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Korean Meteorological Society (한국기상학회)
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An Analysis of Observed and Simulated Wind in the Snowfall Event in Yeongdong Region on 8 February 2020

2020년 2월 8일 영동지역 강설 사례 시 관측과 수치모의 된 바람 분석

  • Kim, Hae-Min (High Impact Weather Research Department, National Institute of Meteorological Sciences, KMA) ;
  • Nam, Hyoung-Gu (High Impact Weather Research Department, National Institute of Meteorological Sciences, KMA) ;
  • Kim, Baek-Jo (High Impact Weather Research Department, National Institute of Meteorological Sciences, KMA) ;
  • Jee, Joon-Bum (Rearch Center for Atmospheric Environment, Hankuk University of Foreign Studies)
  • 김해민 (국립기상과학원 재해기상연구부) ;
  • 남형구 (국립기상과학원 재해기상연구부) ;
  • 김백조 (국립기상과학원 재해기상연구부) ;
  • 지준범 (한국외국어대학교 대기환경연구센터)
  • Received : 2021.05.05
  • Accepted : 2021.08.06
  • Published : 2021.11.30
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Abstract

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.

Keywords

Acknowledgement

이 연구는 기상청 국립기상과학원 「재해기상 감시·분석·예측기술 지원 및 활용연구」 (KMA2018-00123)의 지원으로 수행되었습니다.

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