• Atmosphere
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• v.17 no.1
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• pp.27-44
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• 2007

The purpose of this study is to investigate predictability of the seasonal simulation by the METRI (Meteorological Research Institute) AGCM (Atmospheric General Circulation Model), which is a long-term prediction model for the METRI 3-month prediction system. We examine the performance skill of climate simulation and predictability by the analysis of variance of the METRI AGCM, focusing on the precipitation, 850 hPa temperature, and 500 hPa geopotential height. According to the result, the METRI AGCM shows systematic errors with seasonal march, and represents large errors over the equatorial region, compared to the observation. Also, the response of the METRI AGCM by the variation of the sea surface temperature is obvious for the wintertime and springtime. However, the METRI AGCM does not show the significant ENSO-related signal in autumn. In case of prediction over the east Asian region, errors between the prediction results and the observation are not quite large with the lead-time. However, in the predictability assessment using the analysis of variance method, longer lead-time makes the prediction better, and the predictability becomes better in the springtime.

• Atmosphere
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• v.19 no.2
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• pp.127-143
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• 2009

This study investigates characteristics of wintertime simulation conducted by METRI AGCM utilizing new radiation parameterization scheme. New radiation scheme is based on the method of Chou et al., and is utilized in the METRI AGCM recently. In order to analyze characteristics of seasonal simulation in boreal winter, hindcast dataset from 1979 to 2005 is produced in two experiments - control run (CTRL) and new model's run (RADI). Also, changes in performance skill and predictability due to implementation of new radiation scheme are examined. In the wintertime simulation, the RADI experiment tends to reduce warm bias in the upper troposphere probably due to intensification of longwave radiative cooling over the whole troposphere. The radiative cooling effect is related to weakening of longitudinal temperature gradient, leading to weaker tropospheric jet in the upper troposphere. In addition, changes in vertical thermodynamic structure have an influence on reduction of tropical precipitation. Moreover, the RADI case is less sensitive to variation of tropical sea surface temperature than the CTRL case, even though the RADI case simulates the mean climate pattern well. It implies that the RADI run does not have significant improvement in seasonal prediction point of view.

• Journal of the Korean Society of Hazard Mitigation
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• v.8 no.6
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• pp.37-45
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• 2008

It is expected that conditions of water resources will be changed in Korea in accordance with world wide climate change. In order to deal with this problem and find a way of minimizing the effect of future climate change, the usefulness of climate model simulation information is examined in this study. The objective of this study is to assess the applicability of GCM (General Circulation Model) information for Korean water resources management through uncertainty analysis. The methods are based on probabilistic measures of the effectiveness of GCM simulations of an indicator variable for discriminating high versus low regional observations of a target variable. The formulation uses the significance probability of the Kolmogorov-Smirnov test for detecting differences between two variables. An estimator that accounts for climate model simulation and spatial association between the GCM data and observed data is used. Atmospheric general circulation model (AGCM) simulations done by ECMWF (European Centre for Medium-Range Weather Forecasts) with a resolution of $2^{\circ}{\times}2^{\circ}$, and METRI (Meteorological Research Institute, Korea) with resolutions of $2^{\circ}{\times}2^{\circ}$ and $4^{\circ}{\times}5^{\circ}$, were used for indicator variables, while observed mean areal precipitation (MAP) data, discharge data and mean areal temperature data on the seven major river basins in Korea were used for target variables. The results show that GCM simulations are useful in discriminating the high from the low of the observed precipitation, discharge, and temperature values. Temperature especially can be useful regardless of model and season.