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

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.35 no.3
• /
• pp.545-556
• /
• 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 Bio-Environment Control
• /
• v.24 no.3
• /
• pp.226-234
• /
• 2015

To provide the data necessary to determine exposure coefficients used for calculating the snow load acting on a greenhouse, we compared the exposure coefficients in the greenhouse structure design standards for various countries. We determined the exposure coefficient for each region and tried to improve on the method used to decide it. Our results are as follows: After comparing the exposure coefficients in the standards of various countries, we could determine that the main factors affecting the exposure coefficient were terrain roughness, wind speed, and whether a windbreak was present. On comparing national standards, the exposure coefficients could be divided into three groups: exposure coefficients of 0.8(0.9) for areas with strong winds, 1.0(1.1) for partially exposed areas, and 1.2 for areas with dense windbreaks. After analyzing the exposure coefficients for 94 areas in South Korea according to the ISO4355 standard, all of the areas had two coefficients (1.0 and 0.8), except Daegwallyeong (0.5) and Yeosu (0.6), which had one coefficient each. In South Korea, the probability of snow is greater inland than in coastal areas and there are fewer days with a maximum wind velocity > $5m{\cdot}s^{-1}$ inland. When determining the exposure coefficients in South Korea, we can subdivide the country into three regions: coastal areas with strong winds have an exposure coefficient of 0.8; inland areas have a coefficient of 1.0; and areas with dense windbreaks have an exposure coefficient of 1.2. Further research that considers the number of days with a wind velocity > $5m{\cdot}s^{-1}$ as the threshold wind speed is needed before we can make specific recommendations for the exposure coefficient for different regions.