• 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.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.99-99
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• 2021

본 연구에서는 기상 자료와 적설 특성 자료의 관계를 도출하고, 이와 추계 일기 생성 모형을 활용하여 합성 적설심 시계열을 모의하는 방법에 대하여 제안한다. 추계 일기 생성 모형에서는 적설량을 직접 모의하지 않기 때문에 강수량을 적설량으로 변환해야한다. 이를 위해 도입한 관계식은 다음과 같다. 첫째로 기상청 적설 예보의 적설 유무 판단 기준을 이용하였다. 이 기준에서는 상대습도와 지상기온에 따라 강수의 형태를 비, 눈, 진눈깨비로 구분한다. 둘째로 강수가 적설로 판단되었을 때 강수량을 신적설심으로 환산하는 수상당량비를 지상기온과 회귀 분석하였다. 선행 연구에 따라 3시간 1 mm 이상 5 mm 이하 강수와 3시간 5 mm 이상 강수 사상에 대하여 나누어 sigmoid형 곡선을 이용하여 회귀 분석하였다. 마지막으로 융설에 의한 적설심 감소량을 지상기온과 복사량의 함수로 표현하였으며, 각 변수의 계수는 입자 군집 최적화 방법을 통하여 보정하였다. 추계 일기 생성 모형으로는 AWE-GEN 모형을 활용하였으며, 시험 자료로 강릉(105) 종관기상관측소의 24년 기간(1982-2005) 자료를 활용하여 합성 적설심 시계열을 생성하였다. 합성 적설심 시계열 모의 과정은 다음과 같다. (1) 추계 일기 생성 모형으로 합성 일기 자료 생성, (2) 강수 발생 시 적설 유무 판단, (3) 적설로 판단 시 수상당량비를 계산하여 신적설심 추정, (4) 기존 적설심에 신적설심을 더하고, 적설심 감소량만큼 감소. 위와 같은 과정으로 200년 길이 합성 적설심 시계열을 모의한 결과 극한 사상을 과소 추정하는 경향이 나타나 추가적인 개선이 필요한 것으로 판단된다.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.80-80
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• 2018

겨울철 대설 현상에 따른 도로 결빙과 항공기 운항 지연, 비닐하우스 및 가건물 붕괴와 같은 피해가 증가함에 따라 대처방안을 마련하는 일이 중요시 되고 있다. 이를 위해 정확한 적설 정보가 근본적으로 필요하지만, 문제는 적설량을 정량적으로 관측하는 일이 간단하지 않다는 점이다. 최근에는 무게식 우량계를 이용한 적설 관측이 수행되고 있지만, 강설량이 많을 경우 우량계가 눈에 덮이는 캐핑(capping) 현상으로 인해 제대로 관측하기 어려운 문제가 있다. 본 연구에서는 무게식 우량계의 이러한 한계를 보완하고 자료의 활용성을 높이기 위해 광학우적계(Parsivel)로 관측된 강설입자정보를 이용하여 적설량을 보정하는 방법을 제안하였다. 무게식 우량계 자료는 대관령 구름물리선도센터에 설치되어 있는 플루비오(Pluvio)의 적설 관측 자료를 이용하였다. 먼저, 관측된 플루비오 자료에서 단위 시간동안의 신적설을 산정한 후 과도한 관측값과 같은 노이즈를 제거하였다. 또한 플루비오와 동일 기간에 관측된 광학우적계 자료에 대해 강설 입자가 $10/m^3$ 초과로 나타나는 사상을 강수 기간으로 결정하고 두 자료가 모두 '0'인 경우 무강수로 나타냈다. 그 결과 강수 입자가 관측된 적설 기간에 플루비오가 우수하게 강설 사상을 관측하고 있음을 확인하였고, 부적합한 자료를 보정할 수 있었다. 이러한 방법으로 적설 자료를 개선할 경우 향후 레이더를 이용한 공간적 강설 추정의 정확도를 크게 개선할 수 있을 것으로 판단된다.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.357-357
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• 2011

폭설은 짧은 시간에 많은 양의 눈이 오는 기상현상으로, 자연재해에 속하며 각종 피해를 유발한다. 우리나라는 주로 산지가 많고 삼면이 바다로 둘러싸인 지형으로 폭설의 발생 및 영향은 국지적으로 차이가 많이난다. 이에 우리나라 폭설의 지역별 위험도를 이해하기 위해서는 체계적인 지역구분과 연구가 필요하다. 본 연구는 우리나라 폭설의 지역별 위험도를 분석하기 위해 지난 39년 겨울철동안(Oct-Apr, 1971-2010) 68개의 지상기상관측소에서 측정한 일별 최심신적설량을 이용하여 우리나라 대설지역을 바탕으로 크게 울릉도, 영동 해안북부(속초와 강릉), 서태백산맥(춘천, 홍천, 양평, 원주 등), 소백산맥북서부(부여, 보은, 대전 등), 남해안 (해남, 완도, 장흥 등)의 폭설지역으로 세분화하였다. 폭설지역을 기상청의 대설특보 기준에 따라 대설주의보(5cm이상)와 대설경보(20cm이상)가 발령됐던 기간으로 빈도분석을 시행하였다. 대설주의보의 발생일수는 총 5,712일로 전체 폭설 발생일의 68%를 차지한다. 이 중 대설경보의 발생일수는 총 1,976일로 전체 폭설 발생일의 23%를 차지한다. 울릉도에서는 대설주의보의 발령일수가 총 602회로 가장 눈이 많은 지역으로 나타났으며, 그 반대로 가장 눈이 적은 지역인 남해안은 3cm이상일 경우에 대설주의보를 발령하며, 이 지역에서의 대설주의보의 발령일수가 지역별 평균 21회였다. 영동북부해안에서는 대설주의보의 발령일수가 지역별 평균 180회, 서태백산맥에서의 대설주의보 발령일수가 지역별 평균 87회, 소백산맥북서부에서의 대설주의보 발령 일수가 지역별 평균 122회로 우리나라의 폭설지역에 속하는 것으로 나타났다. 각 관측소의 39년 겨울철 최심 신적설량을 대설주의보와 대설경보의 빈도수에 따른 지역별 위험 지역을 IDW (Inverse Distance Weighting) 기법을 이용하여 공간 분포도를 작성하였다. 본 연구의 결과는 폭설 위험 지역의 지역별 빈도 분석 결과를 위험 분포도로 도시화하여 매년 반복적으로 발생하는 폭설로 인한 피해 경감 및 사회 경제적 안정에 기여할 수 있을 것으로 사료된다.

• Proceedings of the Korean Statistical Society Conference
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• 2005.11a
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• pp.101-105
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• 2005

호남지역에 대한 대설특보 예보를 위한 통계모형 개발을 수행하였다. 일 신적설량에 따라 세법주(0: 비발생, 1: 대설주의보, 2: 대설경보)로 구분되는 순서형 자료 형태를 지니고 있다. 두가지 통계 모형(다등급 로지스틱 회귀모형, 신경회로망 모형)을 고려하였으며, 수치모델 출력자료를 이용한 역학-통계모형 기법의 하나인 MOS(model output statistics)를 적용하여 축적된 수치모델 예보자료와 관측치의 관계를 통계모형식으로 추정하여 예측모형을 개발하였다. 군집분석을 사용하여 훈련자료와 검증자료를 구분하였으며, 예보치 생성을 위하여 문턱치를 고려하였다.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.1
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• pp.97-104
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• 2012

In this paper, the GPS precipitable water vapor was retrieved by estimating of GPS signal delay in the troposphere during the progress of heavy snowfall on the Gangwon Province, 2011. For this period, the time series analysis between GPS precipitable water vapor and fresh snow depth was accomplished. The time series and the comparison with the GPS precipitable water vapor and the fresh snow depth indicates that the temporal change of two variations is closely related to the progress of the heavy snowfall. Also, the periodicity of GPS precipitable water vapor using the wavelet transform method was showed a similar cycle of saturated water vapor pressure as the limitation of this study span. The result shows that the decrement of GPS precipitable water vapor was conflicted with the increment of fresh snow depth at two sites, Gangneung and Uljin. The correlation between the GPS precipitable water vapor and the saturated water vapor pressure for the event was showed a positive correlation, compare with the non-heavy snowfall periods.

• Korean Journal of Agricultural and Forest Meteorology
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• v.4 no.4
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• pp.248-253
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• 2002

This study was to provide information about snow falling phenomenon in Korea for 1934 years from BC 6 to 1928 based on the records of old literatures, which are the true record of the Chosun dynasty, records of king Kojong and Soonjong, and some data including history of the Koryo in internet home page of Korea meteorological administration. Key words used in search procedure were totally 20 words such as snow, heavy snow, big snow, snow pellets, snowstorm, avalanche, etc. The searching contents consisted of the time of the first and the last snow, the amount of snow falling, snow damage, the thought about heavy snow phenomenon, and unusual weather conditions related to snow. The earliest record for the first snow was July of the rural calendar in 733 and the latest record for the last snow was June 11 of the lunar calendar. From these records, it could be estimated that there were some snow falling even in summer season. The amount of almost heavy snow ranged from 1.2 m to 1.5 m, but sometimes there were some records about the amount of snow falling higher than 3 meters. It was also found that there were three records about big heavy snow damages. In 1524 and 1525, approximately 100 and 140 peoples in Kyungsung, Hamgyung Province were dead due to heavy snowstorm. It was also recorded that 91 people in Jeiu island were dead in 1670 because of snow damage. Some singular records about snow were also found in old literatures. There was a congratulatory ceremony of new snow when the first snow was falling in the year. There was also a ritual praying for snow when there was no snow in the year. It was also found that there was snow falling with worms and red snow falling.

• Journal of the Korean earth science society
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• v.26 no.5
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• pp.395-403
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• 2005

This study is focused on the relationship between snowfall and the Bowen’s Ratio (sensible heat flux/latent heat flux) through calculation of heat exchange between air and sea for snowfall events in Jeju Island from 1993 to 2003. The four weather stations for this study are located at Jeju, Seoguipo, Seongsanpo and Gosan in Jeju Island. In order to improve the reliability of snowfall forecast, the Bowen’s Ratio for snowfall, which includes influences from the atmosphere such as wind, is compared with the temperature difference between air and sea for snowfall. As a results, in the case for fresh snowfall, the minimum temperature differences between air and sea were 10, 12.3, 11.5, and $14.3^{\circ}C$ at Jeju, Seoguipo, Seongsanpo and Gosan, respectively. The probabilities of fresh snowfall were 26, 29, 13, and $23\%$, respectively, when the temperature differences were higher than the previous values. On the other hand, the minimum Bowen ratios were 0.59, 0.60, 0.65 and 0.65 at Jeju, Seoguipo, Seongsanpo and Gosan, respectively. The probabilities of fresh snowfall were 33, 70, 31 and $58\%$ respectively, when the Bowen ratio is higher than those. The reason for this is because the probability of fresh snowfall with the Bowen ratio was higher than the probability with temperature difference between air and sea. This result occurred because heat exchange by wind increased the probability of snowfall, along with the temperature difference between air and sea, and the Bowen ratio. Therefore, snowfall forecast of Jeju Island is significantly influenced by the sea, whereas forecast with Bowen ratio seems to have higher reliability than that with the temperature difference between air and sea. The data analysis for the ten-year period $(1993\~2002)$ showed that when each fresh snowfall was within 0.0 to 0.9cm, the average Bowen’s ratio was 0.63 to 0.67, and when each fresh snowfall was 1.0 to 4.9 cm, the average Bowen’s ratio was over 0.72. Therefore, fresh snowfall shows a proportional relationship with the Bowen’s ratio during snowfall.

• Journal of the Korean Geographical Society
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• v.43 no.5
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• pp.715-727
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• 2008

This study analyzed changes on the best condition of temperature and relative humidity for making artificial snows in the Yongpyong Ski Resort using data from Daegwallyeong. Depth of snowfall and snowfall days have decrease since 1990s. If the Yongpyong Ski Resort has only to depend on natural snows, it would be difficult to make and maintain ski slope. There are two times of snowmaking during ski seasons: one is the first snowmaking (October-November) for opening ski slopes and the other is the reinforcement of snowmaking (December-March) for maintaining snow quality during the seasons. Days having the best condition for the first snowmaking (daily minimum temperature below $-1^{\circ}C$ and daily average relative humidity 60 to 80 percent) decreased after 1970s. Days having the best condition for the reinforcement of snowmaking also decreased. While temperature changes are more evident than humidity changes for the first snowmaking, humidity changes are more obvious than change of temperature for the reinforcement of snowmaking. In the future climate projection by A1B scenarios, the length of ski seasons projected to decrease a 10 to 40 percent against the period of 1973-2008. The climate condition for the snowmaking projected to be poor, especially the due to increase of temperature.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.4
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• pp.317-324
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• 2015

GNSS was firstly proposed for application in weather forecasting in the mid-1980s. It has continued to demonstrate the practical uses in GNSS meteorology, and other relevant researches are currently being conducted. Precipitable Water Vapor (PWV), calculated based on the GNSS signal delays due to the troposphere of the Earth, represents the amount of the water vapor in the atmosphere, and it is therefore widely used in the analysis of various weather phenomena such as monitoring of weather conditions and climate change detection. In this study we calculated the PWV through the meteorological information from an Automatic Weather Station (AWS) as well as GNSS data processing of a Continuously Operating Reference Station (CORS) in order to analyze the heavy snowfall of the Ulsan area in early 2014. Song’s model was adopted for the weighted mean temperature model (T_m), which is the most important parameter in the calculation of PWV. The study period is a total of 56 days (February 2013 and 2014). The average PWV of February 2014 was determined to be 11.29 mm, which is 11.34% lower than that of the heavy snowfall period. The average PWV of February 2013 was determined to be 10.34 mm, which is 8.41% lower than that of not the heavy snowfall period. In addition, certain meteorological factors obtained from AWS were compared as well, resulting in a very low correlation of 0.29 with the saturated vapor pressure calculated using the empirical formula of Magnus. The behavioral pattern of PWV has a tendency to change depending on the precipitation type, specifically, snow or rain. It was identified that the PWV showed a sudden increase and a subsequent rapid drop about 6.5 hours before precipitation. It can be concluded that the pattern analysis of GNSS PWV is an effective method to analyze the precursor phenomenon of precipitation.