• Environmental Sciences Bulletin of The Korean Environmental Sciences Society
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• v.10 no.S_1
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• pp.23-28
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• 2001

A new numerical weather prediction and dispersion model, the Operational Multi-scale Environment model with Grid Adaptivity(OMEGA) including an embedded Atmospheric Dispersion Model(ADM), is introduced as a next generation atmospheric simulation system for real-time hazard predictions, such as severe weather or the transport of hazardous release. OMEGA is based on an unstructured grid that can facilitate a continuously varying horizontal grid resolution ranging from 100 km down to 1 km and a vertical resolution from 20 -30 meters in the boundary layer to 1 km in the free atmosphere. OMEGA is also naturally scale spanning and time. In particular, the unstructured grid cells in the horizontal dimension can increase the local resolution to better capture the topography or important physical features of the atmospheric circulation and cloud dynamics. This means the OMEGA can readily adapt its grid to a stationary surface, terrain features, or dynamic features in an evolving weather pattern. While adaptive numerical techniques have yet to be extensively applied in atmospheric models, the OMEGA model is the first to exploit the adaptive nature of an unstructured gridding technique for atmospheric simulation and real-time hazard prediction. The purpose of this paper is to provide a detailed description of the OMEGA model, the OMEGA system, and a detailed comparison of OMEGA forecast results with observed data.

• Magazine of the Korean Society of Agricultural Engineers
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• v.36 no.2
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• pp.44-55
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• 1994

This paper describes the development of real-time irrigation reservoir operation models that adequately allocate available water resources for paddy rice irrigation. Water requirement deficiency index(WRDI) was proposed as a guide to evaluate the operational performance of release schemes by comparing accumulated differences between daily release requirements for irrigated areas and actual release amounts. Seven reservoir release rules were developed, which are constant release rate method (CRR), mean storage curve method(MSC), frequency analysis method of reservoir storage rate(FAS), storage requirement curve method(SRC), constant optimal storage rate method (COS), ten-day optimal storage rate method(TOS), and release optimization method(ROM). Long-term forecasting reservoir operation model(LFROM) was formulated to find an optimal release scheme which minimizes WRDIs with long-term weather generation. Rainfall sequences, rainfall amount, and evaporation amount throughout the growing season were to be forecasted and the results used as an input for the model. And short-term forecasting reservoir operation model(SFROM) was developed to find an optimal release scheme which minimizes WRDIs with short-term weather forecasts. The model uses rainfall sequences forecasted by the weather service, and uses rainfall and evaporation amounts generated according to rainfall sequences.

• Journal of Environmental Science International
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• v.27 no.7
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• pp.531-541
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• 2018

Road freezing caused by snowfall during wintertime causes traffic congestion and many accidents. To prevent such problems, we developed, in this study, a system to predict road freezing based on weather forecast data and the freezing generation modules. The weather forecast data were obtained from a high-resolution model with 1 km resolution for Jeju Island from 00:00 KST on December 1, 2017, to 23:00 KST on February 28, 2018. The results of the weather forecast data show that index of agreement (IOA) temperature was higher than 0.85 at all points, and that for wind speed was higher than 0.7 except in Seogwipo city. In order to evaluate the results of the freezing predictions, we used model evaluation metrics obtained from a confusion matrix. These metrics revealed that, the Imacho module showed good performance in precision and accuracy and that the Karlsson module showed good performance in specificity and FP rate. In particular, Cohen's kappa value was shown to be excellent for both modules, demonstrating that the algorithm is reliable. The superiority of both the modules shows that the new system can prevent traffic problems related to road freezing in the Jeju area during wintertime.

• Journal of the Korean Geographical Society
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• v.46 no.2
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• pp.168-180
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• 2011

The accuracy of rainfall data for a hydrological modeling study is important. NEXRAD (Next Generation Radar) rainfall data estimated by WRS-88D (Weather Surveillance Radar - 1988 Doppler) radar system has advantages of its finer spatial and temporal resolution. In this study, NEXRAD rainfall data was tested and compared with conventional weather station data using the previously calibrated SWAT (Soil and Water Assessment Tool) model to identify local storms and to analyze the impacts on hydrology. The previous study used NEXRAD data from the year of 2000 and the NEXRAD data was substituted with weather station data in the model simulation in this study. In a selected watershed and a selected year (2006), rainfall data between two datasets showed discrepancies mainly due to the distance between weather station and study area. The largest difference between two datasets was 94.5 mm (NEXRAD was larger) and 71.6 mm (weather station was larger) respectively. The differences indicate that either recorded rainfalls were occurred mostly out of the study area or local storms only in the study area. The flow output from the study area was also compared with observed data, and modeled flow agreed much better when the simulation used NEXRAD data.

• Korean Journal of Remote Sensing
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• v.39 no.3
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• pp.355-361
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• 2023

Temperature of the Earth's surface is a crucial physical variable in understanding weather and atmospheric dynamics and in coping with extreme heat events that have a great impact on living organismsincluding humans. Thermalsensors on satellites have been a useful meansfor acquiring surface temperature information for wide areas on the globe, and thus characterization of its estimation uncertainty is of central importance for the utilization of the data. Among various factors that affect the estimation, the uncertainty caused by the algorithm itself has not been tested for the atmospheric environment of Korean vicinity. Thisstudy derivesthe uncertainty of the single-channel algorithm under the local atmospheric and oceanic conditions by using reanalysis data and buoy temperature data collected around Korea. Atmospheric profiles were retrieved from two types of reanalysis data, the fifth generation of European Centre for Medium-Range Weather Forecasts reanalysis of the global climate and weather (ERA5) and Modern-Era Retrospective analysis for Research and Applications-2 (MERRA-2) to investigate the effect of reanalysis data. MODerate resolution atmospheric TRANsmission (MODTRAN) was used as a radiative transfer code for simulating top of atmosphere radiance and the atmospheric correction for the temperature estimation. Water temperatures used for MODTRAN simulations and uncertainty estimation for the single-channel algorithm were obtained from marine weather buoyslocated in seas around the Korean Peninsula. Experiment results showed that the uncertainty of the algorithm varies by the water vapor contents in the atmosphere and is around 0.35K in the driest atmosphere and 0.46K in overall, regardless of the reanalysis data type. The uncertainty increased roughly in a linear manner as total precipitable water increased.

• Journal of Korea Water Resources Association
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• v.50 no.1
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• pp.17-28
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• 2017

A recent increase in extreme weather events and flash floods associated with the enhanced climate variability results in an increase in climate-related disasters. For these reasons, various studies based on a high resolution weather radar system have been carried out. The weather radar can provide estimates of precipitation in real-time over a wide area, while ground-based rain gauges only provides a point estimate in space. Weather radar is thus capable of identifying changes in rainfall structure as it moves through an ungauged basin. However, the advantage of the weather radar rainfall estimates has been limited by a variety of sources of uncertainty in the radar reflectivity process, including systematic and random errors. In this study, we developed an ensemble radar rainfall estimation scheme using the multivariate copula method. The results presented in this study confirmed that the proposed ensemble technique can effectively reproduce the rainfall statistics such as mean, variance and skewness (more importantly the extremes) as well as the spatio-temporal structure of rainfall fields.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.11
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• pp.1994-2000
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• 2008

The output power of photovoltaic(PV) generation system is strongly affected by weather conditions. To make up for the defect of solar energy, energy storages such as battery and electrolyzer are usually integrated with photovoltaic cell. This paper focuses on the way to store energy surplus with battery and electrolyzer and to provide energy with battery. Photovoltaic generation system is modeled with PV cell, DC/DC converter, DC/AC inverter, battery and electrolyzer. The operation algorithm to regulate PV output power with battery and electrolyzer is suggested. The simulation results show that battery and electrolyzer effectively cooperate with each other to compensate the fluctuation of PV generation system.

• Journal of Environmental Science International
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• v.25 no.10
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• pp.1369-1379
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• 2016

This research assessed the disparity in anion generation according to the vertical structure of a Zelkova Serrata tree for the purpose of creating a pleasant and green city environment. Measurements for the study were conducted between July and August of 2014 in Chung-ju in the central region of the Republic of Korea. The average anion generation of vertical structure trees during active photosynthesis periods was: L Section ($839.0ea/cm^3$) > M Section ($664.6ea/cm^3$) > U Section ($472.0ea/cm^3$). According to DMRT analysis, significant difference was found in the average between the L, or M Locations and the U Locations. During dormant photosynthesis periods, records showed that the anion production at the M Location ($1,212.5ea/cm^3$) > L Location ($1,050.4ea/cm^3$) > H Location ($844.1ea/cm^3$), According to DMRT analysis, the difference within each location was significant for ${\alpha}=0.05$. In a comprehensive analysis of the weather factors in each vertical structure, anion generation during active photosynthesis periods showed a positive correlation with solar radiation and a negative correlation with wind speed. Dormant photosynthesis periods showed negative correlations with both solar radiation and temperature, and positive correlations with relative humidity and wind speed. Predictions from a multicenter retrospective study showed that during active photosynthesis periods, $Y_1=282.443X_1+512.07$, and $Y_2=314.337X_1+16.913X_2$, while during dormant photosynthesis periods, $Y_1=391.009X_1+840.043$, and $Y_2=351.412X_1+32.765X_2$.

• Journal of the Korean Solar Energy Society
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• v.24 no.3
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• pp.47-54
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• 2004

Photovoltaic energy and wind energy are highly dependent on the season, time and extremely intermittent energy sources. Because of these reasons, in view of the reliability the photovoltaic and the wind power generation system have many problems(energy conversion, energy storage, load control etc.) comparing with conventional power plant. In order to solve these existing problems, hybrid generation system composed of photovoltaic(500W) and wind power system(400W) was suggested. But, hybrid generation system cannot always generate stable output due to the varying weather condition. So, the auxiliary power compensation unit that uses elastic energy of spiral spring was added to hybrid generation system for the present study. It was partly confirmed that hybrid generation system was generated a stable outputs by spiral spring was continuously provided to load.

• Journal of Electrical Engineering and Technology
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• v.12 no.1
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• pp.64-71
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• 2017

Considering the volatility, intermittent and random of photovoltaic (PV) generation systems, accurate forecasting of PV power output is important for the grid scheduling and energy management. In order to improve the accuracy of short-term power forecasting of PV systems, this paper proposes a prediction model based on environmental factors and support vector machine optimized by genetic algorithm (GA-SVM). In order to improve the prediction accuracy of this model, weather conditions are divided into three types, and the gray correlation coefficient algorithm is used to find out a similar day of the predicted day. To avoid parameters optimization into local optima, this paper uses genetic algorithm to optimize SVM parameters. Example verification shows that the prediction accuracy in three types of weather will remain at between 10% -15% and the short-term PV power forecasting model proposed is effective and promising.