Journal of Environmental Science International (한국환경과학회지)

The Korean Environmental Sciences Society (한국환경과학회)
권호 표지
DOI QR코드

DOI QR Code

A RAMS Atmospheric Field I Predicted by an Improved Initial Input Dataset - An Application of NOAA SST data -

초기 입력 자료의 개선에 의한 RAMS 기상장의 예측 I - NOAA SST자료의 적용 -

  • Won, Gyeong-Mee (Division of Earth Environmental System, Pusan National University) ;
  • Jeong, Gi-Ho (Department of Chemistry, Pusan National University) ;
  • Lee, Hwa-Woon (Division of Earth Environmental System, Pusan National University) ;
  • Jung, Woo-Sik (Department of Atmospheric Environment Information Engineering, Inje University) ;
  • Lee, Kang-Yoel (Korea Environment Institute)
  • 원경미 (부산대학교 지구환경시스템학부 대기환경과학) ;
  • 정기호 (부산대학교 물리화학부 화학) ;
  • 이화운 (부산대학교 지구환경시스템학부 대기환경과학) ;
  • 정우식 (인제대학교 대기환경정보공학과) ;
  • 이강열 (한국환경정책평가연구원)
  • Published : 2009.05.31
Download PDF
⟨ Previous Next ⟩

Abstract

In an effort to examine the Regional Atmospheric Modeling System (RAMS ver. 4.3) to the initial meteorological input data, detailed observational data of NOAA satellite SST (Sea Surface Temperature) was employed. The NOAA satellite SST which is currently provided daily as a seven-day mean value with resolution of 0.1 $^{\circ}$ grid spacing was used instead of the climatologically derived monthly mean SST using in RAMS. In addition, the RAMS SST data must be changed new one because it was constructed in 1993. For more realistic initial meteorological fields, the NOAA satellite SST was incorporated into the RAMS-preprocess package named ISentropic Analysis package (ISAN). When the NOAA SST data was imposed to the initial condition of prognostic RAMS model, the resultant performance of near surface atmospheric fields was discussed and compared with that of default option of SST. We got the good results that the new SST data was made in a standard RAMS format and showed the detailed variation of SST. As the modeling grid became smaller, the SST differences of the NOAA SST run and the RAMS SST43 (default) run in diurnal variation were very minor but this research can apply to further study for the realistic SST situation and the development in predicting regional atmospheric field which imply the regional circulation due to differential surface heating between sea and land or climatological phenomenon.

Keywords

References

  1. 기상청 , 2006, 기상업무발전 기본계획 2007년 - 2011년, 7pp.
  2. 이미선, 서애숙, 이충기, 1996, NOAA/AVHRR 자료응용기법 연구 - 운정, 지표온도, 반사도, 해수면 온도, 식생지수, 산불, 홍수 분석-, 한국원격탐사학회지, 12(1), 60-80
  3. Clark T. L., Farely R. D., 1984, Severe downslope windstorm calculations in two and three spatial dimensions using anelastic interactive grid nesting: A possible mechanism for gustiness, J. Atmos. Sci., 41, 329-350 https://doi.org/10.1175/1520-0469(1984)041<0329:SDWCIT>2.0.CO;2
  4. Pielke R. A., 1974, A three dimensional numerical model of the sea breeze over south Florida, Mon. Weath. Rev., 102, 115-139 https://doi.org/10.1175/1520-0493(1974)102<0115:ATDNMO>2.0.CO;2
  5. Tripoli G. J., Cotton W. R., 1986, An intense, quasi-steady thunderstorm over mountainous terrain Part IV: Three dimensional numerical simulation, J. Atmos. Sci., 43, 896-914 https://doi.org/10.1175/1520-0469(1986)043<0894:AIQSTO>2.0.CO;2
  6. Tremback C. J., Kessler R., 1985, A surface temperature and moisture parameterization for use in mesoscale numerical models, 7th AMS Conference on Numerical Weather Prediction, June 17-20, Montreal, Quebec, Canada, Amer. Meteor. Soc., Boston, 355-358
  7. Pielke R. A., Cotton W. R., Walko R. L., Tremback C. J., Lyons W. A., 1992, A Comprehensive meteorological modeling system - RAMS, Meteor. Atmos. Phys., 49, 69-91 https://doi.org/10.1007/BF01025401
  8. Qian M. W., Giraud C., 2000, A preliminary Numerical Simulation of Bora wind with a Limited Area Model of Atmospheric Circulation, Il Nuovo Cimento, 23C, 5, 515-523
  9. Walko R. L., Tremback C. J., Pielke R. A., Cotton W. R., 1995, An interactive nesting algorithm for stretched grids and variable nesting ratios, J. Appl. Meteor., 34, 994-999 https://doi.org/10.1175/1520-0450(1995)034<0994:AINAFS>2.0.CO;2
  10. ATMET, 2002, RAMS Technical description, RAMS Technical Manual at Atmospheric Meteorological and Environmental Technology site (http://www.atmet.com)
  11. Wang W., Warner T. T., 1988, Use of four-dimensional data assimilation by Newtonian relaxation and latent-heat forcing to improve a mesoscale-model precipitation forecast: A case study, Mon. Wea. Rev., 116, 2593-2613 https://doi.org/10.1175/1520-0493(1988)116<2593:UOFDDA>2.0.CO;2
  12. Lewis J., Derber J., 1985, The use of adjoint equations to solve a variational adjustment problem with advective constraints, Tellus, 37A, 309-322 https://doi.org/10.1111/j.1600-0870.1985.tb00430.x
  13. Copeland J. H., Pielke R. A., Cotton W. R., 1991, The effect of four-dimensional data density on assimilation for a shallow-water model with the adjoint method: Preliminary results, Proceedings, Ninth AMS Conference on Numerical Weather Prediction, October 14-18, Denver, Colorado, Amer. Meteor. Soc., Boston, 183-185
  14. 김철희, 나진균, 박철진, 박진호, 임차순, 윤이, 김민섭, 박춘화, 김용준, 2003, 유해화학물질 대기확산 예측을 위한 RAMS 기상모델의 적용 및 평가, 한국대기환경학회지, 19(5), 595-610
  15. Bjerkness J., 1969, Atmospheric teleconnections from the equatorial Pacific., Mon. Wea. Rev., 97, 163-172 https://doi.org/10.1175/1520-0493(1969)097<0163:ATFTEP>2.3.CO;2
  16. Tremback C. J., 1990, Numerical simulation of a mesoscale convective complex: model development and numerical results, Ph.D. dissertation, Atmos. Sci. Paper No 465, Department of Atmospheric Sciences, Colorado State University, Fort Collins, CO 80523
  17. Mahrer Y., Pielke R. A., 1977, A numerical study of the airflow over irregular terrain, Beitrage Zur Physik der Atmosphare, 50, 98-113