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

상세 해수면 온도자료의 반영에 따른 국지 기상정 개선에 관한 수치연구

  • 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)
  • 전원배 (부산대학교 지구환경시스템학부) ;
  • 이화운 (부산대학교 지구환경시스템학부) ;
  • 이순환 (부산대학교 BK21 연안환경시스템사업단) ;
  • 최현정 (부산대학교 지구환경시스템학부) ;
  • 임헌호 (부산대학교 지구환경시스템학부)
  • Published : 2009.08.31

Abstract

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.

Keywords

References

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