• Journal of Korea Water Resources Association
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• v.55 no.12
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• pp.1149-1154
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• 2022

The purpose of this research is to select representative observation stations for winter observation equipment performance tests and to present indoor and outdoor conditions for performance tests by considering snowfall, snowfall days, latitude, and altitude distribution for observation stations operated by the Korea Meteorological Administration. Using the snowfall data observed during the winter for 30 years (1981-2010), ten representative observation stations are selected to consider the classification of snowfall days by class, latitude, and altitude distribution of observation stations. As a result of analysis, the suitable point for outdoor experiments was selected as Daegwallyeong, the average number of snowfall days and snowfall days of 5cm or more were 57.5 and 13.2 days, respectively. The indoor experimental conditions are considered to be suitable under temperatures of -15 to 5℃ and humidity of 50% or higher. Results of this research can be used as basic information for conditions and test beds for performance tests of equipment that can respond to heavy snow disasters in winter.

• Journal of the Korean Geographical Society
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• v.38 no.4
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• pp.463-477
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• 2003

This study identified the effects of global temperature rise on snowfall change over Korea selecting Seoul, Gangneung, Gunsan, and Daegu as study areas. The trend of snowfall change has generally decreased since 1950s over Korea, but has only increased in Gunsan since 1990s. The variation of snowfall days are similar to those of snowfall. The relationship between snowfall over Korea and the anomaly of global mean temperature in spring has a negative correlation. The change of Siberian High intensity also has a good relationship with snowfall in both Gunsan and Gangneung; the former is positively correlated while the latter is negatively correlated. This result might suggest that if the intensity of Siberian High would weakens due the ongoing global warming in the future, there would be a possibility that the amount snowfall could decrease in Gunsan but it could increase in Gangneung.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.2
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• pp.125-136
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• 2018

Heavy snowfall disasters are the third most serious natural disasters, after typhoon and heavy rainfall disasters, in terms of economic disaster damage in South Korea. The average annual economic damage of heavy snowfall disasters was approximately eighty-eight billion won during the period of 2005-2014. In spite of significant economic damage, there have been few economic studies regarding heavy snowfall disasters in South Korea. The objective of this research is to identify the association between economic damage of heavy snowfall disasters and damage effect factors of snowfall amounts, snowfall days, population densities, and non-urban area ratios using a regression analysis model. Economic damage data sets of heavy snowfall disasters during the period of 2005-2014 were obtained from the Natural Disaster Yearbook published by the Ministry of Public Safety and Security. Weather-related data sets, such as snowfall amounts and snowfall days were collected from the Korea Meteorological Administration. Demographic and urban data sets, including population densities and non-urban area ratios, were provided by the Local Government Yearbook. Outcomes of this study can assist with heavy snowfall disaster management policies of South Korea.

• Journal of Korea Planning Association
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• v.53 no.6
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• pp.117-130
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• 2018

Heavy snow is a natural disaster that causes serious economic damage. Since snowfall has been increasing recently, there is a need for measures against heavy snowfall. In order to make a policy decision on heavy snowfall, it is necessary to estimate the precise amount of damage by heavy snowfall. The direct damage of the heavy snow is severe, however the indirect damage caused by the road congestion and the urban dysfunction is also serious. Therefore, it is necessary to estimate indirect damage of snowfall. The purpose of this study is to estimate the effects on the regional economy from the limitation in traffic logistics caused by heavy snow using the transport demand model and inoperability input-output Model. The result shows that the amount of production loss caused by the heavy snow is KRW 2,460 billion per year and if the period of snowfall removal is shortened by one day or two days, it could be reduced to KRW 1,219 or 2,787 billion in production loss.

• Journal of the Korean Association of Geographic Information Studies
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• v.20 no.3
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• pp.42-51
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• 2017

Snowfall is an important natural hazard in Korea. In recent years, the socioeconomic importance of impact-based forecasts of meteorological phenomena have been highlighted. To further develop forecasts, we first need to analyze the climatic characteristics of each region. In this study, homogeneous regions for snowfall analysis were classified using a self-organizing map for impact-based forecast and warning services. Homogeneous regions of snowfall were analyzed into seven clusters and the characteristics of each group were investigated using snowfall, observation days, and maximum snowfall. Daegwallyeong, Gangneung-si, and Jeongeup-si were classified as areas with high snowfall and Gyeongsangdo was classified as an area with low snowfall. Comparison with previous studies showed that representative areas were well distinguished, but snowfall characteristics were found to be different. The results of this study are of relevance to future policy decisions that use impact-based forecasting in each region.

• Journal of Environmental Science International
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• v.16 no.12
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• pp.1439-1449
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• 2007

Heavy snowfall was occurred over the south-western part of the Korean Peninsula called as Honam Districts, on two days from 21 December 2005. The development mechanism of snowfall and its characteristics were analysed using observation and numerical data provided by Korea Meteorological Administration. In comparison with other years Arctic air mass developed and maintained during all December 2005 due to active planetary waves with three branches. And jet streams at lower and higher levels make easy development of snow convection cells. Especially thermal low induced by mesoscale heat and dynamic sources, also help the developments of convection cells in strong ascension. The understanding the relation between synoptic and mesoscale circumstance, therefore, is also important to predict the heavy snowfall and to prevent the disaster.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.35 no.3
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• pp.545-556
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• 2015

This study is to project the future snowfall and to assess heavy snowfall vulnerable area in South Korea using ground measured snowfall data and RCP climate change scenarios. To identify the present spatio-temporal heavy snowfall distribution pattern of South Korea, the 40 years (1971~2010) snowfall data from 92 weather stations were used. The heavy snowfall days above 20 cm and areas has increased especially since 2000. The future snowfall was projected by HadGEM3-RA RCP 4.5 and 8.5 scenarios using the bias-corrected temperature and snow-water equivalent precipitation of each weather station. The maximum snowfall in baseline period (1984~2013) was 122 cm and the future maximum snow depth was projected 186.1 cm, 172.5 mm and 172.5 cm in 2020s (2011~2040), 2050s (2041~2070) and 2080s (2071~2099) for RCP 4.5 scenario, and 254.4 cm, 161.6 cm and 194.8 cm for RCP 8.5 scenario respectively. To analyze the future heavy snowfall vulnerable area, the present snow load design criteria for greenhouse (cm), cattleshed ($kg/m^2$), and building structure ($kN/m^2$) of each administrative district was applied. The 3 facilities located in present heavy snowfall areas were about two times vulnerable in the future and the areas were also extended.

• Journal of the Korean Geographical Society
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• v.43 no.6
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• pp.843-857
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• 2008

This study analyzed distribution of natural disaster and trend of related climatic elements in mountainous region of Gangwon-do. In mountainous region of Gangwon-do, there have been 27 natural disasters of which heavy rainfall have the leading cause for the last 5 years(16 times in 2003-2007). It has been 9 natural disasters in Jinbu-myeon Pyeongchang-gun, the most frequent area. The mountainous region has been larger natural damage than its surrounding regions and there has been more damage at higher altitudes. While the heavy rainfall have caused damage over the northwest of mountains, most typhoons have damaged southern part of mountains. Most mountainous region suffers from strong wind but damage by snow is small. In mountainous region of Gangwon-do, annual precipitation, intensity of precipitation and heavy rainfall days have been increasing since 2000 and this tendency is significant in its intensity. However, annual snowfall, snowfall days and heavy snowfall days have been clearly decreasing since 2000. In case heavy rainfall accompanies strong wind, the damages are larger in mountainous region of Gangwon-do. Therefore it is important to be prepared for heavy rainfall and strong wind.

• Journal of Environmental Science International
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• v.23 no.8
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• pp.1481-1493
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• 2014

In order to understand the relation between the distribution of sea surface temperature and heavy snowfall over western coast of the Korean peninsula, several numerical assessments were carried out. Numerical model used in this study is WRF, and sea surface temperature data were FNL(National Center for Environment Prediction-Final operational global analysis), RTG(Real Time Global analysis), and OSTIA(Operational Sea Surface Temperature and Sea Ice Analysis). There were produced on the basis of remote sensing data, such as a variety of satellite and in situ observation. The analysis focused on the heavy snowfall over Honam districts for 2 days from 29 December 2010. In comparison with RTG and OSTIA SST data, sensible and latent heat fluexes estimated by numerical simulation with FNL data were higher than those with RTG and OSTIA SST data, due to higher sea surface temperature of FNL. General distribution of RTG and OSTIA SST showed similar, however, fine spatial differences appear in near western coast of the peninsula. Estimated snow fall amount with OSTIA SST was occurred far from the western coast because of higher SST over sea far from coast than that near coast. On the other hand, snowfall amount near coast is larger than that over distance sea in simulation with RTG SST. The difference of snowfall amount between numerical assessment with RTG and OSTIA is induced from the fine difference of SST spatial distributions over the Yellow sea. So, the prediction accuracy of snowfall amount is strongly associated with the SST distribution not only over near coast but also over far from the western coast of the Korean peninsula.

• International Journal of Highway Engineering
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• v.19 no.3
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• pp.83-90
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• 2017

PURPOSES : In this study, systematic road snow-removal capabilities were estimated based on previous historical data for road-snowremoval works. The final results can be used to aid decision-making strategies for cost-effective snow-removal works by regional offices. METHODS : First, road snow-removal historical data from the road snow-removal management system (RSMS), operated by the Ministry of Land, Infrastructure and Transport, were employed to determine specific characteristics of the snow-removal capabilities by region. The actual owned amount and actual used amount of infrastructure were analyzed for the past three years. Second, the regional offices were classified using K-means clustering into groups "close" to one another. Actual used snow-removal infrastructure was determined from the number of snow-removal working days. Finally, the correlation between the de-icing materials used and infrastructure was analyzed. Significant differences were found among the amounts of used infrastructure depending on snowfall intensity for each regional office during the past three years. RESULTS:The results showed that the amount of snow-removal infrastructure used for low heavy-snowfall intensity did not appear to depend on the amount of heavy snowfall, and therefore, high variation is observed in each area. CONCLUSIONS:This implies that the final analysis results will be useful when making decisions on snow-removal works.