National Institute of Meteorological Research KMA

Seoul, South Korea

National Institute of Meteorological Research KMA

Seoul, South Korea

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Lee D.S.,Korea Ocean Research and Development Institute | Oh S.-H.,Korea Ocean Research and Development Institute | Yi J.-H.,Korea Ocean Research and Development Institute | Park W.-S.,Korea Ocean Research and Development Institute | And 4 more authors.
Renewable Energy | Year: 2010

The change of water discharge capability of the sluice caisson of tidal power plant according to the change of geometrical shape of the sluice caisson was investigated by performing laboratory experiments. The major design parameters that constitute general shape of the sluice caisson were deduced and a total of 32 different shapes of sluice caisson models were subjected to the hydraulic experiments. For every sluice caisson model, the water discharge capability was estimated with five different flow rates and three different water level conditions. The experiments were carried out in an open channel flume with a great care to measure flow rate and water level accurately, which are key physical quantities in estimating the water discharge capability of the sluice caisson models. By analyzing the experimental results, influence of the respective design parameters on the performance of the sluice caisson was examined and the general guidelines to enhance the water discharge capability were suggested. The discharge coefficient of the best sluice caisson model ranged from 2.3 to 3.1 depending on the experimental conditions, which is far higher than the values that were adopted in the past feasibility studies in Korea. © 2010 Elsevier Ltd.


You S.H.,National Institute of Meteorological Research KMA
Terrestrial, Atmospheric and Oceanic Sciences | Year: 2010

This study was performed to compare storm surges simulated by the operational storm surges/tide forecast system (STORM : Storm surges/Tide Operational Model) of the Korea Meteorological Administration (KMA) with observations from 30 coastal tidal stations during nine typhoons that occurred between 2005 and 2007. The results (bias) showed that for cases of overestimation (or underestimation), storm surges tended to be overestimated (as well as underestimated) at all coastal stations. The maximum positive bias was approximately 6.92 cm for Typhoon Ewiniar (2006), while the maximum negative bias was approximately -12.06 cm for Typhoon Khanun (2005). The maximum and minimum root mean square errors (RMSEs) were 14.61 and 6.78 cm, which occurred for Typhoons Khanun (2005) and Usagi (2007), respectively. For all nine typhoons, total averaged RMSE was approximately 10.2 cm. Large differences between modeled and observed storm surges occurred in two cases. In the first, a very weak typhoon, such as Typhoon Khanun (2005), caused low storm surges. In the other, exemplified by Typhoon Nari (2007), there were errors in the predicted typhoon strength used as input data for the storm surge model.


Jung B.-J.,Yonsei University | Kim H.M.,Yonsei University | Kim Y.-H.,National Institute of Meteorological Research KMA | Jeon E.-H.,National Institute of Meteorological Research KMA | Kim K.-H.,National Institute of Meteorological Research KMA
Asia-Pacific Journal of Atmospheric Sciences | Year: 2010

In this study, the impact of various types of observations on the track forecast of Tropical Cyclone (TC) Jangmi (200815) is examined by using the Weather Research and Forecasting (WRF) model and the corresponding three-dimensional variational (3DVAR) data assimilation system. TC Jangmi is a recurving typhoon that is observed as part of the THORPEX Pacific Asian Regional Campaign (T-PARC). Conventional observations from the Korea Meteorological Administration (KMA) and targeted dropsonde observations from the Dropwindsonde Observations for Typhoon Surveillance near the Taiwan Region (DOTSTAR) were used for a series of observation system experiments (OSEs). We found that the assimilation of observations in oceanic areas is important to analyze environmental flows (such as the North Pacific high) and to predict the recurvature of TC Jangmi. The assimilation of targeted dropsonde observations (DROP) results in a significant impact on the track forecast. Observations of ocean surface winds (QSCAT) and satellite temperature soundings (SATEM) also contribute positively to the track forecast, especially two- to three-day forecasts. The impact of sensitivity guidance such as real-time singular vectors (SVs) was evaluated in additional experiments. © 2010 Korean Meteorological Society and Springer Netherlands.


You S.H.,Observation Infrastructure Bureau KMA | Lee Y.H.,National Institute of Meteorological Research KMA | Lee W.J.,National Institute of Meteorological Research KMA
Natural Hazards | Year: 2012

A genetic algorithm was used to optimize the parameters of the two-dimensional Storm Surge/Tide Operational Model (STORM) to improve sea level predictions of storm surges. The model was then tested using data from Typhoon Maemi, which landed on the Korean Peninsula in 2003. The following model parameters were used: the coefficients for bottom drag, background horizontal diffusivity, Smagorinsky's horizontal viscosity, and sea level pressure scaling. The simulation results using the optimized parameters improved sea level predictions. This study demonstrates that parameter optimizations and their adequate applications are essential for improving model performance. © 2011 Springer Science+Business Media B.V.


You S.H.,Observation Infrastructure Bureau KMA | Lee Y.H.,National Institute of Meteorological Research KMA | Lee W.J.,National Institute of Meteorological Research KMA
Advances in Atmospheric Sciences | Year: 2011

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. © 2011 China National Committee for International Association of Meteorology and Atmospheric Sciences (IAMAS), Institute of Atmospheric Physics (IAP) and Science Press and Springer-Verlag Berlin Heidelberg.

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