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Intercomparison of Shortwave Radiative Transfer Models for a Rayleigh Atmosphere

레일리 대기에서 단파 영역에서의 복사전달모델 결과들의 상호 비교

  • Yoo, Jung-Moon (Department of Science Education, Ewha Womans University) ;
  • Jeong, Myeong-Jae (NASA/GSFC) ;
  • Lee, Kyu-Tae (Department of Atmospheric & Environmental Sciences, Kangnung National University) ;
  • Kim, Jhoon (Department of Earth System Sciences, Yonsei University) ;
  • Ho, Chang-Hoi (School of Earth & Environmental Sciences, Seoul National University) ;
  • Ahn, Myoung-Hwan (Remote Sensing Research Laboratory, METRI/KMA) ;
  • Hur, Young-Min (Department of Science Education, Ewha Womans University) ;
  • Rhee, Ju-Eun (Department of Science Education, Ewha Womans University) ;
  • Yoo, Hye-Lim (Department of Science Education, Ewha Womans University) ;
  • Chung, Chu-Yong (Remote Sensing Research Laboratory, METRI/KMA) ;
  • Shin, In-Chul (Remote Sensing Research Laboratory, METRI/KMA) ;
  • Choi, Yong-Sang (School of Earth & Environmental Sciences, Seoul National University) ;
  • Kim, Young Mi (School of Earth & Environmental Sciences, Seoul National University)
  • Published : 2007.06.30

Abstract

Intercomparison between eight radiative transfer codes used for the studies of COMS (Communications, Ocean, and Meteorological Satellite) in Korea was performed under pure molecular, i.e., Rayleigh atmospheres in four shortwave fluxes: 1) direct solar irradiance at the surface, 2) diffuse irradiance at the surface, 3) diffuse upward flux at the surface, and 4) diffuse upward flux at the top of the atmosphere. The result (hereafter called the H15) from Halthore et al.'s study (2005) which intercompared and averaged 15 codes was used as a benchmark to examine the COMS models. Uncertainty of the seven COMS models except STREAMER was ${\pm}4%$ with respect to the H15, comparable with ${\pm}3%$ of Halthore et al.'s (2005). The uncertainty increased under a large $SZA=75^{\circ}$. The SBDART model generally agreed with the H15 better than the 6S model, but both models in the shortwave infrared region were equally good. The direct solar irradiance fluxes at the surface, computed by the SBDARTs of four different users, were different showing a relative error of 1.4% $(12.1Wm^{-2})$. This reason was partially due to differently installing the wavelength resolution in the flux integration. This study may be useful for selecting the optimum model in the shortwave region.

본 연구에서는 레일리(순수 기체) 대기 조건 하에서 국내 COMS 연구자들이 사용하는 여덟 개 단파 복사전달모델에서 산출된 네 종류 복사속(flux) 성분을 상호비교함으로써 상대 오차를 조사하였다. 이들 복사속 성분은 지표에서의 직달 일사, 하향 산란, 상향 산란, 그리고 대기 상부에서의 상향 산란이다. 또한 국내 모델의 평가를 위하여, 15개모델을 평균한 Halthore et al.(2005) 결과(예, H15)를 기준값으로 사용하였다. 동일한 태양천정각에서 모델 간의 불일치는 열대 대기에서 수증기에 기인하였고, 한대 대기에서는 오존에 기인하였다. STREAMER를 제외한 국내 7개 모델의 지상에서의 하향 직달일사값은 H15에 대하여 ${\pm}4%$내에서 일치하였다. 이러한 상대 오차는 태양천정각이 커질 때 증가하였으며, Halthore et al.(2005)에서의 ${\pm}3%$와 근접하였다. 네 종류 복사속 분석에서 SBDART 모델이 6S 모델에 비하여 전반적으로 우수하였으나, 근적외 파장역에서는 서로 비교할만하였다. 네개 기관의 연구자들이 같은 SBDART 모델에서 산출한 지표에서의 하향 직달일사값 간에도 $12.1Wm^{-2}(1.4%)$의 불일치가 존재하였다. 불일치의 원인은 부분적으로 복사속 적분에 있어서 서로 다르게 설정된 파장 분해능에도 있었다. 본 연구는 단파 영역에서 최적 모델을 선정하는 데 도움을 줄 수 있다.

Keywords

References

  1. 기상연구소, 2005, 통신해양기상위성 기상자료 처리시스템(II). 846 p
  2. 이광목, 2000, 대기복사(장파복사와 응용). 시그마프레스, 서울, 174 p
  3. Berk, A., and Coauthors, 2003, MODTRAN-4 Version 3 Revision 1 User's Manual, Air Force Research Laboratory. Hanscom AFB, MA 01731-3010, 91 p
  4. Cermak, J.B., and Bendix, J., 2005, A microphysics-based approach to fog/low stratus detection and discrimination using satellite data. COST 722 Midterm Workshop, Langen, Germany
  5. Chou, M.D., and Lee, K.T., 1996, Parameterizations for the absorption of solar radiation by water vapor and ozone. Journal of the Atmospheric Sciences, 53, 1203-1208 https://doi.org/10.1175/1520-0469(1996)053<1203:PFTAOS>2.0.CO;2
  6. Halthore, R.N., and Coauthors, 2005, Intercomparison of shortwave radiative transfer codes and measurements. Journal of Geophysical Research, 110, D11206 https://doi.org/10.1029/2004JD005293
  7. Key, J.R., 2002, Streamer User's Guide, NOAA/NESDIS, Madison, Wisconsin, 108 p
  8. Knapp, K.R., and Vonder Haar, T.H., 2002, Aerosol optical depth retrieved from GOES-8: Uncertainty study and retrieval validation over South America. Journal of Geophysical Research, 107, D7, 4055-4059 https://doi.org/10.1029/2001JD000505
  9. Peixoto, J.P., and Oort, A.H., 1992, Physics of Climate, MIT, New York, 520 p
  10. Ricchiazzi, P., Yang, C, Gautier, C, and Sowle, D., 1998, A research and teaching software tool for plane-parallei radiative transfer in the earth's atmosphere. Bulletin of the American Meteorological Society, 79, 2101-2114 https://doi.org/10.1175/1520-0477(1998)079<2101:SARATS>2.0.CO;2
  11. Underwood, S.J., Ellrod, GP., and Kuhnert, A.L., 2004, A multiple-case analysis of nocturnal radiation-fog development in the central valley of California utilizing the GOES nighttime fog product. Journal of Applied Meteorology, 43, 297-310 https://doi.org/10.1175/1520-0450(2004)043<0297:AMAONR>2.0.CO;2
  12. Vermote, E.F., Tanre, D., Deuze, J.L., Herman, M., and Morcrette, J. J., 1997, Second simulation of the satellite signal in the solar spectrum, 6S: An overview. IEEE Transactions on Geoscience and Remote Sensing, 35 (3), 675-686 https://doi.org/10.1109/36.581987
  13. Yoo, J.M., Jeong, M.J., and Yun, M.Y, 2006, Optical characteristics of fog from satellite observation (MODIS) and numerical simulation. The Journal of the Korean Meteorological Society, 42 (5), 291-305

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