DOI QR코드

DOI QR Code

Comparison of the Properties of Yeongdong and Yeongseo Heavy Rain

영동과 영서 호우의 특성 비교

  • Kwon, Tae-Yong (Department of Atmospheric and Environmental Sciences, Gangneung-Wonju National University) ;
  • Kim, Jae-Sik (Department of Atmospheric and Environmental Sciences, Gangneung-Wonju National University) ;
  • Kim, Byung-Gon (Department of Atmospheric and Environmental Sciences, Gangneung-Wonju National University)
  • 권태영 (강릉원주대학교대기환경과학과) ;
  • 김재식 (강릉원주대학교대기환경과학과) ;
  • 김병곤 (강릉원주대학교대기환경과학과)
  • Received : 2012.08.16
  • Accepted : 2013.03.25
  • Published : 2013.09.30

Abstract

Heavy rain over the Gangwon region has distinct characteristics in the temporal and spatial distribution of rainfall, most of which are concentrated on a very short period of time and either part of Yeongdong and Yeongseo regions. According to its regional distribution, heavy rain events over the Gangwon region may be classified into Yeongdong and Yeongseo heavy rain in which rainfalls of more than 110 mm $(6 hrs)^{-1}$ (heavy rain warning) have been observed in at least one of the weather stations over only Yeongdong or Yeongseo region, but over the other region the rainfalls are less than 70 mm $(6 hrs)^{-1}$ (heavy rain advisory). To differentiate between Yeongdong and Yeongseo heavy rain, 9 cases for Yeongdong heavy rain and 8 cases for Yeongseo heavy rain are examined on their synoptic and mesoscale environments using some meteorological parameters and ingredients. In addition, 8 cases are examined in which heavy rain warning or advisory are issued in both Yeongdong and Yeongseo regions. The cases for each heavy rain type have shown largely similar features in some meteorological parameters and ingredients. Based on an ingredient analysis, there are three common and basic ingredients for the three heavy rain types: instability, moisture, and lift. However, it is found that the distinct and important process producing strong upward vertical motions may discriminate among three heavy rain types very well. Yeongdong heavy rain is characterized by strong orographic lifting, Yeongseo heavy rain by high instability (high CAPE), and heavy rain over both regions by strong synoptic-scale ascent (strong 850 hPa Q-Vector convergence, diagnostics for ascent). These ingredients and diagnostics for the ingredients can be used to forecasting the potential for regional heavy rain. And also by knowing which of ingredients is important for each heavy rain type, forecasters can concentrate on only a few ingredients from numerous diagnostic and prognostic products for forecasting heavy rain events.

Keywords

References

  1. 김영철, 김형우, 함숙정, 2000: 한반도 호우의 불안정 분석. 2000년 봄 학술대회 논문집, 29-31.
  2. 김인혜, 권태영, 김덕래, 2012: 영동지역 악기상 사례에 대한 MTSAT 위성 영상의 특징. 대기, 22, 29-45.
  3. 김진석, 유재훈, 2002: 태풍전면에서의 강원도 영동지방 집중호우. 한국기상학회지, 12, 140-143.
  4. 김진철, 박옥란, 허진호, 양진관, 2008: 우리나라에서 발생 하는 집중호우의 주요 호우인자 도출. 2008 년봄학술대회 논문집, 278-279.
  5. 노준우, 2003: 종관 배경에 따른 한반도 집중호우의 분류. 서울대학교 대학원 석사학위논문, 118 pp.
  6. 박기준, 이영곤, 김세원, 2010: 재해기상연구 선진화 방안 연구. 한국기상학회 가을 학술대회 논문집, 356-357.
  7. 이동규, 박정균, 2002: 집중호우 발생 가능성 진단 알고리 즘에 대한 사전 연구. 한국기상학회지, 12, 459-462.
  8. 이재규, 김유진, 2008: 북동 기류와 관련된 영동해안 지역의 대설 사례에 대한 WRF 수치모의 연구. 대기, 18, 339-354.
  9. 이재규, 권태영, 정일웅, 김병곤, 2011: 강원지역 재해기상 요소의 상세분석 기법 개발 I. 국립기상연구소, 재해 기상연구센터, 802 pp.
  10. 이재병, 2001: 전남 서부남해안 지방 집중호우의 종관적 예측방법. 한국기상학회지, 11, 129-131.
  11. 이재병, 김종찬, 이재용, 2004: 호남지방 호우의 국지특성과 중규모적 예측방법 연구. 한국기상학회 2004년도 봄철 학술발표회, 154-155.
  12. 임병환, 정영선, 박승균, 김성진, 이정환, 정준석, 김남욱, 이현, 정순갑, 2002: 기상청 기상분석시스템 개발. 한국기상학회지, 12, 586-588.
  13. 전계학, 2011: 태풍의 온대저기압 변질 후 발생하는 집중 호우. 예보기술발표회 초록집, 32-33.
  14. 정광범. 김지언. 권태영. 2004: 영동지역 겨울철 강수와 관련된 하층 바람의 특성. 한국기상학회지. 40. 369-380.
  15. 정일웅, 김병곤, 손철, 안명환, 이규태, 이시영, 이재규, 2007: 강원지역 국지 특이 기상연구소 (가칭) 설립에 관한 기획연구. 기상청, 155 pp.
  16. 조구희, 조영준, 권태영, 2004: 겨울철 영동지역 강수 사례와 관련된 기단의 특성. 한국기상학회지, 40, 381-393.
  17. 조서환, 안기창, 박승균, 박윤호, 2002: 호우 가능성점검표 자동작성 및 활용성 고찰. 한국기상학회지, 12, 388-390.
  18. Doswell, C. A., III, 1987: The distinction between large-scale and mesoscale contribution to severe convec-tion: A case study example. Wea. Forecasting, 2, 3-16. https://doi.org/10.1175/1520-0434(1987)002<0003:TDBLSA>2.0.CO;2
  19. Doswell, C. A., III,, H. E. Brooks, and R. A. Maddox, 1996: Flash flood forecasting: An ingredients-based methodol-ogy. Wea. Forecasting, 11, 560-581. https://doi.org/10.1175/1520-0434(1996)011<0560:FFFAIB>2.0.CO;2
  20. Kirkpatrick, C., E. W. McCaul, Jr., and C. Cohen, 2007: The motion of simulated convective storms as a func-tion of basic environmental parameters. Mon. Wea. Rev., 135, 3033-3051. https://doi.org/10.1175/MWR3447.1
  21. Kirkpatrick, C., 2011: Sensitivity of simulated convective storms to environmental CAPE. Mon. Wea. Rev., 139, 3514-3532. https://doi.org/10.1175/2011MWR3631.1
  22. Konrad, C.-E., 1997: Synoptic-scale features associated with warm season heavy rainfall over the interior southeastern united states. Wea. Forecasting, 12, 557-571. https://doi.org/10.1175/1520-0434(1997)012<0557:SSFAWW>2.0.CO;2
  23. Lin, Y.-L., S. Chiao, T.-A. Wang, M. L. Kaplan, and R. P. Weglarz, 2001: Some common Ingredients for heavy orographic rainfall. Wea. Forecasting, 16, 633-660. https://doi.org/10.1175/1520-0434(2001)016<0633:SCIFHO>2.0.CO;2
  24. Maddox, R. A., C. F. Chappell, and L. R. Hoxit, 1979: Synoptic and meso-$\alpha$ scale aspects of flash flood events. Bull. Amer. Meteor. Soc., 60, 115-123. https://doi.org/10.1175/1520-0477-60.2.115
  25. McNulty, R. P., 1995: Severe and convective weather: A Central Region forecasting challenge. Wea. Forecast-ing, 10, 187-202. https://doi.org/10.1175/1520-0434(1995)010<0187:SACWAC>2.0.CO;2
  26. Schultz, D. M., and P. N. Schumacher, 1999: The use and misuse of conditional symmetric instability. Mon. Wea. Rev., 127, 2709-2732. https://doi.org/10.1175/1520-0493(1999)127<2709:TUAMOC>2.0.CO;2
  27. Thompson, R. L., R. Edwards, J. A. Hart, K. L. Elmore, and P. Markowski, 2003: Close proximity soundings within supercell environments obtained from the rapid update cycle. Wea. Forecasting, 18, 1243-1261. https://doi.org/10.1175/1520-0434(2003)018<1243:CPSWSE>2.0.CO;2
  28. Weisman, M. L., and J. B. Klemp, 1982: The dependence of numerically simulated $\alpha$ onvective storms on verti-cal wind shear and buoyancy. Mon. Wea. Rev., 110, 504-520. https://doi.org/10.1175/1520-0493(1982)110<0504:TDONSC>2.0.CO;2
  29. Wetzel, S. W., and J. E. Martin, 2001: An operational ingredients based methodology for forecasting mid-latitude winter season precipitation. Wea. Forecast­ing, 16, 156-167. https://doi.org/10.1175/1520-0434(2001)016<0156:AOIBMF>2.0.CO;2
  30. Woodcock, F., 1980: On the Use of Analogues to improve regression forecasts. Mon. Wea. Rev., 108, 292-297. https://doi.org/10.1175/1520-0493(1980)108<0292:OTUOAT>2.0.CO;2

Cited by

  1. Classification of Atmospheric Vertical Environment Associated with Heavy Rainfall using Long-Term Radiosonde Observational Data, 1997~2013 vol.25, pp.4, 2015, https://doi.org/10.14191/Atmos.2015.25.4.611
  2. Thermodynamic Characteristics Associated with Localized Torrential Rainfall Events in the Middle West Region of Korean Peninsula vol.24, pp.4, 2014, https://doi.org/10.14191/Atmos.2014.24.4.457
  3. Thermodynamic characteristics associated with localized torrential rainfall events in the southwest region of the Korean peninsula vol.51, pp.3, 2015, https://doi.org/10.1007/s13143-015-0073-6
  4. Studies on the Predictability of Heavy Rainfall Using Prognostic Variables in Numerical Model vol.26, pp.4, 2016, https://doi.org/10.14191/Atmos.2016.26.4.495
  5. Characteristics Analysis of Snow Particle Size Distribution in Gangwon Region according to Topography vol.40, pp.3, 2019, https://doi.org/10.5467/JKESS.2019.40.3.227
  6. Characteristics of Sea Surface Temperature Variation during the High Impact Weather over the Korean Peninsula vol.40, pp.3, 2019, https://doi.org/10.5467/JKESS.2019.40.3.240