• Korean Journal of Environmental Agriculture
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• v.25 no.1
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• pp.1-6
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• 2006

This study was carried out to investigate yearly change in the precipitation component and the source strength to acid precipitation at Iksan area from 1997 to 2003. The average ratio of acid precipitation was 70.0% in 1997, 56.3% in 1998 and 36.4% in 2003. On the other hand, it ranged from 6.9 to 19.2% when precipitation was less from 1999 to 2002. The average annual wet depositions of major ionic component in precipitation were calculated by multiplying equivalent concentration by precipitation. The order of major anion component in precipitation was ${SO_4}^{2-}>Cl^->{NO_3}^-$. On the other hand, the concentration of cation component were ${Ca_2}^+>Na^+>{NH_4}^+>{Mg_2}^+>K^+$ in order. The negative correlation was shown between pH and ionic component in precipitation except for ${Ca_2}^+\;and\;Na^+$. The correlation coefficient between pH and ${SO_4}^{2-}$ was highly significant as -0.508, which suggests that ${SO_4}^{2-}$ played important role in increasing the acidity of precipitation. Also the anions such as ${SO_4}^{2-}\;and\;{NO_3}^-$ were highly significant with cations such as ${Ca_2}^+,\;{Mg_2}^+,\;K^+,\;{NH_4}^+\;and\;Na^+$. As a result though pH was enable to use the acidity index of precipitation in somewhere, evaluating only pH in precipitation was insufficient as the index to establish corresponding strategy for acid rain.

• Journal of Environmental Science International
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• v.4 no.5
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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.

• Journal of Environmental Science International
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• v.4 no.5
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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.

• Journal of the Korean earth science society
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• v.26 no.5
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• pp.417-428
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• 2005

The seasonal variation and frequency of precipitation phenomenon of the Korean Peninsula in summer show strong local weather phenomena because of its topographical and geographical factors in the northeastern area of Asia. The characteristics of the prevailing weather patterns in summer precipitation in Korea have great influences on the variation patterns and the appearances over a ten-day period during the summer precipitation. The purpose of this paper is to induce variation patterns over a period 10 days during the summer precipitation, clarify the variations of their space scales, and study the subdivision of precipitation regions in Korea according to the combinations of precipitation amounts and variation pattern during the period, using the mean values during the years $1991\~2003$ at 78 stations in Korea. The classified precipitation of a period of 10 days of summer precipitation, and the principal component vector and the amplitude coefficient by the principal component analysis were used for this study. The characteristics of variation pattern over the ten-day period can be chiefly divided into two categories and the accumulated contributory rate of these is $64.3\%$. The variation patterns of summer precipitation during period of 10 days in Korea are classified into 9 types from A to K. In addition, regional divisions of summer precipitation in Korea can be classified into 17 types.

• Bulletin of the Korean Chemical Society
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• v.23 no.3
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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.

• Journal of the Korean association of regional geographers
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• v.11 no.1
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• pp.101-113
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• 2005

The seasonal variation and frequency of precipitation phenomenon of the Honam region in summer show strong local weather phenomena because of its topographical and geographical factors in southwestern area of Korea. The propose of this treatise is to induce variation patterns over a period 10 days of summer precipitation(that is one of the important elements of the precipitation characteristics), clarify the variations of their space scales, and study the subdivision of precipitation regions in Honam according to the combinations of precipitation amounts and variation pattern over a period of a 10 days of summer precipitation, using the mean values during the years 1994$\sim$2003 at 79 stations(the surface synoptic stations 16 AWS 63) of Honam region. The classified precipitation of a period of 10 days summer precipitation, and the principal component vector and the amplitude coefficient by the principal component analysis were used for this study. The characteristics of variation pattern over a period of 10 days of summer precipitation can be chiefly divided into four categories and the accumulated contributory rate of these is 78.0%. And the change patterns of summer precipitation during a period of 10 days in honam region are classified into 11 types from A to K And regional divisions of summer precipitation in Honam region can be classified into 18 types.

• Journal of Environmental Science International
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• v.5 no.2
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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.

• The Korean Journal of Applied Statistics
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• v.19 no.3
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• pp.431-445
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• 2006

In this paper we review some methods for analyzing functional data and illustrate real application of functional data analysis. Representing methods for functional data by using basis function, analyzing functional variation by functional principal component analysis and functional linear models are reviewed. For a real application, we use temperature and precipitation data measured in Korea from the January of 1970 to the May of 2004. We apply functional principal component analysis for each data and test the significance of regional division done by using shining hours. We also estimate functional regression model for temperature and precipitation.

• Korean Journal of Remote Sensing
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• v.33 no.4
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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.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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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.