• Journal of the Korean earth science society
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• v.32 no.7
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• pp.750-760
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• 2011

In this study, the reproducibility of the simulated current climate by using two regional climate models, such as Seoul National University Regional Climate Model (SNURCM) and Weather Resuearch and Forecasting (WRF), is evaluated in advance to produce the standard regional climate scenario of future climate. Within the evaluation framework of a COordinated Regional climate Downscaling EXperiment (CORDEX), 28-year-long (1978-2005) regional climate simulation was conducted by using the Hadley Centre Global Environmental Model (HadGEM2-AO) global simulation data of the National Institute of Meteorological Research (NIMR) as a lateral boundary forcing. The simulated annual surface temperatures were in good agreement with the observation; the spatial correlation coefficients between each model and observation were over 0.98. The cold bias, however, were shown over the northern boundary in the both simulated results. In evaluation of the simulated precipitation, the skill was reasonable and good. The spatial correlation coefficients for the precipitation over the land area were 0.85 and 0.79 in SNURCM and WRF, respectively. It is noted that two regional climate models (RCMs) have different characteristics for the distribution of precipitation over equatorial and midlatitude areas. SNURCM shows better distribution of the simulated precipitation associated with the East Asia summer monsoon in the mid-latitude areas, but WRF shows better in the equatorial areas in comparison to each other. The simulated precipitation is overestimated in summer season (JJA) rather than in spring season (MAM), whereas the spatial distribution of the precipitation in spring season corresponds to the observation better than in summer season. Also the RCMs were capable of reproducing the annual variability of the maximum amount and its timing in July, in which the skills over the inland area were in better agreement with the observation than over the maritime area. The simulated regional climates, however, have the limitation to represent the number of days for extremely hot temperature and heavy rainfall over South Korea.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.3 no.1 s.4
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• pp.45-52
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• 2004

There are many cities installing ITS(Intelligent Transportation Systems) and running TMC(Trafnc Management Center) to improve mobility and safety of roadway transportation by providing roadway information to drivers. There are many devices in ITS which collect real-time traffic data. We can obtain many valuable traffic data from the devices. But it's impossible to avoid missing traffic data for many reasons such as roadway condition, adversary weather, communication shutdown and problems of the devices itself. We couldn't do any secondary process such as travel time forecasting and other transportation related research due to the missing data. If we use the traffic data to produce AADT and DHV, essential data in roadway planning and design, We might get skewed data that could make big loss. Therefore, He study have explored some imputation techniques such as heuristic methods, regression model, EM algorithm and time-series analysis for the missing traffic volume data using some evaluating indices such as MAPE, RMSE, and Inequality coefficient. We could get the best result from time-series model generating 5.0$\%$, 0.03 and 110 as MAPE, Inequality coefficient and RMSE, respectively. Other techniques produce a little different results, but the results were very encouraging.

• Journal of Satellite, Information and Communications
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• v.12 no.3
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• pp.22-34
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• 2017

The K-DRUM(K-water hydrologic & hydraulic Distributed RUnoff Model), a distributed rainfall-runoff model of K-water, calculates predicted runoff and water surface level of a dam using precipitation data. In order to obtain long-term hydrometeorological information, K-DRUM requires long-term weather forecast. In this study, we built a system providing long-term hydrometeorological information using predicted rainfall ensemble of GloSea5(Global Seasonal Forecast System version 5), which is the seasonal meteorological forecasting system of KMA introduced in 2014. This system produces K-DRUM input data by automatic pre-processing and bias-correcting GloSea5 data, then derives long-term inflow predictions via K-DRUM. Web-based UI was developed for users to monitor the hydrometeorological information such as rainfall, runoff, and water surface level of dams. Through this UI, users can also test various dam management scenarios by adjusting discharge amount for decision-making.

• Atmosphere
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• v.26 no.4
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• pp.617-633
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• 2016

Jangbogo station is located in Terra Nova Bay over the East Antarctica, which is often affected by individual storms moving along nearby storm tracks and a katabatic flow from the continental interior towards the coast. A numerical simulation for two strong wind events of maximum instantaneous wind speed ($41.17m\;s^{-1}$) and daily mean wind speed ($23.92m\;s^{-1}$) at Jangbogo station are conducted using the polar-optimized version of Weather Research and Forecasting model (Polar WRF). Verifying model results from 3 km grid resolution simulation against AWS observation at Jangbogo station, the case of maximum instantaneous wind speed is relatively simulated well with high skill in wind with a bias of $-3.3m\;s^{-1}$ and standard deviation of $5.4m\;s^{-1}$. The case of maximum daily mean wind speed showed comparatively lower accuracy for the simulation of wind speed with a bias of -7.0 m/s and standard deviation of $8.6m\;s^{-1}$. From the analysis, it is revealed that the each case has different origins for strong wind. The highest maximum instantaneous wind case is caused by the approach of the strong synoptic low pressure system moving toward Terra Nova Bay from North and the other daily wind maximum speed case is mainly caused by the katabatic flow from the interiors of Terra Nova Bay towards the coast. Our evaluation suggests that the Polar WRF can be used as a useful dynamic downscaling tool for the simulation and investigation of high wind events at Jangbogo station. However, additional efforts in utilizing the high resolution terrain is required to reduce the simulation error of high wind mainly caused by katabatic flow, which is received a lot of influence of the surrounding terrain.

• Korean Journal of Agricultural and Forest Meteorology
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• v.9 no.3
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• pp.209-215
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• 2007

To improve the accuracy of frost warning system for pear orchard in a complex terrain in Naju area, the daily minimum temperature forecasted by Korea Meteorological Administration (KMA) was interpolated using a regional climate model based on topoclimatic estimation and optimum scale interpolation from 2004 to 2005. Based on the validation experiments done for three pear orchards in the spring of 2004, the results showed a good agreement between the observed and predicted values, resulting in improved predictability compared to the forecast from Korea Meteorological Administration. The differences between the observed and the predicted temperatures were $-2.1{\sim}2.7^{\circ}C$ (on average $-0.4^{\circ}C$) in the valley, $-1.6{\sim}2.7^{\circ}C$ (on average $-0.4^{\circ}C$) in the riverside and $-1.1{\sim}3.5^{\circ}C$ (on average $0.6^{\circ}C$) in the hills. Notably, the errors have been reduced significantly for the valley and riverside areas that are more affected by the cold air drainage and more susceptible to frost damage than hills.

• Atmosphere
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• v.26 no.3
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• pp.357-372
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• 2016

Northeast Asian regions have recently become the main source of anthropogenic and natural aerosols. Measurement of aerosols on the sea in these regions have been rarely conducted since the experimental campaigns such as ACE-ASIA (Asian Pacific Regional Aerosol Characterization Experiment) in 2001. Research vessel observations of aerosol mass and chemical composition were performed on the Yellow and south sea around the Korean peninsula. The ship measurements showed six representative cases such as aerosol event and non-event cases during the study periods. On non-event cases, the anthropogenic chemical and natural soil composition on the Yellow sea were greater than those on the south sea. On aerosol event cases such as haze, haze with dust, and dust, the measured mass concentrations of anthropogenic chemical and element compositions were clearly changed by the events. In particular, methanesulfonate ($MSA^-$, $CH_3SO_3^-$), a main component of natural oceanic aerosol important for sulfur circulation on Earth, was first observed by the vessel in Korea, and its concentration on the Yellow sea was three times that on the south sea during the study period. Sea salt concentration important to chemical composition on the sea is related to wind speed. Coefficients of determination ($R^2$) between wind speed and sea salt concentration were 0.68 in $PM_{10}$ and 0.82 in $PM_{2.5}$. Maximum wave height was not found to be correlated to the sea salt concentration. When sea-salt comes into contact with pollutants, the total sea-salt mass is reduced, i.e., a loss of $Cl^-$ concentration from NaCl, the main chemical composing sea salt, is estimated by reaction with $HNO_3$(gas) and $H_2SO_4$(gas). The $Cl^-$ concentration loss by $SO_4^{2-}$ and $NO_3^-$ more easily increased for $PM_{10}$ compared to $PM_{2.5}$. The results of this study will be applied to verifying a dust-haze forecasting model. In addition, continued vessel measurements of aerosol data will become important to research for climate change studies in the future.

• Atmosphere
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• v.25 no.4
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• pp.639-657
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• 2015

There is an increasing need to improve the air quality over South Korea to protect public health from local and remote anthropogenic pollutant emissions that are in an increasing trend. Here, we evaluate the performance of the WRF-Chem (Weather Research and Forecasting-Chemistry) model in simulating near-surface air quality of major Korean cities, and investigate the impacts of time-varying chemical initial and lateral boundary conditions (IC/BCs) on the air quality simulation using a chemical downscaling technique. The model domain was configured over the East Asian region and anthropogenic MICS-Asia 2010 emissions and biogenic MEGAN-2 emissions were applied with RACM gaseous chemistry and MADE/SORGAM aerosol mechanism. Two simulations were conducted for a 30-days period on April 2010 with chemical IC/BCs from the WRF-Chem default chemical species profiles ('WRF experiment') and the MOZART-4 (Model for OZone And Related chemical Tracers version 4) ('WRF_MOZART experiment'), respectively. The WRF_MOZART experiment has showed a better performance to predict near-surface CO, $NO_2$, $SO_2$, and $O_3$ mixing ratios at 7 major Korean cities than the WRF experiment, showing lower mean bias error (MBE) and higher index of agreement (IOA). The quantitative impacts of the chemical IC/BCs have depended on atmospheric residence time of the pollutants as well as the relative difference of chemical mixing ratios between the WRF and WRF_MOZART experiments at the lateral boundaries. Specifically, the WRF_MOZART experiment has reduced MBE in CO and O3 mixing ratios by 60~80 ppb and 5~10 ppb over South Korea than those in the WRF-Chem default simulation, while it has a marginal impact on $NO_2$ and $SO_2$ mixing ratios. Without using MOZART-4 chemical IC, the WRF simulation has required approximately 6-days chemical spin-up time for the East Asian model domain. Overall, the results indicate that realistic chemical IC/BCs are prerequisite in the WRF-Chem simulation to improve a forecast skill of local air quality over South Korea, even in case the model domain is sufficiently large to represent anthropogenic emissions from China, Japan, and South Korea.

• Korean Journal of Agricultural and Forest Meteorology
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• v.11 no.2
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• pp.79-85
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• 2009

Net radiation ($R_N$) is a driving force of biological and physical processes between the surface and the atmosphere and its knowledge is critical to weather forecasting and water resource management. The measurement of $R_N$ is, however, scarce and it is typically estimated from an empirical relationship. This study presented two different methods of $R_N$ estimation over three major plant functional types (i.e., a deciduous forest, a coniferous forest, and a farmland) in Korea. One is a linear regression method between $R_N$ and solar radiation and the other is a radiation balance method. The two methods were examined using the data collected in 2008 at the three sites. Based on the linear regression method over a year, $R_N$ was 70% of the incoming shortwave radiation ($R_S{\downarrow}$) for a deciduous forest, 79% for a coniferous forest, and 64% for a farmland, indicating that the relationship was plant functional type-specific. For the radiation balance method, the inclusion of longwave radiation component slightly improved $R_N$ estimations. Overall, there was a good agreement between the observed and the estimated $R_N$ from both methods, indicating a reliable applicability of the two methods in estimating $R_N$.

• Journal of the East Asian Society of Dietary Life
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• v.12 no.1
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• pp.38-46
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• 2002

This study was carried out in order to investigate dextran formation and internal structure during fermentation of the oligosaccharide Jeung-Pyun. The dextran and sugar reducing contents of Jeung-Pyun batter and the specific volume and the internal structure of Jeung-Pyun were analyzed as a function of fermentation time. The specific volume of Jeung-Pyun peaked at the 7th hour of fermentation. The dextran content of Jeung-Pyun batters peaked at the 7~13th hour of fermentation, and Fructooligosaccharide Jeung-Pyun had the least peak value. Reducing sugar content of Jeung-Pyun batters slowly decreased as fermentation progressed. From the air pore size and distribution of Jeung-Pyun observed by SEM, the sucrose Jeung-Pyun fermented for 3~7 hours and oligosaccharide one fermented for 7 hours were judged as the best. It was concluded that dextran may be formed by fermentation of oligosaccharides as well as sucrose and dextran has a significant role on the volume expansion of Jeung-Pyun.

• Journal of Korea Water Resources Association
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• v.46 no.8
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• pp.857-871
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• 2013

The interest in rainfall observation and forecasting using remote sensing method like RADAR (Radio Detection and Ranging) and satellite image is increased according to increased damage by rapid weather change like regional torrential rain and flash flood. In this study, the basin runoff was calculated using adaptive neuro-fuzzy technique, one of the data driven model and MAPLE (McGill Algorithm for Precipitation Nowcasting by Lagrangian Extrapolation) forecasted precipitation data as one of the input variables. The flood estimation method using neuro-fuzzy technique and RADAR forecasted precipitation data was evaluated. Six rainfall events occurred at flood season in 2010 and 2011 in Chungju Reservoir basin were used for the input data. The flood estimation results according to the rainfall data used as training, checking and testing data in the model setup process were compared. The 15 models were composed of combination of the input variables and the results according to change of clustering methods were compared and analysed. From this study was that using the relatively larger clustering radius and the biggest flood ever happened for training data showed the better flood estimation. The model using MAPLE forecasted precipitation data showed relatively better result at inflow estimation Chungju Reservoir.