• Journal of Korean Society for Atmospheric Environment
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• v.14 no.6
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• pp.563-576
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• 1998

To study the influences of the emission sources during lune 13∼15 1997 in Seoul, MESOPVFF II model has been used. The MESOPVFF II model includes terrain effects, chemical transformation and removal processes. Data of 20 surface meteorological stations and the upper air station on mid-west area in Korea were used as a DWM (Diagnostic Wind Model) input data. This model is likely to be applicable because the predicted SO2 concentration was well matched with measured 502 concentration in Seoul and Kyonggido. In generally air pollutants in Seoul have major influence on the other cities but the result of modeling appeared also air pollutants of the other cities influence on Seoul. Finally, in the case of calculating the air quality by diffusion model, the influences of air pollutants emitted in metropolitan area as well as the emission rate in modeling area should be considered.

• Water for future
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• v.28 no.3
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• pp.123-132
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• 1995

The subject research attempts to develop a hydrologic-hydraulic forecasting system suitable for use in large river basins. A conceptual hydrologic rainfall-runoff model is used to produce streamflow from meteorological and hydrologic input data over each subbasin, while a hydraulic model is used to route the catchment outflows in the stream network. For operational flow prediction, an efficient state estimator has been designed for the real-time updating of model states from newly recorded data. The real-time application of the forecasting system indicates that this model produces reliable short-term predicted results.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.24 no.11
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• pp.759-766
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• 2012

To estimate the cooling load for the following day, outdoor temperature and humidity are needed in hourly base. But the meteorological administration forecasts only maximum and minimum temperature. New methodology is proposed for predicting hourly outdoor temperature and humidity by using the forecasted maximum and minimum temperature. The correlations for normalized outdoor temperature and specific humidity has been derived from the weather data for five years at Seoul, Daejeon and Pusan. The correlations for normalized temperature are independent of date, while the correlations for specific humidity are linearly dependent on date. The predicted results show fairly good agreement with the measured data. The prediction program is also developed for hourly outdoor dry bulb temperature, specific humidity, dew point, relative humidity, enthalpy and specific volume.

• Proceedings of the Korea Water Resources Association Conference
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• 2002.05a
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• pp.27-40
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• 2002

Developed at Colorado State University, CASC2D-SED is a physically-based model simulating the hydrologic response of a watershed to a distributed rainfall field. The time-dependent processes include: precipitation, interception, infiltration, surface runoff and channel routing, upland erosion, transport and sedimentation. CASC2D-SED is applied to Goodwin Creek, Mississippi. The watershed covers 21 $\textrm{km}^2$ and has been extensively monitored both at the outlet and at several internal locations by the ARS-NSL at Oxford, MS. The model has been calibrated and validated using rainfall data from 16 meteorological stations,6 stream gaging stations and 6 sediment gaging stations. Sediment erosion/deposition rates by size fraction are predicted both in space and time. Geovisualization, a powerful data exploration technique based on GIS technology, is used to analyze and display the dynamic output time series generated by the CASC2D-SED model.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.12
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• pp.2202-2211
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• 2010

The wind power prediction system is composed of a meteorological forecasting module, calculation module of wind power output and HMI(Human Machine Interface) visualization system. The final information from this system is a short-term (6hr ahead) and mid-term (48hr ahead) wind power prediction value. The meteorological forecasting module for wind speed and direction forecasting is a combination of physical and statistical model. In this system, the WRF(Weather Research and Forecasting) model, which is a three-dimensional numerical weather model, is used as the physical model and the GFS(Global Forecasting System) models is used for initial condition forecasting. The 100m resolution terrain data is used to improve the accuracy of this system. In addition, optimization of the physical model carried out using historic weather data in Jeju. The mid-term prediction value from the physical model is used in the statistical method for a short-term prediction. The final power prediction is calculated using an optimal adjustment between the currently observed data and data predicted from the power curve model. The final wind power prediction value is provided to customs using a HMI visualization system. The aim of this study is to further improve the accuracy of this prediction system and develop a practical system for power system operation and the energy market in the Smart-Grid.

• Journal of Korean Society of Transportation
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• v.29 no.2
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• pp.123-131
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• 2011

This study proposes a model for road surface temperature prediction on basis of the heat-energy balance equation between atmosphere and road surface. The overall model is consisted of two types of modules: 1) Canopy 1 is used to describe heat transfer between soil surface and atmosphere; and 2) Canopy 2 can reflect the characteristics of pavement type. Input data used in the model run is obtained from the Korea Meteorological For model validation, the observed and predicted surface temperature data are compared using data collected on MoonEui Bridge along CheongWon-Sangju Expressway, and the comparison is made on winter and other seasons separately. Analysis results show that average difference between two temperatures lies within ${\pm}2^{\circ}C$ which is considered as appropriate from a micrometeorology point of view. The model proposed in this paper can be adopted as a useful tool in practical applications for winter maintenance. This study being a fundamental research is anticipated to be a starting point for further development of robust surface road temperature prediction algorithms.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.25 no.6
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• pp.310-316
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• 2013

This study was designed to investigate a method for short-term, real-time energy demand prediction, to cope with changing loads for the effective operation and management of buildings. Through a case study, a novel methodology for real-time energy demand prediction with the use of weather forecasting data was suggested. To perform the input and output operations of weather data, and to calculate solar radiation and EnergyPlus, the BCVTB (Building Control Virtual Test Bed) was designed. Through the BCVTB, energy demand prediction for the next 24 hours was carried out, based on 4 real-time weather data and 2 solar radiation calculations. The weather parameters used in a model equation to calculate solar radiation were sourced from the weather data of the KMA (Korea Meteorological Administration). Depending on the local weather forecast data, the results showed their corresponding predicted values. Thus, this methodology was successfully applicable to anywhere that local weather forecast data is available.

• Journal of the Korean Geographical Society
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• v.43 no.1
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• pp.1-19
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• 2008

This study intends to clarify the characteristics and causes of current changes in wintertime precipitation in Korea and to predict the future directions based on surface observational $(1973/04\sim2006/07)$ and modeled (GFDL 2.1) climate data. Analyses of surface observation data demonstrate that without changes in the total amount of precipitation, snowfall in winter (November-April) has reduced by 4.3cm/decade over the $1973\sim2007$ period. Moreover, the frequency and intensity of snowfall have decreased; the duration of snow season has shortened; and the snow-to-rain day ratio (STDR) has decreased. These patterns indicate that the type of wintertime precipitation has changed from snow to rain in recent decades. The snow-to-rain change in winter is associated with the increases of air temperature (AT) over South Korea. Analyses of synoptic charts reveal that the warming pattern is associated with the formation of a positive pressure anomaly core over northeast Asia by a hemispheric positive winter Arctic Oscillation (AO) mode. Moreover, the differentiated warming of AT versus sea surface temperature (SST) under the high pressure anomaly core reduces the air-sea temperature gradient, and subsequently it increases the atmospheric stability above oceans, which is associated with less formation of snow cloud. Comparisons of modeled data between torrent $(1981\sim2000)$ and future $(2081\sim2100)$ periods suggest that the intensified warming with larger anthropogenic greenhouse gas emission in the $21^{st}$ century will amplify the magnitude of these changes. More reduction of snow impossible days as well as more abbreviation of snow seasons is predicted in the $21^{st}$ century.

• Journal of the Korean earth science society
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• v.36 no.4
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• pp.301-314
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• 2015

The purpose of this study was to investigate the impact of ground-based glaciogenic seeding on orographic clouds in the Daegwallyeong area on 13 March, 2013. The experiments was conducted by releasing silver iodide (AgI) under following conditions: surface temperature below $-4^{\circ}C$, wind direction between 45 and $130^{\circ}$, and wind speed less than $5ms^{-1}$. Two seeding rates, $38gh^{-1}$ (SR1) and $113gh^{-1}$ (SR2), were tested to obtain an appropriate AgI ratio for snowfall enhancement in the Daegwallyeong area. Numerical simulations were carried out by using the WRF (Weather Research and Forecast) model with AgI point-source module which predicted dispersion fields of AgI particles. The results indicated that the target orographic clouds contained adequate amount of supercooled liquid water and that the dispersion of AgI particles tended to move along the prevailing wind direction. To validate the seeding effects, the observation data from FM-120 and MPS as well as PARSIVEL disdrometer were analyzed. In this case study, glaciogenic seeding significantly increased the concentration of small ice particles below 1 mm in diameter. The observation results suggest that SR1 seeding be reasonable to use the ground-based seeding in the Daegwallyeong area.

• Journal of Korean Society for Atmospheric Environment
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• v.10 no.E
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• pp.357-370
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• 1994

This paper introduces an Eulerian long- range transport model coupled with a mesoscale atmospheric model. The model has been applied to the simulation of tracer distribution during two cases of Cross Appalachian Tracer Experiment (CAPIEX). Meteorological fields are Predicted by CSU RAMS with four-dimensional assimilation and tracer transport is computed from an Eulerian dispersion model. The atmospheric model with a four-dimensional assimilation has produced meteorological fields that agree well with observation and has proved its high potential as a generator of meteorological data for a long-range transport model. The Present transport model Produces reasonable simulations of observed tracer transport although it was partially successful in the case with complicated structure in observed concentration. Model with Bott's 2nd-order scheme performs as well as that with Bott's 4th-order scheme and increased explicit horizontal diffusivity. Diagnosis of the model results indicates that the Present long-range transport model has a good potential as a framework for the acid deposition model with detailed cloud and chemical processes.