Climate Dynamics

, Volume 49, Issue 4, pp 1449–1462 | Cite as

Projection of tropical cyclone-generated extreme wave climate based on CMIP5 multi-model ensemble in the Western North Pacific

  • Tomoya ShimuraEmail author
  • Nobuhito Mori
  • Mark A. Hemer


Climate change impacts on future ocean wave climate have been studied using a suite of Global Climate Models (GCM). We investigated the representation of extreme (annual maximum) wave climate in the Atmosphere-Ocean GCM (AOGCM) driven wave climate projections, specifically looking at tropical cyclone (TC)-generated extreme waves in the Western North Pacific. The representation of the extreme wave climate by AOGCM driven wave climate projections was evaluated by comparing with higher-resolution AGCM driven wave climate projections, reanalysis and observations. We find better performance of AOGCM’s to simulate TCs leads to significantly improved representation of the extreme wave climate. The better performing models can produce more than \(30\hbox { ms}^{-1}\) wind speed in TCs and the frequency of occurrence of TCs is 80 % of the observed frequency of occurrence. The projected changes in the extreme wave climate are dominated by changes in TC-generated waves. Although the projected changes in TC-generated wave heights show the coherent decreases in some models with greater TC skill, there is a large variation in the projected changes among models. The other models which are less able to resolve the TC characteristics display projected changes dominated by non-TC generated waves systems, which is the decrease in wave heights around latitudes 30\(^{\circ }\)N. Although there is a large variation in the projected changes in TC-generated waves, the change ratio is 2 times larger than those of non-TC waves. Therefore, appropriate interpretation of the TC-generated wave changes and its variation is important for risk assessment.


Ocean surface wave Extreme wave climate Climate change Tropical cyclone 



The authors acknowledge the WCRP’s Working Group on Coupled Modelling for the CMIP5 data sets. TS were supported by the Japan Society for the Promotion of Science (JSPS) Fellowships for Young Scientists and Grant-in-Aid for JSPS Fellows (15J07767). This research was supported under the SOUSEI Program by the Ministry of Education, Culture, Sports, Science, and Technology-Japan (MEXT). MH was supported by the Australian Climate Change Science Programme of the Department of the Environment, Australian Government. This paper is a contribution to the JCOMM Coordinated Ocean Wave Climate Project (COWCLIP).


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Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  1. 1.Disaster Prevention Research InstituteKyoto UniversityGokasho, UjiJapan
  2. 2.Oceans and AtmosphereCSIROHobartAustralia

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