How to Cite

Nakajo, S., Umeda, J., & Mori, N. (2020). APPLICABILITY OF D4PDF DATASET TO GLOBAL STOCHASTIC TROPICAL CYCLONE MODEL. Coastal Engineering Proceedings, (36v), papers.26.


Disaster damage caused by tropical cyclone has grown every year. However, our experience of tropical cyclone is not enough to evaluate very low frequent and catastrophic disaster event. Stochastic tropical cyclone model has been used for assessment of tropical cyclone disaster. Global stochastic model was improved by using a lot of ensemble Global Climate Model simulation data (d4PDF) instead of limited number of observation data. The model bias included d4PDF was corrected by each regional grid by simple statistical method and interpolation. The accuracy of new model was verified at representative regional area in different basins. Generally, the improvement is remarkable where tropical cyclones rarely passed. The variation of joint PDF of tropical cyclone change rate between previous model and present model agree with model improvement. As an example of application, the frequencies of strong tropical cyclone events of two cases were estimated.


Emanuel, K., Sundararajan, R. and Williams, J. 2008. Hurricanes and global warming :Results from downscaling IPCC AR4 simulations, BAMS, 89(3), 347-367.

James, M. K. and Mason, L. B. 2005. Synthetic tropical cyclone database, Journal of Waterway, Port, Coastal and Ocean Engineering, 131(4), 181-192.

Knapp, K. R., Kruk, M. C., Levinson, D. H., Diamond, H., J. and Neumann, C. J. 2010. The International Best Track Archive for Climate Stewardship (IBTrACS), BAMS, 91(3), 363-376.

Lee, C-Y., Tippett, M. K., Sobel, A. H. and Camargo, S. J. 2016. Autoregressive modeling for tropical cyclone intensity climatology, Journal of Climate, 29, 7815-7830.

Mizuta, R. et al. 2017. Over 5000 years of ensemble future climate simulations by 60 km global and 20 km regional atmospheric models, BAMS, 98(7), 1383-1398.

Mori, N., Yasuda, T., Arikawa, T., Kataoka, T., Nakajo, S., Suzuki, K., Yamanaka, Y., Webb, A. 2019. 2018 Typhoon Jebi post-event survey of coastal damage in the Kansai region, Japan, Coastal Engineering Journal, 61(3), 278-294.

Nakajo, S., Mori, N., Yasuda, T. and Mase, H. 2014. Global stochastic tropical cyclone model based on principal component analysis and cluster analysis, Journal of Applied Meteorology and Climatology, 53(6), 1547-1577.

Nott, J., Green, C., Townsend, I. and Callaghan, J. 2014. The World Record Storm Surge and the Most Intense Southern Hemisphere Tropical Cyclone: New Evidence and Modeling, BAMS, 95(5), 757-765.

Russell, L. R. 1968. Probability distributions for Texas Gulf coast hurricane effects of engineering interest, PhD thesis, Stanford University.

Vickery, P. J. and Twisdale, L. A. 1995. Prediction of hurricane wind speed in the United States, Journal of Structural Engineering., 121(11), 1691-1699.

Vickery, P. J., Skerlj, P. F. and Twisdale, L. A. 2000. Simulation of hurricane risk in the U.S. using empirical track model, Journal of Structural Engineering., 126(10), 1222-1237.

Whittingham, H. E. 1958. The Bathurst Bay Hurricane and associated storm surge, Australian Meteorological Magazine, 23, 14–36.

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