• Journal of the Society of Disaster Information
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• v.16 no.1
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• pp.21-33
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• 2020

Purpose: The objective of this research is to classify snowfall area types with consideration of past regional snowfall characteristics and times for the effective local snow removal response systems of 229 local government districts. Method: This research first collected snowfall data of South Korea meteorological stations, and classified regional types using successive snowfall time. This research finally produced GIS maps using regional type information of snowfalls by applying GIS analysis methods. Result: This research provides five types of snowfall regions including 'frequent heavy snowfall regions', 'frequent light snowfall regions', 'rare heavy snowfall regions', 'average snowfall regions', and 'rare light snowfall regions' based on analysis results. Conclusion: Results of this research can be used as basic information for regional demand estimations of snow removal equipments, materials, vehicles, and personnel for the efficient snow removal response systems.

• Atmosphere
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• v.31 no.2
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• pp.157-170
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• 2021

To investigate the effect of snowfall on the traffic of general roads in Gangwon-do, case analysis was performed in Gangneung, Pyeongchang, and Chuncheon using ASOS (Automated Synoptic Observing System) snowfall data and VDS (Vehicle Detector System) traffic data. First, we analyzed how much the traffic volume and speed decrease in snowfall cases on regional roads compared to non-snow cases, and the characteristics of monthly reduction due to snowfall were investigated. In addition, Pearson correlation analysis and regression analysis were performed to quantitatively grasp the effect of snowfall on traffic volume and speed, and sensitivity tests for snowfall intensity and cumulative snowfall were performed. The results showed that the amount of snowfall caused decrease both in the traffic volume and speed from usual (non-snowfall) condition. However, the trend was different by region: The decrease rate in traffic volume was in the order of Gangneung (17~22%), Chuncheon (14~17%), and Pyeongchang (11~14%). The decrease rate in traffic speed was in the order of Chuncheon (9~10%), Gangneung (8~9%), Pyeongchang (5~6%). No significant results were found in the monthly decrease rate analysis. In all regions, traffic volume and speed showed a negative correlation with snowfall. It was confirmed that the greater the amount of traffic entering the road, the greater the slope of the trend line indicating the change in snowfall due to the traffic volume. As a result of the sensitivity test for snowfall intensity and cumulative snowfall, the snowfall information at intervals of 6-hours was the most significant.

• Journal of the Korean Geographical Society
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• v.38 no.2
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• pp.173-183
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• 2003

This study aims to understand the patterns of spatial distribution of snowfall by Siberian High in the Honam region in Korea. In the Honam region, Siberian High induces snowfall dominantly. There is a huge amount of snowfall in the westward of the Noryung mountain ranges to the Wert coast in the Honam region affected by northwesterly wind directly from the Siberian High. The westward of the Noryung mountain ranges such as a heavy snowfall region has a various pattern of distribution of snowfall due to topography. The coast region has a large amount of snowfall by sea effect. And, snowfall amount is decreased from the coast to the inland plain. However, in front of mountain, snowfall is increase by reason of a forced ascending air to the mountain. In general the region where frequently appear a cumuliform cloud has a large amount of snowfall. A cumuliform cloud is frequent in the mountainous region in inland, the coast, and the inland plain in order Snowfall is intense in the coast and the mountainous region, and weak in the inland plain. In the mountainous region, a cumuliform cloud induced tv a forced ascending air by reason of topography generates snowfall mostly. This fact is the main difference with snowfall in the mountainous region and the coast region. In the result, in the Honam region, snowfall distribution and snowfall pattern are various, according to geographical climate factor such as sea and topography. The heavy snowfall region in the Honam region is divided into the coast region affected by sea effect and the mountainous region affected by topography effect.

• Journal of the Korean Geographical Society
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• v.41 no.4 s.115
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• pp.457-469
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• 2006

This study aims to understand the characteristics of spatial distribution of snowfall and to analyze its development mechanism in Honam province in Korea. The areas of snowfall in Honan area can be divided into the seven sub-area by snowfall pattern. In the west coastal area of heavy snowfall and the southwest coastal area of heavy snowfall, snowfall develops over reason of ocean by Siberian High while in the northern inland area of heavy snowfall and the southern inland area of heavy snowfall, it develops when a strong Siberian High affects to inland. Then, much snowfall is by a forced ascending due to topography in Namwon, Imsil and Gwangju of the northwestward of the Noryung and Sobaek mountain ranges while it is weak in Jeonju and Suncheon of the low plains and the southeastward. In the mountainous area of heavy snowfall and the south coastal area of light snowfall, cyclone is also one of causes of snowfall. In the southwest coastal area, snowfall is meager than the southwest coastal area of heavy snowfall because this area is far from the west coast. It is confirmed that the snowfall difference of the coast, inland and mountainous area appears by temperature difference of sea surface and 850hPa temperature, wind speed of Siberian High.

• International Journal of Highway Engineering
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• v.14 no.4
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• pp.93-101
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• 2012

PURPOSES : Adverse weather conditions such as heavy rain, heavy snowfall, and thick fog and so on have highly affect on the change in traffic conditions on the road. In particular, heavy snowfall causes capacity reduction as well as crash occurrence. This study investigated the effects of snowfall on speed on a freeway. METHODS : Vehicle detection systems data were matched with corresponding weather station data by regression analysis. RESULTS : The results show that the travel speed is reduced by 6.7% under little snowfall and by 12.8% under heavy snowfall. Regarding the speed variation, 8.7% and 114.7% increases are observed under little snowfall and heavy snowfall, respectively. It is also found that 1 cm increase in snowfall leads to 0.4% decrease in travel speed. In addition, the travel speed increases by 0.4% when the temperature increases by $1^{\circ}C$. CONCLUSIONS : It is expected that the outcome of this study will be useful in establishing more effective strategies for winter operations and road maintenance in practice.

• Journal of the Korean earth science society
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• v.38 no.3
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• pp.182-193
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• 2017

A typical snowfall pattern occurs over the east coastal region of the Korean Peninsula, known as the Yeongdong region. The precipitation over the Yeongdong region is influenced by the cold and dry northeasterly wind which advects over warm and moist sea surface of the East Sea of Korea. This study reveals the influence of large-scale factors, affecting local to remote areas, on the mesoscale snowfall system over the Yeongdong region. The National Centers for Environmental Prediction-Department of Energy reanalysis dataset, Extended Reconstructed sea surface temperature, and observed snowfall data are analyzed to reveal the relationship between February snowfall and large-scale factors from 1981 to 2014. The Yeongdong snowfall is associated with the sea level pressure patterns over the Gaema Plateau and North Pacific near the Bering Sea, which is remotely associated to the sea surface temperature (SST) variability over the North Pacific. It is presented that the relationship between the Yeongdong snowfall and large-scale factors is strengthened after 1999 when the central north Pacific has warm anomalous SST. These enhanced relationships explain the atmospheric patterns of recent strong snowfall years (2010, 2011, and 2014). It is suggested that the newly defined index in this study based on related SST variability can be used for a seasonal predictor of the Yeongdong snowfall with 2-month leading.

• Atmosphere
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• v.14 no.3
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• pp.3-18
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• 2004

A heavy snowfall event occurred over the middle part of the Korean peninsula on March 4, 2004. The numerical models of KMA failed to forecast this heavy snowfall event because this event was due to small scale disturbance by low lever convergence and atmospheric instability. The analyses for this heavy snowfall have been performed to give forecasters useful suggestions for forecasting heavy snowfall events in the future. The analyses for the snowfall event were recounted by the Hourly Korean Peninsula Analysis Weather Chart (HKPAWC) presenting on the KMA intranet system. We confirmed that warm air flows of low level into south central Korea in conjunction with strong southwesterly winds played important role in the heavy snowfall event. We suggested several check points to improve the forecast of heavy snowfall events in the future through the results of the analyses.

• 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 the Korean Society of Hazard Mitigation
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• v.7 no.2 s.25
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• pp.53-63
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• 2007

This study is to evaluate the probable snowfall depth by the point frequency analysis and to draw the map of probable snowfall depth in Korea. The 14 probability distributions which has been widely used in hydrologic frequency analysis are applied to the annual maximum depth of snowfall data. The parameters of each probability distribution are estimated by method of moments, maximum likelihood method and method of probability weighted moments. The estimated parameters were checked by parameter validity conditions of each assumed probability distribution. Four tests that are $X^2-test$, Kolmogorov-Smirnov test, Cramer von Mises test and probability plot correlation coefficient test are used in this study to determine the goodness of fit of the distributions. Mostly the 2-parameter gamma distribution was determined as appropriate distribution for the annual maximum new snowfall depth. The probable snowfall depth were obtained from appropriate distribution for the selected return periods and the maps of probable snowfall depth were presented. It will be useful to specify the snowfall load for the design of agricultural facilities such as vinyl house and cattle shed.

• Atmosphere
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• v.31 no.4
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• pp.433-443
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• 2021

The wind speed and wind direction in Yeongdong are one of the crucial meteorological factors for forecasting snowfall in this area. To improve the snowfall forecast in Yeongdong region, Yeongdong Extreme Snowfall-Windstorm Experiment, YES-WEX was designed. We examined the wind field variation simulated with Local Data Assimilation and Prediction System (LDAPS) using observed wind field during YES-WEX period. The simulated wind speed was overestimated over the East Sea and especially 2 to 4 times in the coastal line. The vertical wind in Yeongdong region, which is a crucial factor in the snowfall forecast, was not well simulated at the low level (850 hPa~1000 hPa) until 12 hours before the forecast. The snowfall distribution was also not accurately simulated. Three hours after the snowfall on the East Sea coast was observed, the snowfall was simulated. To improve the forecast accuracy of snowfall in Yeongdong region, it is important to understand the weather conditions using the observed and simulated data. In the future, data in the northern part of the East Sea and the mountain slope of Taebaek observed from the meteorological aircraft, ship, and drone would help in understanding the snowfall phenomenon and improving forecasts.