Skip to main content

Advertisement

SpringerLink
Log in

Response of tropical cyclone Phailin (2013) in the Bay of Bengal to climate perturbations

  • Published:
Climate Dynamics Aims and scope Submit manuscript

Abstract

Tropical cyclones in the Bay of Bengal (BoB) are the major source of loss of properties and lives in the adjacent coastal regions during post-monsoon (October–November) season. This study explores the impact of large-scale environmental change on tropical cyclone (TC) Phailin (2013) in the Bay of Bengal. An ensemble simulation with a regional atmospheric model using different physics and initial conditions is able to capture the observed track of Phailin. The cyclone intensity, however, is underestimated due to the coarse resolution (10 km) of the model. To explore Phailin’s response to a warming climate, a global climate model change signal is added to the cyclone environment using the pseudo-global warming approach, and the ensemble is run again. It is found that changes in the track of Phailin would be small, except around the time of landfall, when Phailin shifts southward in its track. The cyclone becomes more intense and larger, but the translation speed remains nearly unchanged. An analysis of physical processes indicates a deeper TC core due to enhanced latent heating. The vertical distribution of temperature and wind indicates that the eye of Phailin would have a greater vertical extent in the future climate. The expanded size is found to be due to an increase in environmental humidity and temperature in the lower-troposphere leading to an increase in environmental convective available potential energy. The translation speed remains nearly unchanged due to insignificant changes in the steering flow. The result suggests that Phailin, under a warmer climate, may have higher damage potential (~ 22%) compared to the present at the time of landfall.

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

Access this article

Log in via an institution

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

Similar content being viewed by others

References

  • Balaguru K, Taraphdar S, Leung LR, Foltz GR (2014) Increase in the intensity of post-monsoon Bay of Bengal tropical cyclones. Geophys Res Lett 41(10):3594–3601

    Article  Google Scholar 

  • Carr LE III, Elsberry RL (1990) Observational evidence for predictions of tropical cyclone propagation relative to environmental steering. J Atmos Sci 47:542–548

    Article  Google Scholar 

  • Chan KTF, Chan JCL (2012) Size and strength of tropical cyclones as inferred from QuikSCAT data. Mon Weather Rev 140:811–824

    Article  Google Scholar 

  • Chan KTF, Chan JCL (2015) Impacts of vortex intensity and outer winds on tropical cyclone size. Q J R Meteorol Soc 141:525–537

    Article  Google Scholar 

  • Chan JC, Gray WM (1982) Tropical cyclone movement and surrounding flow relationships. Mon Weather Rev 110:1354–1374

    Article  Google Scholar 

  • Chandrasekar R, Balaji C (2012) Sensitivity of tropical cyclone Jal simulations to physics parameterizations. J Earth Syst Sci 121(4):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. Nat Hazards 80:223–247

    Article  Google Scholar 

  • Chavas DR, Lin N, Dong W, Lin Y (2016) Observed tropical cyclone size revisited. J Clim. https://doi.org/10.1175/JCLI-D-15-0731.1

    Google Scholar 

  • Chen F, Dudhia J (2001) Coupling an advanced land surface hydrology model with the Penn State–NCAR MM5 modeling system. Part I: model implementation and sensitivity. Mon Weather Rev 129:569–585

    Article  Google Scholar 

  • Davis C, Wang W, Chen SS, Chen Y, Corbosiero K, DeMaria M, Dudhia J, Holland G, Klemp J, Michalakes J, Reeves H, Rotunno R, Snyder C, Xiao Q (2008) Prediction of landfalling hurricanes with the advanced hurricane WRF model. Mon Weather Rev. 136:1990–2005

    Article  Google Scholar 

  • Dee DP, Uppala SM, Simmons AJ, Berrisford P, Poil P, Kobayashi S, Andrae U, Balmaseda MA, Balsamo G, Bauer P, Bechtold P, Beljaars ACM, van de Berg L, Bidlot J, Bormann N, Delsol C, Dragani R, Fuentes M, Geer AJ, Haimberger L, Healy SB, Hersbach H, Hólm EV, Isaksen L, Kållberg P, Köhler M, Matricardi M, McNally AP, Monge-Sanz BM, Morcrette JJ, Park BK, Peubey C, de Rosnay P, Tavolato C, Thépaut JN, Vitart F (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/full

    Article  Google Scholar 

  • Deser C, Phillips A, Bourdette V, Teng H (2012) Uncertainty in climate change projections: the role of internal variability. Clim Dyn 38:527–546

    Article  Google Scholar 

  • Dhanya M, Gopalakrishnan D, Chandrasekar A, Singh SK, Prasad VS (2016) The impact of assimilating MeghaTropiques SAPHIR radiances in the simulation of tropical cyclones over the Bay of Bengal using the WRF model. Int J Remote Sens 37(13):3086–3103

    Article  Google Scholar 

  • Done JM, PaiMazumder D, Towler E, Kishtawal CM (2015) Estimating impacts of north Atlantic tropical cyclones using an index of damage potential. Clim Change. https://doi.org/10.1007/s10584-015-1513-0

    Google Scholar 

  • Emanuel K (1999) Thermodynamic control of hurricane intensity. Nature 401(6754):665–669

    Article  Google Scholar 

  • Emanuel K (2005) Increasing destructiveness of tropical cyclones over the past 30 years. Nature 436(7051):686–688

    Article  Google Scholar 

  • Emanuel K (2007) Environmental factors affecting tropical cyclone power dissipation. J Clim 20:5497–5509

    Article  Google Scholar 

  • Emanuel K (2013) Downscaling CMIP5 climate models shows increased tropical cyclone activity over the 21st century. Proc Natl Acad Sci 110(30):12219–12224

    Article  Google Scholar 

  • Emanuel K, Sundararajan R, Williams J (2008) Hurricanes and global warming: results from downscaling IPCC AR4 simulation. Bull Am Meteorol Soc 89:347–367

    Article  Google Scholar 

  • Fierro AO, Rogers RF, Marks FD, Nolan DS (2009) The impact of horizontal grid spacing on the microphysical and kinematic structures of strong tropical cyclones simulated with the WRF ARW model. Mon Weather Rev 137:3717–3747

    Article  Google Scholar 

  • Franklin JL, Lord SJ, Feuer SE, Marks FD Jr (1993) The kinematic structure of Hurricane Gloria (1985) determined from nested analyses of dropsonde and doppler radar data. Mon Weather Rev 121:2433–2451

    Article  Google Scholar 

  • Gaffen D, Elliott W, Robock A (1992) Relationships between tropospheric water vapor and surface temperature as observed by radiosondes. Geophys Res Lett 19:1839–1842

    Article  Google Scholar 

  • George JE, Gray WM (1976) Tropical cyclone motion and surrounding parameters relationships. J Appl Meteorol 15:1252–1264

    Article  Google Scholar 

  • Goni GJ, Trinanes JA (2003) Ocean thermal structure monitoring could aid in intensity forecast of tropical cyclone. EOS 84(51):573–580

    Article  Google Scholar 

  • Goswami P, Mohapatra G (2014) A comparative evaluation of impact of domain size and parameterization scheme on simulation of tropical cyclones in the Bay of Bengal. J Geophys Res Atmos 119(1):10–22

    Article  Google Scholar 

  • Gutmann ED, Rasmussen RM, Liu C, Ikeda K, Bruyere CL, Done JM, Garre L, Friis-Hansen P, Veldore V (2018) Changes in hurricanes from a 13-yr convection-permitting pseudo-global warming simulation. J Clim 31:3643–3657

    Article  Google Scholar 

  • Hill KA, Lackmann GM (2009) Influence of environmental humidity on tropical cyclone size. Mon Weather Rev 137:3294–3315

    Article  Google Scholar 

  • Hill KA, Lackmann GM (2011) The impact of future climate change on tropical cyclone intensity and structure: a downscaling approach. J Clim 24(17):4644–4661

    Article  Google Scholar 

  • Holland GJ (1984) Tropical cyclone motion: environmental interaction plus a Beta effect. J Atmos Sci 40:328–342

    Article  Google Scholar 

  • Holland G, Bruyère CL (2014) Recent intense hurricane response to global climate change. Clim Dyn 42:617–627

    Article  Google Scholar 

  • Holland G, Done JM, Ge M, Douglas R (2016) An index for cyclone damage potential. In: 32nd conf. on hurricanes and tropical meteorology, San Juan, PR, Amer. Meteor. Soc., 5C.8. https://ams.confex.com/ams/32Hurr/webprogram/Paper293660.html. Accessed June 2017

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

    Article  Google Scholar 

  • Hoyos CD, Agudelo PA, Webster PJ, Curry JA (2006) Deconvolution of the factors contributing to the increase in global hurricane intensity. Science 312:94–97

    Article  Google Scholar 

  • Iacono MJ, Delamere JS, Mlawer EJ, Shephard MW, Clough SA, Collins WD (2008) Radiative forcing by longlived greenhouse gases: calculations with the AER radiative transfer models. J Geophys Res 113:D13103

    Article  Google Scholar 

  • IMD Report (2013) Very severe cyclonic storm, Phailin over the Bay of Bengal (08–14 October 2013): a report. India Meteorological Department, Technical Report, October 2013. (http://www.rsmcnewdelhi.imd.gov.in/images/pdf/publications/preliminary-report/phailin.pdf). Accessed June 2017

  • Islam T, Peterson RE (2009) Climatology of landfalling tropical cyclones in Bangladesh 1877–2003. Nat Hazards 48(1):115–135

    Article  Google Scholar 

  • Jackson D, Stephens G (1995) A study of SSM/I-derived columnar water vapor over the global oceans. J Clim 8:2025–2038

    Article  Google Scholar 

  • Kain JS (2004) The Kain–Fritsch convective parameterization: an update. J Appl Meteorol 43:170–181

    Article  Google Scholar 

  • Kanase RD, Salvekar P (2014) Study of weak intensity cyclones over Bay of Bengal using WRF model. Atmos Clim Sci 4:534–548

    Google Scholar 

  • Kanemaru K, Masunaga K (2013) A satellite study of the relationship between sea surface temperature and column water vapor over tropical and subtropical oceans. J Clim 26:4204–4218

    Article  Google Scholar 

  • Kasahara A (1957) The numerical prediction of hurricane movement with the barotropic model. J Meteorol 14:386–402

    Article  Google Scholar 

  • Kasahara A (1960) The numerical prediction of Hurricane movement with a two-level baroclinic mode

  • Knutson TR, Tuleya RE (2004) Impact of CO2-induced warming on simulated hurricane intensity and precipitation: sensitivity to the choice of climate model and convective parameterization. J Clim 17(18):3477–3495

    Article  Google Scholar 

  • Knutson TR, McBride JL, Chan J, Emanuel K, Holland G, Landsea C, Held I, Kossin JP, Srivastava AK, Sugi M (2010) Tropical cyclones and climate change. Nat Geosci 3(3):157–163

    Article  Google Scholar 

  • Knutson TR, Sirutis JJ, Vecchi GA, Garner S, Zhao M, Kim HS, Bender M, Tuleya RE, Held IM, Villarini G (2013) Dynamical downscaling projections of twenty-first-century atlantic hurricane activity: CMIP3 and CMIP5 model-based scenarios. J Clim 26:6591–6617. https://doi.org/10.1175/JCLI-D-12-00539.1

    Article  Google Scholar 

  • Kossin JP (2018) A global slowdown of tropical cyclone translation speed. Nature 558:104–107

    Article  Google Scholar 

  • Kotal S, Bhattacharya S, Bhowmik SR, Kundu P (2014) Growth of cyclone Viyaru and Phailin—a comparative study. J Earth Syst Sci 123(7):1619–1635

    Article  Google Scholar 

  • Kummerow C, Simpson J, Thiele O, Barnes W, Chang ATC, Stocker E, Adler RF, Hou A, Kakar R, Wentz F, Ashcroft P, Kozu T, Hong Y, Okamoto K, Iguchi T, Kuroiwa H, Im E, Haddad Z, Huffman G, Ferrier B, Olson WS, Zipser E, Smith EA, Wilheit TT, North G, Krishnamurti T, Nakamura K (1998) The status of the tropical rainfall measuring mission (TRMM) after two years in orbit. J Appl Meteorol 122:1965–1968

    Google Scholar 

  • Lackmann GM (2013) The south-central US flood of may 2010: present and future. J Clim 26(13):4688–4709

    Article  Google Scholar 

  • Lackmann GM (2015) Hurricane Sandy before 1900 and after 2100. Bull Am Meteorol Soc 96(4):547–560

    Article  Google Scholar 

  • Leipper DF, Volgenau D (1972) Hurricane heat potential of the Gulf of Mexico. J Phys Ocean 2:218–224

    Article  Google Scholar 

  • Lim KSS, Hong SY (2010) Development of an effective double-moment cloud microphysics scheme with prognostic cloud condensation nuclei (CCN) for weather and climate models. Mon Weather Rev 138:1587–1612

    Article  Google Scholar 

  • Lin I-I, Chen CH, Pun IF, Liu WT, Wu CC (2009) Warm ocean anomaly, air sea fluxes, and the rapid intensification of tropical cyclone Nargis (2008). Geophys Res Lett 36:L03817. https://doi.org/10.1029/2008GL035815

    Google Scholar 

  • Lonfat M, Marks FD Jr, Chen SS (2004) Precipitation distribution in tropical cyclones using the Tropical Rainfall Measuring Mission (TRMM) microwave imager: a global perspective. Mon Weather Rev 132:1645–1660

    Article  Google Scholar 

  • Lotliker AA, Kumar TS, Reddem VS, Nayak S (2014) Cyclone Phailin enhanced the productivity following its passage: evidence from satellite data. Curr Sci 106(3):360–361

    Google Scholar 

  • Mallard MS, Lackmann GM, Aiyyer A (2013a) Atlantic hurricanes and climate change. Part II: role of thermodynamic changes in decreased hurricane frequency. J Clim 26(21):8513–8528

    Article  Google Scholar 

  • Mallard MS, Lackmann GM, Aiyyer A, Hill K (2013b) Atlantic hurricanes and climate change. Part I: experimental design and isolation of thermodynamic effects. J Clim 26(13):4876–4893

    Article  Google Scholar 

  • Mandal M, Singh KS, Balaji M, Mohapatra M (2015) Performance of WRF-ARW model in real time prediction of Bay of Bengal cyclone ‘Phailin’. Pure Appl Geophys. https://doi.org/10.1007/s00024-015-1206-7

    Google Scholar 

  • Manganello JV, Hodges KI, Kinter JL III, Cash BA, Marx L, Jung T, Achuthavarier D, Adams JM, Altshuler EL, Huang B, Jin EK (2012) Tropical cyclone climatology in a 10-km global atmospheric GCM: toward weather-resolving climate modeling. J Clim 25:3867–3893

    Article  Google Scholar 

  • Marks FD Jr, Houze RA, Gamache JF (1992) Dual-aircraft investigation of the inner core of Hurricane Nobert. Part I: kinematic structure. J Atmos Sci 49:919–942

    Article  Google Scholar 

  • McNeeley SM, Tessendorf SA, Lazrus H, Heikkila T, Ferguson IM, Arrigo JS, Attari SZ, Cianfrani CM, Dilling L, Gurdak JJ, Kampf SK (2012) Catalyzing frontiers in water-climate-society research. Bull Am Meteorol Soc. https://doi.org/10.1175/BAMS-D-11-00221.1

    Google Scholar 

  • McPhaden MJ, Foltz GR, Lee T, Murty V, Ravichandran M, Vecchi GA, Vialard J, Wiggert JD, Yu L (2009) Ocean-atmosphere interactions during cyclone Nargis. EOS Trans Am Geophys Union 90(7):53–54

    Article  Google Scholar 

  • Mukhopadhyay P, Taraphdar S, Goswami B (2011) Influence of moist processes on track and intensity forecast of cyclones over the north Indian Ocean. J Geophys Res Atmos. https://doi.org/10.1029/2010JD014700

    Google Scholar 

  • Prakash KR, Pant V (2017) Upper oceanic response to tropical cyclone Phailin in the Bay of Bengal using a coupled atmosphere-ocean model. Ocean Dyn 67(1):51–64. https://doi.org/10.1007/s10236-016-1020-5

    Article  Google Scholar 

  • Rakesh V, Goswami P (2011) Impact of background error statistics on forecasting of tropical cyclones over the north Indian Ocean. J Geophys Res Atmos. https://doi.org/10.1029/2011JD015751

    Google Scholar 

  • Rasmussen R, Liu C, Ikeda K, Gochis D, Yates D, Chen F, Tewari M, Barlage M, Dudhia J, Yu W, Miller K (2011) High-resolution coupled climate runoff simulations of seasonal snowfall over Colorado: a process study of current and warmer climate. J Clim 24(12):3015–3048

    Article  Google Scholar 

  • Ray P, Zhang C, Moncrieff MW, Dudhia J, Caron JM, Leung R, Brueyere C (2011) Role of atmospheric mean state on the initiation of the Madden-Julian oscillation in a tropical channel model. Clim Dyn 36:161–184

    Article  Google Scholar 

  • Ray P, Zhang C, Dudhia J, Li T, Moncrieff MW (2012) Tropical channel model. In: Druyan LM (ed) Climate models. InTech Open Access Publisher, London, pp 3–18. ISBN 978-953-308-181-6

    Google Scholar 

  • Reynes A (2003) Environmental steering flow analysis for central north Pacific tropical cyclone based on NCEP-NCAR reanalysis data. M.S. thesis, U of Hawaii

  • Riahi K, Rao S, Krey V, Cho C, Chirkov V, Fischer G, Kindermann G, Nakicenovic N, Rafaj P (2011) RCP 8.5—a scenario of comparatively high greenhouse gas emissions. Clim Change 109(1–2):33. https://doi.org/10.1007/s10584-011-0149-y

    Article  Google Scholar 

  • Sahoo B, Bhaskaran PK (2016) Assessment on historical cyclone tracks in the Bay of Bengal, east coast of India. Int J Climatol 36(1):95–109

    Article  Google Scholar 

  • Schar C, Frei C, Luthi D, Davies HC (1996) Surrogate climate-change scenarios for regional climate models. Geophys Res Lett 23(6):669–672

    Article  Google Scholar 

  • Sengupta D, Ray PK, Bhat GS (2002) Spring warming the eastern Arabian Sea and Bay of Bengal from buoy data. Geophys Res Lett 29(15):1–4. https://doi.org/10.1029/2002GL015340

    Article  Google Scholar 

  • Sengupta D, Goddalehundi BR, Anitha D (2008) Cyclone-induced mixing does not cool SST in the post-monsoon north Bay of Bengal. Atmos Sci Lett 9(1):1–6

    Article  Google Scholar 

  • Shay LK, Goni GJ, Black PG (2000) Effects of a warm oceanic feature on Hurricane Opal. Mon Weather Rev 128:1366–1383

    Article  Google Scholar 

  • Shen W, Tuleya RE, Ginis I (2000) A sensitivity study of the thermodynamic environment on GFDL model hurricane intensity: implications for global warming. J Clim 13(1):109–121

    Article  Google Scholar 

  • Singh R, Kishtawal C, Pal P (2011) Use of atmospheric infrared sounder clear-sky and cloud-cleared radiances in the weather research and forecasting 3DVAR assimilation system for mesoscale weather predictions over the Indian region. J Geophys Res Atmos. https://doi.org/10.1029/2011JD016379

    Google Scholar 

  • Skamarock W, Klemp J, Dudhia J, Gill D, Barker D, Duda M, Huang X, Wang W, Powers J (2008) A description of the advanced research WRF version 3, NCAR tech note ncar/tn 475 str. UCAR Communications

  • Solomon S (ed) (2007) The physical science basis: working group I contribution to the fourth assessment report of the IPCC (Vol. 4). Cambridge University Press, Cambridge, p 996

    Google Scholar 

  • Sooraj KP, Terray P, Mujumder M (2015) Global warming and the weakening of the Asian summer monsoon circulation: assessments from the CMIP 5 models. Clim Dyn 45:233–252

    Article  Google Scholar 

  • Srinivas C, Bhaskar Rao D, 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. Q J R Meteorol Soc 139(676):1810–1825

    Article  Google Scholar 

  • Stephens G (1990) On the relationship between water vapor over the oceans and sea surface temperature. J Clim 3:634–645

    Article  Google Scholar 

  • Stocker T (ed) (2014) The physical science basis: Working Group I contribution to the fifth assessment report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge

    Google Scholar 

  • Subramani D, Chandrasekar R, Srinivasa RK, Balaji C (2014) A new ensemble-based data assimilation algorithm to improve track prediction of tropical cyclones. Nat Hazards 71:659–682

    Article  Google Scholar 

  • Sun Y, Zhong Z, Li T, Yi L, Hu Y, Wan H, Chen H, Liao Q, Ma C, Li Q (2017) Impact of ocean warming on tropical cyclone size and its destructiveness. Sci Rep. https://doi.org/10.1038/s41598-017-08533-6

    Google Scholar 

  • Tanaka HL, Ishizaki N, Nohara D (2005) Intercomparison of the intensities and trends of Hadley, Walker, and monsoon circulations in the global warming projects. SOLA 1:077–080

    Article  Google Scholar 

  • Taraphdar S, Mukhopadhyay P, Leung LR, Zhang F, Abhilash S, Goswami B (2014) The role of moist processes in the intrinsic predictability of Indian Ocean cyclones. J Geophys Res Atmos 119(13):8032–8048

    Article  Google Scholar 

  • Thompson G, Rasmussen RM, Manning K (2004) Explicit forecasts of winter precipitation using an improved bulk microphysics scheme. Part I: description and sensitivity analysis. Mon Weather Rev 132:519–542

    Article  Google Scholar 

  • Tiedtke M (1989) A comprehensive mass flux scheme for cumulus parameterization in large scale model. Mon Weather Rev 117:1779–1800

    Article  Google Scholar 

  • Trenberth K, Fasullo J, Smith L (2005) Trends and variability in column-integrated atmospheric water vapor. Clim Dyn. 24:741–758

    Article  Google Scholar 

  • Villarini G, Vecchi GA (2013) Projected increases in North Atlantic tropical cyclone intensity from CMIP5 models. J Clim 26(3231):3240

    Google Scholar 

  • Wang Y (2009) How do outer spiral rainbands affect tropical cyclone structure and intensity? J Atmos Sci 66:1250–1273

    Article  Google Scholar 

  • Webster PJ (2008) Myanmar’s deadly daffodil. Nat Geosci 1(8):488–490

    Article  Google Scholar 

  • Wu CC, Kurihara Y (1996) A numerical study of the feedback mechanisms of hurricane–environment interaction on hurricane movement from potential vorticity perspective. J Atmos Sci 53:2264–2282

    Article  Google Scholar 

  • Wu L, Su H, Fovell RG, Wang B, Shen JT, Kahn BH, Hristova-Veleva SM, Lambrightsen BH, Fetzer EJ, Jian JH (2012) Relationship of environmental relative humidity with North Atlantic tropical cyclone intensity and intensification rate. Geophys Res Lett. https://doi.org/10.1029/2012GL053546

    Google Scholar 

  • Zhang DL, Anthes RA (1982) A high-resolution model of the planetary boundary layer-sensitivity tests and comparisons with SESAME-79 data. J Appl Meteorol 21:1594–1609

    Article  Google Scholar 

Download references

Acknowledgements

The data for future climate simulation was obtained from http://rda.ucar.edu/datasets/ds316.1/. We thank three anonymous reviewers for their insightful comments that resulted in significant improvements in the paper. We thank Chris Combs for editing an earlier version of the paper.

Author information

Authors and Affiliations

  1. IBM Research, New Delhi, India

    Rashmi Mittal

  2. IBM Thomas J. Watson Research Center, Yorktown Heights, NY, USA

    Mukul Tewari

  3. Colorado State University, Fort Collins, CO, USA

    Chandrasekar Radhakrishnan

  4. Meteorology, Florida Institute of Technology, Melbourne, FL, 32901, USA

    Pallav Ray

  5. National Centre for Medium Range Weather Forecasting (NCMRWF), Ministry of Earth Sciences, Noida, India

    Tarkeshwar Singh

  6. College of Marine Science, University of South Florida, St. Petersburg, FL, USA

    Alexander K. Nickerson

Authors
  1. Rashmi Mittal
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Mukul Tewari
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Chandrasekar Radhakrishnan
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Pallav Ray
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Tarkeshwar Singh
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Alexander K. Nickerson
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Pallav Ray.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Mittal, R., Tewari, M., Radhakrishnan, C. et al. Response of tropical cyclone Phailin (2013) in the Bay of Bengal to climate perturbations. Clim Dyn 53, 2013–2030 (2019). https://doi.org/10.1007/s00382-019-04761-w

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00382-019-04761-w

Keywords

Search

Navigation