• Journal of the Korean Association of Geographic Information Studies
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• v.14 no.3
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• pp.188-202
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• 2011

Due to emissions of greenhouse gases caused by increased use of fossil fuels, the climate change has been detected and this phenomenon would affect even larger changes in temperature and precipitation of South Korea. Especially, the increase of temperature by climate change can affect the amount and pattern of snowfall. Accordingly, we tried to predict future snowfall and the snowfall pattern changes by using the downscaled GCM (general circulation model) scenarios. Causes of snow varies greatly, but the information provided by GCM are maximum / minimum temperature, rainfall, solar radiation. In this study, the possibility of snow was focused on correlation between minimum temperatures and future precipitation. First, we collected the newest fresh snow depth offered by KMA (Korea meteorological administration), then we estimate the temperature of snow falling conditions. These estimated temperature conditions were distributed spatially and regionally by IDW (Inverse Distance Weight) interpolation. Finally, the distributed temperature conditions (or boundaries) were applied to GCM, and the future snowfall was predicted. The results showed a wide range of variation for each scenario. Our models predict that snowfall will decrease in the study region. This may be caused by global warming. Temperature rise caused by global warming highlights the effectiveness of these mechanisms that concerned with the temporal and spatial changes in snow, and would affect the spring water resources.

• 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.1
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• pp.1-19
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• 2008

This study intends to clarify the characteristics and causes of current changes in wintertime precipitation in Korea and to predict the future directions based on surface observational $(1973/04\sim2006/07)$ and modeled (GFDL 2.1) climate data. Analyses of surface observation data demonstrate that without changes in the total amount of precipitation, snowfall in winter (November-April) has reduced by 4.3cm/decade over the $1973\sim2007$ period. Moreover, the frequency and intensity of snowfall have decreased; the duration of snow season has shortened; and the snow-to-rain day ratio (STDR) has decreased. These patterns indicate that the type of wintertime precipitation has changed from snow to rain in recent decades. The snow-to-rain change in winter is associated with the increases of air temperature (AT) over South Korea. Analyses of synoptic charts reveal that the warming pattern is associated with the formation of a positive pressure anomaly core over northeast Asia by a hemispheric positive winter Arctic Oscillation (AO) mode. Moreover, the differentiated warming of AT versus sea surface temperature (SST) under the high pressure anomaly core reduces the air-sea temperature gradient, and subsequently it increases the atmospheric stability above oceans, which is associated with less formation of snow cloud. Comparisons of modeled data between torrent $(1981\sim2000)$ and future $(2081\sim2100)$ periods suggest that the intensified warming with larger anthropogenic greenhouse gas emission in the $21^{st}$ century will amplify the magnitude of these changes. More reduction of snow impossible days as well as more abbreviation of snow seasons is predicted in the $21^{st}$ century.