Inland Tropical Cyclones and the “Brown Ocean” Concept



In several regions of the world, tropical cyclones have been known to maintain or increase strength after landfall without transitioning to extratropical systems. It is hypothesized that these inland areas help sustain tropical cyclones when there has been plentiful rainfall, leading to unusually wet soil and strong latent heat release. Additionally, given the symmetric structure of warm-core cyclones, the atmosphere should tend toward barotropic conditions that mimic an ocean environment. Observational and modeling studies support this “brown ocean” concept, providing a global climatology of inland tropical cyclones, pinpointing regions that are more favorable for re-intensification, and analyzing individual cyclones to better understand the associated land-atmosphere feedbacks.


Brown Ocean Convective available potential energy (CAPE) Extratropical transition HYDRUS model Landfalling hurricanes Latent heat flux (LHF) Modern-Era Retrospective Analysis for Research and Applications (MERRA) Planetary boundary layer (PBL) Radar Saffir-Simpson scale Satellite Soil moisture Tropical cyclone maintenance or intensification (TCMI) Weather Research and Forecasting model (WRF) 


  1. Andersen T, Shepherd JM (2013) A global spatio-temporal analysis of inland tropical cyclone maintenance or intensification. Int J Climatol 34:391–402. doi: 10.1002/joc.3693 CrossRefGoogle Scholar
  2. Andersen T, Radcliffe D, Shepherd JM (2013) Quantifying surface energy fluxes in the vicinity of inland-tracking tropical cyclones. J Appl Meteorol Climatol 52:2797–2808. doi: 10.1175/JAMC-D-13-035 CrossRefGoogle Scholar
  3. Arndt DS, Basara JB, McPherson RA et al (2009) Observations of the overland reintensification of tropical storm Erin, 2007. Bull Am Meteorol Soc 90:1079–1093. doi: 10.1175/2009BAMS2644.1 CrossRefGoogle Scholar
  4. Au-Yeung AYM, Chan JCL (2010) The effect of a river delta and coastal roughness variation on a landfalling tropical cyclone. J Geophys Res Atmos 115:D19121. doi: 10.1029/2009JD013631 CrossRefGoogle Scholar
  5. Bender MA, Knutson TR, Tuleya RE et al (2010) Modeled impact of anthropogenic warming on the frequency of intense Atlantic hurricanes. Science 327:454–458. doi: 10.1126/science.1180568 CrossRefGoogle Scholar
  6. Bosilovich MG, Sun WY (1999) Numerical simulation of the 1993 midwestern flood: land atmosphere interactions. J Climate 12:1490–1505. doi: 10.1175/1520-0442(1999)012<1490:NSOTMF>2.0.CO;2 CrossRefGoogle Scholar
  7. Bozeman ML, Niyogi D, Gopalakrishnan S et al (2012) An HWRF-based ensemble assessment of the land surface feedback on the post-landfall intensification of tropical storm Fay (2008). Nat Hazards 63:1543–1571. doi: 10.1007/s11069-011-9841-5 CrossRefGoogle Scholar
  8. Chang H, Niyogi D, Kumar A et al (2009) Possible relation between land surface feedback and the post-landfall structure of monsoon depressions. Geophys Res Let 36:1–6. doi: 10.1029/2009GL037781 Google Scholar
  9. Chen LS (2012) Research progress on the structure and intensity change for the landfalling tropical cyclones. J Trop Meteor 18:113–118. doi: 10.3969/j.issn.10068775.2012.02.001 Google Scholar
  10. 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. Mon Weather Rev 129:569–585. doi: 10.1175/1520-0493(2001)129<0569:CAALSH>2.0.CO;2 CrossRefGoogle Scholar
  11. Chen SH, Sun WY (2002) A one-dimensional time dependent cloud model. J Meteorol Soc Jpn 80:99–118. doi: 10.2151/jmsj.80.99 CrossRefGoogle Scholar
  12. Clark CA, Arritt RW (1995) Numerical simulations of the effect of soil moisture and vegetation cover on the development of deep convection. J Appl Meteorol 34:2029–2045. doi: 10.1175/1520-0450(1995)034<2029:NSOTEO>2.0.CO;2 CrossRefGoogle Scholar
  13. Deshpande MS, Pattnaik S, Salvekar PS (2012) Impact of cloud parameterization on the numerical simulation of a super cyclone. Ann Geophys 30:775–795. doi: 10.5194/angeo-30-775-2012 CrossRefGoogle Scholar
  14. Dong M, Chen L, Li Y et al (2010) Rainfall reinforcement associated with landfalling tropical cyclones. J Atmos Sci 67:3541–3558. doi: 10.1175/2010JAS3268.1 CrossRefGoogle Scholar
  15. Dudhia J (1989) Numerical study of convection observed during the winter monsoon experiment using a mesoscale two-dimensional model. J Atmos Sci 46:3077–3107. doi: 10.1175/1520-0469(1989)046<3077:NSOCOD>2.0.CO;2 CrossRefGoogle Scholar
  16. Emanuel K, Callaghan J, Otto P (2008) A hypothesis for the redevelopment of warm-core cyclones over northern Australia. Mon Weather Rev 136:3863–3872. doi: 10.1175/2008MWR2409.1 CrossRefGoogle Scholar
  17. Evans C, Schumacher RS, Galarneau TJ (2011) Sensitivity in the overland reintensification of tropical cyclone Erin (2007) to near-surface soil moisture characteristics. Mon Weather Rev 139:3848–3870. doi: 10.1175/2011MWR3593.1 CrossRefGoogle Scholar
  18. Frank W (1977) The structure and energetics of the tropical cyclone II. Dynamics and energetics. Mon Weather Rev 105:1136–1150. doi: 10.1175/15200493(1977)105<1136:TSAEOT>2.0.CO;2 CrossRefGoogle Scholar
  19. Gao S, Chiu LS (2010) Surface latent heat flux and rainfall associated with rapidly intensifying tropical cyclones over the western North Pacific. Int J Remote Sens 31:4699–4710. doi: 10.1080/01431161.2010.485149 CrossRefGoogle Scholar
  20. Guimond SR, Bourassa MA, Reasor PD (2011) A latent heat retrieval and its effects on the intensity and structure change of hurricane Guillermo (1997). Part I: the algorithm and observations. J Atmos Sci 68:1549–1567. doi: 10.1175/2011JAS3700.1 CrossRefGoogle Scholar
  21. Hart RE, Evans JL (2001) A climatology of the extratropical transition of Atlantic tropical cyclones. J Climate 14:546–564. doi: 10.1175/1520-0442(2001)014<0546:ACOTET>2.0.CO;2 CrossRefGoogle Scholar
  22. Hill KA, Lackmann GM (2011) The impact of future climate change on TC intensity and structure: a downscaling approach. J Climate 24:4644–4661. doi: 10.1175/2011JCLI3761.1 CrossRefGoogle Scholar
  23. Hong SY, Noh Y, Dudhia J (2006) A new vertical diffusion package with an explicit treatment of entrainment processes. Mon Weather Rev 134:318–2341. doi: 10.1175/MWR3199.1 CrossRefGoogle Scholar
  24. Kain JS, Fritsch JM (1990) A one-dimensional entraining/detraining plume model and its application in convective parameterization. J Atmos Sci 47:2784–2802. doi: 10.1175/1520-0469(1990)047<2784:AODEPM>2.0.CO;2 CrossRefGoogle Scholar
  25. Kantha L (2010) Discussion of “A hydrodynamics-based surge scale for hurricanes”. Ocean Eng 37:1081–1084. doi: 10.1016/j.oceaneng.2010.04.003 CrossRefGoogle Scholar
  26. Kellner O, Niyogi D, Lei M et al (2012) The role of anomalous soil moisture on the inland reintensification of tropical storm Erin (2007). Nat Hazards 139:1573–1600. doi: 10.1007/s11069-011-9966-6 CrossRefGoogle Scholar
  27. Kishtawal CM, Niyogi D, Kumar A et al (2012) Sensitivity of inland decay of North Atlantic tropical cyclones to soil parameters. Nat Hazards 63:1527–1542. doi: 10.1007/s11069-011-0015-2 CrossRefGoogle Scholar
  28. Klein P, Harr P, Elsberry R (2000) Extratropical transition of western North Pacific tropical cyclones: an overview and conceptual model of the transformation stage. Weather Forecast 15:373–395. doi: 10.1175/1520-0434(2000)015<0373:ETOWNP>2.0.CO;2 CrossRefGoogle Scholar
  29. Knapp KR, Kruk MC, Levinson DH et al (2010) The International Best Track Archive for Climate Stewardship (IBTrACS): unifying tropical cyclone best track data. Bull Am Meteorol Soc 91:363–376. doi: 10.1175/2009BAMS2755.1 CrossRefGoogle Scholar
  30. Kossin JP, Emanuel KA, Vecchi GA (2014) The poleward migration of the location of tropical cyclone maximum intensity. Nature 509:349–352. doi: 10.1038/nature13278 CrossRefGoogle Scholar
  31. Lee SW, Lee DK, Chang DE (2011) Impact of horizontal resolution and cumulus parameterization scheme on the simulation of heavy rainfall events over the Korean Peninsula. Adv Atmos Sci 28:1–15. doi: 10.1007/s00376-010-9217-x CrossRefGoogle Scholar
  32. Lin N, Smith JA, Villarini G et al (2010) Modeling extreme rainfall, winds, and surge from hurricane Isabel (2003). Weather Forecast 25:1342–1361. doi: 10.1175/2010WAF2222349.1 CrossRefGoogle Scholar
  33. Liu J, Curry JA, Clayson CA et al (2011) High-resolution satellite surface latent heat fluxes in North Atlantic hurricanes. Mon Weather Rev 139:2735–2747. doi: 10.1175/2011MWR3548.1 CrossRefGoogle Scholar
  34. Lynn BH, Tao WK, Wetzel PJ (1998) A study of landscape-generated deep moist convection. Mon Weather Rev 126:928–942. doi: 10.1175/1520-0493(1998)126<0928:ASOLGD>2.0.CO;2 CrossRefGoogle Scholar
  35. Ma LM, Tan ZM (2009) Improving the behavior of the cumulus parameterization for tropical cyclone prediction: convection trigger. Atmos Res 92:190–211. doi: 10.1016/j.atmosres.2008.09.022 CrossRefGoogle Scholar
  36. Mlawer EJ, Taubman SJ, Brown PD et al (1997) Radiative transfer for inhomogeneous atmospheres: RRTM, a validated correlated-k model for the longwave. J Geophys Res Atmos 102:16663–16682. doi: 10.1029/97JD00237 CrossRefGoogle Scholar
  37. Murakami H, Wang Y, Yoshimura H et al (2012) Future changes in tropical cyclone activity projected by the new high-resolution MRI-AGCM. J Climate 25:3237–3260. doi: 10.1175/JCLI-D-11-00415.1 CrossRefGoogle Scholar
  38. 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. doi: 10.5065/D6M043C6
  39. Prater BE, Evans JL (2002) Sensitivity of modeled tropical cyclone track and structure of hurricane Irene (1999) to the convective parameterization scheme. Meteorol Atmos Phys 80:103–115. doi: 10.1007/s007030200018 CrossRefGoogle Scholar
  40. Radcliffe DE, Šimůnek J (2010) Soil physics with HYDRUS: modeling and applications. CRC Press, Boca Raton, p 373Google Scholar
  41. Rakhecha P, Singh VP (2009) Applied hydrometeorology, 1st edn. Springer-Verlag, New York, p 364, LLCCrossRefGoogle Scholar
  42. Rappaport EN (2014) Fatalities in the United States from Atlantic tropical cyclones: new data and interpretation. Bull Am Meteorol Soc 95:341–346. doi: 10.1175/BAMS-D-12-00074.1 CrossRefGoogle Scholar
  43. Senkbeil JC, Sheridan SC (2006) A post landfall hurricane classification system for the United States. J Coast Res 22:1025–1034. doi: 10.2112/05-0532.1 CrossRefGoogle Scholar
  44. Shen W, Ginis I, Tuleya R (2002) A numerical investigation of land surface water on landfalling hurricanes. J Atmos Sci 59:789–802. doi: 10.1175/1520-0469(2002)059<0789:ANIOLS>2.0.CO;2 CrossRefGoogle Scholar
  45. Shepherd JM (2012) What we can learn from the satellite-based rainfall footprint of superstorm Sandy: a preliminary synopsis. In: Earthzine. Accessed 16 Dec 2012
  46. Shepherd JM, Knutson T (2007) The current debate on the linkage between global warming and hurricanes. Geog Compass 1:1–24. doi: 10.1111/j.1749-8198.2006.00002.x CrossRefGoogle Scholar
  47. Shepherd JM, Grundstein A, Mote TL (2007) Quantifying the contribution of tropical cyclones to extreme rainfall along the coastal southeastern United States. Geophys Res Lett 34:1–5. doi: 10.1029/2007GL031694 CrossRefGoogle Scholar
  48. Skamarock WC, Klemp JB, Dudhia J et al (2008) A description of the advanced research WRF version 3. NCAR Tech. Note NCAR/TN-4751STR, p 125Google Scholar
  49. Trenberth KE, Fasullo J (2007) Water and energy budgets and hurricanes and implications for climate change. J Geophys Res 112:1–10. doi: 10.1029/2006JD008304 Google Scholar
  50. Tuleya RE (1994) Tropical storm development and decay: sensitivity to surface boundary conditions. Mon Weather Rev 122:291–304. doi: 10.1175/1520-0493(1994)122<0291:TSDADS>2.0.CO;2 CrossRefGoogle Scholar
  51. Tuleya RE, Kurihara Y (1978) A numerical simulation of the landfall of tropical cyclones. J Atmos Sci 35:242–257CrossRefGoogle Scholar
  52. Wang JF, Bras RL, Eltahir EAB (2000) The impact of observed deforestation on the mesoscale distribution of rainfall and clouds in Amazonia. J Hydrometeorol 1:267–286. doi: 10.1175/1525-7541(2000)001<0267:TIOODO>2.0.CO;2 CrossRefGoogle Scholar
  53. Xie BG, Zhang FQ (2012) Impacts of typhoon track and island topography on the heavy rainfalls in Taiwan associated with Morakot (2009). Mon Weather Rev 140:3379–3394. doi: 10.1175/MWR-D-11-00240.1 CrossRefGoogle Scholar
  54. Zhang YC, Rossow WB (1997) Estimating meridional energy transports by the atmospheric and oceanic general circulations using boundary fluxes. J Climate 10:2358–2373. doi: 10.1175/1520-0442(1997)010<2358:EMETBT>2.0.CO;2 CrossRefGoogle Scholar
  55. Zhang Y, Cassardo C, Ye CA et al (2011) The role of the land surface processes in the rainfall generated by a landfall typhoon: a simulation of the typhoon Sepat (2007). Asia-Pacific J Atmos Sci 47:63–77. doi: 10.1007/s13143-011-1006-7 CrossRefGoogle Scholar
  56. Zhu P (2008) Impact of land-surface roughness on surface winds during hurricane landfall. Q J R Meteor Soc 134:1051–1057. doi: 10.1002/qj.265 CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Research SquareDurhamUSA
  2. 2.Department of GeographyUniversity of GeorgiaAthensUSA

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