• Atmosphere
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• v.27 no.3
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• pp.261-276
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• 2017

The main objectives of this study are to introduce Global Seasonal forecasting system version5 (GloSea5) of KMA and to evaluate the performance of ensemble prediction of system. KMA has performed an operational seasonal forecast system which is a joint system between KMA and UK Met office since 2014. GloSea5 is a fully coupled global climate model which consists of atmosphere (UM), ocean (NEMO), land surface (JULES) and sea ice (CICE) components through the coupler OASIS. The model resolution, used in GloSea5, is N216L85 (~60 km in mid-latitudes) in the atmosphere and ORCA0.25L75 ($0.25^{\circ}$ on a tri-polar grid) in the ocean. In this research, we evaluate the performance of this system using by RMSE, Correlation and MSSS for ensemble mean values. The forecast (FCST) and hindcast (HCST) are separately verified, and the operational data of GloSea5 are used from 2014 to 2015. The performance skills are similar to the past study. For example, the RMSE of h500 is increased from 22.30 gpm of 1 week forecast to 53.82 gpm of 7 week forecast but there is a similar error about 50~53 gpm after 3 week forecast. The Nino Index of SST shows a great correlation (higher than 0.9) up to 7 week forecast in Nino 3.4 area. It can be concluded that GloSea5 has a great performance for seasonal prediction.

• Atmosphere
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• v.29 no.4
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• pp.391-401
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• 2019

This study first investigates the changes of the mean and extreme temperatures and precipitation in East Asia (EA) under stabilized 1.5℃ and 2℃ warming conditions above preindustrial levels provided by HAPPI project. Here, five model with 925 members for 10-year historical period (2006~2015) and 1.5/2.0℃ future warming scenarios (2091~2100) have been used and monthly based data have been analyzed. The results show that the spatial distribution fields over EA and domain averaged variables in HAPPI 1.5/2.0℃ hindcast simulations are comparable to observations. It is found that the magnitude of mean temperature warming in EA and Korea is similar to the global mean, but for extreme temperatures local higher warming trend for minimum temperature is significant. In terms of precipitation, most subregion in EA will see more increased precipitation under 1.5/2.0℃ warming compared to the global mean. These attribute for probability density function of analyzed variables to get wider with increasing mean values in 1.5/2.0℃ warming conditions. As the result of vulnerability of 0.5℃ additional warming from 1.5 to 2.0℃, 0.5℃ additional warming contributes to the increases in extreme events and especially the impact over South Korea is slightly larger than EA. Therefore, limiting global warming by 0.5℃ can help avoid the increases in extreme temperature and precipitation events in terms of intensity and frequency.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.31 no.6
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• pp.478-484
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• 2019

The submarine cable for Yongsu wave power plant was cut in 2014 winter. This study investigated the probability of high-wave occurrence exceeding the 50-year return period and the underestimation of armor unit weight used to protect the cable. The observation data from KMA buoy and the hindcast wave data were reviewed to determine the return period of wave height during the winter. In order to investigate the armor unit weight of cable-protection, we calculated the required weight of armor unit using not only Design Standard for Harbor and Fishery Port, but also the previous researches for the wave with large incident angle. As a result, it appeared that the high wave exceeding the 50-year return period did not occur during the winter of 2014 and the armor unit weight of the cable protection was not sufficient to sustain the obliquely incident wave, which induced the cable protection failure.

• 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 Korea Water Resources Association
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• v.44 no.3
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• pp.209-220
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• 2011

Input uncertainty is one of the major sources of uncertainty in hydrologic modeling. In this paper, first, three alternate rainfall inputs generated by different interpolation schemes were used to see the impact on a distributed watershed model. Later, the residuals of precipitation interpolations were tested as a source of ensemble streamflow generation in two river basins in the U.S. Using the Monte Carlo parameter search, the relationship between input and parameter uncertainty was also categorized to see sensitivity of the parameters to input differences. This analysis is useful not only to find the parameters that need more attention but also to transfer parameters calibrated for station measurement to the simulation using different inputs such as downscaled data from weather generator outputs. Input ensembles that preserves local statistical characteristics are used to generate streamflow ensembles hindcast, and showed that the ensemble sets are capturing the observed steamflow properly. This procedure is especially important to consider input uncertainties in the simulation of streamflow forecast.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.19 no.6
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• pp.574-585
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• 2007

To analyze the incident wave characteristics around Haeundae beach the long-term deep water wave data computed by wave hindcast method were used and a continuous wave observation was carried out for 1 year at the 20 m of water depth in front of Haeundae beach. Wave observation data showd that the prevalent wave direction was SSW-S in spring and summer seasons while E-SE in autumn and winter. A numerical modeling shows that the waves from E-SE are refracted strongly due to the shoal developed at the south-east side of Haeundae beach. The simulation also shows inflowing nearshore current along the east coast of the beach develops strongly in autumn and winter. Radioactive isotope tracer experiment for 155 days indicated that the tracers moves to the on-shore direction in the 1st and 2nd tracking then dispersed to the E-W direction along the shore.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.10 no.4
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• pp.165-173
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• 1998

Analytical solutions to predict the movement rate of submerged mound are derived using the convection coefficient and the joint distribution function of wave heights and periods. Assuming that the sediment is moved onshore due to the velocity asymmetry of Stokes' second order nonlinear wave theory, the micro-scale bedload transport equation is applied to the sediment conservation. The nonlinear convection-diffusion equation can then be obtained which governs the migration of submerged mound. The movement rate decreases exponentially with increasing the water depth, but the movement rate tends to increase as the spectral width parameter, $ u$ increases. In comparison of the analytical solution with the measured data, it is found that the analytical solution overestimates the movement rate. However, the agreement between the analytical solution and the measured data is encouraging since this over-estimation may be due to the inaccuracy of input data and the limitation of sediment transport model. In particular, the movement rates with respect to the water depth predicted by the analytical solution are in very good agreement with the estimated result using the discritization technique with the hindcast wave data.

• Atmosphere
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• v.28 no.3
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• pp.233-245
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• 2018

This study explores the Subseasonal-to-Seasonal (S2S) prediction skills of the Northern Hemisphere mid-latitude geopotential height in the Global Seasonal forecasting model version 5 (GloSea5) hindcast experiment. The prediction skills are quantitatively verified for the period of 1991~2010 by computing the Anomaly Correlation Coefficient (ACC) and Mean Square Skill Score (MSSS). GloSea5 model shows a higher prediction skill in winter than in summer at most levels regardless of verification methods. Quantitatively, the prediction limit diagnosed with ACC skill of 500 hPa geopotential height, averaged over $30^{\circ}N{\sim}90^{\circ}N$, is 11.0 days in winter, but only 9.1 days in summer. These prediction limits are primarily set by the planetary-scale eddy phase errors. The stratospheric prediction skills are typically higher than the tropospheric skills except in the summer upper-stratosphere where prediction skills are substantially lower than upper-troposphere. The lack of the summer upper-stratospheric prediction skill is caused by zonal mean error, perhaps strongly related to model mean bias in the stratosphere.

• Atmosphere
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• v.30 no.3
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• pp.209-220
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• 2020

Seasonal predictability and variability of tropical storms (TCs) simulated in the Global Seasonal Forecast System version 5 (GloSea5) of the Korea Meteorological Administration (KMA) is assessed in Northern Hemisphere in 1996~2009. In the KMA, the GloSea5-Global Atmosphere version 3.0 (GloSea5-GA3) that was previously operated was switched to the GloSea5-Global Coupled version 2.0 (GloSea5-GC2) with data assimilation system since May 2016. In this study, frequency, track, duration, and strength of the TCs in the North Indian Ocean, Western Pacific, Eastern Pacific, and North Atlantic regions derived from the GloSea5-GC2 and GloSea5-GA3 are examined against the best track data during the research period. In general, the GloSea5 shows a good skill for the prediction of seasonally averaged number of the TCs in the Eastern and Western Pacific regions, but underestimation of those in the North Atlantic region. Both the GloSea5-GA3 and GC2 are not able to predict the recurvature of the TCs in the North Western Pacific Ocean (NWPO), which implies that there is no skill for the prediction of landfalls in the Korean peninsula. The GloSea5-GC2 has higher skills for predictability and variability of the TCs than the GloSea5-GA3, although continuous improvements in the operational system for seasonal forecast are still necessary to simulate TCs more realistically in the future.

• Atmosphere
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• v.30 no.3
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• pp.293-309
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• 2020

There are lots of indices that define the intensity of East Asian summer monsoon (EASM) in climate systems. This paper assesses the prediction skill for EASM indices in a Global Seasonal Forecasting System (GloSea5) that is currently operating at KMA. Total 5 different types of EASM indices (WNPMI, EAMI, WYI, GUOI, and SAHI) are selected to investigate how well GloSea5 reproduces them using hindcasts with 12 ensemble members with 1~3 lead months. Each index from GloSea5 is compared to that from ERA-Interim. Hindcast results for the period 1991~2010 show the highest prediction skill for WNPMI which is defined as the difference between the zonal winds at 850 hPa over East China Sea and South China Sea. WYI, defined as the difference between the zonal winds of upper and lower level over the Indian Ocean far from East Asia, is comparatively well captured by GloSea5. Though the prediction skill for EAMI which is defined by using meridional winds over areas of East Asia and Korea directly affected by EASM is comparatively low, it seems that EAMI is useful for predicting the variability of precipitation by EASM over East Asia. The regressed atmospheric fields with EASM index and the correlation with precipitation also show that GloSea5 best predicts the synoptic environment of East Asia for WNPMI among 5 EASM indices. Note that the result in this study is limited to interpret only for GloSea5 since the prediction skill for EASM index depends greatly on climate forecast model systems.