Skip to main content
SpringerLink
Log in

Role of Planetary Boundary Layer Processes in the Simulation of Tropical Cyclones Over the Bay of Bengal

  • Published:
Pure and Applied Geophysics Aims and scope Submit manuscript

Abstract

The behaviour of planetary boundary layer (PBL) schemes initialized at different life stages of a tropical cyclone (TC) is studied by considering seven Bay of Bengal TC cases. In each TC case, the Advanced Research Weather Research and Forecasting (WRF-ARW) model is initialized at four life stages (depression to very severe cyclone storm) with National Center for Environmental Prediction (NCEP) Global analysis and integrated up to 96 h. A set of six PBL sensitivity experiments are conducted at four stages for all seven TC cases to analyse the impact of the model boundary layer in simulating the TC track and intensity parameters. The model-produced track, intensity and rainfall patterns are evaluated with the best track, intensity and gridded rainfall estimates obtained from the India Meteorological Department (IMD). The spatial and radius/height section simulated fields are evaluated with satellite retrievals. Results depict that the six PBL schemes during model initialization at different stages of a TC have produced sizable differences in the simulation of track and intensity parameters. The local and nonlocal schemes produced different results based on the TC stage at which the model is initialized. The results also suggest that if the model is initialized with a non-organized cyclonic vortex such as depression stage of the storm, PBL schemes exhibit high sensitivity and spread in terms of both track and intensity. While the spread between PBL schemes was significantly reduced and found close to the observed estimates when the model was initialized at the advanced stages of the TC. In addition, the local 1.5-order closure scheme simulated the storm parameters relatively better when the cyclone vortex was not well organized in the model's initial conditions, while the non-local and first-order closure schemes perform better with initial model conditions of a well-defined cyclonic vortex.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16

Similar content being viewed by others

References

  • Anthes, R. A. (1982). Tropical cyclones: Their evolution, structure and effects. Ephrata: American Meteorological Society.

    Book  Google Scholar 

  • Bhaskar Rao, D. V., & Hari Prasad, D. (2006). Numerical prediction of the Orissa super-cyclone: Sensitivity to the parameterization of convection, boundary layer and explicit moisture processes. Mausam, 57(1), 61–78.

    Google Scholar 

  • Bhaskar Rao, D. V., & Hari Prasad, D. (2007). Sensitivity of tropical cyclone intensification to boundary layer and convective processes. Natural Hazard, 41(3), 429–445.

    Article  Google Scholar 

  • Bhaskar Rao, D. V., Hari Prasad, D., & Srinivas, D. (2009). Impact of horizontal resolution and the advantages of the nested domains approach in the prediction of tropical cyclone intensification and movement. Journal of Geophysical Research, 114(D11106), 24.

    Google Scholar 

  • Bhaskar Rao, D. V., Hari Prasad, D., Srinivas, D., & Anjaneyulu, Y. (2010). Role of vertical resolution in numerical models towards the intensification, structure and track of tropical cyclones. Marine Geodesy, 33(4), 338–355.

    Article  Google Scholar 

  • Blackadar, A. K. (1978). Modeling pollutant transfer during daytime convection, In Preprints Fourth Symposium on Atmospheric Turbulence, Diffusion and Air Quality. Reno, Am. Meteor. Soc., pp. 443–447.

  • Bougeault, P., & Lacarrere, P. (1989). Parameterization of orography-induced turbulence in a Mesobeta-Scale model. Monthly Weather Review, 117, 1872–1890.

    Article  Google Scholar 

  • Braun, S. A., & Tao, W.-K. (2000). Sensitivity of high resolution of hurricane Bob (1991) to planetary boundary layer parameterizations. Monthly Weather Review, 128, 3941–3961.

    Article  Google Scholar 

  • Chandrasekar, R., & Balaji, C. (2012). Sensitivity of tropical cyclone Jal simulations to physics parameterizations. Journal of Earth System Science, 121, 923–946.

    Article  Google Scholar 

  • Chandrasekar, R., & Balaji, C. (2016). Impact of physics parameterization and 3DVAR data assimilation on prediction of tropical cyclones in the Bay of Bengal region. Natural Hazards, 80(1), 223–247.

    Article  Google Scholar 

  • Cohen, A. E., Cavallo, S. M., Coniglio, M. C., & Brooks, H. E. (2015). A review of planetary boundary layer parameterization schemes and their sensitivity in simulating southeastern U.S. cold season severe weather environments. Weather and Forecasting, 30, 591–612. https://doi.org/10.1175/WAF-D-14-00105.1.

    Article  Google Scholar 

  • Dasari, H., Rao, V. B., Ramakrishna, S. S. V. S., Paparao, G., & Ramesh Kumar, P. (2017). On the movement of tropical cyclone LEHAR. Earth Systems and Environment, 1, 21. https://doi.org/10.1007/s41748-017-0025-7.

    Article  Google Scholar 

  • Demuth, J. L., DeMaria, M., Knaff, J. A., & Vonder Haar, T. H. (2004). Evaluation of Advanced Microwave Sounding Unit tropical-cyclone intensity and size estimation algorithms. J. Appl. Meteor., 43, 282–296.

    Article  Google Scholar 

  • Deshpande, M., Pattnaik, S., & Salvekar, P. S. (2010). Impact of physical parameterization schemes of numerical simulation of super cyclone Gonu. Natural Hazards, 55, 211–231. https://doi.org/10.1007/s11069-010-9521-x.

    Article  Google Scholar 

  • Durre, I., Vose, R. S., & Wuertz, D. B. (2006). Overview of the integrated global radiosonde archive. Journal of Climate, 19(1), 53–68.

    Article  Google Scholar 

  • Fovell, R. G., & Su, H. (2007). Impact of cloud microphysics on hurricane track forecasts. Geophysical Research Letters, 34, L24810. https://doi.org/10.1029/2007GL031723.

    Article  Google Scholar 

  • Gray, W. M. (1968). Global view of the origin of tropical disturbances and storms. Monthly Weather Review, 96, 669–700.

    Article  Google Scholar 

  • Greeshma, M. M., Srinivas, C. V., Yesubabu, V., Naidu, C. V., Baskaran, R., & Venkatraman, B. (2015). Impact of local data assimilation on tropical cyclone predictions over the Bay of Bengal using the ARW model. Annales Geophysicae, 33, 805–828.

    Article  Google Scholar 

  • Grenier, H., & Bretherton, C. S. (2001). A moist PBL parameterization for large-scale models and its application to subtropical cloud-topped marine boundary layers. Monthly Weather Review, 129, 357–377.

    Article  Google Scholar 

  • Hari Prasad, K. B. R. R., Srinivas, C. V., Satyanarayana, A. N. V., Naidu, C. V., Baskaran, R., & Venkatraman, B. (2015). Formulation of stability-dependent empirical relations for turbulent intensities from surface layer turbulence measurements for dispersion parameterization in a lagrangian particle dispersion model. Meteorology and Atmospheric Physics, 127(4), 435–450. https://doi.org/10.1007/s00703-015-0373-5.

    Article  Google Scholar 

  • Hill, K. A., & Lackmann, G. L. (2009). Analysis of idealized tropical cyclone simulations using the Weather Research and Forecasting model: Sensitivity to turbulence parameterization and grid spacing. Monthly Weather Review, 137, 745–765.

    Article  Google Scholar 

  • Holtslag, A. A. M., & Boville, B. A. (1993). Local versus nonlocal boundary-layer diffusion in a global climate model. Journal of Climate, 6, 1825–1842.

    Article  Google Scholar 

  • Hong, S. Y., Noh, Y., & Dudhia, J. (2006). A new vertical diffusion package with an explicit treatment of entrainment processes. Monthly Weather Review, 134, 2318–2341.

    Article  Google Scholar 

  • Hong, S. Y., & Pan, H. L. (1996). Nonlocal boundary layer vertical diffusion in a medium-range forecast model. Monthly Weather Review, 124, 2322–2339.

    Article  Google Scholar 

  • Kanase, R. D., Mukhopadhyay, P., & Salvekar, P. S. (2015). Understanding the role of cloud and Convective processes in simulating the weaker tropical cyclones over Indian Seas. Pure and Applied Geophysics, 172(6), 1751–1779. https://doi.org/10.1007/s00024-014-0996-3.

    Article  Google Scholar 

  • Kanase, R. D., & Salvekar, P. S. (2015). Effect of physical parameterization schemes on track and intensity of cyclone LAILA using WRF model. Asia-Pacific Journal of Atmospheric Sciences, 51, 205–227. https://doi.org/10.1007/s13143-015-0071-8.

    Article  Google Scholar 

  • Kepert, J. D. (2012). Choosing a boundary layer parameterisation for tropical cyclone modeling. Monthly Weather Review, 140, 1427–1445.

    Article  Google Scholar 

  • Knaff, J. A., DeMaria, M. (2006). A multi-platform satellite tropical cyclone wind analysis system. AMS 14th Conference on Satellite Meteorology and Oceanography. 29 January-3 February, Atlanta, GA

  • Knaff, J. A., Sampson, C. R., DeMaria, M., Marchok, T. P., Gross, J. M., & McAdie, C. J. (2007). Statistical tropical cyclone wind radii prediction using climatology and persistence. Weather and Forecasting, 22, 781–791. https://doi.org/10.1175/WAF1026.1.

    Article  Google Scholar 

  • Kumar, V., Jain, S. K., & Singh, Y. (2010). Analysis of long-term rainfall trends in India. Hydrological Sciences Journal, 55(4), 484–496. https://doi.org/10.1080/02626667.2010.481373.

    Article  Google Scholar 

  • Langousis, A., Veneziano, D., & Chen, S. (2009). Boundary layer model for moving tropical cyclones. In J. Elsner & T. Jagger (Eds.), Hurricanes and climate change. Boston: Springer.

    Google Scholar 

  • Ma, Z., Fei, J., Huang, X., & Cheng, X. (2012). Sensitivity of tropical cyclone intensity and structure to vertical resolution in WRF. Asia-Pacific Journal of Atmospheric Science, 48(1), 67–81. https://doi.org/10.1007/s13143-012-0007-5.

    Article  Google Scholar 

  • Mandal, M., Mohanty, U. C., & Raman, S. (2004). A Study on the impact of parameterization of physical processes on prediction of tropical cyclones over the Bay of Bengal with NCAR/PSU mesoscale model. Natural Hazards, 31, 391–414.

    Article  Google Scholar 

  • Mandal, M., Singh, K. S., Balaji, M., & Mohapatra, M. (2016). Performance of WRF-ARW model in real-time prediction of Bay of Bengal cyclone `Phailin’. Pure and Applied Geophysics, 173(5), 1783–1801.

    Article  Google Scholar 

  • McFarquhar, G. M., Zhang, H., Heymsfield, G., Hood, R., Dudhia, J., Halverson, J. B., et al. (2006). Factors affecting the evolution of Hurricane Erin (2001) and the distributions of Hydrometeors: Role of microphysical processes. Journal of Atmospheric Science, 63, 127–150.

    Article  Google Scholar 

  • Mellor, G. L., & Yamada, T. (1982). Development of a turbulence closure model for geophysical fluid problems. Reviews of Geophysics and Space Physics, 20, 851–875.

    Article  Google Scholar 

  • Mohanty, U. C., Mandal, M., & Raman, S. (2004). Simulation of Orissa Super Cyclone (1999) using PSU/NCAR mesoscale model. Natural Hazards, 31, 373–390.

    Article  Google Scholar 

  • Mohanty, U. C., Osuri, K. K., & Pattanayak, S. (2014). Mesoscale modelling for tropical cyclone forecasting over the North Indian Ocean. Monitoring and prediction of tropical cyclones in the Indian Ocean and Climate Change (pp. 274–286). Dordrecht: Springer.

    Book  Google Scholar 

  • Mohanty, U. C., Osuri, K. K., Routray, A., Mohapatra, M., & Pattanayak, S. (2010). Simulation of Bay of Bengal tropical cyclones with WRF model: Impact of initial and boundary conditions. Marine Geodesy, 33(4), 294–314.

    Article  Google Scholar 

  • Monsoon 2014 A report, IMD Met. Monograph: ESSO Document No.: ESSO/IMD/SYNOPTIC MET/01(2015)/17.

  • Montgomery, M. T., Smith, R. K., & Nguyen, S. V. (2010). Sensitivity of tropical-cyclone models to the surface drag coefficient. Quarterly Journal Royal Meteorological Society, 136, 1945–1953.

    Article  Google Scholar 

  • Murphy, A. H. (1993). What is a good forecast? An essay on the nature of goodness in weather forecasting. Weather and Forecasting, 8, 281–293.

    Article  Google Scholar 

  • Nakanishi, M., & Niino, H. (2004). An improved Mellor-Yamada level-3 model with condensation physics: Its design and verification. Boundary-Layer Meteorol., 112, 1–31.

    Article  Google Scholar 

  • Osuri, K. K., Mohanty, U. C., & Routray, A. (2014). Role of surface roughness length on simulation of cyclone Aila. Monitoring and prediction of tropical cyclones in the Indian Ocean and climate change (pp. 255–262). Dordrecht: Springer.

    Book  Google Scholar 

  • Osuri, K. K., Mohanty, U. C., Routray, A., Kulkarni, M. A., & Mohapatra, M. (2012). Customization of WRF-ARW model with physical parameterization schemes for the simulation of tropical cyclones over North Indian Ocean. Natural Hazards, 63, 1337–1359.

    Article  Google Scholar 

  • Osuri, K. K., Mohanty, U. C., Routray, A., Mohapatra, M., & Niyogi, D. (2013). Real-time track prediction of tropical cyclones over the North Indian Ocean using the ARW model. Journal of Applied Meteorology and Climatology, 52, 2476–2492.

    Article  Google Scholar 

  • Osuri, K. K., Mohanty, U. C., Routray, A., & Niyogi, D. (2015). Improved prediction of Bay of Bengal tropical cyclones through assimilation of Doppler weather radar observations. Monthly Weather Review, 143, 4533–4560.

    Article  Google Scholar 

  • Pattnaik, S., & Krishnamurti, T. N. (2007). Impact of cloud microphysical processes on hurricane intensity, part 1: Control run. Meteorology and Atmospheric Physics, 97, 117–126.

    Article  Google Scholar 

  • Raghavan, S., & Sen Sarma, A. K. (2000). Tropical cyclone impacts in India and neighbourhood. In P. Roger & P. Roger (Eds.), Storms (pp. 339–356). London: Routledge.

    Google Scholar 

  • Samala, B. K., Nagaraju, C., Banerjee, S., Kaginalkar, A., & Dalvi, M. (2013). Study of the Indian summer monsoon using WRF–ROMS regional coupled model simulations. Atmospheric Science Letters, 14, 20–27. https://doi.org/10.1002/asl2.409.

    Article  Google Scholar 

  • Sateesh, M., Srinivas, C. V., & Raju, P. V. S. (2017). Numerical simulation of tropical cyclone thane: role of boundary layer and surface drag parameterization schemes. Natural Hazards, 89, 1255–1271.

    Article  Google Scholar 

  • Singh, K. S., & Bhaskaran, P. K. (2017). Impact of PBL and convection parameterization schemes for prediction of severe land-falling Bay of Bengal cyclones using WRF-ARW model. Journal of Atmospheric and Solar-Terrestrial Physics. https://doi.org/10.1016/j.jastp.2017.11.004.

    Google Scholar 

  • Smith, R. K., Montgomery, M. T., & Nguyen, V. S. (2009). Tropical cyclone spin-up revisited. Quarterly Journal Royal Meteorological Society, 135, 1321–1335.

    Article  Google Scholar 

  • Smith, R. K., Montgomery, M. T., & Thomsen, G. L. (2014). Sensitivity of tropical-cyclone models to the surface drag coefficient in different boundary-layer schemes. Quarterly Journal of the Royal Meteorological Society, 140, 792–804.

    Article  Google Scholar 

  • Smith, R. K., & Thomsen, G. L. (2010). Dependence of tropical-cyclone intensification on the boundary-layer representation in a numerical model. Quarterly Journal of the Royal Meteorological Society, 136, 1671–1685.

    Article  Google Scholar 

  • Srikanth, M., Satyanarayana, A. N. V., Srinivas, C. V., & Tyagi, Bhishma. (2016). Performance evaluation of PBL schemes of ARW model in simulating thermo-dynamical structure of pre-monsoon convective episodes over Kharagpur using STORM data sets. Pure and Applied Geophysics, 173(5), 1803–1827.

    Article  Google Scholar 

  • Srinivas, C. V., Bhaskar Rao, D. V., Yesubabu, V., Baskaran, R., & Venkatraman, B. (2012). Tropical cyclone predictions over the Bay of Bengal using the high-resolution advanced research weather research and forecasting (ARW) model. Quarterly Journal Royal Meteorological Society, 139, 1810–1825.

    Article  Google Scholar 

  • Srinivas, C. V., Venkatesan, R., Bhaskar Rao, D. V., & Hariprasad, D. (2007). Numerical simulation of Andhra severe cyclone (2003): Model sensitivity to boundary layer and convection parameterization. Pure and Applied Geophysics, 164, 1–23.

    Article  Google Scholar 

  • Srinivas, C. V., Yesubabu, V., Hari Prasad, K. B. R. R., & Venkatraman, B. (2013). Real-time prediction of a severe cyclone ‘Jal’ over Bay of Bengal using a high-resolution mesoscale model WRF (ARW). Natural Hazards, 65, 331–357.

    Article  Google Scholar 

  • Sunilkumar, K., Narayana Rao, T., Saikranthi, K., & Purnachandra Rao, M. (2015). Comprehensive evaluation of multisatellite precipitation estimates over India using gridded rainfall data. Journal of Geophysical Research: Atmospheres, 120, 8987–9005. https://doi.org/10.1002/2015JD023437.

    Google Scholar 

  • Thomas, Ancy, Samala, B. K., & Kaginalkar, A. (2014). Simulation of North Indian Ocean tropical cyclones using RAMS numerical weather prediction model. Tropical Cyclone Research and Review, 3(1), 44–52.

    Google Scholar 

  • W.M.O., Recommendations for the verification and intercomparison of QPFs and PQPFs from Operational NWP Models, 2008; Revision 2, WWRP 2009-1, TD-No.1485, 34PP.

  • Xie, B., Fung, J. C. H., Chan, A., & Lau, A. K. H. (2012). Evaluation of nonlocal and local planetary boundary layer schemes in the WRF Model. Journal of Geophysical Research, 117, D12103. https://doi.org/10.1029/2011JD017080.

    Google Scholar 

  • Yesubabu, V., Srinivas, C. V., Hari Prasad, K. B. R. R., Baskaran, R. (2014a). A study on the impact of observation assimilation on the numerical simulation of tropical cyclones JAL and THANE using 3DVAR. https://doi.org/10.1007/s00024-013-0741-3.

  • Yesubabu, V., Srinivas, C. V., Ramakrishna, S. S. V. S., & Hari Prasad, K. B. R. R. (2014b). Impact of period and timescale of FDDA analysis nudging on the numerical simulation of tropical cyclones in the Bay of Bengal. Natural Hazards, 74(3), 2109–2128. https://doi.org/10.1007/s11069-014-1293-2.

    Article  Google Scholar 

Download references

Acknowledgements

The authors thank the ISRO-RESPOND project for providing financial support and necessary facilities to carry out the research work. We also thank the UGC, Government of India for providing the high-performance computing cluster (HPC) to carry out the experiments. The Indian Meteorological Department is acknowledged for providing the best track data and DWR products. The authors acknowledge the Cooperative Institute for Research in the Atmosphere (CIRA) and NOAA for providing various real-time cyclone products and CMORPH rainfall data used for the study.

Author information

Authors and Affiliations

  1. Department of Physics, S. V. University, Tirupati, 517502, India

    K. Vijaya Kumari, S. Karuna Sagar & S. Vijaya Bhaskara Rao

  2. Weather Climate Research Group, National Atmospheric Research Laboratories (NARL), Gadanki, Chittoor District, Andhra Pradesh, 517112, India

    Yesubabu Viswanadhapalli

  3. Physical Sciences and Engineering Division, King Abudullah University of Science and Technology (KAUST), Thuwal, 23955-6900, Kingdom of Saudi Arabia

    Hari Prasad Dasari

  4. National Centre for Medium Range Weather Forecasting (NCMRWF), Ministry of Earth Sciences (MoES), Noida, 201 309, India

    S. Karuna Sagar

Authors
  1. K. Vijaya Kumari
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. S. Karuna Sagar
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Yesubabu Viswanadhapalli
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Hari Prasad Dasari
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. S. Vijaya Bhaskara Rao
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yesubabu Viswanadhapalli.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Vijaya Kumari, K., Karuna Sagar, S., Viswanadhapalli, Y. et al. Role of Planetary Boundary Layer Processes in the Simulation of Tropical Cyclones Over the Bay of Bengal. Pure Appl. Geophys. 176, 951–977 (2019). https://doi.org/10.1007/s00024-018-2017-4

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00024-018-2017-4

Keywords

Search

Navigation