DOI QR코드

DOI QR Code

상세 해수면 온도자료의 반영에 따른 국지 기상정 개선에 관한 수치연구

Numerical Study on the Impact of SST Spacial Distribution on Regional Circulation

  • 전원배 (부산대학교 지구환경시스템학부) ;
  • 이화운 (부산대학교 지구환경시스템학부) ;
  • 이순환 (부산대학교 BK21 연안환경시스템사업단) ;
  • 최현정 (부산대학교 지구환경시스템학부) ;
  • 임헌호 (부산대학교 지구환경시스템학부)
  • Jeon, Won-Bae (Division of Earth Environmental System, Pusan National University) ;
  • Lee, Hwa-Woon (Division of Earth Environmental System, Pusan National University) ;
  • Lee, Soon-Hwan (BK21 Coastal Environment System School, Pusan National University) ;
  • Choi, Hyun-Jung (Division of Earth Environmental System, Pusan National University) ;
  • Leem, Heon-Ho (Division of Earth Environmental System, Pusan National University)
  • 발행 : 2009.08.31

초록

Numerical simulations were carried out to understand the effect of Sea Surface Temperature (SST) spatial distribution on regional circulation. A three-dimensional non-hydrostatic atmospheric model RAMS, version 6.0, was applied to examine the impact of SST forcing on regional circulation. New Generation Sea Surface Temperature (NGSST) data were implemented to RAMS to compare the results of modeling with default SST data. Several numerical experiments have been undertaken to evaluate the effect of SST for initialization. First was the case with NGSST data (Case NG), second was the case with RAMS monthly data (Case RM) and third was the case with seasonally averaged RAMS monthly data (Case RS). Case NG showed accurate spatial distributions of SST but, the results of RM and RS were $3{\sim}4^{\circ}C$ lower than buoy observation data. By analyzing practical sea surface conditions, large difference in horizontal temperature and wind field for each run were revealed. Case RM and Case RS showed similar horizontal and vertical distributions of temperature and wind field but, Case NG estimated the intensity of sea breeze weakly and land breeze strongly. These differences were due to the difference of the temperature gradient caused by different spatial distributions of SST. Diurnal variations of temperature and wind speed for Case NG indicated great agreement with the observation data and statistics such as root mean squared error, index of agreement, regression were also better than Case RM and Case RS.

키워드

참고문헌

  1. 김희종, 윤일희, 권병혁(2004) 울릉도에서 구름 유입시 관측한 해양대기경계층의 열수지에 관한 사례연구, 한국지구과학회지, 25(7), 629-636
  2. 안중배, 조익현(1998) 한반도 주변 해수면 온도에 따른 중규모 대기 모형 반응, 한국기상학회지, 34(4), 643-651
  3. 이화운, 원경미, 조인숙 (1999) 대기확산의 수치모의에서 SST 효과, 한국대기환경학회지, 15(6), 767-777
  4. 이화운, 전원배, 이순환, 최현정(2008) 복잡 연안지역의 지표면 자료 상세화에 따른 수치기상장 분석, 한국대기환경학회지, 24(6), 649-661 https://doi.org/10.5572/KOSAE.2008.24.6.649
  5. 장승민, 김성수, 최영찬, 김수강(2006) 제주도 기온과 주변해역 해수면 온도와의 상관관계에 관한 연구, 한국해양환경공학회지, 9(1), 55-62
  6. Burls, N. and C.J.C. Reason (2008) Modelling the sensitivity of coastal winds over the Southern Benguela upwelling system to different SST forcing, Journal of Marine System, 74, 561-584 https://doi.org/10.1016/j.jmarsys.2008.04.009
  7. LaCasse, K.M., M.E. Splitt, S.M. Lazarus, and W.M. Lapenta (2008) The impact of high-resolution sea surface temperatures on the simulated nocturnal Florida marine boundary layer, Monthly Weather Review, 136(4), 1349-1372 https://doi.org/10.1175/2007MWR2167.1
  8. Phadnis, M.J., F.R. Robe, A.M. Klausmann, and J.S. Scire (2003) Importance of the spatial resolution of seasurface-temperature data in meteorological modeling, Thirteenth PSU/NCAR Mesoscale Model User’s Workshop (http://www.mmm.ucar.edu /mm5/workshop/ws03/session2/Phadnis.pdf)
  9. Sakaida, F., S. Takahashi, T. Shimada, Y. Kawai, H. Kawamura, K. Hosoda, and L. Guan (2005) The production of the new generation sea surface temperature (NGSST-O ver.1.0) in Tohoku University, International Geoscience and Remote Sensing Symposium (IGARSS), 4, 2602-2605