterizations. J. Meteor. Soc. Japan, 86A, 33–44.
Efstathiou, G. A., N. M. Zoumakis, D. Melas, and P. Kassomenos, 2012: Impact of precipitating ice on the simulation of heavy rainfall event with advanced research WRF using two bulk microphysical schemes. Asia-Pac. J. Atmos. Sci., 48, 357–368.
Efstathiou, G. A., N. M. Zoumakis, D. Melas, and P. Kassomenos, 2013: Sensitivity of WRF to boundary layer parameterizations in simulating a heavy rainfall event using different microphysical schemes. Effect on large-scale processes. Atmos. Res., 132–133, 125–143, http://dx.doi.org/10.1016/j.atmosres.2013.05.004.
Emanuel, K. A., 1986: An air-sea interaction theory for tropical cyclones. Part I: Steady state maintenance. J. Atmos. Sci., 43, 585–604.
Emanuel, K. A., 2004: Tropical cyclone energetics and structure. Atmospheric Turbulence and Mesoscale Meteorology, edited by: Federovich, E., Rotunno, R., and Stevens, B., Cambridge University Press, 165–192.
Emanuel, K. A., J. D. Neelin, and C. S. Bretherton, 1994: On large scale circulations of convecting atmospheres. Quart. J. Roy. Meteor. Soc., 120, 1111–1143.
Frank, W. M., and E. A Ritchie, 2001: Effects of vertical wind shear on the intensity and structure of numerically simulated hurricanes. Mon. Wea. Rev., 129, 2249–2269.
Gray, W. M., 1968: Global view of the origin of tropical disturbances and storms. Mon. Wea. Rev., 96, 669–700.
Grell, G. A., and D. Devenyi, 2002: A generalized approach to parameterizing convection combining ensemble and data assimilation techniques. Geophys. Res. Lett. 29, 14, 38-138-4, doi:10.1029/2002-GL015311.
Hill, K. V., and G. M. Lackman, 2009: Analysis of idealized tropical cyclone simulations using the Weather Research and Forecasting Model: Sensitivity to turbulence parameterization and grid spacing. Mon. Wea. Rev., 137, 745–765.
Hong, S.-Y., and J.-O. J. Lim, 2006: The WRF Single-Moment 6-Class Microphysics Scheme (WSM6). J. Korean Meteor. Soc., 42, 129–151.
Hong, S.-Y., Y. Noh, and J. Dudhia, 2006: A new vertical diffusion package with an explicit treatment of entrainment processes. Mon. Wea. Rev., 134, 2318–2341.
Hong, S.-Y., and H.-L. Pan, 1996: Nonlocal boundary layer vertical diffusion in a medium range forecast model. Mon. Wea. Rev. 124, 2322–2339.
Hu, X.-M., J. W. Nielsen-Gammon, and F. Zhang, 2010: Evaluation of three planetary boundary layer schemes in the WRF model. J. Appl. Meteor. Climatol., 49, 1831–1844.
Janjic, Z. I., 1990: The step-mountain coordinate: physical package. Mon. Wea. Rev., 118, 1429–1443.
Janjic, Z. I., 1996: The surface layer in the NCEP Eta Model. Eleventh Conference on Numerical Weather Prediction. Norfolk, VA, 19–23 August. American Meteorology Society Boston, MA, 354–355.
Janjic, Z. I., 2000: Comments on “Development and evaluation of a convection scheme for use in climate models”. J. Atmos. Sci., 57, 3686.
Janjic, Z. I., 2002: Nonsingular Implementation of the Mellor-Yamada Level 2.5 Scheme in the NCEP Meso Model. NCEP Office Note 437, 61.
Jankov, I., W. A. Gallus, M. Segal, B. Shaw, and S. E. Koch, 2005: The impact of different WRF model physical parameterizations and their interactions on warm season MCS rainfall. Wea. Forcasting, 20, 1048–1060.
Jankov, I., P. J. Schultz, C. J. Anderson, and S. E. Koch, 2007: The impact of different physical parameterizations and their interactions on cold season QPF in the American River Basin. J. Hydrometeor., 8, 1141–1151.
Kain, J. S., 2004: The Kain-Fritsch convective parameterization: An update. J. Appl. Meteorol., 43, 170–181.
Kanase, R. D., and P. S. Salvekar, 2014a: Study of weak intensity cyclones over bay of Bengal using WRF model. Atmos. Climate Sci., 4, 534–548.
Kanase, R. D., P. Mukhopadhyay, and P. S. Salvekar, 2014b: Understanding the role of cloud and convective process in simulating the weaker cyclones over Indian Seas. Pure Appl. Geophys., doi:10.1007/s00024-014-0996-3.
Kuo, Y-H., and R. J. Reed, 1988: Numerical simulation of an explosively deepening cyclone in the eastern Pacific. Mon. Wea. Rev., 116, 2081–2105.
Li, X., and Z. Pu, 2008: Sensitivity of numerical simulation of early rapid intensification of Hurricane Emily (2005) to cloud microphysical and planetary boundary layer parameterizations. Mon. Wea. Rev., 136, 4819–4838.
Lord, S. J., and J. M. Lord, 1988: Vertical velocity structure in an axisymmetric, nonhydrostatic tropical cyclone model. J. Atmos. Sci., 45, 1453–1461.
Lord, S. J., H. E. Willoughby, and J. M. Piotrowicz, 1984: Role of a parameterized ice-phase microphysics in an axisymmetric, nonhydrostatic tropical cyclone model. J. Atmos. Sci., 41, 2836–2848.
Lorenz, E. N., 1963: Deterministic nonperiodic flow. J. Atmos. Sci., 20, 130–141.
Mellor, G. L., and T. Yamada, 1982: Development of a turbulence closure model for geophysical fluid problems. Rev. Geophys. Space Physics, 20, 851–875.
Merrill, R. T., 1988: Environmental influence on Hurricane intensification. J. Atmos. Sci., 45, 1678–1687.
Mlawer, E. J., S. J. Taubman, P. D. Brown, M. J. Iacono, and S. A. Clough, 1997: Radiative transfer for inhomogeneous atmosphere: RRTM, a validated correlated-k model for the longwave. J. Geophy. Res., 102, 16663–16682.
Mohanty, U. C., K. K. Osuri, A. Routray, M. Mohapatra, and S. Pattanayak, 2010: Simulation of bay of Bengal tropical cyclones with WRF model: Impact of initial and boundary conditions. Mar. Geod., 33, 294–314.
Montgomery, M. T., and R. K. Smith, 2011: Paradigms for tropicalcyclone intensification. Quart. J. Roy. Meteor. Soc., 137, 1–31.
Montgomery, M. T., J. Persing, and R. K. Smith, 2015: Putting to rest WISHE-ful misconceptions for tropical cyclone intensification. J. Adv. Modeling Earth Syst., 7, 92–109, doi:10.1002/2014MS000362.
Montgomery, M. T., S. V. Nguyen, R. K. Smith, and J. Persing, 2009: Do tropical cyclones intensify by WISHE?. Quart. J. Roy. Meteor. Soc., 135, 1697–1714.
Mullen, S. L., and D. P. Baumhefner, 1989: The impact of initial condition uncertainty on numerical simulations of large scale explosive cyclogenesis. Mon. Wea. Rev., 117, 2800–2821.
Mukhopadhyay, P., S. Taraphdar, and B. N. Goswami, 2011: Influence of moist processes on track and intensity forecast of cyclones over the north Indian Ocean. J. Geophys. Res., D05116, doi:10.1029/2010-JD014700.
Osuri, K. K., U. C. Mohanty, A. Routray, M. A. Kulkarni, and M. Mohapatra, 2012: Customization of WRF-ARW model with Physical parameterization schemes for the simulation of tropical cyclones over North Indian Ocean. Nat. Hazards, 63, 1337–1359.
Osuri, K. K., U. C. Mohanty, A. Routray, M. Mohapatra, and D. Nivogi, 2013: A real-time track prediction of tropical cyclones over the North Indian Ocean using the ARW model. J. Appl. Meteor. Climatol., 52, 2476–2492.
Pattanaik, D. R., and Y. V. Rama Rao, 2009: Track prediction of very severe cyclone ‘Nargis’ using high resolution weather research forecasting (WRF) model. J. Earth Syst. Sci., 118, 4, 309–329.
Pattanayak, S., and U. C. Mohanty, 2008: A comparative study on performance of MM5 and WRF models in simulation of tropical cyclones over Indian seas. Curr. Sci. India, 95, 923–936.
Pielke, R. A., and Coauthors, 2006: A new paradigm for parameterizations in numerical weather prediction and other atmospheric models. Natl. Wea. Digest, 30, 93–99.
Raju, P. V. S., J. Potty, and U. C. Mohanty, 2011: Sensitivity of physical parameterizations on prediction of tropical cyclone Nargis over the Bay of Bengal using WRF model. Meteor. Atmos. Phys., 113, 125–137.
Ritchie, E. A., 2002: Topic 1.2: Environmental effects. Topic Chairman and Rapporteur Report. The 5th WMO InternationalWorkshop on Tropical Cyclones IWTC-V, WMO Tech. Doc. WMO TD 1136.
Rodgers, E. B., J. J. Baik, and H. F. Pierce, 1994a: The environmental influence on tropical cyclone precipitation. J. Appl. Meteorol., 33, 573–593.
Rodgers, E. B., S. W. Chang, and H. F. Pierce, 1994b: A satellite observational and numerical study of precipitation characteristics in western North Atlantic tropical cyclones. J. Appl. Meteorol., 33, 129–139.
Ross, R. J., and Y. Kurihara, 1995: A numerical study on influence of Hurricane Gloria (1985) on the environment. Mon. Wea. Rev., 123, 332–346.
RSMC Report, 2011: A report on cyclonic disturbances over North Indian Ocean during 2010. New Delhi, India, India Meteorological Department.
Sanders, F., 1987: Skill of NMC operational models in prediction of explosive cyclogenesis. Wea. Forecasting, 2, 322–336.
Shin, H. H., and S.-Y. Hong, 2011: Intercomparison of planetary boundarylayer parametrizations in the WRF model for a single day from CASES-99. Bound.-Layer Meteor., 139, 261–281.
Skamarock, W. C., J. B. Klemp, J. Dudhia, D. Gill, D. Barker, W. Wang, X. Y. Huang, and J. G. Powers, 2008: A description of the advanced research WRF version 3, NCAR Technical Note, 475.
Smith, R. K., 1997: On the theory of CISK. Quart. J. Roy. Meteor. Soc., 123, 407–418.
Srinivas, C. V., R. Venkatesan, D. V. Bhaskar Rao, and D. Hari Prasad, 2007: Numerical simulation of Andhra severe cyclone (2003). model sensitivity to the boundary layer and convective parameterization. Pure Appl. Geophys., 164, 1465–1487.
Srinivas, C. V., R. Venkatesan, V. Yesubabu, and C. Nagaraju, 2010: Impact of assimilation of conventional and satellite meteorological observations on the numerical simulation of a Bay of Bengal tropical cyclone of Nov 2008 near Tamilnadu using WRF model. Meteor. Atmos. Phys., 110, 19–44.
Srinivas, C. V., D. V. Bhaskar Rao, V. Yesubabu, R. Baskarana, and B. Venkatraman, 2013: Tropical cyclone predictions over the Bay of Bengal using the high-resolution Advanced Research Weather Research and Forecasting (ARW) model. Quart. J. Roy. Meteor. Soc., 139, 1810–1825.
Srinivas D., and D. V. Bhaskar Rao, 2014: Implications of vortex initialization and model spin-up in tropical cyclone prediction using Advanced Research Weather Research and Forecasting Model. Nat. Hazards, 73, 1043–1062.
Tao, W., J. J. Shi, S. S. Chen, S. Lang, P. Lin, S.-Y. Hong, C. P. Lidard, and A. Hou, A, 2011: Impact of microphysical schemes on hurricane intensity and track. Asia-Pac. J. Atmos. Sci., 47, 1–16.
Trivedi, D. K., J. Sanjay, and S. S. Singh, 2002: Numerical simulation of a super cyclonic storm, Orissa 1999: Impact of initial conditions. Meteor. Appl., 9, 367–376.
Trivedi, D. K., P. Mukhopadhyay, and S. S. Vaidya, 2006: Impact of physical parameterization schemes on the numerical simulation of Orissa super cyclone (1999). Mausam, 57, 97–110.
Tuleya, R. E., and Y. Kurihara, 1981: A numerical study on the effects of environmental flow on tropical storm genesis. Mon. Weather Rev., 109, 2487–2506.
Wang, Y., and C.-C. Wu, 2004: Current understanding of tropical cyclone structure and intensity changes — A review. Meteor. Atmos. Phys., 87, 257–278.
White, B., J. Paegle, W. J. Steenburgh, J. D. Horel, R. T. Swanson, L. K. Cook, D. J. Onton, and J. G. Miles, 1999: Short-term forecast validation of six models. Wea. Forecasting, 14, 84–108.
Wu, C.-C., and H.-J. Cheng, 1999: An observational study of environmental influences on the intensity changes of Typhoons Flo (1990) and Gene (1990). Mon. Wea. Rev., 127, 3003–3031.
Yesubabu, V., C. V. Srinivas, S. S. V. S. Ramakrishna, and K. B. R. R. Hariprasad, 2014: Impact of period and timescale of FDDA analysis nudging on the numerical simulation of tropical cyclones in the Bay of Bengal. Nat. Hazards, 74, 2109–2128.
Zehr, R. M., 1992: Tropical cyclogenesis in the western North Pacific. NOAA Tech. Rep. NESDIS 61, 181.
Zeng, Z., Y. Wang, and C. C. Wu, 2007: Environmental dynamical control of tropical cyclone intensity — An observational study. Mon. Wea. Rev., 135, 38–59.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Kanase, R.D., Salvekar, P.S. Effect of physical parameterization schemes on track and intensity of cyclone LAILA using WRF model. Asia-Pacific J Atmos Sci 51, 205–227 (2015). https://doi.org/10.1007/s13143-015-0071-8
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s13143-015-0071-8