Robustness and uncertainties in global multivariate wind-wave climate projections

Article metrics

Abstract

Understanding climate-driven impacts on the multivariate global wind-wave climate is paramount to effective offshore/coastal climate adaptation planning. However, the use of single-method ensembles and variations arising from different methodologies has resulted in unquantified uncertainty amongst existing global wave climate projections. Here, assessing the first coherent, community-driven, multi-method ensemble of global wave climate projections, we demonstrate widespread ocean regions with robust changes in annual mean significant wave height and mean wave period of 5–15% and shifts in mean wave direction of 5–15°, under a high-emission scenario. Approximately 50% of the world’s coastline is at risk from wave climate change, with ~40% revealing robust changes in at least two variables. Furthermore, we find that uncertainty in current projections is dominated by climate model-driven uncertainty, and that single-method modelling studies are unable to capture up to ~50% of the total associated uncertainty.

Access optionsAccess options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Fig. 1: Hierarchical clustering of annual \({\bar{\boldsymbol{H}}}_{\boldsymbol{s}}\) for the present-day climate (1979–2004).
Fig. 2: Simulated wave climatological mean fields for the present day (1979–2004) and projected changes in climatological wave values for the period 2081–2100 under RCP4.5 and RCP8.5.
Fig. 3: Robust projected changes in offshore \({\bar{\boldsymbol{H}}}_{\mathbf{s}}\),\({\bar{\boldsymbol{T}}}_{\mathbf{m}}\) and \({\bar{\boldsymbol{\theta }}}_{\boldsymbol{m}}\) for 2080–2100 (under RCP8.5) in the vicinity of the world’s coastlines.
Fig. 4: Hierarchical clustering of projected relative changes in annual \({\bar{\boldsymbol{H}}}_{\boldsymbol{s}}\) (2081–2100 relative to 1979–2004).
Fig. 5: Relative contribution of different sources of uncertainty to projected future changes in the mean of annual/seasonal \({\bar{\boldsymbol{H}}}_{\boldsymbol{s}}\).

Data availability

The data that support the findings of this study are available from the corresponding author on request, or via the COWCLIP data access portal at https://cowclip.org/data-access/.

References

  1. 1.

    Melet, A., Meyssignac, B., Almar, R. & Le Cozannet, G. Under-estimated wave contribution to coastal sea-level rise. Nat. Clim. Change 8, 234–239 (2018).

  2. 2.

    Serafin, A. K., Ruggiero, P. & Stockdon, H. F. The relative contribution of waves, tides, and nontidal residuals to extreme total water levels on U.S. West Coast sandy beaches. Geophys. Res. Lett. 44, 1839–1847 (2017).

  3. 3.

    Harley, M. D. et al. Extreme coastal erosion enhanced by anomalous extratropical storm wave direction. Sci. Rep. 7, 6033 (2017).

  4. 4.

    Barnard, P. L. et al. Extreme oceanographic forcing and coastal response due to the 2015–2016 El Niño. Nat. Commun. 8, 14365 (2017).

  5. 5.

    Barnard, P. L. et al. Coastal vulnerability across the Pacific dominated by El Niño/Southern Oscillation. Nat. Geosci. 8, 801–807 (2015).

  6. 6.

    Hoeke, R. K. et al. Widespread inundation of Pacific islands triggered by distant-source wind-waves. Glob. Planet. Change 108, 128–138 (2013).

  7. 7.

    Feagin, R. A. et al. Does vegetation prevent wave erosion of salt marsh edges? Proc. Natl Acad. Sci. USA 106, 10109–10113 (2009).

  8. 8.

    Young, I. R. & Ribal, Agustinus Multiplatform evaluation of global trends in wind speed and wave height. Science 364, 548–552 (2019).

  9. 9.

    Wandres, M., Pattiaratchi, C. & Hemer, M. A. Projected changes of the southwest Australian wave climate under two atmospheric greenhouse gas concentration pathways. Ocean Model. 117, 70–87 (2017).

  10. 10.

    Albert, S. et al. Interactions between sea-level rise and wave exposure on reef island dynamics in the Solomon Islands. Environ. Res. Lett. 11, 054011 (2016).

  11. 11.

    Oliveira, F. S. B. F. A case study of wave climate changes due to nearshore morphological evolution. J. Coast. Res. 24, 21–32 (2008).

  12. 12.

    Storlazzi, C. D. et al. Most atolls will be uninhabitable by the mid-21st century because of sea-level rise exacerbating wave-driven flooding. Sci. Adv. 4, eaap9741 (2018).

  13. 13.

    Ranasinghe, R. Assessing climate change impacts on open sandy coasts: a review. Earth Sci. Rev. 160, 320–332 (2016).

  14. 14.

    Coelho, C., Silva, R., Veloso-Gomes, F. & Taveira-Pinto, F. Potential effects of climate change on northwest Portuguese coastal zones. ICES J. Mar. Sci. 66, 1497–1507 (2009).

  15. 15.

    Suh, K.-D., Kim, S.-W., Mori, N. & Mase, H. Effect of climate change on performance-based design of caisson breakwaters. J. Waterw. Port. Coast. Ocean Eng. 138, 215–225 (2012).

  16. 16.

    Cowell, P. J., Roy, P. S. & Jones, R. A. Simulation of large-scale coastal change using a morphological behaviour model. Mar. Geol. 126, 45–61 (1995).

  17. 17.

    Hurst, M. D., Rood, D. H., Ellis, M. A., Anderson, R. S. & Dornbusch, U. Recent acceleration in coastal cliff retreat rates on the south coast of Great Britain. Proc. Natl Acad. Sci. USA 113, 13336–13341 (2016).

  18. 18.

    Tebaldi, C., Arblaster, J. M. & Knutti, R. Mapping model agreement on future climate projections. Geophys. Res. Lett. 38, L23701 (2011).

  19. 19.

    Magnan, A. K. et al. Addressing the risk of maladaptation to climate change. WIREs Clim. Change 7, 646–665 (2016).

  20. 20.

    Jones, R. N. et al. in Climate Change 2014: Impacts, Adaptation, and Vulnerability (eds Field, C. B. et al.) Ch. 2 (IPCC, Cambridge Univ. Press, 2014).

  21. 21.

    Morim, J., Hemer, M., Cartwright, N., Strauss, D. & Andutta, F. On the concordance of 21st century wind-wave climate projections. Glob. Planet. Change 167, 160–171 (2018).

  22. 22.

    Hemer, M. A., Wang, X. L., Weisse, R. & Swail, V. R. Advancing wind-waves climate science. Bull. Am. Meteorol. Soc. 93, 791–796 (2012).

  23. 23.

    Hemer, M. A., Fan, Y., Mori, N., Semedo, A. & Wang, X. L. Projected changes in wave climate from a multi-model ensemble. Nat. Clim. Change 3, 471–476 (2013).

  24. 24.

    Church, J. A. et al. in Climate Change 2013: The Physical Science Basis (eds Stocker, T. F. et al.) 1140–1141 (IPCC, Cambridge Univ. Press, 2013).

  25. 25.

    Hemer, M. A. & Trenham, C. E. Evaluation of a CMIP5 derived dynamical global wind wave climate model ensemble. Ocean Model. 103, 190–203 (2016).

  26. 26.

    Mentaschi, L., Vousdoukas, M. I., Voukouvalas, E., Dosio, A. & Feyen, L. Global changes of extreme coastal wave energy fluxes triggered by intensified teleconnection patterns. Geophys. Res. Lett. 44, 2416–2426 (2017).

  27. 27.

    Erikson, L. H., Hegermiller, C. A., Barnard, P. L., Ruggiero, P. & van Ormondt, M. Projected wave conditions in the Eastern North Pacific under the influence of two CMIP5 climate scenarios. Ocean Model. 96, 171–185 (2015).

  28. 28.

    Bricheno, L. M. & Wolf, J. Future wave conditions of Europe, in response to high-end climate change scenarios. J. Geophys. Res. Oceans 123, 8762–8791 (2018).

  29. 29.

    Casas-Prat, M., Wang, X. L. & Swart, N. CMIP5-based global wave climate projections including the entire Arctic Ocean. Ocean Model. 123, 66–85 (2018).

  30. 30.

    Semedo, A. et al. CMIP5-derived single-forcing, single-model, and single-scenario wind-wave climate ensemble: configuration and performance evaluation. J. Mar. Sci. Eng. 6, 90 (2018).

  31. 31.

    Timmermans, B., Stone, D., Wehner, M. & Krishnan, H. Impact of tropical cyclones on modeled extreme wind-wave climate. Geophys. Res. Lett. 44, 1393–1401 (2017).

  32. 32.

    Tomoya, S., Nobuhito, M. & A., H. M. Variability and future decreases in winter wave heights in the Western North Pacific. Geophys. Res. Lett. 43, 2716–2722 (2016).

  33. 33.

    Camus., P. et al. Statistical wave climate projections for coastal impact assessments. Earth’s Future 5, 918–933 (2017).

  34. 34.

    Wang, X. L., Feng, Y. & Swail, V. R., Climate change signal and uncertainty in CMIP5-based projections of global ocean surface wave heights. J. Geophys. Res. Oceans 120, 3859–3871 (2015).

  35. 35.

    Vousdoukas, M. I. et al. Global probabilistic projections of extreme sea levels show intensification of coastal flood hazard. Nat. Commun. 9, 2360 (2018).

  36. 36.

    Vousdoukas, M. I. et al. Climatic and socioeconomic controls of future coastal flood risk in Europe. Nat. Clim. Change 8, 776–780 (2018).

  37. 37.

    Hinkel, J. et al. Coastal flood damage and adaptation costs under 21st century sea-level rise. Proc. Natl Acad. Sci. USA 111, 3292–3297 (2014).

  38. 38.

    Hallegatte, S., Green, C., Nicholls, R. J. & Corfee-Morlot, J. Future flood losses in major coastal cities. Nat. Clim. Change 3, 802–806 (2013).

  39. 39.

    Wahl, T. et al. Understanding extreme sea levels for broad-scale coastal impact and adaptation analysis. Nat. Commun. 8, 16075 (2017).

  40. 40.

    Arkema, K. K. et al. Coastal habitats shield people and property from sea-level rise and storms. Nat. Clim. Change 3, 913–918 (2013).

  41. 41.

    Hemer, M., Wang, X., Webb, A. & COWCLIP contributors Report of the 2018 Meeting for the WCRP-JCOMM Coordinated Ocean Wave Climate Project (COWCLIP) (WMO, 2018).

  42. 42.

    Hemer, M., Wang, W., Charles, E., Hegermiller, C. & COWCLIP contributors Report of the 2014 Meeting for the WCRP-JCOMM Coordinated Global Wave Climate Projections (COWCLIP) (WMO, 2014).

  43. 43.

    Ribal, A. & Young, I. R. 33 years of globally calibrated wave height and wind speed data based on altimeter observations. Sci. Data 6, 77 (2019).

  44. 44.

    Stopa, J. E. & Cheung, K. F. Intercomparison of wind and wave data from the ECMWF Reanalysis Interim and the NCEP Climate Forecast System Reanalysis. Ocean Model. 75, 65–83 (2014).

  45. 45.

    Dee, D. P. et al. The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Q. J. R. Meteorol. Soc. 137, 553–597 (2011).

  46. 46.

    Taylor, K. E. Summarizing multiple aspects of model performance in a single diagram. J. Geophys. Res. Atmos. 106, 7183–7192 (2001).

  47. 47.

    Wang, X. L., Feng, Y. & Swail, V. R. Changes in global ocean wave heights as projected using multimodel CMIP5 simulations. Geophys. Res. Lett. 41, 1026–1034 (2014).

  48. 48.

    Kar-Man Chang, E. CMIP5 projected change in Northern Hemisphere winter cyclones with associated extreme winds. J. Clim. 31, 6527–6542 (2018).

  49. 49.

    Karnauskas, K. B., Lundquist, J. K. & Zhang, L. Southward shift of the global wind energy resource under high carbon dioxide emissions. Nat. Geosci. 11, 38–43 (2018).

  50. 50.

    Sigmond, M., Reader, M. C., Fyfe, J. C. & Gillett, N. P. Drivers of past and future Southern Ocean change: stratospheric ozone versus greenhouse gas impacts. Geophys. Res. Lett. 38, L12601 (2011).

  51. 51.

    Millar, R. J. et al. Emission budgets and pathways consistent with limiting warming to 1.5 °C. Nat. Geosci. 10, 741–747 (2017).

  52. 52.

    Sierra, J. P. & Casas-Prat, M. Analysis of potential impacts on coastal areas due to changes in wave conditions. Climatic Change 124, 861–876 (2014).

  53. 53.

    Vousdoukas, M. I., Mentaschi, L., Voukouvalas, E., Verlaan, M. & Feyen, L. Extreme sea levels on the rise along Europe’s coasts. Earth’s Future 5, 304–323 (2017).

  54. 54.

    Sallenger, Jr, A. H., Doran, K. S. & Howd, P. A. Hotspot of accelerated sea-level rise on the Atlantic coast of North America. Nat. Clim. Change 2, 884–888 (2012).

  55. 55.

    Almar, R. et al. Response of the Bight of Benin (Gulf of Guinea, West Africa) coastline to anthropogenic and natural forcing. Part 1: Wave climate variability and impacts on the longshore sediment transport. Cont. Shelf Res. 110, 48–59 (2015).

  56. 56.

    Khon, V. C. et al. Wave heights in the 21st century Arctic Ocean simulated with a regional climate model. Geophys. Res. Lett. 41, 2956–2961 (2014).

  57. 57.

    Jacob, D. et al. EURO-CORDEX: new high-resolution climate change projections for European impact research. Reg. Environ. Change 14, 563–578 (2014).

  58. 58.

    Stopa, J. E. Wind forcing calibration and wave hindcast comparison using multiple reanalysis and merged satellite wind datasets. Ocean Model. 127, 55–69 (2018).

  59. 59.

    Campos, R. M., Alves, J. H. G. M., Guedes Soares, C., Guimaraes, L. G. & Parente, C. E. Extreme wind-wave modeling and analysis in the south Atlantic Ocean. Ocean Model. 124, 75–93 (2018).

  60. 60.

    Hasselmann, S., Hasselmann, K., Allender, J. H. & Barnett, T. P. Computations and parameterizations of the nonlinear energy transfer in a gravity-wave specturm. Part II: parameterizations of the nonlinear energy transfer for application in wave models. J. Phys. Oceanogr. 15, 1378–1391 (1985).

  61. 61.

    van Vledder, G. P., C. Hulst, S. T. & McConochie, J. D. Source term balance in a severe storm in the Southern North Sea. Ocean Dynam. 66, 1681–1697 (2016).

  62. 62.

    Dietrich, J. C. et al. Limiters for spectral propagation velocities in SWAN. Ocean Model. 70, 85–102 (2013).

  63. 63.

    Reguero, B. G., Losada, I. J. & Méndez, F. J. A recent increase in global wave power as a consequence of oceanic warming. Nat. Commun. 10, 205 (2019).

  64. 64.

    Stammer, D., Van Der Wal, R., Nicholls, J. R. & Schlosser, P. WCRP/IOC Sea Level 2017 Conference Statement. International WCRP/IOC Conference 2017 – Regional Sea Level Changes and Coastal Impacts (Columbia Univ., 2017).

  65. 65.

    Young, I. R., Sanina, E. & Babanin, A. V. Calibration and cross validation of a global wind and wave database of altimeter, radiometer, and scatterometer measurements. J. Atmos. Ocean. Technol. 34, 1285–1306 (2017).

  66. 66.

    Semedo, A. et al. Projection of global wave climate change toward the end of the twenty-first century. J. Clim. 26, 8269–8288 (2013).

  67. 67.

    Kumar, P., Min, S.-K., Weller, E., Lee, H. & Wang, X. L. Influence of climate variability on extreme ocean surface wave heights assessed from ERA-Interim and ERA-20C. J. Clim. 29, 4031–4046 (2016).

  68. 68.

    Ward, J. H. Hierarchical grouping to optimize an objective function. J. Am. Stat. Assoc. 58, 236–244 (1963).

  69. 69.

    Storch, H. V. & Zwiers, F. W. Statistical Analysis in Climate Research (Cambridge Univ. Press, 1999).

  70. 70.

    Flato, G. et al. in Climate Change 2013: The Physical Science Basis (eds Stocker, T. F. et al.) 741–882 (IPCC, Cambridge Univ. Press, 2013).

  71. 71.

    Bosshard, T. et al. Quantifying uncertainty sources in an ensemble of hydrological climate-impact projections. Water Resour. Res. 49, 1523–1536 (2013).

  72. 72.

    Garcia, R. A., Burgess, N. D., Cabeza, M., Rahbek, C. & Araújo, M. B. Exploring consensus in 21st century projections of climatically suitable areas for African vertebrates. Glob. Change Biol. 18, 1253–1269 (2012).

  73. 73.

    Zhao, Y. et al. Potential escalation of heat-related working costs with climate and socioeconomic changes in China. Proc. Natl Acad. Sci. USA 113, 4640 (2016).

  74. 74.

    Collins, M. et al. in Climate Change 2013: The Physical Science Basis (eds Stocker, T. F. et al.) 1041–1042 (IPCC, Cambridge Univ. Press, 2013).

  75. 75.

    Skinner, C. B. & Diffenbaugh, N. S. Projected changes in African easterly wave intensity and track in response to greenhouse forcing. Proc. Natl Acad. Sci. USA 111, 6882 (2014).

  76. 76.

    Wessel, P. & Smith, W. H. F. A global, self-consistent, hierarchical, high-resolution shoreline database. J. Geophys. Res. Solid Earth 101, 8741–8743 (1996).

  77. 77.

    Shope, J. B., Storlazzi, C. D., Erikson, L. H. & Hegermiller, C. A. Changes to extreme wave climates of islands within the Western Tropical Pacific throughout the 21st century under RCP 4.5 and RCP 8.5, with implications for island vulnerability and sustainability. Glob. Planet. Change 141, 25–38 (2016).

  78. 78.

    Perez, J., Menendez, M. & Losada, I. J. GOW2: a global wave hindcast for coastal applications. Coast. Eng. 124, 1–11 (2017).

Download references

Acknowledgements

This study represents Task 3 of the second phase of COWCLIP (https://cowclip.org/), an international collaborative working group endorsed by the Joint Technical Commission for Oceanography and Marine Meteorology, a partnership between the World Meteorological Organization) and the Intergovernmental Oceanographic Commission of UNESCO. We acknowledge the different climate-modelling groups, the Program for Climate Model Diagnosis and Intercomparison and the World Climate Research Program’s Working Group on Coupled Modelling. We acknowledge ECMWF for availability of ERAI data, and Australia’s Integrated Marine Observing System for altimeter wind/wave data, used for model validation. J.M., M.H. and C.T. acknowledge the support of the Australian Government National Environmental Science Program Earth Systems and Climate Change Hub. B.T. and M.W. acknowledge the support of the Regional and Global Climate Modeling Program of the US Department of Energy, Office of Science, Office of Biological and Environmental Research, through contract No. DE-AC02–05CH11231, and the National Energy Research Supercomputing Center of the LBNL. I.Y. acknowledges ongoing support from the Australian Research Council through grant No. DP160100738, and to the Integrated Marine Observing System. N.M., T.S., A.B. and B.K. acknowledge the support of the TOUGOU Program by MEXT, Japan, JSPS-Kakenhi Program. L.E. acknowledges the support of the US Geological Survey Coastal and Marine Hazards/Resources Program. Ø.B. and O.A. acknowledge the support of the Research Council of Norway through the ExWaMar project through grant No. 256466. We thank all contributors to the COWCLIP project, including C. Appendini (National Autonomous University of Mexico, Mexico), F. Ardhuin (Ifremer, France), N. Groll (Helmholtz-Zentrum Geesthacht Zentrum, Germany), S. Gallagher (Met Éireann, Ireland), S. Gulev (Moscow State University, Russia) and W. Perrie (Bedford Institute of Oceanography, Canada).

Author information

All authors (except C.T., N.C., M.W., B.T. and F.A.) had input into experimental design via workshops. J.M. led the analysis of ensemble, algorithm development for data analysis and writing of the manuscript. M.H. co-led and conceived the experiment, supervised analysis, provided CSIRO ensemble data and co-wrote the manuscript. X.L.W. co-led and conceived the experiment, developed community codes, provided ECCC ensemble data and contributed to analysis and writing of the manuscript. N.C. supervised analysis and contributed to writing the manuscript. C.T. provided CSIRO ensemble data, coordinated data and contributed to writing the manuscript. I.Y. provided satellite data and contributed to analysis and writing the manuscript. A.S. provided IHE ensemble data and contributed to analysis and writing the manuscript. N.M. and T.S. provided KU ensemble data and contributed to writing the manuscript. L.E. provided USGS ensemble data and contributed to writing the manuscript. O.A. and Ø.B. contributed ERAI statistics. M.D., A.B. and J. Staneva contributed IHE ensemble data. L.M. contributed Joint Research Centre ensemble data and developed community codes. M.C.-P. contributed ECCC ensemble data and contributed to writing the manuscript. P.C. and M.M. contributed IHC ensemble data and contributed to writing the manuscript. B.T. and M.W. contributed LBNL ensemble data and contributed to writing the manuscript. L.B. and J.W. contributed NOC ensemble data. A.W. and B.K. had input via workshops. J. Stopa contributed to analysis and writing the manuscript. F.A. assisted with figure development.

Correspondence to Joao Morim.

Additional information

Peer review information: Nature Climate Change thanks Gonéri Le Cozannet and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Supplementary Information

Supplementary Tables 1–4, Figs. 1–29 and references.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark