Abstract
The tropical cyclones (TCs) are most likely to increase over the North Indian Ocean (NIO) due to rapid heating in a warming climate. However, past studies have made contrasting statements while analyzing different study periods. This study examines the variability of TC’s characteristics such as severity, frequency, and longevity over the Arabian Sea (ARB) and the Bay of Bengal (BoB) during the satellite era (1990–2017). The cumulative frequency of depression, deep depression events and intense storms (combining very severe cyclonic storms, extremely severe cyclonic storms, and super cyclonic storms) have been found to increase (decrease) in the ARB (BoB). However, the cumulative frequency of all TCs (wind speed > 61 kmph) in the two basins has shown an insignificant change during the study period. The number of annual cyclonic days over both the basins has also witnessed a slight enhancement, suggesting an increase in the duration of TCs. Wind-driven energy metrics “power dissipation index (PDI)” and “accumulated cyclone energy (ACE)” are computed and compared against the mean sea level pressure-driven metric “accumulated cyclone intensity (ACI)” using the ‘Best-Tracks’ data from the India Meteorological Department (IMD), analyzing the climatology of cyclone’s destruction potential, energy, and intensity. The trends for three metrics have revealed a rise (fall) in the ARB (BoB), although not significant. Results indicate that the ARB basin has shown a higher capability of developing very intense TCs when compared to the BoB basin in recent years. Annually integrated values of the employed metrics have evidently affirmed the associated variations during the El Nino, La Nina, and Indian Ocean Dipole (IOD) phases. ACI values over both the basins were found to be increased in the La Nina years, whereas it decreased (increased) in the negative IOD years over the ARB (BoB).
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Data availability
The datasets used in this study are freely available and can be downloaded from the following links:
https://ggweather.com/enso/oni.htm.
http://www.bom.gov.au/climate/iod/.
https://psl.noaa.gov/gcos_wgsp/Timeseries/Data/nino34.long.data.
https://rsmcnewdelhi.imd.gov.in/report.php?internal_menu=MzM .
https://cds.climate.copernicus.eu/cdsapp#!/search?type=dataset.
References
Balaji M, Chakraborty A, Mandal M (2018) Changes in tropical cyclone activity in north Indian Ocean during satellite era (1981–2014). Int J Climatol. https://doi.org/10.1002/joc.5463
Bell GD, Chelliah M (2006) Leading tropical modes associated with interannual and multidecadal fluctuations in North Atlantic hurricane activity. J Clim 19:590–612. https://doi.org/10.1175/JCLI3659.1
Bell GD et al (2000) Climate assessment for 1999. Bull Am Meteorol Soc 81:1328. https://doi.org/10.1175/1520-0477(2000)81[s1:CAF]2.0.CO;2
Bhardwaj P, Singh O (2020) Climatological characteristics of Bay of Bengal tropical cyclones: 1972–2017. Theoret Appl Climatol 139(1–2):615–629. https://doi.org/10.1007/s00704-019-02989-4
Bhardwaj P, Pattanaik DR, Singh O (2019) Tropical cyclone activity over Bay of Bengal in relation to El Niño-Southern Oscillation. Int J Climatol 39:5452–5469. https://doi.org/10.1002/joc.6165
Camargo SJ, Sobel AH (2005) Western North Pacific tropical cyclone intensity and ENSO. J Clim 18:2996–3006. https://doi.org/10.1175/JCLI3457.1
Cione JJ, Uhlhorn EW (2003) Sea surface variability in hurricanes: implications with respect to intensity change. Mon Wea Rev 131:1783–1796. https://doi.org/10.1175//2562.1
Deo AA, Ganer DW (2014) Tropical cyclone activity over the Indian ocean in the warmer climate. In: Monitoring and Prediction of Tropical Cyclones in the Indian Ocean and Climate Change, Mohanty UC (ed). Springer: Dordrecht, pp 72–80. https://www.springer.com/gp/book/9789400777194
Deshpande M, Singh VK, Ganadhi MK (2021) Changing status of tropical cyclones over the north Indian Ocean. Clim Dyn. https://doi.org/10.1007/s00382-021-05880-z
Ebita A et al (2011) The Japanese 55-year reanalysis “JRA-55”: an interim report. SOLA 7:149–152. https://doi.org/10.2151/sola.2011-038
Emanuel KA (1987) The dependence of hurricane intensity on climate. Nature 326:483–485. https://doi.org/10.1038/326483a0
Emanuel K (2005) Increasing destructiveness of tropical cyclones over the past 30 years. Nature 436:686–688. https://doi.org/10.1038/nature03906
Emanuel K (2007) Environmental factors affecting tropical cyclone power dissipation. J Clim 20:5497–5509. https://doi.org/10.1175/2007JCLI1571.1
Evan AT, Camargo SJ (2011) A climatology of Arabian sea cyclonic storms. J Clim 24:140–158. https://doi.org/10.1175/2010JCLI3611.1
Girishkumar MS, Ravichandran M (2012) The influence of ENSO on tropical cyclone activity in the Bay of Bengal during October to December. J Geophys Res 117:c02033. https://doi.org/10.1029/2011JC007417
Hari V, Pathak A, Koppa A (2021) Dual response of Arabian Sea cyclones and strength of Indian monsoon to Southern Atlantic Ocean. Climate Dynamics 1–13.
Kendall MG (1938) A new measure of rank correlation. Biometrika 30(1–2):81–89. https://doi.org/10.1093/biomet/30.1-2.81
Klotzbach PJ (2006) Trends in global tropical cyclone activity over the past twenty years (1986–2005). Geophys Res Lett. https://doi.org/10.1029/2006GL025881
Lander MA, Guard CP (1998) A look at global tropical cyclone activity during 1995: contrasting high Atlantic activity with low activity in other basins. Mon Wea Rev 126:1163–1173. https://doi.org/10.1175/1520-0493(1998)126%3c1163:ALAGTC%3e2.0.CO;2
Miller BI (1958) On the maximum intensity of hurricanes. J Meteor 15:184–195. https://doi.org/10.1175/1520-0469(1958)015%3c0184:OTMIOH%3e2.0.CO;2
Mohapatra M, Kumar VV (2017) Interannual variation of tropical cyclone energy metrics over North Indian Ocean. Clim Dyn 48:1431–1445. https://doi.org/10.1007/s00382-016-3150-3
Mohapatra M, Bandyopadhyay BK, Tyagi A (2012) Best track parameters of tropical cyclones over the North Indian Ocean: a review. Nat Haz 63:1285–1317. https://doi.org/10.1007/s11069-011-9935-0
Palmen E (1948) On the formation and structure of tropical hurricanes. Geophysica 3:26–38. http://www.geophysica.fi/pdf/geophysica_1948_3_1_026_palmen.pdf
Rani SI, George JP, Rajagopal EN, Renshaw R, Maycock A, Barker DM, Rajeevan M (2021) IMDAA: high resolution satellite-era reanalysis for the Indian Monsoon Region. J Clim 34:1–78
Rayner NA, Parker DE, Horton EB, Folland CK, Alexander LV, Rowell DP, Kent EC, Lan AK (2003) Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late nineteenth century. J Geophys Res. https://doi.org/10.1029/2002jd002670
Riehl H (1979) Climate and weather in the tropics. Academic Press, New York, p 394
Saha S, Moorthi S, Pan H-L, Wu X, Wang J, Nadiga S et al (2010) The NCEP climate forecast system reanalysis. Bull Am Meteor Soc 91(8):1015–1058. https://doi.org/10.1175/2010bams3001.1
Sahoo B, Bhaskaran PK (2016) Assessment on historical cyclone tracks in the Bay of Bengal, east coast of India. Int J Climatol 36:95–109. https://doi.org/10.1002/joc.4331
Singh OP (2008) Indian Ocean dipole mode and tropical cyclone frequency. Curr Sci 94:29–31
Tiwari G, Rameshan A, Kumar P, Javed A, Mishra AK (2021) Understanding the post-monsoon tropical cyclone variability and trend over the Bay of Bengal during the satellite era. Q J R Meteorol Soc 148(742):1–14. https://doi.org/10.1002/qj.4189
Wahiduzzaman M, Yeasmin A (2019) Statistical forecasting of tropical cyclone landfall activities over the North Indian Ocean rim countries. Atmos Res 227:89–100. https://doi.org/10.1016/j.atmosres.2019.04.034
Wahiduzzaman M, Yeasmin A (2020) A kernel density estimation approach of North Indian Ocean tropical cyclone formation and the association with convective available potential energy and equivalent potential temperature. Meteorol Atmos Phys 132:603–612. https://doi.org/10.1007/s00703-019-00711-7
Wahiduzzaman M, Oliver ECJ, Wotherspoon SJ et al (2017) A climatological model of North Indian Ocean tropical cyclone genesis, tracks and landfall. Clim Dyn 49:2585–2603. https://doi.org/10.1007/s00382-016-3461-4
Wahiduzzaman M, Cheung K, Luo JJ et al (2021) Impact assessment of Indian Ocean Dipole on the North Indian Ocean tropical cyclone prediction using a Statistical model. Clim Dyn. https://doi.org/10.1007/s00382-021-05960-0
Wu L, Wang B, Braun SA (2008) Implications of tropical cyclone power dissipation index. Int J Climatol 28:727–731. https://doi.org/10.1002/joc.1573
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
Acknowledgements
The first author is thankful to the Department of Science and Technology, Government of India, for giving the DST-INSPIRE research fellowship, registration number IF160165. Indian Institute of Science Education and Research (IISER) Bhopal has provided the research facilities and laboratory environment. Pankaj Kumar acknowledges funding from the Department of Science and Technology (DST), Government of India, grant number DST/INT/RUS/RSF/P-33/G, and the Russian Science Foundation (Project No.: 19-47-02015). Aaquib Javed acknowledges IISER Bhopal for the PhD fellowship. For data used in the study, India Meteorological Department, European Centre for Medium-range Weather Forecasting, National Oceanic and Atmospheric Administration-Physical Sciences Laboratory, Climate Prediction Center, and Met Office Hadley Centre are acknowledged.
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Tiwari, G., Kumar, P., Javed, A. et al. Assessing tropical cyclones characteristics over the Arabian Sea and Bay of Bengal in the recent decades. Meteorol Atmos Phys 134, 44 (2022). https://doi.org/10.1007/s00703-022-00883-9
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DOI: https://doi.org/10.1007/s00703-022-00883-9