영동 지역 한기 축적과 강설의 연관성 분석
- 발행기관 강릉원주대학교 일반대학원
- 발행년도 2020
- 학위수여년월 2021. 2
- 학위명 석사
- 학과 및 전공 도움말 일반대학원 대기환경과학과
- 실제URI http://www.dcollection.net/handler/kangnung/000000010850
- UCI I804:42001-000000010850
- 본문언어 한국어
초록/요약 도움말
영동지역은 겨울철 강설에 의한 재해가 자주 발생하는데, 대설 사례는 강설 예측의 정확도가 상대적으로 높아서 적절한 대비가 가능하지만 약한 강설의 경우는 강설 예측 정확도가 낮은 실정이다. 본 연구에서는 강설 예보 정확도를 떨어뜨리는 여러 요인들 중 하나인 한기 축적 현상(Cold Air Damming: CAD)과 강설의 연관성에 대하여 분석하였다. 영동지역에서 한기 축적 현상은 북풍내지 북동풍 계열의 바람이 태백 산맥의 저지효과로 인하여 산맥과 평행하게 바람이 불면서 (barrier jet) 산맥의 동쪽 산사면에 한기가 쌓이게 되는 현상을 의미한다. 본 연구에서는 영동지역에서의 한기 축적 현상을 중규모적인 관점에서 해석하기 위해 2019년과 2020년에 강릉원주대학교, 강원지방기상청, 국립기상과학원 등에서 공동으로 시행한 공동입체관측 자료를 이용하였다. 주로 사용한 관측 자료는 강릉, 속초, 동해상에서의 레윈존데 관측 자료이며, 각 지점에서 동일 시간대에 관측한 자료를 이용하였다. 분석결과 총 3가지의 한기 축적 사례를 선정할 수 있었으며, 2개의 강한 한기 축적사례와 1개의 약한 한기 축적 사례로 구분 지을 수 있었다. 강한 한기 축적 사례는 2019년 2월 14일과 2020년 2월 6일 사례가 해당된다. 이 사례는 지난 강설집중관측캠페인 기간 전체 사운딩 자료와 비교하였을 떼. 약 2km 이내의 하층 온도가 가장 낮은 범위에 해당하는 것을 볼 수 있었고, 역전층이 강하게 발달(△T>2.0℃, △Z>700m)하였다. 그리고, 연직 바람 구조는 약 1.5km 이하에서는 서풍 계열이 강하게 발달하였고, 약 1-2km 사이에서는 동풍 계열이 약하게 발달하는 것을 확인할 수 있었다. 약한 한기 축적 사례는 2020년 2월 8일 사례로 하층이 온도가 낮기는 하지만, 강한 한기 축적 사례에 비해서 상대적으로 온도가 2-3℃ 높은 경향이 있었다. 역전층은 상대적으로 약하게 발달(△T>1.5℃, △Z>300m) 하였으며, 연직 바람의 구조에서는 시간에 따른 변동성이 크게 나타나는 것을 확인할 수 있었다. 추가로, LDAPS 자료를 활용한 바람과 기온의 연직 및 수평 분포를 분석하였다. 강한 한기 축적 사례들은 태백산맥 동쪽의 산사면에 한기가 쌓여 있는 것이 확연하게 나타났으며, 한 기 축적 층에서는 서풍계열 바람이불고, 동해상에서 불어오는 바람과 해안선 부근 동해상에서 수렴대가 형성되는것을 확인할 수 있었다. 약한 한기 축적 사례의 경우는 상대적으로 한기 축적이 뚜렷하지 않았다. 영동지역 입체공동관측을 통하여 한기 축적 현상을 시공간적 분포 특성과 한기 축적 발생시의 눈구름과 강설 위치가 영동내륙으로 진입하지 못하고 해안가나 동해상에 제한되는 것을 확인할 수 있었다. 향후 지속적인 집중관측과 모델링을 활용하여 한기 축적이 강설의 위치나 강설량에 미치는 영향에 대한 추가 분석이 필요하다. 주제어 : 한기 축적 현상, 강설, 레윈 존데, 영동지역, LDAPS
more초록/요약 도움말
The Yeongdong region has frequently suffered from heavy snowfall in winter. The performance of weak snowfall forecast is relatively poor whereas that is quite good enough to prepare for the heavy snowfall, since the first is very conducive to synoptic and mesoscale interactions, but the latter is largely dictated by large scale synoptic forcing. Cold Air Damming (CAD), one of the dominant causes in lowering the skill score of snowfall forecast, is examined using the intensive observation of snowfall in cooperation with Gangwon Regional Meteorological Office and National Institute of Meteorological Studies. The intensive observation has been made in 2019 to 2020 winter seasons. The rawinsonde observation and LDAPS data are mainly used for the understanding of thermodynamic characteristics of CAD at Gangneung, Sokcho, and East Sea. We have three CAD events for two years; the first two (February 14, 2019 and February 6, 2020) are strong ones and the last (February 8, 2020) is weak. For the strong CAD events, the temperature below 2 km belongs to the lowest range in comparisons th that of the previous 5-years (2014 – 2019) observation, with the stronger inversion strength (△T>2.0℃) and thicker depth (△Z>700m). Further, the northwesterly was predominant below 1.5 km, whereas the weak easterly wind was exhibited above the CAD layer. Meanwhile, the weak CAD (February 8, 2002), it was relatively warmer than strong CADs, with weaker inversion strength (△T>1.5℃) and shallow depth (△Z>300m). In addition, the northeasterly was more and deeply developed above the shallow northwesterly CAD layer. We found snowfall tends of be strongly affected by CAD such that snow cloud and convergence zone could not penentrate in Yeongdong inland and retreat to East Sea against strong cold air accumulation along the easter side of Taeback Mountains. We need to inverstigate the influence of CAD on snowfall in the Yeongdong region using continuous intensive observation and modeling studies. In addition, the effect of synoptic and mesoscale interactions such as nighttime drainage wind and land breeze on snowfall should be investigated. Key words : Cold Air Damming(CAD), Snowfall, Rawinsonde, Yeongdong region, LDAPS
more목차 도움말
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2.1. 관측 지점 및 자료 ··················································································· 3
2.2. 한기 축적 사례 분류방법 ··········································································· 6
제 3 장. 연구결과 ········································································································ 10
3.1 사례분석 ········································································································ 15
3.1.1 2019년 2월 13~14일 강한 한기 축적 사례 ··································· 15
3.1.2 2020년 2월 6일 강한 한기 축적 사례 ··········································· 19
3.1.3 2020년 2월 8일 약한 한기 축적 사례 ··········································· 23
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