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Robustness and uncertainties in global multivariate wind-wave climate projections

Nature Climate Change volume 9, pages 711–718 (2019)Cite this article

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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.

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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 \({\bar{\boldsymbol{H}}}_{\boldsymbol{s}}\).

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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. 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).

    Article  Google Scholar 

  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).

    Google Scholar 

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

    Article  CAS  Google Scholar 

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

    Article  CAS  Google Scholar 

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

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

    Article  Google Scholar 

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

    Article  Google Scholar 

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

    Article  CAS  Google Scholar 

  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).

    Article  Google Scholar 

  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).

    Article  Google Scholar 

  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).

    Article  Google Scholar 

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

    Article  Google Scholar 

  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).

    Article  Google Scholar 

  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).

    Article  Google Scholar 

  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).

    Article  Google Scholar 

  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).

    Article  CAS  Google Scholar 

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

    Article  Google Scholar 

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

    Article  Google Scholar 

  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. 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).

    Article  Google Scholar 

  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).

    Article  Google Scholar 

  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).

    Article  Google Scholar 

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

    Article  Google Scholar 

  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).

    Article  Google Scholar 

  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).

    Article  Google Scholar 

  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. 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).

    Article  Google Scholar 

  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).

    Article  Google Scholar 

  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).

    Article  Google Scholar 

  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).

    Article  Google Scholar 

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

    Article  Google Scholar 

  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).

    Article  Google Scholar 

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

    Article  CAS  Google Scholar 

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

    Article  Google Scholar 

  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).

    Article  CAS  Google Scholar 

  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).

    Article  Google Scholar 

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

  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).

    Article  Google Scholar 

  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. 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. 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).

    Article  Google Scholar 

  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).

    Article  Google Scholar 

  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).

    Article  Google Scholar 

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

    Article  Google Scholar 

  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).

    Article  Google Scholar 

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

    Article  Google Scholar 

  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).

    Article  CAS  Google Scholar 

  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).

    Article  CAS  Google Scholar 

  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. 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).

    Article  Google Scholar 

  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).

    Article  Google Scholar 

  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).

    Article  Google Scholar 

  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).

    Article  Google Scholar 

  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).

    Article  Google Scholar 

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

    Article  Google Scholar 

  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).

    Article  Google Scholar 

  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).

    Article  Google Scholar 

  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).

    Article  Google Scholar 

  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).

    Article  Google Scholar 

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

    Article  Google Scholar 

  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).

    Article  CAS  Google Scholar 

  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. 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).

    Article  Google Scholar 

  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).

    Article  Google Scholar 

  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).

    Article  Google Scholar 

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

    Article  Google Scholar 

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

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

    Article  Google Scholar 

  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).

    Article  Google Scholar 

  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).

    Article  CAS  Google Scholar 

  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. 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).

    Article  CAS  Google Scholar 

  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).

    Article  Google Scholar 

  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).

    Article  Google Scholar 

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

    Article  Google Scholar 

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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).

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Authors and Affiliations

  1. School of Built Environment and Engineering, Griffith University, Southport, Queensland, Australia

    Joao Morim, Nick Cartwright & Fernando Andutta

  2. Commonwealth Scientific and Industrial Research Organisation Oceans and Atmosphere, Hobart, Tasmania, Australia

    Joao Morim, Mark Hemer & Claire Trenham

  3. US Geological Survey, Pacific Coastal and Marine Science Center, Santa Cruz, CA, USA

    Joao Morim & Li Erikson

  4. Environment and Climate Change Canada, Climate Research Division, Toronto, Ontario, Canada

    Xiaolan L. Wang & Mercè Casas-Prat

  5. IHE-Delft, Department of Water Science and Engineering, Delft, the Netherlands

    Alvaro Semedo

  6. Instituto Dom Luiz, Faculty of Sciences of the University of Lisbon, Lisbon, Portugal

    Alvaro Semedo

  7. Department of Infrastructure Engineering, University of Melbourne, Parkville, Victoria, Australia

    Ian Young

  8. National Oceanographic Centre, Liverpool, UK

    Lucy Bricheno & Judith Wolf

  9. Environmental Hydraulics Institute (IHCantabria), Universidad de Cantabria, Santander, Spain

    Paula Camus & Melisa Menendez

  10. European Commission, Joint Research Centre, Ispra, Italy

    Lorenzo Mentaschi

  11. Disaster Prevention Research Institute, Kyoto University, Kyoto, Japan

    Nobuhito Mori, Tomoya Shimura & Adrean Webb

  12. Climate and Ecosystems Science Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA

    Ben Timmermans

  13. Norwegian Meteorological Institute, Bergen, Norway

    Ole Aarnes & Øyvind Breivik

  14. Geophysical Institute, University of Bergen, Bergen, Norway

    Øyvind Breivik

  15. Helmholtz-Zentrum Geesthacht Centre for Materials and Coastal Research, Geesthacht, Germany

    Arno Behrens & Joanna Staneva

  16. Institute of Oceanography, Center for Earth System Research and Sustainability, Universität Hamburg, Hamburg, Germany

    Mikhail Dobrynin

  17. Computational Research Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA

    Michael Wehner

  18. Graduate School of Advanced Integrated Studies in Human Survivability/Hakubi Center for Advanced Research, Kyoto University, Kyoto, Japan

    Bahareh Kamranzad

  19. Department of Ocean and Resources Engineering, University of Hawai’i at Mānoa, Honolulu, HI, USA

    Justin Stopa

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Contributions

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.

Corresponding author

Correspondence to Joao Morim.

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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.

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Morim, J., Hemer, M., Wang, X.L. et al. Robustness and uncertainties in global multivariate wind-wave climate projections. Nat. Clim. Chang. 9, 711–718 (2019). https://doi.org/10.1038/s41558-019-0542-5

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