• 천문학논총
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• 제15권spc2호
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• pp.1-13
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• 2000

Through the coupling between the near-earth space environment and the polar ionosphere via geomagnetic field lines, the variations occurred in the magnetosphere are transferred to the polar region. According to recent studies, however, the polar ionosphere reacts not only passively to such variations, but also plays active roles in modifying the near-earth space environment. So the study of the polar ionosphere in terms of geomagnetic disturbance becomes one of the major elements in space weather research. Although it is an indirect method, ground magnetic disturbance data can be used in estimating the ionospheric current distribution. By employing a realistic ionospheric conductivity model, it is further possible to obtain the distributions of electric potential, field-aligned current, Joule heating rate and energy injection rate associated with precipitating auroral particles and their energy spectra in a global scale with a high time resolution. Considering that the ground magnetic disturbances are recorded simultaneously over the entire polar region wherever magnetic station is located, we are able to separate temporal disturbances from spatial ones. On the other hand, satellite measurements are indispensible in the space weather research, since they provide us with in situ measurements. Unfortunately it is not easy to separate temporal variations from spatial ones specifically measured by a single satellite. To demonstrate the usefulness of ground magnetic disturbance data in space weather research, various ionospheric quantities are calculated through the KRM method, one of the magneto gram inversion methods. In particular, we attempt to show how these quantities depend on the ionospheric conductivity model employed.

• 한국농공학회논문집
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• 제57권6호
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• pp.173-183
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• 2015

The aim of this study was to develop a soil moisture simulation model equipped with meteorological data enhanced by WRF (Weather Research and Forecast) model, and this soil moisture model was applied for quantifying soil moisture content and irrigation requirement. The WRF model can provide grid based meteorological data at various resolutions. For applicability assessment, comparative analyses were conducted using WRF data and weather data obtained from weather station located close to test bed. Water balance of each upland grid was assessed for soils represented with four layers. The soil moisture contents simulated using the soil moisture model were compared with observed data to evaluate the capacity of the model qualitatively and quantitatively with performance statistics such as correlation coefficient (R), coefficient of determination (R2) and root mean squared error (RMSE). As a result, R is 0.76, $R^2$ is 0.58 and RMSE 5.45 mm in soil layer 1 and R 0.61, $R^2$ 0.37 and RMSE 6.73 mm in soil layer 2 and R 0.52, $R^2$ 0.27 and RMSE 8.64 mm in soil layer 3 and R 0.68, $R^2$ 0.45 and RMSE 5.29 mm in soil layer 4. The estimated soil moisture contents and irrigation requirements of each soil layer showed spatiotemporally varied distributions depending on weather and soil texture data incorporated. The estimated soil moisture contents using weather station data showed uniform distribution about all grids. However the estimated soil moisture contents from WRF data showed spatially varied distribution. Also, the estimated irrigation requirements applied WRF data showed spatial variabilities reflecting regional differences of weather conditions.

• 한국측량학회지
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• 제37권1호
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• pp.1-7
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• 2019

본 연구에서는 GNSS (Global Navigation Satellite System) 신호가 전송되는 동안 발생하는 오차 중 대류권 지연오차를 추정하고, 이를 날씨 및 계절별 요소와 비교 분석했다. 이를 위해, 내륙지역인 충주와 평창, 해안지역인 제주, 거문도의 총 4개의 상시관측소를 선정하고, 2016년 중 매주 하루씩, 각 상시관측소마다 총 48일의 데이터를 이용하여 과학기술용 자료처리 소프트웨어로 정밀절대측위를 수행했다. 겨울철 대류권 지연오차는 평균 2400mm 미만으로, 2600mm 수준인 여름의 경우와 비교했을 때 약 200mm 가량 차이가 발생했다. 추정한 대류권 지연오차는 절대적인 지연량의 차이를 제외하면 모든 상시관측소에 대해서 변화 양상이 비슷하며, 해안지역의 지연오차가 상대적으로 크게 나타났다. 또한, 겨울에는 24시간 대류권 지연오차의 변화량이 상대적으로 적으며, 평균적인 대류권 지연오차는 상시관측소의 표고와 직접적인 관계가 있는 것으로 나타났다. 건조하고 온도 차이가 큰 내륙지역에서는 습도보다 강수량에 영향을 받은 대류권 지연오차의 변화가 발생하고, 다습한 해안지역에서는 강수보다 바다의 습도로 인한 변화가 큰 것으로 판단된다. 온도와 증기압의 상관계수는 모든 지역에서 0.9 이상을 나타냈으며, 대류권 지연오차는 온도와 높은 선형적 상관성을 보였다. 향후 연간 데이터 전체를 이용하여 시간적 해상도를 높인 연구분석을 수행함으로써 보다 신뢰도 높은 상관성 분석이 이루어질 필요가 있다.

• 한국태양에너지학회 논문집
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• 제26권2호
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• pp.27-34
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• 2006

In this paper, a forecasting model of wind speed at Walryong Site, Jeju Island is presented, which has been developed and evaluated as a first step toward establishing Korea Forecasting Model of Wind Power Generation. The forecasting model is constructed based on neural network and is trained with wind speed data observed at Cosan Weather Station located near by Walryong Site. Due to short period of measurements at Walryong Site for training statistical model Gosan Weather Station's long-term data are substituted and then transplanted to Walryong Site by using Measure-Correlate-Predict technique. One to three-hour advance forecasting of wind speed show good agreements with the monitoring data of Walryong site with the correlation factors 0.96 and 0.88, respectively.

• Corrosion Science and Technology
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• 제2권5호
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• pp.207-211
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• 2003

The weather resistance of five coatings systems based on alkyd, chlorinated rubber, epoxy, polyurethane and fluoropolymer were studied by natural exposure test and accelerated test. The coatings were exposed at Hanoi station with urban industry atmosphere and at Baichay station with marine atmosphere. The degradation of coatings was evaluated by gloss measurement and surface analysis by scanning electronic microscopy. The results obtained show that among coatings tested the gloss of polyurethane and fluoropolymer coatings remained highly and those of alkyd, chlorinated rubber and epoxy coatings were very low after two years of atmospheric exposure. Under accelerating conditions the gloss of fluoropolymer coatings remained highly after 80 cycles of testing. By comparison with accelerating test in UV-condensation chamber the conditions at atmospheric stations are more aggressive.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2005년도 Proceedings of ISRS 2005
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• pp.388-391
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• 2005

The characteristics of the total ozone variations measured by the ground-based Brewer Ozone Spectrophotometer and the Total Ozone Mapping Spectrometer (TOMS) over Pohang are statistically examined from January 1994 to December 2004. First of all, in the correlation analysis of the total ozone measured from the Brewer Ozone Spectrophotometer and the TOMS, the correlation coefficient was 0.88 and the used data were 2190. The annual mean value of the total ozone is 311 DU with the standard deviation of 13 DU. The maximum and the minimum value were found in March (343 DU) and in September (282 DU), respectively. It was also revealed that the longest seasonal variation is in Spring (341 DU) and the smallest is in Autumn (283 DU). The time series data of the total ozone indicates that the annual variation is significant and the variations for three months and six months are relatively weak. Finally, the annual mean total ozones in Pohang (Brewer), Seoul (Brewer) and Busan (TOMS) are 312 DU, 324 DU and 304 DU, respectively.

• 한국물환경학회지
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• 제32권3호
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• pp.310-317
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• 2016

It has been a big problem to estimate rainfall for the studies of mud-debris flows because the estimated rainfall from the nearest AWS (Automatic Weather Station) can tend to be quite inaccurate at individual sites. This study attempts to improve this problem through accurate rainfall depth estimation by applying an artificial neural network with radar rainfall data. For this, three models were made according to utilizing methodologies of rainfall data. The first model uses the nearest rainfall, observing the site from an ungauged site. The second uses only radar rainfall data and the third model integrates the above two models using both radar and observed rainfall at the sites around the ungauged site. This methodology was applied to the metropolitan area in Korea. It appeared as though the third model improved rainfall estimations by the largest margin. Therefore, the proposed methodology can be applied to forecast mud-debris flows in ungageed sites.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2007년도 Proceedings of ISRS 2007
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• pp.410-413
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• 2007

Water vapor in the atmosphere is an influential factor of the hydrosphere cycle, which exchanges heat through phase change and is essential to precipitation. Because of its significance in altering weather, the estimation of water vapor amount and distribution is crucial to determine the precision of the weather forecasting and the understanding of regional/local climate. It is shown that it is reliable to measure precipitable water (PW) using long baseline (500-2000km) GPS observations. However, it becomes infeasible to derive absolute PW from GPS observations in Taiwan due to geometric limitation of relatively short-baseline network. In this study, a method of deriving Near-Real-Time PW from short baseline GPS observations is proposed. This method uses a reference station to derive a regression model for wet delay, and to interpolate the difference of wet delay among stations. Then, the precipitable water is obtained by using a conversion factor derived from radiosondes. The method has been tested by using the reference station located on Mt. Ho-Hwan with eleven stations around Taiwan. The result indicates that short baseline GPS observations can be used to precisely estimate the precipitable water in near-real-time.

• 한국태양에너지학회 논문집
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• 제31권6호
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• pp.72-77
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• 2011

The purpose for installation of offshore weather station is a measurement of wind resources and so on. If weather station is operated, it will be possible to analysis for wind resource and arrangement of wind farm by using measured data. In this paper, we carried out the development of offshore wind resource measurement system for measuring offshore wind resource. Also, In order to monitor for real-time wind data with 1 Hz, we installed the wireless transmission system. All wind characteristic data are sent to the server PC through the this system is connected outport of DataLogger. Transmitted wind data were used in order to look at in the Web-page and tablet PC on a real time basis in a graph. In this paper, we will introduce about the wind resource measurement and remote monitoring system that is the result of study.

• 한국태양에너지학회 논문집
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• 제31권2호
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• pp.72-81
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• 2011

The wind data obtained from an AWS(Automated Weather Station) was used to predict the AEP(annual energy production) of Gangwon wind farm having a total capacity of 98 MWin Korea. A wind energy prediction program based on the Reynolds averaged Navier-Stokes equation was used. Predictions were made for three consecutive years starting from 2007 and the results were compared with the actual AEPs presented in the CDM (Clean Development Mechanism) monitoring report of the wind farm. The results from the prediction program were close to the actual AEPs and the errors were within 7.8%.