Development of Stochastic Typhoon Model for Performance Design of Coastal Structures

Hashimoto, Noriaki; Kawai, Hiroki; Matsuura, Kuniaki; KAWAGUCHI, KOJI

doi:10.1142/9789812701916_0292

Cited by 3 publications

(3 citation statements)

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“…Among several research on stochastic typhoon models, Hashimoto et al (2004) divided typhoons affecting Japan from 1951 to 1999 into five seasons, (a) June and July, (b) August, (c) September, (d) October, and (e) other months, and estimated the parameters, (a) the location of the typhoon center, (b) the central pressure, (c) the radius of maximum wind speed, and their variation with time, in each season in each rectangular cell with a width of 1.5 degrees in longitude and a height of 1.5 degrees in latitude. On this analysis, the radius of maximum wind speed of each typhoon was estimated from the central pressure and the radius of a constant pressure contour on weather maps, provided from the Japan Meteorological Agency.…”

Section: Stochastic Typhoon Model and Future Typhoon Changementioning

confidence: 99%

Uncertainty of Extreme Storm Surge Estimation by High Wind Sea Surface Drag Coefficient and Future Typhoon Change

Kawai

Hashimoto

Yamashiro

et al. 2011

Int. Conf. Coastal. Eng.

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Japan has been constructing long coastal defense since the storm surge disaster with a loss of 5,000 lives by Typhoon Vera in 1959. The defense is designed for the storm water level including the storm surge of the standard typhoon based on Typhoon Vera. Stochastic typhoon model, simulating various typhoon track and intensity with Monte Carlo method, is one of useful tools to estimate the return period. According to recent research output the return period of the storm surge of the standard typhoon is near 100 years or more at three major bays in Japan. But there is uncer-tainty by some of parameters and models in the stochastic simulation. Sea surface drag coefficient under high wind speed and future change in typhoon intensity and track are critical to extreme values of the storm surges.

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Section: Stochastic Typhoon Model and Future Typhoon Changementioning

confidence: 99%

Uncertainty of Extreme Storm Surge Estimation by High Wind Sea Surface Drag Coefficient and Future Typhoon Change

Kawai

Hashimoto

Yamashiro

et al. 2011

Int. Conf. Coastal. Eng.

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“…There are several STMs which artificially generate typhoons that can be applied in coastal engineering studies (e.g. Hatada and Yamaguchi, 1996;Kato et al, 2003;Hashimoto et al, 2004;Kawai et al, 2006Kawai et al, , 2008 because STM is useful by statistically estimating typhoons tracks, the central atmospheric pressures and moving speeds and so on. Their simulation areas typically lie to the north of 23N because most of these studies focused on typhoon characteristics around Japan.…”

Section: Introductionmentioning

confidence: 99%

Stochastic Typhoon Model and Its Application to Future Typhoon Projection

Yasuda

Mase

Kunitomi³

et al. 2011

Int. Conf. Coastal. Eng.

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This study presents a stochastic typhoon model (STM) for estimating the characteristics of typhoons in the present and future climate conditions. Differences of statistical characteristics between present and future typhoons were estimated from projections by an Atmospheric General Circulation Model (AGCM) under a climate change scenario and are taken into account in the stochastic modelling of future typhoons as a climate change signal. From the STM results which utilize the Monte Carlo simulation, it was found that the frequency of typhoon landfall in Osaka bay area, Japan, will decrease, although the mean value of atmospheric central pressure of typhoon will not change significantly. The arrival probability of stronger typhoons will increase in the future climate scenario.

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“…Hatada and Yamaguchi, 1996;Kato et al, 2003;Hashimoto et al, 2004;Kawai et al, 2006Kawai et al, , 2008. Their simulation areas are typically higher than 23°N because most of these studies focused on typhoon characteristics around Japan.…”

Section: Introductionmentioning

confidence: 99%

Projection of future typhoons landing on Japan based on a stochastic typhoon model utilizing AGCM projections

Yasuda

Mase

Mori

2010

Hydrological Research Letters

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Abstract:This study presents a stochastic typhoon model (STM) for estimating the characteristics of typhoons in the present and future climate conditions. Differences between statistical characteristics of present and future typhoons were estimated from projections by an Atmospheric General Circulation Model (AGCM) under a climate change scenario and are taken into account in the stochastic modeling of future typhoons as a climate change signal. From the STM results which utilize the Monte Carlo simulation, it was found that the frequency of typhoon landfall in Japan, especially in three major bay areas, will decrease and the mean value of typhoon central atmospheric pressure will not change significantly. An important point is that the arrival probability of stronger typhoons will increase in the future climate scenario.

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Development of Stochastic Typhoon Model for Performance Design of Coastal Structures

Cited by 3 publications

References 0 publications

Uncertainty of Extreme Storm Surge Estimation by High Wind Sea Surface Drag Coefficient and Future Typhoon Change

Uncertainty of Extreme Storm Surge Estimation by High Wind Sea Surface Drag Coefficient and Future Typhoon Change

Stochastic Typhoon Model and Its Application to Future Typhoon Projection

Projection of future typhoons landing on Japan based on a stochastic typhoon model utilizing AGCM projections

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