Parameterization and Application of Storm Surge/Tide Modeling Using a Genetic Algorithm for Typhoon Periods |
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Authors: | Sung Hyup YOU Yong Hee LEE and Woo Jeong LEE |
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Institution: | Marine Meteorology Division, Observation Infrastructure Bureau/KMA, Korea,Forecast Research Laboratory, National Institute of Meteorological Research/KMA, Korea,Global Environment System Research Laboratory, National Institute of Meteorological Research/KMA, Korea |
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Abstract: | A genetic algorithm was used to optimize the parameters of the
two-dimensional Storm Surge/Tide Operational Model (STORM) to improve sea
level predictions. The genetic algorithm was applied to nine typhoons that
affected the Korean Peninsula during 2005--2007. The following model
parameters were used: the bottom drag coefficient, the background horizontal
diffusivity, Smagorinski's horizontal viscosity, and the sea level pressure
scaling. Generally, the simulation results using the optimized, mean, and
median parameter values improved sea level predictions. The four estimated
parameters improved the sea level prediction by 76% and 54% in the
bias and root mean square error for Typhoon Kalmaegi (0807) in 2008,
respectively. One-month simulations of February and August 2008 were also
improved using the estimated parameters. This study demonstrates that
parameter optimization on STORM can improve sea level prediction. |
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Keywords: | genetic algorithm STORM sea level typhoon |
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