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Pure and Applied Geophysics

, Volume 176, Issue 1, pp 441–461 | Cite as

Moisture Budget of the Tropical Cyclones Formed over the Bay of Bengal: Role of Soil Moisture After Landfall

  • N. Nanaji Rao
  • V. Brahmananda Rao
  • S. S. V. S. RamakrishnaEmail author
  • B. R. Srinivasa Rao
Article
  • 119 Downloads

Abstract

In the present study, the water budget of the Bay of Bengal tropical cyclones at varying intensities is analyzed. Results show that rainfall is not directly related to the intensities of tropical cyclones. A secondary peak in precipitation after landfall causes huge damage through floods and mud slides. The analysis of the water budget shows that the moisture flux convergence was the dominant term before landfall and contributes to 61% of the rainfall, while the remaining 39% is contributed by evaporation. After landfall, evaporation contributed 63% of the rainfall and 37% of rainfall was contributed by moisture flux convergence. The contribution of evaporation changed little with time in all the 12 case studies. Out of the 12 cyclones of varying intensities, seven cyclones either showed a secondary peak in precipitation or maintained a high rainfall over land. For the high rainfall over land, after the landfall, soil moisture was found to be important both in the observation and simulations of the Weather Research and Forecasting model. The predicted cyclone track errors are reduced in the model experiment with soil moisture, while the predicted cyclone intensity errors are less in the experiment without soil moisture. Accurate soil-moisture data are required for better prediction of cyclone track and their intensities.

Keywords

Tropical cyclones moisture budget precipitation evaporation landfall WRF–ARW model 

Notes

Acknowledgements

Plots in this work are made using the GrADS, software which is freely available online. The authors are thankful to the Indian Meteorological Department for making available all the observations for validation.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

References

  1. Andersen, T. K., & Shepherd, J. M. (2014). A global spatiotemporal analysis of inland tropical cyclone maintenance or intensification. International Journal of Climatology, 34, 391–402.  https://doi.org/10.1002/joc.3693.CrossRefGoogle Scholar
  2. Baisya, H., Pattnaik, S., Hazra, V., Sisodiya, A., & Rai, D. (2018). Ramifications of atmospheric humidity on monsoon depressions over the Indian Subcontinent. Scientific Reports, 8, 9927.  https://doi.org/10.1038/s41598-018-28365-2.CrossRefGoogle Scholar
  3. Baisya, H., Pattnaik, Sandeep, & Rajesh, P. V. (2017). Land surface-precipitation feedback analysis for a landfalling monsoon depression in the Indian, region. Journal of Advances in Modeling Earth Systems, 9, 712–726.  https://doi.org/10.1002/2016MS000829.CrossRefGoogle Scholar
  4. Braun, S. A., Montgomery, M. T., Mallen, K. J., & Reasor, P. D. (2010). Simulation and interpretation of the genesis of Tropical Storm Gert (2005) as part of the NASA Tropical Cloud Systems and Processes Experiment. Journal of Atmospheric Science, 67(4), 999–1025.CrossRefGoogle Scholar
  5. Charney, J. G., & Eliassen, A. (1964). On the growth of the hurricane depression. Journal of Atmospheric Science, 21, 68–75.CrossRefGoogle Scholar
  6. Chen, F., & 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.CrossRefGoogle Scholar
  7. DeMaria, M., DeMaria, R. T., Knaff, J. A., & Molenar, D. (2012). Tropical cyclone lightning and rapid intensity change. Monthly Weather Review, 140, 1828–1842.  https://doi.org/10.1175/MWR-D-11-00236.1.CrossRefGoogle Scholar
  8. DeMaria, M., Sampson, C. R., Knaff, J. A., & Musgrave, K. D. (2014). Is tropical cyclone intensity guidance improving? Bulletin of the American Meteorological Society, 95, 387–398.  https://doi.org/10.1175/BAMS-D-12-00240.1.CrossRefGoogle Scholar
  9. Dube, S. K., Rao, A. D., Sinha, P. C., Murty, T. S., & Bahulayan, N. (1997). Storm surge in the Bay of Bengal and Arabian Sea: The problem and its prediction. Mausam, 48, 283–304.Google Scholar
  10. Dunkerton, T. J., Montgomery, M. T., & Wang, Z. (2009). Tropical cyclogenesis in a tropical wave critical layer: Easterly waves. Atmospheric Chemistry and Physics, 9(15), 5587–5646.CrossRefGoogle Scholar
  11. Emanuel, K. A. (1986). An air–sea interaction theory for tropical cyclones. Part I: Steady state maintenance. Journal of Atmospheric Science, 43, 585–604.CrossRefGoogle Scholar
  12. Emanuel, K., Callaghan, J., & Otto, P. (2008). A hypothesis for the redevelopment of warm–core cyclones over northern Australia. Monthly Weather Review, 136, 3863–3872.  https://doi.org/10.1175/2008MWR2409.1.CrossRefGoogle Scholar
  13. Environmental Modeling Center. (2003). The GFS atmospheric model. NCEP Office Note, p. 44214. http://www.emc.ncep.noaa.gov/officenotes/newernotes/on442.pdf.
  14. Evans, C., Schumacher, R. S., & Galarneau, T. J. (2011). Sensitivity in the overland reintensification of Tropical Cyclone Erin (2007) to near surface soil moisture characteristics. Monthly Weather Review, 139, 3848–3870.  https://doi.org/10.1175/2011MWR3593.1.CrossRefGoogle Scholar
  15. Falvey, R. (2012). Summary of the 2011 Western Pacific/Indian Ocean tropical cyclone season. In: Proceedings of 66th interdepartmental Hurricane conference, Charleston, SC, OFCM. http://www.ofcm.gov/ihc12/Presentations/01b-Session/05-JTWC_2012_IHC_Final.pdf.
  16. Gao, S., Zhai, S., Chen, B., & Li, T. (2017). Water budget and intensity change of tropical cyclones over the western North Pacific. Mon: Weather Review.  https://doi.org/10.1175/MWR-D-17-0033.1.CrossRefGoogle Scholar
  17. Gray, W. M. (1968). Global view of the origin of tropical disturbances and storms. Monthly Weather Review, 96, 669–700.CrossRefGoogle Scholar
  18. Gray, W. M. (1975) Tropical cyclone genesis. Dept of Atmospheric Science Paper, 234, Colorado State University, Fort Collins, CO, p. 121.Google Scholar
  19. Gray, W. M. (1985). Technical document WMO/TD No. 72 (Vol. 1, pp. 3–19). Geneva: WMO.Google Scholar
  20. Haque, S. M. A. (1952). The initiation of cyclonic circulation in a vertically unstable stagnant air mass. Quarterly Journal of the Royal Meteorological Society, 78, 394–406.CrossRefGoogle Scholar
  21. Hari, P. D., Brahmananda, R. V., Ramakrishna, S. S. V. S., Paparao, G., Nanaji, R., & Kumar, N. R. P. (2017). On the movement of tropical cyclone LEHAR. Earth Systems and Environment.  https://doi.org/10.1007/s41748-017-0025-7.Google Scholar
  22. Hendricks, E. A., Montgomery, M. T., & Davis, C. A. (2004). The role of “vortical” hot towers in the formation of tropical cyclone Diana (1984). Journal of Atmospheric Science, 61(11), 1209–1232.CrossRefGoogle Scholar
  23. Hong, S. Y., & Dudhia, J. (2006). A new vertical diffusion package with explicit treatment of entrainment processes. Monthly Weather Review, 134, 2318–2341.CrossRefGoogle Scholar
  24. Hong, S. Y., Dudhia, J., & Chen, S. H. (2004). A revised approach to ice microphysical processes for the bulk parameterization of clouds and precipitation. Monthly Weather Review, 132, 103–120.CrossRefGoogle Scholar
  25. Huffman, G. J., Adler, R. F., Bolvin, D. T., Gu, G., Nelkin, E. J., Hong, Y., et al. (2007). The TRMM multisatellite precipitation analysis (TMPA): Quasi-global, multiyear, combined-sensor precipitation estimates at fine scales. Journal of Hydrometeorology, 8(1), 38–55.  https://doi.org/10.1175/JHM560.1.CrossRefGoogle Scholar
  26. Jiang, H., Halverson, J. B., Simpson, J., & Zipser, E. J. (2008). On the differences in storm rainfall from hurricanes Isidore and Lili. Part II: Water budget. Weather Forecasting, 23(1), 44–61.CrossRefGoogle Scholar
  27. Kain, J. S. (2004). The Kain–Fritsch convective parameterization: An update. Journal of Applied Meteorology, 43, 170–181.CrossRefGoogle Scholar
  28. Kain, J. S., & Fritsch, J. M. (1993). Convective parameterization for mesoscale models: The Kain–Fritcsh scheme. In K. A. Emanuel & D. J. Raymond (Eds.), The representation of cumulusconvection in numerical models (p. 246). Geneseo: American Meteor Society.Google Scholar
  29. Kalnay, E., et al. (1996). The NCEP/NCAR 40-year reanalysis project. Bulletin of the American Meteorological Society, 77, 437–471.CrossRefGoogle Scholar
  30. Kepert, J. D. (2010). Tropical cyclone structure and dynamics. In J. C. Chan & J. D. Kepert (Eds.), Global perspectives on the tropical cyclones (pp. 3–54). Singapore: World Scientific.CrossRefGoogle Scholar
  31. Kuo, H. L. (1961). Convection in conditionally unstable atmosphere. Tellus, 13, 441–459.CrossRefGoogle Scholar
  32. Landsea, C. W., & Franklin, J. L. (2013). Atlantic hurricane database uncertainty and presentation of a new database format. Monthly Weather Review, 141, 3576–3592.CrossRefGoogle Scholar
  33. Leary, L. A., & Elizabeth, A. R. (2009). Lightning flash rates as an indicator of tropical cyclone genesis in the Eastern North Pacific. Monthly Weather Review, 137, 3456–3470.CrossRefGoogle Scholar
  34. Lilly, D. K. (1960). On the theory of disturbances in a conditionally unstable atmosphere. Monthly Weather Review, 88, 1–17.CrossRefGoogle Scholar
  35. Mahmood, R., Foster, S. A., Keeling, T., Hubbard, K. G., Carlson, C., & Leeper, R. (2006). Impacts of irrigation on 20th century temperature in the northern Great Plains. Global and Planetary Change, 54, 1–18.  https://doi.org/10.1016/j.gloplacha.2005.10.004.CrossRefGoogle Scholar
  36. Maurya, D. K., Rao, P. V. N., Dadhwal, V. K., & Dutt, C. B. S. (2015). Large area soil moisture variations in response to cyclone Phailin in Eastern India. IEEE Geoscience and Remote Sensing Letters, 12(2), 264–268.CrossRefGoogle Scholar
  37. McAdie, C. M., & Lawrence, M. B. (2000). Improvements in tropical cyclone track forecasting in the Atlantic basin, 1970–98. Bulletin of the American Meteorological Society, 81, 989–997.CrossRefGoogle Scholar
  38. Montgomery, M. T., Nicholls, M. E., Cram, T. A., & Saunders, A. B. (2006). A vortical hot tower route to tropical cyclogenesis. Journal of Atmospheric Science, 63(1), 355–386.CrossRefGoogle Scholar
  39. NCEP FNL. (2000). National Centers for Environmental Prediction/National Weather Service/NOAA/U.S. Department of Commerce. 2000, updated daily. NCEP FNL Operational Model Global Tropospheric Analyses, continuing from July 1999. Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory.  https://doi.org/10.5065/d6m043c6.
  40. Ooyama, K. (1964). A dynamical model for the study of tropical cyclone development. Geofisica Internacional, 4, 197–198.Google Scholar
  41. Ooyama, K. (1969). Numerical simulation of the life cycle of tropical cyclones. Journal of Atmospheric Science, 26(1), 3–40.CrossRefGoogle Scholar
  42. Ooyama, K. V. (1982). Concenptual evolution of the theory and modeling of the tropical cyclone. Journal of the Meteorological Society of Japan, 60(1), 369–380.CrossRefGoogle Scholar
  43. 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.CrossRefGoogle Scholar
  44. 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(11), 2476–2492.CrossRefGoogle Scholar
  45. Palmen, E. (1948). On the formation and structure of tropical hurricanes. Geophysica, 3, 26–38.Google Scholar
  46. Peixoto, J., & Oort, A. (1992). Physics of climate (p. 520). Berlin: Springer.Google Scholar
  47. Praveen, K. B., Vialard, J., Lengaigne, M., Murty, V. S. N., & McPhaden, M. J. (2011). TropFlux: Air-sea fluxes for the global tropical oceans-description and evaluations. Climate Dynamics.  https://doi.org/10.1007/s00382-011-1115-0.Google Scholar
  48. Price, C., Asfur, M., & Yair, Y. (2009). Maximum hurricane intensity preceded by increase in lightning frequency. Nature Geoscience, 2, 329–332.CrossRefGoogle Scholar
  49. Rajasree, V. P. M., Kesarkar, A. P., Bhate, J. N., Umakanth, U., Singh, V., & Varma, T. H. (2016). Appraisal of recent theories to understand cyclogenesis pathways of tropical cyclone Madi (2013). Journal of Geophysical Research, 121, 8949–8982.  https://doi.org/10.1002/2016JD025188.Google Scholar
  50. Ramakrishna, S. S. V. S., Srinivas, C. V., Sravani, A., Rao, N. N., Rao, V. L., & Saradhi, N. C. (2014). Simulation of pre monsoon cyclones of two contrasting monsoon years using Meso scale model WRF (ARW). Montoring and prediction of tropical cyclones in the Indian Ocean and Climate Change (pp. 319–336). The Netherlands: Springer.Google Scholar
  51. Ramakrishna, S. S. V. S., Vijaya, Saradhi N., & Srinivas, C. V. (2012). On the role of the Planetary Boundary Layer in the numerical simulation of a severe cyclonic storm Nargis using a mesoscale model. Natural Hazards, 63(3), 1471–1496.CrossRefGoogle Scholar
  52. Riehl, H., & Malkus, J. (1958). On the heat balance in the equatorial trough zone. Geophysica, 6, 503–538.Google Scholar
  53. Rotunno, R., & Emanuel, K. A. (1987). An air-sea interaction theory for tropical cyclones. Part II: Evolutionary study using a non-hydrostatic axisymmetric numerical model. Journal of Atmospheric Science, 44, 542–561.CrossRefGoogle Scholar
  54. Skamarock, W. C., Klemp, J. B., Dudhia, J., Gill, D. O., Barker, D. M., Dudha, M. G., et al. (2008). ‘A description of the advanced research WRF version 30′. NCAR Technical Note NCAR/TN-475 + STR. Boulder: Mesoscale and Microscale Meteorology Divison, National Centre for Atmospheric Research.Google Scholar
  55. Smith, R. K. (1997). On the theory of CISK. Quarterly Journal of the Royal Meteorological Society, 123(538), 407–418.CrossRefGoogle Scholar
  56. Srinivas, C. V., BhaskarRao, D. V., Yesubabu, V., Baskaran, R., & Venkatraman, B. (2013). 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.CrossRefGoogle Scholar
  57. Strong, G. S., Proctor, B., Wang, M., Soulis, E. D., Smith, C. D., Seglenieks, F., et al. (2002). Closing the Mackenzie Basin water budget, water years 1994/95 to 1996/97. Atmosphere Ocean, 40(2), 113–124.CrossRefGoogle Scholar
  58. Syono, S. (1953). On the formation of tropical cyclones. Tellus, 5, 179–195.CrossRefGoogle Scholar
  59. Trenberth, K. E., & Fasullo, J. (2007). Water and energy budgets of hurricanes and implications for climate change. Journal of Geophysical Research, 112, D23107.  https://doi.org/10.1029/2006JD008304.CrossRefGoogle Scholar
  60. Wei, W., Jilong, C., & Ronghui, H. (2013). Water budgets of tropi-cal cyclones: Three case studies. Advances in Atmpsheric Sciences, 30, 468–484.CrossRefGoogle Scholar
  61. Yang, M.-J., Braun, S. A., & Chen, D.-S. (2010). Water budget of typhoon Nari (2001). Monthly Weather Review, 139(12), 3809–3828.CrossRefGoogle Scholar
  62. Zhou, T.-J., & Yu, R. C. (2005). Atmospheric water vapor transport associated with typical anomalous summer rainfall patterns in China. Journal of Geophysical Research, 110, D08104.  https://doi.org/10.1029/2004JD005431.Google Scholar

Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • N. Nanaji Rao
    • 1
  • V. Brahmananda Rao
    • 1
  • S. S. V. S. Ramakrishna
    • 1
    Email author
  • B. R. Srinivasa Rao
    • 1
  1. 1.Department of Meteorology and OceanographyAndhra UniversityVisakhapatnamIndia

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