• 한국환경농학회지
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• 제25권1호
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• pp.1-6
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• 2006

본 연구는 산성비의 대한 장기적이고 종합적인 대책방안을 마련하기 위한 기초 자료를 제공코자 1997년부터 2003년까지 7년 동안 산성강우 현상을 중심으로 조사하였다. 강수의 연차적 산성비 강하비율은 1997년 70.0%, 1998년 56.3%, 2003년 36.4%를 나타냈으나, 강우량이 적은 1999년부터 2002년의 산성비 강하비율은 $6.9{\sim}19.2%$를 보였다. 산성우에 대한 영향 평가시 단기간에 의한 것보다 장기적인 영향으로 발생하기 때문에 산성강하물의 농도뿐만 아니라 침착량의 해석이 필요하다. 강수중 주요 이온성분의 연평균 습성침착량은 각 이온성분의 당량농도에 강수량을 곱하여 산출하였다. 각 이온 성분의 침착량을 살펴보면 음이온은 ${SO_4}^{2-}>Cl^->{NO_3}^-$순이었으며, 양이온의 경우는 ${NH_4}^+>Ca^{2+}>Na^+>Mg^{2+}>K^+$순으로 많았다. 강수 중 주요성분에 대한 상관분석 결과 pH와 강수 이온 성분중 $Ca^{2+}$와 $Na^+$성분을 제외한 모든 성분에서 부의 상관을 나타냈으며 그 외 각 성분간의 상관은 정의 상관을 나타냈다. pH와 ${SO_4}^{2-}$간의 상관계수는 -0.508로 고도의 유의성을 나타냈는데 이는 ${SO_4}^{2-}$성분이 강수중 산성도를 증가시키는 주요원인 물질중 가장 큰 역할을 하고 있음을 추정할 수 있었다. 또한 ${SO_4}^{2-}$와 ${NO_3}^-$ 이온은 $Ca^{2+},\;Mg^{2+},\;K^+,\;{NH_4}^+\;and\;Na^+$ 등 양이온과 고도의 유의성을 보였다.

• 한국환경과학회지
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• 제4권5호
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• pp.1-1
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• 1995

An attempt was made to study the subdivision of Korea by the annual amount and the annual change pattern of monthly precipitation days(that is one of the important elements of the precipitation characteristics), using the mean values for the years 1961-1990 at the 68 stations. The amplitudes of annual change were normalized and using these values, the principal component analysis was applied to determine the annual change patterns. The results show that they are expressed by the combinations of the three change patterns in almost whole regions of Korea. As a result,the annual change pattern of precipitation days in Korea is classified into 8 types from A to e,in detail, 36 types from A0 to e$\circled2$.And regional division of precipitation days in Korea is divided into 13 regions from I a to IIIC,into detail, 41 regions from I no to IIICl.

• 한국환경과학회지
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• 제4권5호
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• pp.387-402
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• 1995

An attempt was made to study the subdivision of Korea by the annual amount and the annual change pattern of monthly precipitation days(that is one of the important elements of the precipitation characteristics), using the mean values for the years 1961-1990 at the 68 stations. The amplitudes of annual change were normalized and using these values, the principal component analysis was applied to determine the annual change patterns. The results show that they are expressed by the combinations of the three change patterns in almost whole regions of Korea. As a result, the annual change pattern of precipitation days in Korea is classified into 8 types from A to e, in detail, 36 types from A0 to e$\circled2$.And regional division of precipitation days in Korea is divided into 13 regions from I a to IIIC, into detail, 41 regions from I no to IIICl.

• 한국지구과학회지
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• 제26권5호
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• pp.417-428
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• 2005

아시아의 동안에 위치한 한반도는 수리적, 지리적 요인에 의해 지역에 따라 강수현상 및 탁월 일기의 다소와 그 계절변화가 크다. 이러한 탁월한 날씨의 특징은 한국의 하계의 강수출현율과 그 순변화에 잘 반영되고 있다. 본 논문은 한국의 78개 관측지점의 하계강수량$(1991\~2003)$의 순별 평균값에 대해 주성분분석법을 응용하여 하계강수량의 순변화형을 추출하고, 그의 공간스케일과 강수량의 다소에 따라 강수지역구분을 한 것이다. 주성분 분석에 의해 추출된 주성분 벡터와 진폭계수(Rs)에 따라 하계 강수량 순변화의 전형적인 특징은 두 개의 순변화형으로 표현되며 그 누적기여율은 $64.3\%$이다. 또한 한국의 하계 강수량의 순변화형은 $A\~K$형까지 9개가 추출되었고, 강수지역은 17개형으로 분류되었다.

• Bulletin of the Korean Chemical Society
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• 제23권3호
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• pp.369-373
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• 2002

The liquid phase oxidation of p-xylene has been carried out with oxygen-enriched gas, and the manganese component was precipitated probably via over-oxidation to $Mn^{4+}$. The precipitation increased with rising oxygen concentration in the reaction gas and occurred mainly in the later part of the oxidation. The activity of the reaction decreased, and the blackening of the product and side reactions to carbon dioxide increased with the degree of precipitation. Precipitation can be decreased with the addition of metal ions, such as cerium, chromium and iron.

• 한국지역지리학회지
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• 제11권1호
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• pp.101-113
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• 2005

한반도의 남서부에 위치한 호남지방은 수리적, 지리적 요인에 의해 지역에 따라 하계의 강수현상 및 탁월일기의 다소와 그 계절변화가 크다. 본 논문은 AWS 63개 지점을 포함한 호남의 79개 기상관측지점의 하계강수량(1994$\sim$2003)과 그 순변화형(강수특성 표현의 중요한 한 요소임)에 대해 순별 강수량의 다소와 순장수량의 주성분벡터와 진폭계수(Rs)를 이용하여, 호남 각 지역에서의 하계강수량 순변화형을 수량적으로 추출하고, 그 공간스케일의 변동을 규명해, 그에 따른 호남지방의 강수지역 구분을 시도한 것이다. 그 결과 호남지방의 하계강수량 순변화의 전형적 특징은 상위 4개의 순변화형으로 표현되며 그 누적기여율은 78.0%이다. 또한 호남지방의 하계강수량의 순변화형은 A-K형까지 11개가 추출되었고, 강수지역은 18개형 지역으로 구분되었다.

• 한국환경과학회지
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• 제5권2호
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• pp.141-152
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• 1996

This study is an attempt to investigate the chemical components of precipitation and its variation according to surface wind. Precipitation samples were collected by an wet-only precipitation sampler during the period of October 1994 to September 1995 at Kyungsan in Korea. The results obtained in t체s study are summerized as follows. The annual average of precipitation pH is 5.0, the highest month of pH is July of 5.5, and the lowest month of pH is December of 4.4. The most frequent appearance is in the range of pH 5.0 to 5.5 and its rate is 56.8%, The order of ion concentration In precipitation is SO42->NO3->Cl- in case of anion and $Ca^{2+}$>$NH_4^{+}$>$Na^+$>$Mg^{2+}$ in case of cation. It is found from our analysis that the correlation coefficient among the precipitation pH and ion components is below r=0.3, while the correlation coefficient between $SO_4^{2-}$ and NO_3^{-}$, $Na^+$ and $Cl^+$ is above r=0.8, respectively. The mean pH of precipitation is 4.8 under the westerly wind and 5.2 under the easterly wind. The concentrations of anion and cation under the westerly wind are more than the concentrations under the easterly wind. In autumn, the concentration of Na+ and $Cl^+$ under the easterly wind are higher than the concentration under the westerly wind. The correlation coefficients between wind speed and pH, ion components show very low correlation of -0.41 r 0.2. But the present study show that the correlation coefficient between wind speed and pH of precipitation is positive and the correlation coefficients between wind speed and ion concentration is negative.

• 응용통계연구
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• 제19권3호
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• pp.431-445
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• 2006

본 연구는 함수적 데이터 분석의 몇 가지 이론에 대해 소개하고 분석 기법을 실제 자료에 적용하는 내용을 다루었다. 함수적 데이터 분석의 이론적 내용으로 기저를 이용해 자료를 함수적 데이터로 표현하는 방법, 그리고 함수적 데이터의 변동성을 조사하는 주성분분석, 선형모형 등에 대해 살펴보았다. 그리고 우리나라 기온 데이터와 강수량 데이터를 대상으로 각각 함수적 데이터 분석 기법을 적용해 보았다. 또한, 기온과 강수량 데이터에 대해 함수적 회귀모형을 적합시켜 두 변수간의 함수관계를 살펴보았다.

• 대한원격탐사학회지
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• 제33권4호
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• pp.445-454
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• 2017

The performance of spatial downscaling models depends on the quality of input coarse scale products. Thus, the impact of intrinsic errors contained in coarse scale satellite products on predictive performance should be properly assessed in parallel with the development of advanced downscaling models. Such an assessment is the main objective of this paper. Based on a synthetic satellite precipitation product at a coarse scale generated from rain gauge data, two synthetic precipitation products with different amounts of error were generated and used as inputs for spatial downscaling. Geographically weighted regression, which typically has very high explanatory power, was selected as the trend component estimation model, and area-to-point kriging was applied for residual correction in the spatial downscaling experiment. When errors in the coarse scale product were greater, the trend component estimates were much more susceptible to errors. But residual correction could reduce the impact of the erroneous trend component estimates, which improved the predictive performance. However, residual correction could not improve predictive performance significantly when substantial errors were contained in the input coarse scale data. Therefore, the development of advanced spatial downscaling models should be focused on correction of intrinsic errors in the coarse scale satellite product if a priori error information could be available, rather than on the application of advanced regression models with high explanatory power.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2021년도 학술발표회
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• pp.134-134
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• 2021

Precipitation is a crucial component of water cycle and play a key role in hydrological processes. Traditionally, gauge-based precipitation is the main method to achieve high accuracy of rainfall estimation, but its distribution is sparsely in mountainous areas. Recently, satellite-based precipitation products (SPPs) provide grid-based precipitation with spatio-temporal variability, but SPPs contain a lot of uncertainty in estimated precipitation, and the spatial resolution quite coarse. To overcome these limitations, this study aims to generate new grid-based daily precipitation using Automatic weather system (AWS) in Korea and multiple SPPs(i.e. CHIRPSv2, CMORPH, GSMaP, TRMMv7) during the period of 2003-2017. And this study used a machine learning based Random Forest (RF) model for generating new merging precipitation. In addition, several statistical linear merging methods are used to compare with the results of the RF model. In order to investigate the efficiency of RF, observed data from 64 observed Automated Synoptic Observation System (ASOS) were collected to evaluate the accuracy of the products through Kling-Gupta efficiency (KGE), probability of detection (POD), false alarm rate (FAR), and critical success index (CSI). As a result, the new precipitation generated through the random forest model showed higher accuracy than each satellite rainfall product and spatio-temporal variability was better reflected than other statistical merging methods. Therefore, a random forest-based ensemble satellite precipitation product can be efficiently used for hydrological simulations in ungauged basins such as the Mekong River.