• 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 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.

• 한국지구과학회:학술대회논문집
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• 2010.04a
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• pp.74-76
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• 2010

영동지방은 서쪽으로는 태백산맥이 남북으로 위치해 있고 동쪽으로 동해와 인접해 있는 지리적인 위치로 전 계절에 걸쳐 지역 특성에 따른 국지적인 기상 현상이 많이 발생하고 있다. 특히, 대설은 영동지방의 기후 특징 중 대표적이라 할 수 있다. 대설 일수가 많고 강설량이 많은 영동지방의 강릉과 속초, 그리고 울릉도는 연 강수량에서 겨울철(12월~2월) 강수량이 각각 약 10%와 20% 이상을 차지하고 있는데 이는 우리나라 다른 지역의 5% 내외에 비하면 매우 높은 것이다. 이 지역의 강설 특징은 좁은 지리적 범위에 국한되어 나타나는 좁고 강한 강수역과 지역적으로 커다란 변화를 보이는 적설량과 강설 일수이다. 해안선으로부터 산맥의 분수계까지의 거리가 중요한 역할을 하고 있으며, 이러한 복잡한 지역에서의 강설의 발생과 강설량의 분포를 이해하기 위해서는 강설의 패턴을 분류하여 연구하는 것이 매우 중요하다. 본 연구에서는 cP 확장 시 영동지방의 강설 패턴을 하층 대류권의 바람장에 따라 산악 강설 패턴, 한기-해안 강설 패턴, 난기-해안 강설 패턴으로 분류하였다. 또한, 각 강설 패턴에 대한 종관적인 대기구조의 특성을 파악한 후 3차원 분석시스템을 이용하여, 2008년 12월 21일부터 22일까지 영동지방에 내린 대설을 한기-해안 강설 패턴으로 분류하고 분석하였다.

• Journal of the Society of Disaster Information
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• v.14 no.2
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• pp.154-164
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• 2018

Purpose: Recent climate change makes weather-related disasters such as summer storms, heavy rains, winter snowfall disasters, and extreme cold temperature increase in trend. Heavy snowfall disasters requires speedy response due to various effects to traffic flows, buildings, and infrastructure. Heavy snowfall disaster response of South Korea is insufficient, even though heavy snowfall disasters affect urban safety. There have been lack of policy studies for heavy snowfall disasters. Method: This research analyzes case studies and explores implications using Information system technologies to snow removal vehicles and equipments for speedy snow removal during the heavy snowfall disasters. Results: Information system technology attachment to snow removal equipments can identify locations of snow removal vehicles and equipments for emergency period to support snow removal of adjacent jurisdictions. Conclusion: Case studies of this research can be further used for efficient application of snow removal tools of local governments.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.37 no.1
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• pp.61-72
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• 2017

Due to the climate change, damages of human life and property caused by natural disaster have recently been increasing consistently. In South Korea, total damage by natural disasters over 20 years from 1994 to 2013 is about 1.0 million dollars. The 13% of total damage caused by heavy snow. This is smaller amount than the damage by heavy rainfall or typhoon, but still could cause severe damage in the society. In this study, the snow damage in Gangwon region was estimated using climate variables (daily maximum snow depth, relative humidity, minimum temperature) and scoio-economic variables (Farm population density, GRDP). Multiple regression analysis with enter method was applied to estimate snow damage. As the results, adjusted R-square is above 0.7 in some sub-regions and shows the good applicability although the extreme values are not predicted well. The developed model might be applied for the prompt disaster response.

• Journal of Wetlands Research
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• v.21 no.2
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• pp.157-162
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• 2019

Recently, the occurrence of unusual heavy snow and cold are increasing due to the unusual global climate change. In particular, the temperature dropped to minus 69 degrees Celsius in the United States on January 8, 2018. In Korea, on February 17, 2014, the auditorium building in Gyeongju Mauna Resort was collapsed due to the heavy snowfall. Because of the tragic accident many studies on the reduction of snow damage is being conducted, but it is difficult to predict the exact damage due to the lack of historical damage data, and uncertainty of meteorological data due to the long distance between the damaged area and the observatory. Therefore, in this study, available data were collected from factors that are thought to be corresponding to snow damage, and the amount of snow damage was estimated categorically using a random forest. At present, the prediction accuracy was not sufficient due to lack of historical damage data and changes of the design code for green houses. However, if accurate weather data are obtained in the affected areas. the accuracy of estimates would increase enough for being used for be the degree preparedness of disaster management.

• Journal of the Korean earth science society
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• v.40 no.3
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• pp.240-258
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• 2019

Typhoons, torrential rainfall, and heavy snowfall cause catastrophic losses each year in the Republic of Korea. Therefore, if we can know the possibility of this phenomenon in advance through regular observations, it will be greatly beneficial to Korean society. Korea is surrounded by sea on its three sides, and the sea surface temperature (SST) directly or indirectly affects the development of typhoons, heavy rainfall, and heavy snowfall. Therefore, the characteristics of SST variability related to the high impact weather are investigated in this paper. The heavy rainfall in Korea was distributed around Seoul, Gyeonggi, and west and southern coast. The heavy snowfall occurred mainly in the eastern coastal (hereafter Youngdong Heavy Snow) and the southwestern region (hereafter Honam-type heavy snow). The SST variability was slightly different depending on the type and major occurrence regions of the high impact weather. When the torrential rain occurred, the SST variability was significantly increased in the regions extending to Jindo-Jeju island-Ieodo-Shanghai in China. When the heavy snow occurred, the SST variability has reduced in the southern sea of Jeju island, regardless of the type of heavy snowfall, whereas the SST variability has increased in the East Sea near $130^{\circ}E$ and $39^{\circ}N$. Areas with high SST variability are anticipated to be used as a basis for studying the atmospheric-oceanic interaction mechanism as well as for determining the background atmospheric aerosol observation area.

• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.2
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• pp.92-101
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• 2020

To prevent and mitigate damage to farms due to heavy snowfall, snow weight information should be provided in addition to snow depth. This study reviews four formulae regarding snow density and weight used in extant studies and applies them in Suwon area to estimate snow weight in Korea. We investigated the observed snow depth of 94 meteorological stations and automatic weather stations (AWS) data over the past 30 years (1988-2017). Based on the spatial distribution of snow depth by area in Korea, much of the fresh snow cover, due to heavy snowfall, occurred in Jeollabuk-do and Gangwon-do. Record snowfalls occurred in Gyeongsangbuk-do and Gangwon-do. However, the most recent heavy snowfall in winter occurred in Gyeonggi-do, Gyeongsangbuk-do, and Jeollanam-do. This implies that even if the snow depth is high, there is no significant damage unless the snow weight is high. The estimation of snow weight in Suwon area yielded different results based on the calculation method of snow density. In general, high snow depth is associated with heavy snow weight. However, maximum snow weight and maximum snow depth do not necessarily occur on the same day. The result of this study can be utilized to estimate the snow weight at other locations in Korea and to carry out snow weight prediction based on a numerical model. Snow weight information is expected to aid in establishing standards for greenhouse design and to reduce the economic losses incurred by farms.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.21 no.4
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• pp.106-111
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• 2013

The heavy snow event occurred on JAN 4, 2010 brought huge disaster such as Gimpo International Airport runway closed, heavy delays of other airport, and property damage of 16 billion won. Though this heavy snow event is involved in the general synoptic scale heavy snow forecast, it recorded too much snow amount and longer duration than expected. To explain this unusual event, we used the conveyor belt theory. By combining the synoptic scale heavy snow forecast and the conveyor belt theory, the characteristics of heavy snow event was well explained.

• Journal of the Korean earth science society
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• v.21 no.3
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• pp.258-275
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• 2000

The purpose of this study is to investigate diurnal variations of snowstorm occurred along the East Coast of the Korean Peninsula. The snowstorm which occurred on 5${\sim}$7 January 1997 have been analyzed. The pressure patterns were analyzed through surface and upper-air chart(850hPa). Diurnal variations of four areas, i. e. Youngdong, Mt. Taebaek, Youngseo and Kyungbuk regions were analyzed through wind direction and speed, cloud amounts, surface temperature, dewpoint temperature, relative humidity and sea level pressure. And snowfall amounts over four areas were analyzed through regional distribution, daily and temporal variations. The snowfall which occurred on January 5 was caused by the weak low pressure which is located in Kyusu region of Japan. The snowfall of January 6 occurred due to the Siberian high's expansion and instability. And northeasterly wind is one factor of the snowstorm which occurred in Mt. Taebaek region on 7 January. Heavy snowfall was caused by westerly wind but easterly wind occurred weak snowfall in Youngdong area. The precipitation of Kyungbuk region(eapecially, Pohang) was less than that of Youngdong region because the air mass which was not modified had influence on Kyungbuk region on 6${\sim}$7 January, 1997.