• 대한기계학회논문집B
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• 제39권9호
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• pp.735-742
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• 2015

본 논문에서는 국지적 기상현상의 모사가 가능하고 AWS, 기상탑, 또는 위성자료의 입력이 필요치 않은 WRF 기상수치모델을 이용하여, 풍력단지의 풍황자원 예측정확도 및 적용타당성을 비교 검증하고자 한다. 풍력단지개발 예비타당성단계에서 요구되는 풍황자원 예측을 위한 WRF 모델의 적용타당성 검증을 위해, 기상탑 풍황측정자료와 WAsP에 의한 풍황자원 예측결과와의 비교 검증을 수행하였고 제주도 북서쪽에 위치한 평대와 우도사이트를 비교 검증용 사이트로 선정하였다. 연 월평균풍속, 와이블분포, 연간발전량 및 바람장미의 예측결과가 실측자료와 비교 검증되었고 WRF 모델의 풍황해석결과는 WAsP의 결과에 비해 높은 예측 정확도를 나타내었다. 풍력단지개발 예비타당성 평가를 위한 WRF 모델의 풍황자원 예측가능성이 최종적으로 확인되었다.

• Journal of Astronomy and Space Sciences
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• 제8권1호
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• pp.99-113
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• 1991

수치적인 방법을 이용하여 인공위성의 궤도를 예보할 수 있는 소프트웨어 시스템 (IODS: ISSA Orbit Determination System)을 개발하였다. IODS의 궤도예보 정확도틀 평가하기 위히여 기상위성 NOAA-ll호와 정지위생 INTELSAT-V의 궤도를 예보하였고, 그 결과를 중앙기상대와 금산 위생통신지구국의 위성추적 자료와 비교하였다. 그리고 인공위성애 미치는 여러가지 섭동력을 정량적으로 분석하였다 한편, 동경 100도에 상공에 위치한 정지위성(KORSAT-l)의 궤도을 가정하여 궤도가 시간에 따라 변하는 양상을 IODS툴 이용하여 분석하였으며, KORSAT-l이 지구의 그림자에 들어가는 식현상을 예측하고 분석하였다.

• 한국태양에너지학회 논문집
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• 제25권3호
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• pp.53-60
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• 2005

Energy resource is very important to the survival in the polar region. Wind energy, which is one of renewable energy, can guarantee the clean, inexhaustible, natural resource in the polar region. It is essential to assess the wind energy resource of the site where wind turbines will be installed. In the present study, the wind characteristics of the antarctic King Sejong station are analysed from its meteorological observation data. The wind resource of the Sejong station is also simulated and predicted using WAsP program. From the results, the Sejong station has very excellent wind resource and the site where small wind turbines will be installed is determined.

• 한국환경보건학회지
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• 제32권6호
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• pp.571-577
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• 2006

Health benefits from implementing air quality control measures were assessed using the Environmental Benefits Mapping and Analysis Program (BenMAP). BenMAP developed by US EPA is a GIS-based software tool that estimates the health impacts and associated economic values connected with changes in ambient air pollution. Once a set of BenMAP-required data was collected, the health benefits from implementing Seoul Air Quality Management Plan (SAQMP), an official AQ improvement plan for Seoul Metropolitan Area, was assessed using BenMAP. The PM10 concentrations assuming the SAQMP implemented successfully were predicted with the MM5 (Mesoscale Meteorological model version 5)/CMAQ (Community Multiscale Air Quality) model. A PM 10 exposure related premature mortality function was adopted trom a well-known epidemiology study. Economic valuation functions driven from benefit transfer methods were utilized. Through the SAQMP, PM10 concentrations were estimated to be lowered by $15{\mu}g/m^3\;to\;75{\mu}g/m^3$ depending on air quality modeling grids. 5,569 premature deaths (95% CI $3,264{\sim}7,809$ deaths) could be avoided in the Seoul Metropolitan Area. The economic value of the deaths avoided was estimated to $13.2 billion $(95%\;CI\;$890\;million{\sim}$28.2\;billion)$ using the benefit transfer value. BenMAP could be a useful tool for developing effective air quality improvement policy, enabling the policy makers to anticipate the effects of regulatory changes on people's health and the economy.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2020년도 학술발표회
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• pp.170-170
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• 2020

Due to the development of technologies, complex computation of huge data set is possible with a prevalent personal computer. Therefore, machine learning methods have been widely applied in the hydrologic field such as regression-based regional frequency analysis (RFA). The main purpose of this study is to compare two frameworks of RFA based on the artificial neural network (ANN) models: quantile regression technique (QRT-ANN) and parameter regression technique (PRT-ANN). As an output layer of the ANN model, the QRT-ANN predicts quantiles for various return periods whereas the PRT-ANN provides prediction of three parameters for the generalized extreme value distribution. Rainfall gauging sites where record length is more than 20 years were selected and their annual maximum rainfalls and various hydro-meteorological variables were used as an input layer of the ANN model. While employing the ANN model, 70% and 30% of gauging sites were used as training set and testing set, respectively. For each technique, ANN model structure such as number of hidden layers and nodes was determined by a leave-one-out validation with calculating root mean square error (RMSE). To assess the performances of two frameworks, RMSEs of quantile predicted by the QRT-ANN are compared to those of the PRT-ANN.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2022년도 학술발표회
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• pp.126-126
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• 2022

Climate change has continued to impact meteorological factors like rainfall in many countries including Nigeria. Thus, altering the rainfall patterns which subsequently affect the crop yield. Maize is an important cereal grown in northern Nigeria, along with sorghum, rice, and millet. Due to the challenge of water scarcity during the dry season, it has become critical to design appropriate strategies for planning, developing, and management of the limited available water resources to increase the maize yield. This study, therefore, determines the quantity of water required to produce maize from planting to harvesting and the impact of drought on maize during different growth stages in the region. Rainfall data from six rain gauge stations for a period of 36 years (1979-2014) was considered for the analysis. The standardized precipitation and evapotranspiration index (SPEI) is used to evaluate the severity of drought. Using the CROPWAT model, the evapotranspiration was calculated using the Penman-Monteith method, while the crop water requirements (CWRs) and irrigation scheduling for the maize crop was also determined. Irrigation was considered for 100% of critical soil moisture loss. At different phases of maize crop growth, the model predicted daily and monthly crop water requirements. The crop water requirement was found to be 319.0 mm and the irrigation requirement was 15.5 mm. The CROPWAT 8.0 model adequately estimated the yield reduction caused by water stress and climatic impacts, which makes this model appropriate for determining the crop water requirements, irrigation planning, and management.

• 한국농림기상학회지
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• 제22권4호
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• pp.287-298
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• 2020

지구온난화로 기후변화 및 이상 기상현상이 증가함에 따라 전 세계적으로 미래 기후 전망에 대한 관심과 연구의 필요성이 증대되고 있다. 온난화로 인한 기온의 상승 경향은 미래에도 지속될 것으로 예상되며, 현재 남해안에 국한되는 아열대 기후구는 점차 북상할 것으로 전망된다. 기후대의 이동은 작물재배지의 변화를 의미하기 때문에 본 연구에서는 변화하는 농업기후 조건에서 작물 재배 적응 대책을 마련할 수 있도록 우리나라의 고해상도 기후 자료를 기반으로 현재-미래에 대한 기후대 전망을 살펴보고자 하였다. 이를 위해 평년 기간(1981-2010)에 대해 제작된 남한과 북한의 통합된 고해상도 월 최고기온 및 최저기온, 월 적산강수량을 확보 및 제작하였고, 쾨펜 기후대 구분 기준에 따라 한반도 기후대를 분류하였다. 동일한 방법으로 기상청의 RCP8.5 기후변화 시나리오를 기반으로 30-270m 격자 해상도로 상세화 된 한반도 지역의 월 단위 기후 자료를 확보하여, 미래에 예상되는 기후대 변화를 전망하였다. RCP8.5 시나리오를 바탕으로 같은 기후 구분 기준을 적용한 결과, 한반도의 기온과 강수량은 지속적으로 증가하여 기후가 점차 단순해지는 것으로 나타났다. 현재 남부지방에 나타나는 온대기후(C)는 점차 확대되어, 2071-2100년대에는 북한의 함경도와 평안도 일부 지역을 제외한 한반도의 대부분이 온대기후(C)가 될 것으로 예상되었다. 반면 냉대 기후(D)는 서서히 북쪽으로 후퇴하여 한반도가 점점 온난 습윤해질 것으로 예상되었다.

• The Korean Journal of Ecology
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• 제23권2호
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• pp.117-123
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• 2000

Changing patterns and the possibility of climate change in the area of Cheiudo island, the southernmost Island in Korea, were analyzed using daily temperature and Precipitation data observed at the Cheiu Regional Meteorological Office from May 1923 to December 1998. A hydrologic simulation model "BROOK" was used to simulate and analyze the dynamics of daily soil moisture content and soil moisture deficit by applying the daily weather data. During the period, significantly increasing pattern was observed in temperature data of both annual and monthly basis, while no significantly changing pattern was observed in precipitation data. During the last 76 years. mean annual temperature was observed to have risen about 1.4$^{\circ}C$, which may show the Possibility of the initiation of climate change on the island whose validity should be tested in future studies after long-term studies on temperature. Based on the simulation, due to increased temperature, significant increase was predicted in evapotranspiration. while no significant decrease was detected in simulated soil moisture content during the period. Changing pattern of annual soil moisture content was markedly different from those of precipitation. In some dominant trees, negative effects of the drought of the late season for the previous year were shown to be statistically significant to radial growth of the tree for the current year. As annual variation of radial growth of trees is mainly affected by the soil moisture content. the information on the dynamics of soil moisture deficit possibly provides us with useful information for the interpretation of tree growth decline on the mountain. mountain.

• 대기
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• 제23권3호
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• pp.275-282
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• 2013

In this study, the numerical model was developed to evaluate the observational environment of sunshine duration and, for evaluating the accuracy and utility of the model, it was verified against the observational data measured at Dae-gu Automated Synoptic Observing System (ASOS) located in an urban area. Three-dimensional topography and building configuration as the surface input data of the model were constructed using a Geographic Information System (GIS) data. First, the accuracy of the computing planetary positions suggested by Paul Schlyter was verified against the data provided by Korea Astronomy and Space Science Institute (KASI) and the results showed that the numerical model predicted the Sun's position (the solar azimuth and altitude angles) quite precisely. Then, this model was applied to reproduce the sunshine duration at the Dae-gu ASOS. The observed and calculated sunshine durations were similar to each other. However, the observed and calculated sunrise (sunset) times were delayed (curtailed), compared to those provided by KASI that considered just the ASOS's position information such as latitude, longitude, and elevation height but did not consider the building and topography information. Further investigation showed that this was caused by not only the topographic characteristic (higher in the east and lower in the west) but also the buildings located in the southeast near the sunrise and the southwest near the sunset. It was found that higher building resolution increased the accuracy of the model. It was concluded that, for the accurate evaluation of the sunshine duration, detailed building and topography information around the observing sites was required and the numerical model developed in this study was successful to predict and/or the sunshine duration of the ASOS located in an urban area.

• 한국농림기상학회지
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• 제7권2호
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• pp.148-155
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• 2005

An accurate prediction of blooming date is crucial for many authorities to schedule and organize successful spring flower festivals in Korea. The Korea Meteorological Administration (KMA) has been using regression models combined with a subjective correction by forecasters to issue blooming date forecasts for major cities. Using mean monthly temperature data for February (observed) and March (predicted), they issue blooming date forecasts in late February to early March each year. The method has been proved accurate enough for the purpose of scheduling spring festivals in the relevant cities, but cannot be used in areas where no official climate and phenology data are available. We suggest a thermal time-based two-step phenological model for predicting the blooming dates of spring flowers, which can be applied to any geographic location regardless of data availability. The model consists of two sequential periods: the rest period described by chilling requirement and the forcing period described by heating requirement. It requires daily maximum and minimum temperature as an input and calculates daily chill units until a pre-determined chilling requirement for rest release. After the projected rest release date, it accumulates daily heat units (growing degree days) until a pre- determined heating requirement for flowering. Model parameters were derived from the observed bud-burst and flowering dates of cherry tree (Prunus serrulata var. spontanea) at KMA Seoul station along with daily temperature data for 1923-1950. The model was applied to the 1955-2004 daily temperature data to estimate the cherry blooming dates and the deviations from the observed dates were compared with those predicted by the KMA method. Our model performed better than the KMA method in predicting the cherry blooming dates during the last 50 years (MAE = 2.31 vs. 1.58, RMSE = 2.96 vs. 2.09), showing a strong feasibility of operational application.