• Atmosphere
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• v.32 no.1
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• pp.61-70
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• 2022

This study evaluates the economic values for the several first precipitation events during Changma period. The selected three years are 2015, 2019, and 2020, where average precipitation amounts across the 58 Korean stations are 12.8, 20.1 and 13.3 mm, respectively. The four categories are used to assess the values including air quality improvement, water resource acquisition/accumulation, drought mitigation, and forest fire prevention/recovery. Economic values for these three years are estimated 50~150 billion won. Among the four factors considered, the effect of air quality improvement is most highly valued, amounting to 70 to 90% of the total economic values. Wet decomposition of air pollution (PM₁₀, NO₂, CO, and SO₂) is the primary reason. The next valuable element is water resource acquisition, which is estimated 9~15 billion won. Effects of drought mitigation and fire prevention are deemed relatively small. This study is the first to estimate the value of the precipitation events during Changma onset. An analysis for more Changma years will be performed to achieve a more reliable estimate.

• Journal of Korean Society of Forest Science
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• v.105 no.1
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• pp.122-131
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• 2016

This study was conducted to analyze the effect of climatic variables on tree-ring growth of Larix leptolepis distributed in Korea by dendroclimatological method. For this, annual tree-ring growth data of Larix leptolepis collected by the $5^{th}$ National Forest Inventory were first organized to analyze yearly growth patterns of the species. To explain the relationship between tree-ring growth of Larix leptolepis and climatic variables, monthly temperature and precipitation data from 1950 to 2010 were compared with tree-ring growth data for each county. When tree-ring growth data were analyzed through cluster analysis based on similarity of climatic conditions, six clusters were identified. In addition, index chronology of Larix leptolepis for each cluster was produced through cross-dating and standardization procedures. The adequacy of index chronologies was tested using basic statistics such as mean sensitivity, auto correlation, signal to noise ratio, and expressed population signal of annual tree-ring growth. Response function analysis was finally conducted to reveal the relationship between tree-ring growth and climatic variables for each cluster. The results of this study are expected to provide valuable information necessary for estimating local growth characteristics of Larix leptolepis and for predicting changes in tree growth patterns caused by climate change.

• Atmosphere
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• v.26 no.4
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• pp.687-696
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• 2016

The western North Pacific subtropical high (WNPSH) in boreal summer has interannual and interdecadal variability, which affects East Asian summer monsoon variability. In particular, it is well known that the intensity of WNPSH is reversely related to that of summer monsoon in North East Asia in association with Pacific Japan (PJ)-like pattern. Many coupled climate models weakly simulate this large-scale teleconnection pattern and also exhibit the diverse variability of WNPSH. This study discusses the inter-model differences of WNPSH simulated by different climate models, which participate in the Coupled Model Intercomparison Project phase 5 (CMIP5). In comparing with reanalysis observation, the 29 CMIP5 models could be assorted into two difference groups in terms of interannual variability of WNPSH. This study also discusses the dynamical or thermodynamics factors for the differences of two groups of the CMIP5 climate models. As results, the regressed precipitation in well-simulating group onto the Nino3.4 index ($5^{\circ}N-5^{\circ}S$, $170^{\circ}W-120^{\circ}W$) is stronger than that in poorly-simulating group. We suggest that this difference of two groups of the CMIP5 climate models would have an effect on simulating the interannual variability of WNPSH.

• Journal of the Korean Association of Geographic Information Studies
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• v.20 no.1
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• pp.42-55
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• 2017

Since the phases and patterns of the climate adaptability of vegetation can greatly differ from region to region, an intensive pixel scale approach is required. In this study, Partial Least Squares (PLS) regression on satellite image-based vegetation index is conducted for to assess the effect of climate factors on vegetation productivity and to predict future productivity of forests vegetation in South Korea. The results indicate that the mean temperature of wettest quarter (Bio8), mean temperature of driest quarter (Bio9), and precipitation of driest month (Bio14) showed higher influence on vegetation productivity. The predicted 2050 EVI in future climate change scenario have declined on average, especially in high elevation zone. The results of this study can be used in productivity monitoring of climate-sensitive vegetation and estimation of changes in forest carbon storage under climate change.

• Ocean and Polar Research
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• v.31 no.1
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• pp.71-76
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• 2009

Drastic changes in the water quality and phytoplankton community of the new Saemankeum Lakeduring the first decade following the construction of the Saemankeum Sea Wall has been considered to be unavoidable. Input of eutrophicated water through the Mankyeong River and Dongjin River might produce more direct effects on the water quality and phytoplankton community, which lead us to launch a long-term semi-weekly investigation at the "Mankyeong Bridge" monitoring point to resolve its short-term effect as well as long-term stabilization of the ecosystem in the new Saemankeum Lake. During 15 months starting from June 2006, the water temperature varied in accordance with the typical seasonal variations in temperate on the coasts, and no significant daily variations evoked by tidal cycle could be detected. However, there was an inverse relationship between seasonal precipitation and salinity even though the range in annual variation was drastically reduced right after the construction of the Saemankeum Sea Wall. Species richness in the phytoplankton community was also reduced due to the narrowed annual range of salinity, which would eliminate the mid-high salinity species from the Mankyeong Bridge monitoring point. Similarly, species diversity was decreased with increased dominance of the phytoplankton community after the construction. Between the two summer seasons during the present study, species diversity was higher in 2007 than in 2006, which might indicate the early stage of a gradual stabilization in the ecosystem including the phytoplankton community at the monitoring station. The phytoplankton community thus needs to be monitored on a long-term basis to identify indirect signals that can be used to assess the stability of the ecosystem in the young Saemankeum Lake.

• Journal of the Korean Ceramic Society
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• v.54 no.5
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• pp.429-437
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• 2017

Micro hollow plate type silica with low refraction properties was synthesized and its hollow structure was applied as an optical structure to develop a light diffusion material that simultaneously satisfies the requirements of good light diffusibility, high transmissibility, and high luminance. The developed light diffusion material was applied to a light diffusion film and the film's optical properties were assessed. Hollow silica was synthesized by precipitation method using $Mg(OH)_2$ core particles, sodium silicate, and ammonium sulfate as the silica precursors. The concentration of the silica precursor was adjusted to control hollow silica shell thickness. The total light transmittance of the light diffusion film composed of the hollow silica was 94.55%, which was 4.57% higher than that of the PC film; new film's haze was 71.20%, which was 70.9% higher. Furthermore, the luminance increased by 5.34% compared to that of the light source. The reason for the results is not only that the micro plate type hollow silica, which has a low refractive property, played a role in reducing the difference in refractive index between the medium boundaries, but also that there was a light-concentrating effect due to the changing of light paths to the front direction inside the hollow structure. Optical simulation verified the enhanced optical properties when hollow silica was applied to the light diffusion film.

• Korean Journal of Remote Sensing
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• v.30 no.5
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• pp.641-650
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• 2014

Now global climate change is changing environmental factors, such as temperature and precipitation, which have a great effect on crop yields. Accordingly, crop yield forecast is becoming more important to global food supplies and sustainable development of rural areas. Worldwide, many countries, such as USA, China, Canada, and institutions, such as FAO, USDA, NASA, maintain the cooperative relationship to operate the crop monitoring system at both the national and global scale. This paper aims to investigate the current developments of crop monitoring systems in terms of information level, remotely-sensed data, and biophysical parameters, and to propose the direction of the advanced corp monitoring system based on remote sensing.

• Journal of Korean Society on Water Environment
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• v.37 no.5
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• pp.369-380
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• 2021

In this work, we analyzed the effects of drought on the water temperature (WT) of Nakdong river basin major river sections using Standardized Precipitation Index (SPI) and WT data. The analysis was carried out on a seasonal basis. After calculating the optimal time scale of the SPI through the correlation between the SPI and WT data, we used the copula theory to model the joint probability distribution between the WT and SPI on the optimal time scale. During spring and fall, the possibility of environmental drought caused by high WT increased in most of the river sections. Notably, in summer, the possibility of environmental drought caused by high WT increased in all river sections. On the other hand, in winter, the possibility of environmental drought caused by low WT increased in most river sections. From the risk map, which quantified the sensitivity of WT to the risk of environmental drought, the river sections Nakbon C, Namgang E, and Nakbon K showed increased stress in the water ecosystem due to high WT when drought occurred in summer. When drought occurred in winter, an increased water ecosystem stress caused by falling WT was observed in the river sections Gilan A, Yongjeon A, Nakbon F, Hwanggang B, Nakbon I, Nakbon J, Nakbon K, Nakbon L, and Nakbon M. The methodology developed in this study will be used in the future to quantify the effects of drought on water quality as well as WT.

• Journal of the Korean GEO-environmental Society
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• v.12 no.10
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• pp.51-56
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• 2011

This study was conducted to investigate the applicability of pulsed electric field (PEF) treatment for the prevention of scaling formation and membrane fouling reduction. To validate the effect of PEF and to identify the mechanism, some experiments with and without PEF treatment were carried out. PEF treatment affected the precipitation of $CaCO_3$ by which $CaCO_3$ particles were actively grown and sedimented. It was confirmed that the calcium ions were decreased as 78% and particle size was grown by PEF treatment. It was also verified that the crystalline structure of $CaCO_3$ was transformed by PEF treatment from Aragonite, which is formed at a high temperature and hard to be removed, to Calcite being stable at room temperature. In PEF treatment, permeate volume and permeation flux were greater than that of without PEF, case while Langelier Index(LI) decreased. From the experiment results, PEF treatment is believed to be an effective method to prevent scaling formation and to mitigate $CaCO_3$ fouling as the pretreatment of membrane filtration.

• Communications for Statistical Applications and Methods
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• v.30 no.2
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• pp.119-133
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• 2023

With the rapid growth of the economy and fossil fuel consumption, the concentration of air pollutants has increased significantly and the air pollution problem is no longer limited to small areas. We conduct statistical analysis with the actual data related to air quality that covers the entire of South Korea using R and Python. Some factors such as SO₂, CO, O₃, NO₂, PM₁₀, precipitation, wind speed, wind direction, vapor pressure, local pressure, sea level pressure, temperature, humidity, and others are used as covariates. The main goal of this paper is to predict air quality index (AQI) spatio-temporal data. The observations of spatio-temporal big datasets like AQI data are correlated both spatially and temporally, and computation of the prediction or forecasting with dependence structure is often infeasible. As such, the likelihood function based on the spatio-temporal model may be complicated and some special modelings are useful for statistically reliable predictions. In this paper, we propose several methods for this big spatio-temporal AQI data. First, random effects with spatio-temporal basis functions model, a classical statistical analysis, is proposed. Next, neural networks model, a deep learning method based on artificial neural networks, is applied. Finally, random forest model, a machine learning method that is closer to computational science, will be introduced. Then we compare the forecasting performance of each other in terms of predictive diagnostics. As a result of the analysis, all three methods predicted the normal level of PM_2.5 well, but the performance seems to be poor at the extreme value.