• 대한원격탐사학회지
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• 제33권1호
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• pp.25-35
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• 2017

Spatial downscaling with fine resolution auxiliary variables has been widely applied to predict precipitation at fine resolution from coarse resolution satellite-based precipitation products. The spatial downscaling framework is usually based on the decomposition of precipitation values into trend and residual components. The fine resolution auxiliary variables contribute to the estimation of the trend components. The main focus of this study is on quantitative analysis of impacts of trend component estimates on predictive performance in spatial downscaling. Two regression models were considered to estimate the trend components: multiple linear regression (MLR) and geographically weighted regression (GWR). After estimating the trend components using the two models,residual components were predicted at fine resolution grids using area-to-point kriging. Finally, the sum of the trend and residual components were considered as downscaling results. From the downscaling experiments with time-series Tropical Rainfall Measuring Mission (TRMM) 3B43 precipitation data, MLR-based downscaling showed the similar or even better predictive performance, compared with GWR-based downscaling with very high explanatory power. Despite very high explanatory power of GWR, the relationships quantified from TRMM precipitation data with errors and the auxiliary variables at coarse resolution may exaggerate the errors in the trend components at fine resolution. As a result, the errors attached to the trend estimates greatly affected the predictive performance. These results indicate that any regression model with high explanatory power does not always improve predictive performance due to intrinsic errors of the input coarse resolution data. Thus, it is suggested that the explanatory power of trend estimation models alone cannot be always used for the selection of an optimal model in spatial downscaling with fine resolution auxiliary variables.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 1989년도 수공학논총 제31권
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• pp.5-16
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• 1989

본 연구에서는 중앙기상대 산하 60개 지점의 84년간(1985-1988) 자료에 의한 전국년평균 강수량을 추정하였다. 미계측 부분에 대하여는 Principal Component를 사용한 회귀식으로써 보와하였으며, 산술평균값, Thiessen 계수에 의한 평균값, 그리고 등우선법에 의한 평균값을 또한 비교하였다.

• 한국환경복원기술학회지
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• 제18권4호
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• pp.15-27
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• 2015

The objectives of this study are to analyze the quantitative ecological principal components of Korean Peninsula using the multivariate spatial environmental datasets and to compare the ecological difference between South and North Korea. Ecological maps with GIS(Geographical Information System) are constructed by PCA(Principal Component Analysis) based on seventeen raster(cell based) variables at 1km resolution. Ecological differences between South and North Korea are extracted by Factor Analysis using ecosystem maps masked from Korean ones. Spatial data include SRTM(Shuttle Radar Topography Mission), Temperature, Precipitation, SWC(Soil Water Content), fPAR(Fraction of Photosynthetically Active Radiation) representing for a productivity, and SR(Solar Radiation), which all cover Korean peninsula. When it performed PCA, the first three scores were assigned to red, green, and blue color. This color triplet indicates the relative mixture of the seventeen environmental conditions inside each ecological region. The first red one represents for 'physiographic conditions' worked by high elevation and solar radiation and low temperature. The second green one stands for 'seasonality' caused by seasonal variations of temperature, precipitation, and productivity. The third blue one means 'wetness condition' worked by high value such as precipitation and soil water contents. FA extraction shows that South Korea has relatively warm and humid ecosystem affected by high temperature, precipitation, and soil water contents whereas North Korea has relatively cold and dry ecosystem due to the high elevation, low temperature and precipitation. Results would be useful at environmental planning on inaccessible land of North Korea.

• Journal of Astronomy and Space Sciences
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• 제32권4호
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• pp.317-325
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• 2015

Energy spectra of electron microbursts from 170 keV to 340 keV have been measured by the solid-state detectors aboard the low-altitude (680 km) polar-orbiting Korean STSAT-1 (Science and Technology SATellite). These measurements have revealed two important characteristics unique to the microbursts: (1) They are produced by a fast-loss cone-filling process in which the interaction time for pitch-angle scattering is less than 50 ms and (2) The e-folding energy of the perpendicular component is larger than that of the parallel component, and the loss cone is not completely filled by electrons. To understand how wave-particle interactions could generate microbursts, we performed a test particle simulation and investigated how the waves scattered electron pitch angles within the timescale required for microburst precipitation. The application of rising-frequency whistler-mode waves to electrons of different energies moving in a dipole magnetic field showed that chorus magnetic wave fields, rather than electric fields, were the main cause of microburst events, which implied that microbursts could be produced by a quasi-adiabatic process. In addition, the simulation results showed that high-energy electrons could resonate with chorus waves at high magnetic latitudes where the loss cone was larger, which might explain the decreased e-folding energy of precipitated microbursts compared to that of trapped electrons.

• 한국농공학회지
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• 제40권4호
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• pp.58-66
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• 1998

Irrigation Reservoir Water Supply Index(IRWSI), which can be applied to the effective supply and management of the irrigation water resources, was developed. IRWSI was formulated as resealed nonexceedance probabilities of two hydrologic components : reservoir storage ratio and precipitation. To generate nonexceedance probability of hydrologic component, it was important to define the optimal one among the various probability distribution function in the state of nature. To define an optimal probability distribution, in this study, four types of probability distribution function were tested by the K-S fitting, and for the calculation of IRWSI, reservoir storage ratio(%) and precipitation used Normal distribution & Gamma distribution, respectively. In this study, the weight coefficients of a and b for each hydrologic component, which is precipitation and reservoir storage ratio, was decided as 0.8 and 0.2, respectively. While some studies changed weight coefficients according to the size of basin area, this study used same values without considering that. From the analysis of drought characteristics, it was found that the IRWSI was sensitive to the size of irrigation area rather than the size of basin area, and the south-eastern region of Korea had been suffered from severe drought damage.

• Carbon letters
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• 제13권3호
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• pp.182-186
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• 2012

A new model and resultant equation for the coagulation of acrylonitrile monomers in precipitation polymerization are suggested in consideration of the surface tension (${\gamma}$) and cohesive energy density ($E_{CED}$). The equation was proven to be quite favorable by considering figure fittings from known surface tensions and cohesive energy densities of certain organic solvents. The relationship between scale value of surface tension (${\gamma}$/M) and cohesive energy density of monomers can be obtained by changing the coagulation bath component for effective precipitation polymerization of acrylonitrile in wet spinning.

• 한국환경농학회지
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• 제15권2호
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• pp.188-197
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• 1996

전북 평야지역의 강수성분 변화 및 산성비 원인물질을 파악하기 위해 호남 농업 시험장내에서 1991년부터 1995년까지 강수의 화학적 조성을 분석 조사한 결과를 요약하면 다음과 같다. 1. '91년부터 '95년까지 5년동안 익산지역 평균산성비 강하율은 47.9%였다. 2. 강수 분획별 pH변화는 초기 강우(5mm이하)때 높고, 두번째 분회(10mm)에서 낮았으나 그 이후에는 증가하는 경향이었고 모든 성분은 첫번째 분회(5mm이하)에서 가장 높았다. 3. 5년 동안 pH 4.0 이하의 강수는 '91년이 5회, '92년이 4회, '95년이 1회 총 10회에 걸쳐 64mm로 년 강수량의 1.4% 수준이었다. 4. 5년 동안 평균 강우성분조성 분포비율은 $SO_4\;^{2-}$ > $NO_3\;^-$ > $Cl^-$ > $NH_4\;^+$ > $Ca^{2+}$ > $K^+$ > $Mg^{2+}$ 순이었다. 5. 익산지역에서 산성비 강하에 기여한 물질의 비율은 $SO_4\;^{2-}$이 52%, $NO_3\;^-$이 25%, $Cl^-$이 23%로 나타났다.

• 대기
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• 제25권1호
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• pp.67-83
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• 2015

Predicting the location and intensity of precipitation still remains a main issue in numerical weather prediction (NWP). Resolution is a very important component of precipitation forecasts in NWP. Compared with a lower resolution model, a higher resolution model can predict small scale (i.e., storm scale) precipitation and depict convection structures more precisely. In addition, an ensemble technique can be used to improve the precipitation forecast because it can estimate uncertainties associated with forecasts. Therefore, NWP using both a higher resolution model and ensemble technique is expected to represent inherent uncertainties of convective scale motion better and lead to improved forecasts. In this study, the limited area ensemble prediction system for the convective-scale (i.e., high resolution) operational Unified Model (UM) in Korea Meteorological Administration (KMA) was developed and evaluated for the ensemble forecasts during August 2012. The model domain covers the limited area over the Korean Peninsula. The high resolution limited area ensemble prediction system developed showed good skill in predicting precipitation, wind, and temperature at the surface as well as meteorological variables at 500 and 850 hPa. To investigate which combination of horizontal resolution and ensemble member is most skillful, the system was run with three different horizontal resolutions (1.5, 2, and 3 km) and ensemble members (8, 12, and 16), and the forecasts from the experiments were evaluated. To assess the quantitative precipitation forecast (QPF) skill of the system, the precipitation forecasts for two heavy rainfall cases during the study period were analyzed using the Fractions Skill Score (FSS) and Probability Matching (PM) method. The PM method was effective in representing the intensity of precipitation and the FSS was effective in verifying the precipitation forecast for the high resolution limited area ensemble prediction system in KMA.

• 대한지리학회:학술대회논문집
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• 대한지리학회 2005년도 춘계학술대회
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• pp.87-88
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• 2005

• 한국응용과학기술학회지
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• 제31권3호
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• pp.446-452
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• 2014

Methanol was directly produced by the partial oxidation of methane with four-component mixed oxide catalysts. Four-component(Mo-Bi-Cr-Si) mixed oxide catalysts were prepared by the co-precipitation and sol-gel methods. The catalyst prepared by the sol-gel method showed about eleven times higher surface area than that prepared by the co-precipitation method. From the $O_2$-TPD experiment of the prepared catalysts, it was proven that there exists two types of oxygen species, and the oxygen species that participates in the partial oxidation reaction is the lattice oxygen desorbing around $750^{\circ}C$. The optimum reaction condition for methanol production was $420^{\circ}C$, 50 bar, flow rate of 115 mL/min, and $CH_4/O_2$ ratio of 10/1.5, providing methane conversion and methanol selectivity of 3.2 and 26.7%, respectively.