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Climate Dynamics

, Volume 53, Issue 3–4, pp 2103–2118 | Cite as

Meridional oscillation in genesis location of tropical cyclones in the postmonsoon Bay of Bengal

  • Kaigui Fan
  • Xidong WangEmail author
  • Gregory R. Foltz
  • Karthik Balaguru
Article

Abstract

It is found that the average genesis location of tropical cyclones (TCs) in the postmonsoon (October–December) Bay of Bengal (BoB) shows a notable meridional oscillation during 1980–2015. During years when the average genesis location shifts northward (north-years), the average maximum sustained wind speed, the average landfall wind speed and the number of category 4–5 TCs are all larger than those during years when the average genesis location displaces southward (south-years). Genesis potential index analysis shows that changes in relative humidity and vertical wind shear are mainly responsible for the meridional oscillation of the average genesis location of TCs. The changes in relative humidity and wind shear are closely related to changes in atmospheric circulation. Composite analysis reveals that sea surface temperature (SST) anomalies over the equatorial Pacific Ocean show a La Niña-like pattern (El Niño-like pattern) during north-years (south-years) of TC genesis locations. The SST anomalies over the equatorial Pacific Ocean induce a strengthened (weakened) Walker circulation during north-years (south-years) of TC genesis locations, influencing the atmospheric circulation over the tropical Indian Ocean. In addition, a stationary Rossby wave train from the North Pacific to the Iranian Plateau (east of Iranian Plateau) during north-years (south-years) induces changes in atmospheric circulation over the extratropical North Indian Ocean. Together, the tropical and extratropical influences contribute to the north–south patterns of relative humidity and vertical wind shear anomalies in the postmonsoon BoB, which drive the meridional oscillation of TC genesis locations. This study has significant implications for the prediction of TCs and disaster prevention and mitigation over the BoB.

Keywords

Bay of Bengal Tropical cyclone El Niño-Southern Oscillation Pacific Decadal Oscillation 

Notes

Acknowledgements

This study is supported by the National Natural Science Foundation (41776004), the Fundamental Research Funds for the Central Universities (2016B12514), the Opening Project of Key Laboratory of Marine Environmental Information Technology and the China Ocean Mineral Resources Research and Development Association Program (DY135-E2-3-02). GF was supported by base funds to NOAA/AOML. The authors sincerely acknowledge the use of TC best track data from Joint Typhoon Warning Center, and atmospheric and oceanic reanalysis from NCEP and ECMWF. Potential intensity is calculated using the MATLAB code available at ftp://texmex.mit.edu/pub/emanuel/TCMAX/. The Fortran code for calculating wave-activity flux can be downloaded from the website at http://www.atmos.rcast.u-tokyo.ac.jp/nishii/programs/index.html.

References

  1. Alam M, Hossain M, Shafee S (2003) Frequency of Bay of Bengal cyclonic storms and depressions crossing different coastal zones. Int J Climatol 23:1119–1125.  https://doi.org/10.1002/joc.927 CrossRefGoogle Scholar
  2. Balaguru K, Taraphdar S, Leung L, Foltz G (2014) Increase in the intensity of postmonsoon Bay of Bengal tropical cyclones. Geophys Res Lett 41:3594–3601.  https://doi.org/10.1002/2014gl060197 CrossRefGoogle Scholar
  3. Balaguru K, Leung L, Lu J, Foltz G (2016) A meridional dipole in premonsoon Bay of Bengal tropical cyclone activity induced by ENSO. J Geophys Res Atmos 121:6954–6968.  https://doi.org/10.1002/2016jd024936 CrossRefGoogle Scholar
  4. Balaji M, Chakraborty A, Mandal M (2018) Changes in tropical cyclone activity in north Indian Ocean during satellite era (1981–2014). Int J Climatol 38:2819–2837.  https://doi.org/10.1002/joc.5463 CrossRefGoogle Scholar
  5. Bister M, Emanuel K (2002) Low frequency variability of tropical cyclone potential intensity 1. Interannual to interdecadal variability. J Geophys Res 107:4801.  https://doi.org/10.1029/2001jd000776 CrossRefGoogle Scholar
  6. Bolton D (1980) The computation of equivalent potential temperature. Mon Weather Rev 108:1046–1053.  https://doi.org/10.1175/1520-0493(1980)108%3c1046:TCOEPT%3e2.0.CO;2 CrossRefGoogle Scholar
  7. Camargo S, Wheeler M, Sobel A (2009) Diagnosis of the MJO modulation of tropical cyclogenesis using an empirical index. J Atmos Sci 66:3061–3074.  https://doi.org/10.1175/2009jas3101.1 CrossRefGoogle Scholar
  8. Dee D et al (2011) The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Q J R Meteorol Soc 137:553–597.  https://doi.org/10.1002/qj.828 CrossRefGoogle Scholar
  9. Emanuel K (2003) Tropical cyclones. Annu Rev Earth Planet Sci 31:75–104.  https://doi.org/10.1146/annurev.earth.31.100901.141259 CrossRefGoogle Scholar
  10. Emanuel K, Nolan D (2004) Tropical cyclone activity and the global climate system. In: Proceedings of the 26th conference on hurricanes and tropical meteorology. American Meteorological Society, Miami, FL, pp 240–241Google Scholar
  11. Felton C, Subrahmanyam B, Murty V (2013) ENSO-modulated cyclogenesis over the Bay of Bengal. J Clim 26:9806–9818.  https://doi.org/10.1175/jcli-d-13-00134.1 CrossRefGoogle Scholar
  12. Girishkumar M, Ravichandran M (2012) The influences of ENSO on tropical cyclone activity in the Bay of Bengal during October–December. J Geophys Res Oceans 117:C02033.  https://doi.org/10.1029/2011jc007417 CrossRefGoogle Scholar
  13. Girishkumar M, Suprit K, Vishnu S, Prakash V, Ravichandran M (2014a) The role of ENSO and MJO on rapid intensification of tropical cyclones in the Bay of Bengal during October–December. Theor Appl Climatol 120:797–810.  https://doi.org/10.1007/s00704-014-1214-z CrossRefGoogle Scholar
  14. Girishkumar M, Thanga Prakash V, Ravichandran M (2014b) Influence of Pacific Decadal Oscillation on the relationship between ENSO and tropical cyclone activity in the Bay of Bengal during October–December. Clim Dyn 44:3469–3479.  https://doi.org/10.1007/s00382-014-2282-6 CrossRefGoogle Scholar
  15. Gon Z, Wang P, Ma J (2002) Application of a simplified calculation scheme for mean meridional circulation mass stream function (in Chinese). J Nanjing Inst Meteorol 25:328–333.  https://doi.org/10.13878/j.cnki.dqkxxb.2002.03.006 Google Scholar
  16. Gray W (1968) Global view of the origin of tropical disturbances and stroms. Mon Weather Rev 96:669–700.  https://doi.org/10.1175/1520-0493(1968)096%3c0669:GVOTOO%3e2.0.CO;2 CrossRefGoogle Scholar
  17. Gray W (1985) Tropical cyclone global climatology. WMO Technical Document WMO/TD 72:3–19Google Scholar
  18. Hu C, Zhang C, Yang S, Chen D, He S (2017) Perspective on the northwestward shift of autumn tropical cyclogenesis locations over the western North Pacific from shifting ENSO. Clim Dyn 51:2455–2465.  https://doi.org/10.1007/s00382-017-4022-1 CrossRefGoogle Scholar
  19. Jiang X, Zhao M, Waliser D (2012) Modulation of tropical cyclones over the Eastern Pacific by the intraseasonal variability simulated in an AGCM. J Clim 25:6524–6538.  https://doi.org/10.1175/jcli-d-11-00531.1 CrossRefGoogle Scholar
  20. Kalnay E et al (1996) The NCEP/NCAR 40-year reanalysis project. Bull Am Meteorol Soc 77:437–472.  https://doi.org/10.1175/1520-0477(1996)077%3c0437:TNYRP%3e2.0.CO;2 CrossRefGoogle Scholar
  21. Kosaka Y, Nakamura H (2006) Structure and dynamics of the summertime Pacific-Japan teleconnection pattern. Q J R Meteorol Soc 132:2009–2030.  https://doi.org/10.1256/qj.05.204 CrossRefGoogle Scholar
  22. Krishnamurthy L, Krishnamurthy V (2013) Influence of PDO on South Asian summer monsoon and monsoon–ENSO relation. Clim Dyn 42:2397–2410.  https://doi.org/10.1007/s00382-013-1856-z CrossRefGoogle Scholar
  23. Kurtzman D, Scanlon B (2007) El Niño-Southern Oscillation and Pacific Decadal Oscillation impacts on precipitation in the southern and central United States: evaluation of spatial distribution and predictions. Water Resour Res.  https://doi.org/10.1029/2007wr005863 Google Scholar
  24. Li Z, Yu W, Li T, Murty V, Tangang F (2013) Bimodal character of cyclone climatology in the Bay of Bengal modulated by monsoon seasonal cycle. J Clim 26:1033–1046.  https://doi.org/10.1175/jcli-d-11-00627.1 CrossRefGoogle Scholar
  25. Liu K, Chan J (2013) Inactive period of Western North Pacific Tropical Cyclone activity in 1998–2011. J Clim 26:2614–2630.  https://doi.org/10.1175/jcli-d-12-00053.1 CrossRefGoogle Scholar
  26. Maue R (2011) Recent historically low global tropical cyclone activity. Geophys Res Lett 38:L14803.  https://doi.org/10.1029/2011gl047711 CrossRefGoogle Scholar
  27. McBride J (1995) Tropical cyclone formation. Global perspective on tropical cyclones. World Meteorological Association, Geneva, pp 63–105Google Scholar
  28. Mohanty U, Mohapatra M, Singh O, Bandyopadhyay B, Rathore L (2013) Monitoring and prediction of tropical cyclones in the Indian Ocean and climate change. Springer Science and Business Media, New YorkGoogle Scholar
  29. Rayner N et al (2003) Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late nineteenth century. J Geophys Res Atmos 108:4407.  https://doi.org/10.1029/2002jd002670 CrossRefGoogle Scholar
  30. Shi N, Wang X, Zhang L, Xu H (2016) Features of Rossby wave propagation associated with the evolution of summertime blocking highs with different configurations over northeast Asia. Mon Weather Rev 144:2531–2546.  https://doi.org/10.1175/mwr-d-15-0369.1 CrossRefGoogle Scholar
  31. Takaya K, Nakamura H (2001) A formulation of a phase-independent wave-activity flux for stationary and migratory quasigeostrophic eddies on a zonally varying basic flow. J Atmos Sci 58:608–627.  https://doi.org/10.1175/1520-0469(2001)058%3c0608:AFOAPI%3e2.0.CO;2 CrossRefGoogle Scholar
  32. Wang P (1994) Diagnosis of mean meridional circulation of the model atmosphere in the GCM with low resolution vertically (in Chinese). J Nanjing Inst Meteorol 17:200–204.  https://doi.org/10.13878/j.cnki.dqkxxb.1994.02.012 Google Scholar
  33. Wang X, Liu H (2015) PDO modulation of ENSO effect on tropical cyclone rapid intensification in the western North Pacific. Clim Dyn 46:15–28.  https://doi.org/10.1007/s00382-015-2563-8 CrossRefGoogle Scholar
  34. Wang L, Chen W, Huang R (2008) Interdecadal modulation of PDO on the impact of ENSO on the east Asian winter monsoon. Geophys Res Lett 35:L20702.  https://doi.org/10.1029/2008gl035287 CrossRefGoogle Scholar
  35. Wang S, Buckley B, Yoon J, Fosu B (2013) Intensification of premonsoon tropical cyclones in the Bay of Bengal and its impacts on Myanmar. J Geophys Res Atmos 118:4373–4384.  https://doi.org/10.1002/jgrd.50396 CrossRefGoogle Scholar
  36. Wang X, Wang C, Zhang L, Wang X (2015) Multidecadal variability of tropical cyclone rapid intensification in the Western North Pacific. J Clim 28:3806–3820.  https://doi.org/10.1175/jcli-d-14-00400.1 CrossRefGoogle Scholar
  37. Wang C, Wang X, Weisberg R, Black M (2017) Variability of tropical cyclone rapid intensification in the North Atlantic and its relationship with climate variations. Clim Dyn 49:3627–3645.  https://doi.org/10.1007/s00382-017-3537-9 CrossRefGoogle Scholar
  38. Webster P, Holland G, Curry J, Chang H (2005) Changes in tropical cyclone number, duration, and intensity in a warming environment. Science 309:1844–1846.  https://doi.org/10.1126/science.1116448 CrossRefGoogle Scholar
  39. Wu R, Wang B (2002) A contrast of the East Asian summer monsoon–ENSO relationship between 1962–77 and 1978–93. J Clim 15:3266–3279.  https://doi.org/10.1175/1520-0442(2002)015%3c3266:ACOTEA%3e2.0.CO;2 CrossRefGoogle Scholar
  40. Yanase W, Satoh M, Taniguchi H, Fujinami H (2012) Seasonal and intraseasonal modulation of tropical cyclogenesis environment over the Bay of Bengal during the extended summer monsoon. J Clim 25:2914–2930.  https://doi.org/10.1175/jcli-d-11-00208.1 CrossRefGoogle Scholar
  41. Yang L, Chen S, Wang C, Wang D, Wang X (2017) Potential impact of the Pacific Decadal Oscillation and sea surface temperature in the tropical Indian Ocean-Western Pacific on the variability of typhoon landfall on the China coast. Clim Dyn 51:2695–2705.  https://doi.org/10.1007/s00382-017-4037-7 CrossRefGoogle Scholar
  42. Yu B, Zwiers F (2007) The impact of combined ENSO and PDO on the PNA climate: a 1,000-year climate modeling study. Clim Dyn 29:837–851.  https://doi.org/10.1007/s00382-007-0267-4 CrossRefGoogle Scholar
  43. Yu B, Zwiers F (2010) Changes in equatorial atmospheric zonal circulations in recent decades. Geophys Res Lett 37:L05701.  https://doi.org/10.1029/2009gl042071 Google Scholar
  44. Yu B, Zwiers F, Boer G, Ting M (2012) Structure and variances of equatorial zonal circulation in a multimodel ensemble. Clim Dyn 39:2403–2419.  https://doi.org/10.1007/s00382-012-1372-6 CrossRefGoogle Scholar
  45. Zhao H, Wang C (2015) Interdecadal modulation on the relationship between ENSO and typhoon activity during the late season in the western North Pacific. Clim Dyn 47:315–328.  https://doi.org/10.1007/s00382-015-2837-1 CrossRefGoogle Scholar
  46. Zhao H, Duan X, Raga G, Klotzbach P (2018) Changes in characteristics of rapidly intensifying Western North Pacific tropical cyclones related to climate regime shifts. J Clim 31:8163–8179.  https://doi.org/10.1175/jcli-d-18-0029.1 CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Kaigui Fan
    • 1
  • Xidong Wang
    • 1
    • 2
    Email author
  • Gregory R. Foltz
    • 3
  • Karthik Balaguru
    • 4
  1. 1.College of OceanographyHohai UniversityNanjingChina
  2. 2.Laboratory for Regional Oceanography and Numerical ModelingQingdao National Laboratory for Marine Science and TechnologyQingdaoChina
  3. 3.Atlantic Oceanographic and Meteorological LaboratoryMiamiUSA
  4. 4.Marine Sciences LaboratoryPacific Northwest National LaboratorySeattleUSA

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