Journal of Environmental Science International (한국환경과학회지)

The Korean Environmental Sciences Society (한국환경과학회)
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The Characteristics of Seasonal Wind Fields around the Pohang Using Cluster Analysis and Detailed Meteorological Model

군집분석과 상세기상모델을 통한 포항지역 계절별 바람장 특성

  • Jeong, Ju-Hee (Division of Earth Environmental System, Pusan National University) ;
  • Oh, In-Bo (Environmental Health Center, University of Ulsan) ;
  • Ko, Dae-Kwun (Research Institute of Industrial Science & Technology) ;
  • Kim, Yoo-Keun (Division of Earth Environmental System, Pusan National University)
  • 정주희 (부산대학교 지구환경시스템학부) ;
  • 오인보 (울산대학교 환경보건센터) ;
  • 고대권 (포항산업과학연구원) ;
  • 김유근 (부산대학교 지구환경시스템학부)
  • Received : 2011.03.15
  • Accepted : 2011.04.22
  • Published : 2011.06.30
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Abstract

The typical characteristics of seasonal winds were studied around the Pohang using two-stage (average linkage then k-means) clustering technique based on u- and v-component wind at 850 hpa from 2004 to 2006 (obtained the Pohang station) and a high-resolution (0.5 km grid for the finest domain) WRF-UCM model along with an up-to-date detailed land use data during the most predominant pattern in each season. The clustering analysis identified statistically distinct wind patterns (7, 4, 5, and 3 clusters) representing each spring, summer, fall, and winter. During the spring, the prevailed pattern (80 days) showed weak upper northwesterly flow and late sea-breeze. Especially at night, land-breeze developed along the shoreline was converged around Yeongil Bay. The representative pattern (92 days) in summer was weak upper southerly flow and intensified sea-breeze combined with sea surface wind. In addition, convergence zone between the large scale background flow and well-developed land-breeze was transported around inland (industrial and residential areas). The predominant wind distribution (94 days) in fall was similar to that of spring showing weak upper-level flow and distinct sea-land breeze circulation. On the other hand, the wind pattern (117 days) of high frequency in winter showed upper northwesterly and surface westerly flows, which was no change in daily wind direction.

Keywords

References

  1. 김유근, 오인보, 강윤희, 황미경, 2007, MM5-CAMx를 이용한 대기오염물질의 재순환현상 모델링: 2004년 6월 수도권 오존오염 사례연구, 한국대기환경학회지, 23(3), 297-310. https://doi.org/10.5572/KOSAE.2007.23.3.297
  2. 박정균, 이동규, 1998, 군집분석에 의한 아시아 동안에서 급격히 발달하는 저기압으 분류와 그 발달기구, 한국기상학회지, 11, 523-547.
  3. 변재영, 최영진, 서범근, 2010, WRF-UCM (Urban Canopy Model)을 이용한 서울 지역의 도시기상 예보 평가, 대기, 20(1), 13-26.
  4. 오인보, 김유근, 황미경, 2005. 수도권지역 오존오염 패턴과 기상학적 특성, 한국대기환경학회지, 21(3), 357-365.
  5. 이순환, 이화운, 김유근, 2002, 복잡지형에서 도시화에 따른 대기오염 확산에 관한 시뮬레이션, 한국대기환경학회지, 18(2), 67-83.
  6. 이화운, 정우식, 김현구, 이순환, 2004, 대기오염 확산 해석을 위한 포항지역 기상장 연구 - 바람장 수치모의, 한국대기환경학회지, 20(1), 1-15.
  7. 이화운, 원혜영, 최현정, 김현구, 2005, 광양만권에서의 자료동화된 대기유동장이 대기오염 물질의 확산장에 미치는 영향에 관한 수치모의, 한국대기환경학회지, 21(2), 169-178.
  8. 정우식, 이화운, 2003, 해풍시작에 영향을 미치는 지형성강풍현상에 대한 수치실험, 한국지구과학회지, 24, 325-336.
  9. 정우식, 이화운, 임헌호, 2007, 바람권역 구분을 통한 부산지역 국지바람 분석 -Part 2: 국지 대기유동장 수치모델을 이용한 상세 바람정보, 한국환경과학회지, 16(1), 103-119. https://doi.org/10.5322/JES.2007.16.1.103
  10. 정종현, 임헌호, 이화운, 장혁상, 손병현, 2008, 포항지역에 대한 바람권역 분석 - Part I : 기상관측자료를 토대로 분석한 성긴 바람권역 분석, 한국환경과학회지, 17(4), 385-396. https://doi.org/10.5322/JES.2008.17.4.385
  11. 최현정, 이화운, 임헌호, 송재활, 2008, 광양만 권역에서의 고농도 오존 사례에 대한 기상 및 대기질 분석, 한국환경과학회지, 17(7), 743-753. https://doi.org/10.5322/JES.2008.17.7.743
  12. 황미경, 김유근, 오인보, 강윤희, 2010, 건물효과를 고려한 연안도시지역 고해상도 기상모델링, 한국대기환경학회지, 26(2), 137-150. https://doi.org/10.5572/KOSAE.2010.26.2.137
  13. 황용식, 김유근, 박종길, 문덕환, 2002, 바람의 강도에 따른 강하먼지와 불용성 성분의 조성특성, 한국환경과학회지, 11(7), 651-662. https://doi.org/10.5322/JES.2002.11.7.651
  14. Ainslie, B., Steyn, D. G., 2007, Spatiotemporal Trends in Episodic Ozone Pollution in the Lower Fraser Valley, British Columbia, in Relation to Mesoscale Atmospheric Circulation Patterns and Emissions, J. Appl. Meteor. Climatol., 46, 1631-1644. https://doi.org/10.1175/JAM2547.1
  15. Cheng, F.-Y., Byun, D., 2008, Application of high resolution land use and land cover data for atmospheric modeling in the Houston-Galveston metropolitan area, Part I: Meteorological simulation results, Atmos. Environ., 42(33), 7795-7811. https://doi.org/10.1016/j.atmosenv.2008.04.055
  16. Davis, R. E., Kalkstein, L. S., 1990, Development of an automated spatial synoptic climatological classification, Int. J. Climatol., 10, 769-794. https://doi.org/10.1002/joc.3370100802
  17. Eder, B. K., Davis, J. M., Bloomfield, P., 1994, An automated classification scheme designed to better elucidate the dependence of ozone on meteorology, J. Appl. Meteorol., 33, 1182-1199. https://doi.org/10.1175/1520-0450(1994)033<1182:AACSDT>2.0.CO;2
  18. Landsberg, H. E., 1981, The urban climate. In International Geophysics Series, 28, Academic Press.
  19. Skamarock, W. C., Klemp, J., Dudhia, J., Gill, D. O., Barker, D. M., Wang, W., Powers, J. G., 2005, A description of the Advanced Research WRF Version 2. NCAR Technical Note, NCAR/TN-468 + STR. Mesoscale and Microscale Meteorology Division, National Center for Atmospheric Research, Boulder, Colorado, USA.

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