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Climate Dynamics

, Volume 53, Issue 3–4, pp 2391–2410 | Cite as

Future wind and wave climate projections in the Indian Ocean based on a super-high-resolution MRI-AGCM3.2S model projection

  • Bahareh KamranzadEmail author
  • Nobuhito Mori
Article

Abstract

In this study, the impact of climate change on wind and wave characteristics has been assessed using super-high-resolution MRI-AGCM3.2S wind data and numerical modeling over the Indian Ocean. Wave characteristics were generated in two 25-year periods covering historical and future projections (RCP8.5), and the assessment indicated that, generally, the spatial distributions of wind speed, significant wave height (Hs) and mean spectral wave period (Tm01) will not dramatically change in the future. The assessment also indicated that the wind direction reversing pattern during monsoons will remain similar. Moreover, future westerly winds in the Southern Indian Ocean (SIO) will shift to the south and a decrease in future wind speed north of the equator will occur, espearound the equator due to cially during winter. The relative change of Hs will be less than wind speed the predominance of swells transferring from the SIO. There will be no considerable change in the future Tm01, except during autumn in the area north of the equator. A novel climate stability index is suggested showing that the semi-enclosed seas in the NIO and the western coasts of India and the Maldives will be areas with the least stability in terms of wave climate. Despite experiencing more intense wind and wave climates, the overall climate will be more stable in the SIO than the NIO.

Keywords

Climate change Wave model Indian Ocean SWAN MRI-AGCM3.2S RCP8.5 

Notes

Acknowledgements

The authors are thankful to everyone who supported modifications of the source code to fix the problem with the drag coefficient in SWAN v. 41.10, including (in alphabetic order) Adem Akpinar, George Lavidas, Tomoya Shimura, Gerbrant van Vledder and Marcel Zijlema. The authors are also grateful to Katherine Cox for editing the manuscript. Part of the research was supported by the Hakubi Center for Advanced Research at Kyoto University, the framework of the Integrated Research Program for Advancing Climate Models (TOUGOU Program), and JSPS Grants-in-Aid for Scientific Research—KAKENHI—supported by the Ministry of Education, Culture, Sports, Science, and Technology-Japan (MEXT).

References

  1. Aguiar-González B, Ponsoni L, Ridderinkhof H, van Aken HM, de Ruijter WPM, Maas LRM (2016) Seasonal variation of the South Indian tropical gyre. Deep Sea Res Part I 110:123–140.  https://doi.org/10.1016/j.dsr.2016.02.004 CrossRefGoogle Scholar
  2. Anoop TR, Sanil Kumar V, Shanas PR, Johnson G (2015) Surface wave climatology and its variability in the North Indian Ocean based on ERA-Interim reanalysis. J Atmos Ocean Technol 32:1372–1385.  https://doi.org/10.1175/JTECH-D-14-00212.1 CrossRefGoogle Scholar
  3. Bhaskaran PK, Gupta N, Dash MK (2014) Wind–wave climate projections for the Indian Ocean from satellite observations. J Mar Sci Res Dev S11:005.  https://doi.org/10.4172/2155-9910.s11-005 Google Scholar
  4. Booij N, Ris RC, Holthuijsen LH (1999) A third-generation wave model for coastal regions. 1. Model description and validation. J Geophys Res 104:7649–7666.  https://doi.org/10.1029/98JC02622 CrossRefGoogle Scholar
  5. Cavaleri L (2009) Wave modeling—missing the peaks. J Phys Oceanogr 39:2757–2778.  https://doi.org/10.1175/2009JPO4067.1 CrossRefGoogle Scholar
  6. Chen G, Chapron B, Ezraty R, Vandemark D (2002) A global view of swell and wind sea climate in the ocean by satellite altimeter and scatterometer. J Atmos Ocean Technol 19:1849–1859.  https://doi.org/10.1175/1520-0426(2002)019%3c1849:AGVOSA%3e2.0.CO;2 CrossRefGoogle Scholar
  7. Dowdy AJ, Mills GA, Timbal B, Wang Y (2014) Fewer large waves projected for eastern Australia due to decreasing storminess. Nat Clim Change 4:283–286.  https://doi.org/10.1038/nclimate2142 CrossRefGoogle Scholar
  8. Dube SK, Rao AD, Sinha PC, Murty TS, Bahulayan N (1997) Storm surge in the Bay of Bengal and Arabian Sea: the problem and its prediction. Mausam 48:283–304Google Scholar
  9. Gray WM (1985) Technical document WMO TD No.72. WMO Geneva Switz 1:3–19Google Scholar
  10. Gupta N, Bhaskaran PK (2016) Inter-dependency of wave parameters and directional analysis of ocean wind–wave climate for the Indian Ocean. Int J Climatol 37:3036–3043.  https://doi.org/10.1002/joc.4898 CrossRefGoogle Scholar
  11. Gupta N, Bhaskaran PK, Dash MK (2015) Recent trends in wind–wave climate for the Indian Ocean. Curr Sci 108(12):2191–2201Google Scholar
  12. Hasselmann S, Hasselmann K (1985) Computations and parameterizations of the nonlinear energy transfer in a gravity-wave spectrum. Part I: a new method for efficient computations of the exact nonlinear transfer integral. J Phys Oceanogr 15:1378–1391.  https://doi.org/10.1175/1520-0485(1985)015<1369:CAPOTN>2.0.CO;2 CrossRefGoogle Scholar
  13. Hasselmann K et al (1973) Measurements of wind–wave growth and swell decay during the Joint North Sea Wave Project (JONSWAP). Dtsch Hydrogr Z Suppl 12:A8Google Scholar
  14. Hemer MA, Trenham CE (2016) Evaluation of a CMIP5 derived dynamical global wind wave climate model ensemble. Ocean Model 103:190–203.  https://doi.org/10.1016/j.ocemod.2015.10.009 CrossRefGoogle Scholar
  15. Hemer MA, Katzfey J, Trenham CE (2013) Global dynamical projections of surface ocean wave climate for a future high greenhouse gas emission scenario. Ocean Model 70:221–245.  https://doi.org/10.1016/j.ocemod.2012.09.008 CrossRefGoogle Scholar
  16. Hibbard KA, Meehl GA, Cox PM, Friedlingstein P (2007) A strategy for climate change stabilization experiments. EOS Trans Am Geophys Union 88:217–221.  https://doi.org/10.1029/2007EO200002 CrossRefGoogle Scholar
  17. Hithin NK, Sanil Kumar V, Shanas PR (2015) Trends of wave height and period in the Central Arabian Sea from 1996 to 2012: a study based on satellite altimeter data. Ocean Eng 108:416–425.  https://doi.org/10.1016/j.oceaneng.2015.08.024 CrossRefGoogle Scholar
  18. Kamranzad B, Mori N (2018) Future projection of wave energy in Indian Ocean based on high resolution MRI-AGCM3.2S projection. Grand Renew Energy, Yokohama, Japan, 20 June 2018. http://www.grand-re2018.org/files/AREA8_program.pdf?0615
  19. Kamranzad B, Etemad-Shahidi A, Chegini V (2013) Assessment of wave energy variation in the Persian Gulf. Ocean Eng 70:72–80.  https://doi.org/10.1016/j.oceaneng.2013.05.027 CrossRefGoogle Scholar
  20. Kamranzad B, Etemad-Shahidi A, Chegini V, Yeganeh-Bakhtiyari A (2015) Climate change impact on wave energy in the Persian Gulf. Ocean Dyn 65:777–794.  https://doi.org/10.1007/s10236-015-0833-y CrossRefGoogle Scholar
  21. Kamranzad B, Chegini V, Etemad-Shahidi A (2016) Temporal-spatial variation of wave energy and nearshore hotspots in the Gulf of Oman based on locally generated wind waves. Renew Energy 94:341–352.  https://doi.org/10.1016/j.renene.2016.03.084 CrossRefGoogle Scholar
  22. Kamranzad B, Etemad-Shahidi A, Chegini V (2017a) Developing an optimum hotspot identifier for wave energy extracting in the northern Persian Gulf. Renew Energy 114:59–71.  https://doi.org/10.1016/j.renene.2017.03.026 CrossRefGoogle Scholar
  23. Kamranzad B, Mori N, Shimura T (2017b) Performances of long-term wave hindcasts in the Northern Indian Ocean. J Jpn Soc Civil Eng Ser B2 Coastal Eng 73(2):I_157–I_162.  https://doi.org/10.2208/kaigan.73.I_157 Google Scholar
  24. Kobayashi S, Ota Y, Harada Y, Ebita A, Moriya M, Onoda H, Onogi K, Kamahor H, Kobayashi C, Endo H, Miyaoka K, Takahashi K (2015) The JRA-55 reanalysis: general specifications and basic characteristics. J Meteor Soc Jpn 93:5–48.  https://doi.org/10.2151/jmsj.2015-001 CrossRefGoogle Scholar
  25. Komen GJ, Hasselmann S, Hasselmann K (1984) On the existence of a fully developed wind sea spectrum. J Phys Oceanogr 14:1271–1285.  https://doi.org/10.1175/1520-0485(1984)014%3c1271:OTEOAF%3e2.0.CO;2 CrossRefGoogle Scholar
  26. Krishna KM (2009) Intensifying tropical cyclones over the North Indian Ocean during summer monsoon-global warming. Global Planet Change 65:12–16.  https://doi.org/10.1016/j.gloplacha.2008.10.007 CrossRefGoogle Scholar
  27. Lecacheux S, Pedreros R, Le Cozannet G, Thiébot J, De La Torre Y, Bulteau T (2012) A method to characterize the different extreme waves for islands exposed to various wave regimes: a case study devoted to Reunion Island. Nat Hazards Earth Syst Sci 12:2425–2437.  https://doi.org/10.5194/nhess-12-2425-2012 CrossRefGoogle Scholar
  28. Mazaheri S, Kamranzad B, Hajivalie F (2013) Modification of 32 years ECMWF wind field using QuikSCAT data for wave hindcasting in Iranian Seas. J Coast Res I65:344–349.  https://doi.org/10.2112/SI65-059.1 CrossRefGoogle Scholar
  29. Mizuta R et al (2012) Climate simulations using MRI-AGCM with 20-km grid. J Meteor Soc Jpn 90A:235–260.  https://doi.org/10.2151/jmsj.2012-A12 CrossRefGoogle Scholar
  30. Mori N, Takemi T (2016) Impact assessment of coastal hazards due to future changes of tropical cyclones in the North Pacific Ocean. Weather Clim Extremes 11:53–69.  https://doi.org/10.1016/j.wace.2015.09.002 CrossRefGoogle Scholar
  31. Mori N, Shimura T, Yasuda T, Mase H (2013) Multi-model climate projections of ocean surface variables under different climate scenarios-future change of waves, sea level and wind. Ocean Eng 71:122–129.  https://doi.org/10.1016/j.oceaneng.2013.02.016 CrossRefGoogle Scholar
  32. Mori N, Shimura T, Kamahori H, Chawla A, Yasuda T, Mase H (2015) Long-term wave hindcast and wave climate analysis by JRA-55. J Jpn Soc Civil Eng B (Coast Eng) 71:I_103–I_108.  https://doi.org/10.2208/kaigan.71.I_103 Google Scholar
  33. Moss RH et al (2010) The next generation of scenarios for climate change research and assessment. Nature 463:747–756.  https://doi.org/10.1038/nature08823 CrossRefGoogle Scholar
  34. Patra A, Bhaskaran PK (2016a) Temporal variability in wind–wave climate and its validation with ESSO-NIOT wave atlas for the head Bay of Bengal. Clim Dyn 49:1271–1288.  https://doi.org/10.1007/s00382-016-3385-z CrossRefGoogle Scholar
  35. Patra A, Bhaskaran PK (2016b) Trends in wind–wave climate over the head Bay of Bengal region. Int J Climatol 36:4222–4240.  https://doi.org/10.1002/joc.4627 CrossRefGoogle Scholar
  36. Remya PG, Kumar R, Basu S, Sarkar A (2012) Wave hindcast experiments in the Indian Ocean using MIKE 21 SW model. J Earth Syst Sci 121:385–392.  https://doi.org/10.1007/s12040-012-0169-7 CrossRefGoogle Scholar
  37. Rhein M, Rintoul SR, Aoki S, Campos E, Chambers D, Feely RA, Gulev S, Johnson GC, Josey SA, Kostianoy A, Mauritzen C, Roemmich D, Talley LD, Wang F (2013) Observations: ocean. In: Stocker TF, Qin D, Plattner G-K, Tignor M, Boschung J, Nauels A, Xia Y, Bex V, Midgley PM (eds) Climate change 2013: the physical science basis. Contribution of working group I to the fifth assessment report of the intergovernmental panel on climate change. Cambridge University Press, CambridgeGoogle Scholar
  38. Ris RC, Holthuijsen LH, Booij N (1999) A third-generation wave model for coastal regions: 2. Verif J Geophys Res 104:7667–7681.  https://doi.org/10.1029/1998JC900123 CrossRefGoogle Scholar
  39. Rogers WE, Babanin AV, Wang DW (2012) Observation-consistent input and whitecapping dissipation in a model for wind-generated surface waves: description and simple calculations. J Atmos Ocean Technol 29:1329–1346CrossRefGoogle Scholar
  40. Roxy MK, Ritika K, Terray P, Masson S (2014) The curious case of Indian Ocean warming. J Clim 27:8501–8509.  https://doi.org/10.1175/JCLI-D-14-00471.1 CrossRefGoogle Scholar
  41. Sanil Kumar V, Anoop TR (2015) Wave energy resource assessment for the Indian shelf seas. Renew Energy 76:212–219.  https://doi.org/10.1016/j.renene.2014.11.034 CrossRefGoogle Scholar
  42. Schott F, McCreary JP (2001) The monsoon circulation of the Indian Ocean. Prog Oceanogr 51:1–123.  https://doi.org/10.1016/S0079-6611(01)00083-0 CrossRefGoogle Scholar
  43. Schott FA, Xie SP, McCreary JP Jr (2009) Indian Ocean circulation and climate variability. Rev Geophys 47:1002.  https://doi.org/10.1029/2007RG000245 CrossRefGoogle Scholar
  44. Seemanth M, Bhowmick SA, Kumar R, Sharma R (2016) Sensitivity analysis of dissipation parameterizations in a third-generation spectral wave model, WAVEWATCH III for Indian Ocean. Ocean Eng 124:252–273.  https://doi.org/10.1016/j.oceaneng.2016.07.023 CrossRefGoogle Scholar
  45. Shanas PR, Sanil Kumar V, Hithin NK (2014) Comparison of gridded multi-mission and along-track mono-mission satellite altimetry wave heights with in situ near-shore buoy data. Ocean Eng 83:24–35.  https://doi.org/10.1016/j.oceaneng.2014.03.014 CrossRefGoogle Scholar
  46. Shanas PR, Aboobacker VM, Albarakati AMA, Zubier KM (2017) Climate driven variability of wind–waves in the Red Sea. Ocean Model 119:105–117.  https://doi.org/10.1016/j.ocemod.2017.10.001 CrossRefGoogle Scholar
  47. Shimura T, Mori N, Mase H (2015) Future projections of extreme ocean wave climates and the relation to tropical cyclones: ensemble experiments of MRI-AGCM3.2H. J Clim 28:9838–9856.  https://doi.org/10.1175/JCLI-D-14-00711.1 CrossRefGoogle Scholar
  48. Shimura T, Mori N, Hemer MA (2016a) Projection of tropical cyclone-generated extreme wave climate based on CMIP5 multi-model ensemble in the Western North Pacific. Clim Dyn 49:1449–1462.  https://doi.org/10.1007/s00382-016-3390-2 CrossRefGoogle Scholar
  49. Shimura T, Mori N, Hemer MA (2016b) Variability and future decreases in winter wave heights in the Western North Pacific. Geophys Res Lett 43:2716–2722.  https://doi.org/10.1002/2016GL067924 CrossRefGoogle Scholar
  50. Swain J, Umesh PA, Balchand AN, Bhaskaran PK (2017) Wave Hindcasting Using WAM and WAVEWATCH III: a comparison study utilizing oceansat-2 (OSCAT) winds. J Oceanogr Mar Res 5:3.  https://doi.org/10.4172/2572-3103.1000166 Google Scholar
  51. Tchernia P (1980) Descriptive regional oceanography. Pergamon Press, OxfordGoogle Scholar
  52. The SWAN team (2016) Swan user manual. Delft University of Technology, Delft, The NetherlandsGoogle Scholar
  53. Tolman HL (2014) WAVEWATCH III Development Group, User manual and system documentation of AVEWATCH III version 418. National Oceanic and Atmospheric Administration, College ParkGoogle Scholar
  54. Umesh PA, Bhaskaran PK, Sandhya KG, Balakrishnan Nair TM (2017) An assessment on the impact of wind forcing on simulation and validation of wave spectra at coastal Puducherry, east coast of India. Ocean Eng 139:14–32.  https://doi.org/10.1016/j.oceaneng.2017.04.043 CrossRefGoogle Scholar
  55. Vethamony P et al (2006) Wave modelling for the north Indian Ocean using MSMR analysed winds. Int J Remote Sens 27:3767–3780.  https://doi.org/10.1080/01431160600675820 CrossRefGoogle Scholar
  56. Wu J (1982) Wind-stress coefficients over sea surface from breeze to hurricane. J Geophys Res 87:9704–9706.  https://doi.org/10.1029/JC087iC12p09704 CrossRefGoogle Scholar
  57. Yang Z, Neary VS, Wang T, Gunawan B, Dallman AR, Wu WC (2017) A wave model test bed study for wave energy resource characterization. Renew Energy 114:132–144.  https://doi.org/10.1016/j.renene.2016.12.057 CrossRefGoogle Scholar
  58. Young IR (1999) Seasonal variability of the global ocean wind and wave climate. Int J Climatol 19:931–950.  https://doi.org/10.1002/(SICI)1097-0088(199907)19:9%3c931:AID-JOC412%3e3.0.CO;2-O CrossRefGoogle Scholar
  59. Zheng CW, Pan J, Li CY (2016) Global oceanic wind speed trends. Ocean Coast Manag 129:15–24.  https://doi.org/10.1016/j.ocecoaman.2016.05.001 CrossRefGoogle Scholar
  60. Zijlema M, van der Westhuysen AJ (2005) On convergence behaviour and numerical accuracy in stationary SWAN simulations of nearshore wind wave spectra. Coast Eng 52:237–256.  https://doi.org/10.1016/j.coastaleng.2004.12.006 CrossRefGoogle Scholar
  61. Zijlema M, van Vledder GP, Holthuijsen LH (2012) Bottom friction and wind drag for wave models. Coast Eng 65:19–26.  https://doi.org/10.1016/j.coastaleng.2012.03.002 CrossRefGoogle Scholar

Copyright information

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

Authors and Affiliations

  1. 1.Graduate School of Advanced Integrated Studies in Human SurvivabilityKyoto UniversityKyotoJapan
  2. 2.Hakubi Center for Advanced ResearchKyoto UniversityKyotoJapan
  3. 3.Disaster Prevention Research InstituteKyoto UniversityKyotoJapan

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