대기 (Atmosphere)

  • 제21권1호
  • /
  • Pages.85-93
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  • 2011
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  • 1598-3560(pISSN)
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  • 2288-3266(eISSN)
한국기상학회 (Korean Meteorological Society)
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위성자료가 기상청 전지구 통합 분석 예측 시스템에 미치는 효과

The Impact of Satellite Observations on the UM-4DVar Analysis and Prediction System at KMA

  • 이주원 (국립기상연구소 예보연구과) ;
  • 이승우 (국립기상연구소 응용기상연구과) ;
  • 한상옥 (국립기상연구소 예보연구과) ;
  • 이승재 (국립기상연구소 예보연구과) ;
  • 장동언 (국립기상연구소 예보연구과)
  • Lee, Juwon (Forecast Research Laboratory, National Institute of Meteorological Research) ;
  • Lee, Seung-Woo (Applied Meteorological Research Laboratory, National Institute of Meteorological Research) ;
  • Han, Sang-Ok (Forecast Research Laboratory, National Institute of Meteorological Research) ;
  • Lee, Seung-Jae (Forecast Research Laboratory, National Institute of Meteorological Research) ;
  • Jang, Dong-Eon (Forecast Research Laboratory, National Institute of Meteorological Research)
  • 투고 : 2011.01.07
  • 심사 : 2011.02.17
  • 발행 : 2011.03.30
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초록

UK Met Office Unified Model (UM) is a grid model applicable for both global and regional model configurations. The Met Office has developed a 4D-Var data assimilation system, which was implemented in the global forecast system on 5 October 2004. In an effort to improve its Numerical Weather Prediction (NWP) system, Korea Meteorological Administration (KMA) has adopted the UM system since 2008. The aim of this study is to provide the basic information on the effects of satellite data assimilation on UM performance by conducting global satellite data denial experiments. Advanced Tiros Operational Vertical Sounder (ATOVS), Infrared Atmospheric Sounding Interferometer (IASI), Special Sensor Microwave Imager Sounder (SSMIS) data, Global Positioning System Radio Occultation (GPSRO) data, Air Craft (CRAFT) data, Atmospheric Infrared Sounder (AIRS) data were assimilated in the UM global system. The contributions of assimilation of each kind of satellite data to improvements in UM performance were evaluated using analysis data of basic variables; geopotential height at 500 hPa, wind speed and temperature at 850 hPa and mean sea level pressure. The statistical verification using Root Mean Square Error (RMSE) showed that most of the satellite data have positive impacts on UM global analysis and forecasts.

키워드

참고문헌

  1. 박옥란, 김용상, 조천호, 2005: 해남 윈드프로파일러와 오토존데 자료를 이용한 관측시스템 연구, 한국기상학회, 41, 57-71.
  2. 이미선, 임은하, 조주영, 이천우, 2002: 기상청 지역예보시스템에서 자료동화과정의 개선. 한국기상학회, 12, 148-151.
  3. 장동언, 장태규, 이용희, 조천호, 안명환, 2005: 단시간 수치 예보를 위한 ATOVS 산출 온도 자료의 활용, 한국기상학회, 41, 599-613.
  4. 황승언, 이승재, 박세영, 주상원, 2006: QuickSCAT 해상풍 자료동화 기법 개발, 수치예보과 기술노트, 2006-02, 35 pp.
  5. Andersson, E., J. Pailleus, J.-N. The paut, J.R. Eyre, A.P. McNally, G.A. Kelly, and P. Courtier, 1994; Use of cloud-cleared radiances in three/four-dimensional variational data assimilation. Q. J. R. Meteorol. Soc., 120, 627-653. https://doi.org/10.1002/qj.49712051707
  6. Cucurull. L., J.C. Derber, R. Treadon, and R.J. Perser, 2006: Assimilation of Global Positioning System Radio Occultation Observations into NCEP's Global Data Assimilation System. Mon. Wea. Rev., 135, 3174-3193.
  7. Cucurull. L., Y.-H. Kuo, D. Barker and S.R.H. Rizvi, 2006: Assessing the impact of simulated COSMIC GPS Radio Occultation data on weather analysis over the Antarctic: A cast study. Mon. Wea. Rev., 134, 3283- 3296. https://doi.org/10.1175/MWR3241.1
  8. Cusack, S., 2002. The Empirically Adjusted Cloud Fraction modification to the cloud scheme. Met Office internal note.
  9. Derber, J., and W.-S. Wu, 1998: The use of TOVS cloudcleared radiances in the NCEP SSI analysis system. Mon. Wea. Rev., 126, 2287-2299. https://doi.org/10.1175/1520-0493(1998)126<2287:TUOTCC>2.0.CO;2
  10. S.H. Derbyshire, I. Beau, P. Bechthold, J.-Y. Grandpeix, J.M. Piriou, J.-L. Redelsperger and P.M.M. Soares, 2004, Sensitivity of moist convection to environmental humidity. Q. J. R. Met. Soc. 130, 3055-3080. https://doi.org/10.1256/qj.03.130
  11. Edwards, J.M., J.-C.Thelen, W.J.Ingram, 2004: The radiation code. UM documentation paper, No. 23.
  12. Eyre, J.R., G.Kelly, A.P.McNally, E.Andersson, and A.Persson, 1993: Assimilation of TOVS radiances through on dimensional variational analysis. Q. J. R. Meteorol. Soc., 119, 1427-1463. https://doi.org/10.1002/qj.49711951411
  13. Hilton, F., N. C. Atkinson, S. J. English and J.R. Eyre, 2009: Selection of IASI channels for user in numerical weather prediction. Q. J. R. Meteorol. Soc., 133, 1977- 1991.
  14. Lee, M.S., 2005: Preliminary tests of first guess at appropriate time with WRF 3DVAR and WRF model. J. of K. Metorol. Soc., 41, 495-505.
  15. Lock, A.P., A.R.Brown, M.R.Bush, Martin, G.M., and R.N.B.Smith, 2000: A new boundary layer mixing scheme. Part I: Scheme description and single-column model tests., Mon. Weather Rev., 128, 3187-3199. https://doi.org/10.1175/1520-0493(2000)128<3187:ANBLMS>2.0.CO;2
  16. Met Office, 2004: Unified Model User Guide. p243.
  17. Pangaud, T., N.Fourrie, and V. Guidard, 2009: Assimilation of AIRS radiances affected by mid-to low-level clouds. Mon. Wea. Rev., 137, 4276-4292. https://doi.org/10.1175/2009MWR3020.1
  18. Tracton, M.S., A.J.Desmarais, R.J.van Haaren, and R.D.McPherson, 1980: The impact of satellite soundings on the National Meteorological Center's analysis and forecast system-The Data Systems Test results. Mon. Wea. Rev., 108, 543-586. https://doi.org/10.1175/1520-0493(1980)108<0543:TIOSSO>2.0.CO;2
  19. Webster, S., Brown, A.R., Cameron, D.R. and Jones, C.P., 2003: Improvements to the representation of orography in the Met Office Unified Model. Q. J. R. Meteorol. Soc., 129, 1989-2010. https://doi.org/10.1256/qj.02.133
  20. Wilks, D., 1995: Statistical Methods in the Atmospheric Sciences: An Introduction. Academic Press, 467 pp.
  21. Wilson, D.R. and Ballard, S.P., 1999: A microphysically based precipitation scheme for the UK Meteorological Office Unified Model. Q. J. R. Meteorol. Soc., 125, 1607-1636. https://doi.org/10.1002/qj.49712555707