• Ocean and Polar Research
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• v.38 no.4
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• pp.331-338
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• 2016

Many studies using tracers have been conducted to understand a physical process in a system. Rain-on-snow could accelerate snowmelt processes, which influences the hydrological process in both temperate and polar regions. Hydrological and ecological conditions will be affected by the amount and timing of discharge reaching the bottom of a snowpack. The discharge consists of the rain-on-snow, pore water penetrating into the snowpack and natural meltwater. In this study, after a rain-on-snow experiment, we conducted an isotopic hydrograph separation to distinguish rainwater and pore water from meltwater. Using the isotopic data of snow and meltwater from Lee et al. (2010), two components were separated based on the assumption that rainwater and pore water are new water and natural meltwater is old water. After the second rain-on-snow experiment, the maximum contributions of rainwater and pore water reached up to 69% of the discharge and then decreased. During the study period, the measured total discharge was 4153 L and 40% (based on hydrogen isotope) of rainwater and pore water was calculated in the discharge, which is not consistent with what Lee et al. (2016) calculated using chemical separation (63%). This inconsistency can be explained by how an end-member was defined in both approaches. The contributions of artificial rainonsnow and pore water to melwater discharge range between the two methods. This study will suggest a mixing calculation from isotopic compositions of the Southern Ocean.

• Magazine of the Korean Society of Agricultural Engineers
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• v.45 no.4
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• pp.98-106
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• 2003

In order to set up structural improvement strategy against meteorological disasters of the shading structures in ginseng fields, structural safety analyses as well as some case studies of structural damage patterns were carried out. According to the results of structural safety analysis, allowable safe snow depth for type B(wood frame with single span) was 25.9 cm, and those for type A(wood frame with multi span) and type C and D (steel frame with multi span) were 17.6 cm, 25.8 cm, and 20.0 cm respectively. So types of shading structures should be selected according to the regional design snow depth. An experiential example study on meteorological disasters indicated that a strong wind damage was experienced once every 20 years, and a heavy snow damage once every 9.5 years. The most serious disasters were caused by heavy snow and it was found that a half break and complete collapse of structures were experienced by about 70% of snow damage. In addition to maintenance, repair and reinforcement, it is also recommended that improved model of shading structures for ginseng cultivation should be developed as a long term countermeasures against meteorological disasters.

• Journal of the Korean Society of Clothing and Textiles
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• v.30 no.4 s.152
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• pp.582-594
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• 2006

The purpose of this study were to develop snow-board lower wear with improved functionality. The study consisted of figure out appropriate ease amount of snow-board lower wear and make products by applying it to pattern design. The results of this study were as follows: On the basis of the analysis of snow-board lower wear on market, 2 pieces of experimental snowboard lower wear were designed, produced, and evaluated the patterns of with different ease, and snowboard lower B for experiment was proved to be better. Snowboard lower wear was produced and evaluated for experiment 2 by giving additional ease to specific parts. Therefore experiment 2 was presented pattern, ease, and size of snowboard lower wear with improved functionality. Sizes and ease of snow-board lower wear for presentation. waist circumference - 96.0cm(l6.4cm, 17.1%); hip circumference - 127.0cm(31.3cm, 24.4%); pants length - 112.0cm(9.6cm, 8.6%); crotch length - 90.0cm(26.8cm, 36.4%); thigh circumference - 78.0cm(23.4cm, 30.0%); knee circumference - 62.0cm(24.7cm, 39.8%); turnup circumference - 62.0cm(36.0cm, 58.1%). Above mentioned sizes and ease of lower wear are medium size(M) for male.

• Journal of Integrative Natural Science
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• v.7 no.1
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• pp.39-44
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• 2014

The results of the synoptic meteorological analysis showed that when the cold and dry continental high pressure was extended, heavy snow occurred at dawn when the upper atmosphere cooled. In particular, when the continental high pressure was extended and the upper pressure trough passed through, heavy snow occurred due to the convergence region formed in the west coast area, sometimes in the inland of the Honam area. In addition, it was verified that the changes in the humidity coefficients in the upper and lower layers are important data for the determination of the probability, start/end and intensity of heavy snow. However, when the area was influenced by the middle-latitude low pressure, the heavy snow was influenced by the wind in the lower layer (925 hPa and 850 hPa), the equivalent potential temperature, the convergence field, the moisture convergence and the topography. In Case 2010 (30 December 2010), OSTIA had the best numerical simulation with diverse atmospheric conditions, and the maximum difference in the numerically simulated snowfall between NCEP/NCAR SST and OSTIA was 20 cm. Although there was a regional difference in the snowfall according to the difference in the SST, OSTIA and RTG SST numerical tests, it was not as significant as in the previous results. A higher SST led to the numerical simulation of larger snowfall, and the difference was greatest near Buan in the west coast area.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.6
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• pp.77-93
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• 2022

In this study, we present an algorithm that analyzes the risk by reflecting regional characteristics for factors affected by direct and indirect damage from heavy-snow. Factors affected by heavy-snow damage by 29 regions are selected as influencing variables, and the concept of sensitivity is derived through the relationship with the amount of damage. A snow damage risk prediction model was developed using a machine learning (XGBoost) algorithm by setting weather conditions (snow cover, humidity, temperature) and sensitivity as independent variables, and setting the risk derived according to changes in the independent variables as dependent variables.

• Korean Journal of Remote Sensing
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• v.28 no.4
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• pp.409-420
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• 2012

Since the Industrial Revolution, CO2 levels have been increasing with climate change. In this study, Analyze time-series changes in snow cover quantitatively and predict the vanishing point of snow cover statistically using remote sensing. The study area is Mt. Kilimanjaro, Tanzania. 23 image data of Landsat-5 TM and Landsat-7 ETM+, spanning the 27 years from June 1984 to July 2011, were acquired. For this study, first, atmospheric correction was performed on each image using the COST atmospheric correction model. Second, the snow cover area was extracted using the NDSI (Normalized Difference Snow Index) algorithm. Third, the minimum height of snow cover was determined using SRTM DEM. Finally, the vanishing point of snow cover was predicted using the trend line of a linear function. Analysis was divided using a total of 23 images and 17 images during the dry season. Results show that snow cover area decreased by approximately $6.47km^2$ from $9.01km^2$ to $2.54km^2$, equivalent to a 73% reduction. The minimum height of snow cover increased by approximately 290 m, from 4,603 m to 4,893 m. Using the trend line result shows that the snow cover area decreased by approximately $0.342km^2$ in the dry season and $0.421km^2$ overall each year. In contrast, the annual increase in the minimum height of snow cover was approximately 9.848 m in the dry season and 11.251 m overall. Based on this analysis of vanishing point, there will be no snow cover 2020 at 95% confidence interval. This study can be used to monitor global climate change by providing the change in snow cover area and reference data when studying this area or similar areas in future research.

• Journal of Korea Water Resources Association
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• v.53 no.4
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• pp.259-271
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• 2020

In Korea, snow damage has happened in the region with little snowfalls in history. Also, accidental damage was caused by heavy snow leads and the public interest on heavy snow has been increased. Therefore, policy about the Natural Disaster Reduction Comprehensive Plan has been changed to include the mitigation measures of snow damage. However, since heavy snow damage was not frequent, studies on snowfall have not been conducted on different points. The characteristics of snow data commonly are not the same as the rainfall data. Some southern coastal areas in Korea are snowless during the year. Therefore, a joint probability distribution was suggested to analyze the snow data with many 0s in a previous research and fitness from the joint probability distribution was higher than the conventional methods. In this study, snow frequency analysis was implemented using the joint probability distribution and compared to the design codes. The results were compared to the design codes. The results of this study can be used as the basic data to develop a procedure for the snow frequency analysis in the future.

• Ocean and Polar Research
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• v.26 no.3
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• pp.439-451
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• 2004

Total solar irradiance (750), total UV irradiunce (TUV) and erythemal UV irradiance (EUV) measured at King Sejong station $(62.22^{\circ}S,\;58.78^{\circ}W)$ in west Antarctica have been used together with total ozone, cloud amount and snow cover to examine the effects of ozone, cloud and snow surface on these surface solar inadiunce over the period of 1998-2003. The data of three solar components for each scan were grouped by cloud amount, n in oktas $(0{\leq}n<3,\;3{\leq}n<4,\;4{\leq}n<5,\;5{\leq}n<6,\;6{\leq}n<7\;and\;7{\leq}n<8)$ and plotted against solar zenith angle (SZA) over the range of $45^{\circ}\;to\;75^{\circ}$. The radiation amplification factor (RAE) is used to quantify ozone effect on EUV. RAF of EUV decreases from 1.51 to 0.94 under clear skies but increases from 0.94 to 1.85 under cloudy skies as SZA increases, and decreases from 1.51 to 1.01 as cloud amount increases. The effects of cloud amount and snow surface on EUV are estimated as a function of SZA and cloud amount after normalization of the data to the reference total ozone of 300 DU. In order to analyse the transmission of solar radiation by cloud, regression analyses have been performed for the maximum values of solar irradiance on clear sky conditions $(0{\leq}n<3)$ and the mean values on cloudy conditions, respectively. The maximum regression values for the clear sky cases were taken to represent minimum aerosol conditions fur the site and thus appropriate for use as a normalization (reference) factor for the other regressions. The overall features for the transmission of the three solar components show a relatively high values around SZAs of $55^{\circ}\;and\;60^{\circ}$ under all sky conditions and cloud amounts $4{\leq}n<5$ and $5{\leq}n<6$. The transmission is, in general, the largest in TUV and the smallest in EUV among the three components of the solar irradiance. If the ground is covered with snow on partly cloudy days $(6{\leq}n<7)$, EUV increases by 20 to 26% compared to snow-free surface around SZA $60^{\circ}-65^{\circ}$, due to multiple reflections and scattering between the surface and the clouds. The relative difference between snow surface and snow-free surface slowly increases from 9% to 20% as total ozone increases from 100 DU to 400 DU under partly cloud conditions $(3{\leq}n<6)$ at SZA $60^{\circ}$. The snow effects on TUV and TSO are relatively high with 32% and 34%, respectively, under clear sky conditions, while the effects changes to 36% and 20% for TUV and TSO, respectively, as cloud amount increases.

• Korean Journal of Remote Sensing
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• v.33 no.3
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• pp.287-299
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• 2017

The Southern Volcanic Zone (SVZ) of Chile consists of many volcanoes, including the Mt.Villarrica and Mt.Llaima, and the two volcanoes are covered with snow at the top of Mountain. The purpose of this study is to analyze the relationship between the ice caps and the volcanic activity of the two volcanoes for 25 years by using the satellite image data are available in a time series. A total of 60 Landsat-5 TM and Landsat-7 ETM + data were used for the study from September 1986 to February 2011. Using NDSI (Normalized Difference Snow Index) algorithm and SRTM DEM, snow cover and snowline were extracted. Finally, the snow cover area, lower-snowline, and upper-snowline, which are quantitative indicators of snow cover change, were directly or indirectly affected by volcanic activity, were extracted from the satellite images. The results show that the volcanic activity of Villarrica volcano is more than 55% when the snow cover is less than 20 and the lower-snowline is 1,880 m in Llaima volcano. In addition, when the upper-snowline of the two volcanoes is below -170m, it can be confirmed that the volcano is differentiated with a probability of about 90%. Therefore, the changes in volcanic snowfall are closely correlated with volcanic activity, and it is possible to indirectly deduce volcanic activity by monitoring the snow.

• Journal of the Korean Society for Railway
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• v.11 no.5
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• pp.441-448
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• 2008

Increasing urban sprawl and climate changes have been causing unexpected high-intensity rainfall events. Thus there are needs to enhance conventional disaster management system for comprehensive actions to secure safety. Therefore long-term and comprehensive flood management plans need to be well established. Recently torrential snowfall are occurring frequently, causing have snow traffic jams on the road. To secure safety and on-time operation of the Bi-modal tram system, well-structured disaster management system capable of analyzing the show pack melt/freezing due to unexpected snowfall are needed. To secure safety of the Bi-modal tram system due to torrential snow-fall, the snow melt simulation capability was investigated. The snow accumulation and snow melt were measured to validate the SWMM snow melt component. It showed that there was a good agreement between measured snow melt data and the simulated ones. Therefore, the Bi-modal tram disaster management system will be able to predict snow melt reasonably well to secure safety of the Bi-modal tram system during the winter. The Bi-modal tram disaster management system can be used to identify top priority area for know removal within the tram route in case of torrential snowfall to secure on-time operation of the tram. Also it can be used for detour route in the tram networks based on the disaster management system prediction.