Journal of the Korean earth science society (한국지구과학회지)

The Korean Earth Science Society (한국지구과학회)
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Sensitivity Experiment of Surface Reflectance to Error-inducing Variables Based on the GEMS Satellite Observations

GEMS 위성관측에 기반한 지면반사도 산출 시에 오차 유발 변수에 대한 민감도 실험

  • Shin, Hee-Woo (Department of Atmospheric and Environmental Sciences, Gangneung-Wonju National University) ;
  • Yoo, Jung-Moon (Department of Science Education, Ewha Womans University)
  • 신희우 (강릉원주대학교 대기환경과학과) ;
  • 유정문 (이화여자대학교 과학교육과)
  • Received : 2017.12.20
  • Accepted : 2018.02.14
  • Published : 2018.02.28
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Abstract

The information of surface reflectance ($R_{sfc}$) is important for the heat balance and the environmental/climate monitoring. The $R_{sfc}$ sensitivity to error-induced variables for the Geostationary Environment Monitoring Spectrometer (GEMS) retrieval from geostationary-orbit satellite observations at 300-500 nm was investigated, utilizing polar-orbit satellite data of the MODerate resolution Imaging Spectroradiometer (MODIS) and Ozone Mapping Instrument (OMI), and the radiative transfer model (RTM) experiment. The variables in this study can be cloud, Rayleigh-scattering, aerosol, ozone and surface type. The cloud detection in high-resolution MODIS pixels ($1km{\times}1km$) was compared with that in GEMS-scale pixels ($8km{\times}7km$). The GEMS detection was consistent (~79%) with the MODIS result. However, the detection probability in partially-cloudy (${\leq}40%$) GEMS pixels decreased due to other effects (i.e., aerosol and surface type). The Rayleigh-scattering effect in RGB images was noticeable over ocean, based on the RTM calculation. The reflectance at top of atmosphere ($R_{toa}$) increased with aerosol amounts in case of $R_{sfc}$<0.2, but decreased in $R_{sfc}{\geq}0.2$. The $R_{sfc}$ errors due to the aerosol increased with wavelength in the UV, but were constant or slightly decreased in the visible. The ozone absorption was most sensitive at 328 nm in the UV region (328-354 nm). The $R_{sfc}$ error was +0.1 because of negative total ozone anomaly (-100 DU) under the condition of $R_{sfc}=0.15$. This study can be useful to estimate $R_{sfc}$ uncertainties in the GEMS retrieval.

지면반사도 정보는 열평형 및 환경/기후 모니터링에 중요하다. 본 연구에서는 정지궤도위성의 Geostationary Environment Monitoring Spectrometer (GEMS) 관측에서 300-500 nm 파장 영역의 지면반사도 산출 시에 오차 유발 요소에 대한 민감도를 조사하였다. 장차 GEMS 지면반사도 산출 시에 오차 분석을 위하여 극궤도 위성의 MODerate resolution Imaging Spectroradiometer (MODIS; 공간 해상도 $1km{\times}1km$) 자료 및 Ozone Mapping Instrument (OMI; $12km{\times}24km$) 자료 그리고 복사전달모델 수치실험도 분석에 사용하였다. 본 연구에서 오차 유발 요소는 구름, 레일리 산란, 에어로졸, 오존 그리고 지면 특성이다. GEMS 저해상도($8km{\times}7km$)에서의 구름 탐지율은 MODIS 대비 약 79%이었으나, GEMS 화소의 운량이 40% 이하에서는 상대적으로 낮았다. 이러한 경향은 구름 이외의 다른 효과(에어로졸, 지면 특성)로 인하여 주로 발생하였다. RGB 영상과 복사전달모델 계산을 기초로 조사된 레일리 산란 효과는 육지에 비하여 해양 지역에서 뚜렷하였다. 지면반사도가 0.2보다 작은 경우에 위성관측 대기상단 반사도는 에어로졸 양에 비례하였으나, 0.2보다 큰 경우에는 그 반대 경향을 보였다. 또한 에어로졸 양에 의한 지면반사도 산출 오차는 자외선 영역에서 파장에 따라 급격하게 증가하였으나, 가시광선에서는 일정하거나 다소 감소하였다. 오존 흡수는 자외선 영역(328-354 nm) 중 328 nm에서 가장 크게 나타났다. 지면반사도가 0.15인 육지 경우에 음의 오존전량 아노말리(-100 DU)로 인한 지면반사도 산출 오차는 +0.1이었다. 본 연구는 GEMS 위성관측을 이용한 지면반사도 원격탐사의 정확도를 높이는데 기여할 수 있다.

Keywords

References

  1. An, J.H., Kim, T.W., and Lee, S.E., 2004, A numerical study of the effects of land characteristics on the air cooling. Korean Journal of Environmental Agriculture, 23(4), 264-271. https://doi.org/10.5338/KJEA.2004.23.4.264
  2. Baldridge, A.M., Hook, S.J., Grove, C.I., and Rivera, G., 2009, The ASTER spectral library version 2.0. Remote Sensing of Environment, 113(4), 711-715. https://doi.org/10.1016/j.rse.2008.11.007
  3. Boersma, K.F., Eskes, H.J., and Brinksma, E.J., 2004, Error analysis for tropospheric $NO_2$ retrieval from space. Journal of Geophysical Research, 109(D4), D04311.
  4. Choi, D.H., and Lee, B.Y., 2007, Analysis of passive cooling effect of membrane shading structure and the tree by field observations in the summer. Journal of the Korean Solar Energy Society, 27(4), 137-146.
  5. Choi, D.H., Lee, B.Y., and Oh, H.Y., 2012, Observation and analysis of the long and short wave radiation according to different altitudes and locations in Daegu during summer. Journal of the Korean Solar Energy Society, 32(4), 1598-6411.
  6. Hall, A., 2003, The role of surface albedo feedback in climate. Journal of Climate, 17, 1550-1568.
  7. Hansen, J.E. and Travis, L.D., 1975, Light scattering in planetary atmospheres. Space Science Reviewer, 16(4), 527-610.
  8. Herman, J. and Celarier, E.A., 1997, Earth surface reflectivity climatology at 340-380 nm from TOMS data. Journal of Geophysical Research, 102(D23), 28003-28011. https://doi.org/10.1029/97JD02074
  9. Hsu, N.C., Tsay, S.C., King, M.D., and Herman, J.R., 2004, Aerosol properties over bright-reflecting source regions. IEEE transactions on geoscience and remote sensing, 42(3), 557-569. https://doi.org/10.1109/TGRS.2004.824067
  10. Hsu, N.C., Tsay, S.C., King, M.D., and Herman, J.R., 2006, Deep blue retrievals of Asian aerosol properties during ACE-Asia. IEEE transactions on geoscience and remote sensing, 44(11), 3180-3195. https://doi.org/10.1109/TGRS.2006.879540
  11. Jeong, M.J., Hsu, N.C., Kwiatkowska, E.J., Franz, B.A., Meister, G., and Salustro, C.E., 2012, Impacts of crossplatform vicarious calibration on the deep blue aerosol retrievals for moderate resolution imaging spectroradiometer aboard Terra. IEEE transactions on geoscience and remote sensing, 49(12), 4877-4888. https://doi.org/10.1109/TGRS.2011.2153205
  12. Kang, J.H., Suh, M.S., and Kwak, C.H., 2009, Classification of land cover over the Korean peninsula using MODIS data. Journal of the Korean Meteorological Society, 19(2), 169-182.
  13. Kaufman, Y.J., and Holben, B.N., 1993, Calibration of the AVHRR visible and near-IR bands by atmospheric scattering, ocean glint and desert reflection. International Journal of Remote Sensing, 14(1), 21-52. https://doi.org/10.1080/01431169308904320
  14. Kim, M.J., Kim, J., and Yoon, J., 2014, Estimation of surface reflectance by utilizing single visible reflectance from COMS meteorological imager. Korean Journal of Remote Sensing, 30(5), 627-639. https://doi.org/10.7780/kjrs.2014.30.5.8
  15. Kleipool, Q., Dobber, M., Haan, J.D., and Levelt, P., 2008, Earth surface reflectance climatology from 3 years of OMI data. Journal of Geophysical Research, 113(D18).
  16. Koelemeijer, R.B.A., de Haan, J.F., and Stammes, P., 2003, A database of spectral surface reflectivity in the range 335-772 nm derived from 5.5 years of GOME observations. Journal of Geophysical Research, 108(D2), 4070. https://doi.org/10.1029/2002JD002429
  17. Kotchenova, S.Y., Vermote, E.F., Matarrese, R., and Klemm Jr, F.J., 2006, Validation of a vector version of the 6S radiative transfer code for atmospheric correction of satellite data. Part I: Path radiance. Optical Society of America, 45(26), 6762-6774.
  18. Krotkov, N.A., McClure, B., Dickerson, R.R., Carn, S.A., Li, C., Bhartia, P.K., Yang, K., Krueger, A.J., Li, Z., Levelt, P.F., Chen, H., Wang, P., and Daren, L., 2008, Validation of $SO_2$ retrievals from the ozone monitoring instrument over NE China. Journal of Geophysical Research, 113(D16), D16S40.
  19. Loeb, N.G., Wielicki, B.A., Doelling, D.R., Smith, G.L., Keyes, D.F., Kato, S., Smith, M.M., and Wong, T., 2009, Toward optimal closure of the earth's top-ofatmosphere radiation budget. Journal of Climate, 22, 748-766. https://doi.org/10.1175/2008JCLI2637.1
  20. Loyola, D.G., Koukouli, M.E., Valks, P., Balis, D.S., Hao, N., Roozendael, M.V., Spurr, R.J.D., Zimmer, W., Kiemle, S., Lerot, C., and Lambert, J.C., 2011, The GOME-2 total column ozone product: Retrieval algorithm and ground-based validation. Journal of Geophysical Research, 116(D7), D07302.
  21. Martins, J.V., Tanre, D., Remer, L., Kaufman, Y., Mattoo, S., and Levy, R., 2002, MODIS cloud screening for remote sensing of aerosols over oceans using spatial variability. Journal of Geophysical Research, 29(12), MOD4 1-4.
  22. Moran, M.S., Jackson, R.D., Slater, P.N., and Teillet, P.M., 1992, Evaluation of simplified procedures for retrieval of land surface reflectance factors from satellite sensor output. Remote Sensing of Environment, 41, 169-184. https://doi.org/10.1016/0034-4257(92)90076-V
  23. Noguchi, K., Richter, A., Rozano, V., Burrows, J.P., and Kita, K., 2014, Effect of surface BRDF of various land cover types on geostationary observations of tropospheric $NO_2$. Atmospheric Measurement Techniques, 7(10), 3497-3508. https://doi.org/10.5194/amt-7-3497-2014
  24. Shettle, E.P. and Fenn, R.W., 1979, FENN models for the aerosols of the lower atmosphere and the effects of humidity variations on their optical propertie. Environmental Research Paper, 676, 1-23.
  25. Shupe, M.D. and Intrieri, J.M., 2003, Cloud radiative forcing of the arctic surface: The influence of cloud properties, surface albedo, and solar zenith angle. Journal of Climate, 17, 616-628.
  26. Sissenwine, N., Dubin, M., and Wexler, H., 1962, The U.S. standard atmosphere, Journal of Geophysical Research, 67(9), 3627-3630. https://doi.org/10.1029/JZ067i009p03627
  27. Veefkind, J.P., de Haan, J.F., Brinksma, E.J., Kroon, M., and Levelt, P.F., 2006, Total ozone from the ozone monitoring instrument (OMI) using the DOAS technique. IEEE transactions on geoscience and remote sensing, 44(5), 1239-1244. https://doi.org/10.1109/TGRS.2006.871204
  28. Vermote, E.F., Tanre, D., Deuze, J.L., Herman, M., and Morcette, 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
  29. Xianqiang, H., Bai, Y., Pan, D., Huang, N., Dong, X., Chen, J., Chen, C.T., and Cui, Q., 2013, Using geostationary satellite ocean color data to map the diurnal dynamics of suspended particulate matter in coastal waters. Remote Sensing of Environment, 133, 225-239. https://doi.org/10.1016/j.rse.2013.01.023
  30. Xiong, J., 2009, MODIS Characterization and Support Team (MCST), MODIS level 1b product user's guide. Members of the MODIS Characterization Support Team For NASA/Goddard Space Flight Center, p. 20.
  31. Yeom, J.M., Han, K.S., and Kim, I.H., 2010, The study of land surface change detection using long-term spot/vegetation. Journal of the Korean Association of Geographic Information Studies, 13(4), 111-124.
  32. Yoo, J.M., Jeong, M.J., Lee, K.T., Kim, J., Rhee, J.E., Hur, Y.M., Kim, B.R., Lee, Y.G., Lee, J.H., Yoon, J.M., and Lee, W.H., 2008, Intercomparison of shortwave radiative transfer models for aerosol-laden atmospheres. Journal of Korean Earth Science Society, 29(2), 128-139. https://doi.org/10.5467/JKESS.2008.29.2.128