Examination of the Quality of GOSAT/CAI Cloud Flag Data over Beijing Using Ground-based Cloud Data

HUO Juan; ZHANG Wenxing; ZENG Xiaoxia; L&uuml; Daren; LIU Yi

doi:10.1007/s00376-013-2267-0

Abstract:

It has been several years since the Greenhouse Gases Observing Satellite (GOSAT) began to observe the distribution of CO2 and CH4 over the globe from space. Results from Thermal and Near-infrared Sensor for Carbon Observation-Cloud and Aerosol Imager (TANSO-CAI) cloud screening are necessary for the retrieval of CO2 and CH4 gas concentrations for GOSAT TANSO-Fourier Transform Spectrometer (FTS) observations. In this study, TANSO-CAI cloud flag data were compared with ground-based cloud data collected by an all-sky imager (ASI) over Beijing from June 2009 to May 2012 to examine the data quality. The results showed that the CAI has an obvious cloudy tendency bias over Beijing, especially in winter. The main reason might be that heavy aerosols in the sky are incorrectly determined as cloudy pixels by the CAI algorithm. Results also showed that the CAI algorithm sometimes neglects some high thin cirrus cloud over this area.

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Examination of the Quality of GOSAT/CAI Cloud Flag Data over Beijing Using Ground-based Cloud Data

Corresponding author: HUO Juan;

1. Key Laboratory for Atmosphere and Global Environment Observation, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029

Manuscript received: 2012-10-25

Manuscript revised: 2013-02-20

Fund Project: The authors acknowledge support from the Strategic Pilot Science and Technology project of the Chinese Academy of Sciences (Grant No. XDA05040200) and the National Natural Science Foundation of China (Grant No. 41275040).

Abstract: It has been several years since the Greenhouse Gases Observing Satellite (GOSAT) began to observe the distribution of CO2 and CH4 over the globe from space. Results from Thermal and Near-infrared Sensor for Carbon Observation-Cloud and Aerosol Imager (TANSO-CAI) cloud screening are necessary for the retrieval of CO2 and CH4 gas concentrations for GOSAT TANSO-Fourier Transform Spectrometer (FTS) observations. In this study, TANSO-CAI cloud flag data were compared with ground-based cloud data collected by an all-sky imager (ASI) over Beijing from June 2009 to May 2012 to examine the data quality. The results showed that the CAI has an obvious cloudy tendency bias over Beijing, especially in winter. The main reason might be that heavy aerosols in the sky are incorrectly determined as cloudy pixels by the CAI algorithm. Results also showed that the CAI algorithm sometimes neglects some high thin cirrus cloud over this area.

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1. Ackerman, S. A.,K. I. Strabala,W. P. Menzel,R. A. Frey,C. C. Moeller, and L. E. Gumley,1998:Discriminating clear-sky from clouds with MODIS.J. Geophys. Res., 103, 32141-32157.
2. Bousquet, P.,P. Peylin,P. Ciais,C. L. Quere,P. Friedlingstein, and P. P. Tans,2000:Regional changes in carbon dioxide fluxes of land and oceans since 1980.Science, 290(5495), 1342-1346.
3. Engelen, R. J.,A. S. Denning,K. R. Gurney, and G. L. Stephens,2001:Global observations of the carbon budget: 1. Expected satellite capabilities for emission spectroscopy in the EOS and NPOESS eras.J. Geophys. Res., 106(D17), 20055-20068.
4. Fan, S.,M. Gloor,J. Mahlman,S. Pacala,J. Sarmiento,T. Takahashi, and A. P. Tans,1998:A large terrestrial carbon sink in North America implied by atmospheric and oceanic carbon dioxide data and models.Science, 282(5388), 442-446.
5. Guan, J. X., and C. C. Li,2010:Spatial distributions and changes of aerosol optical depth over eastern and central china.Acta Scientiarum Naturalium Universitatis Pekinensis, 46, 185-191. (in Chinese)
6. Huo, J., and D. Lu,2009:Cloud determination of all-sky images under low-visibility conditions.J. Atmos. Ocean. Technol., 26, 2172-2181.
7. Ishida, H., and T. Y. Nakjima,2009:Development of an unbiased cloud detection algorithm for a spaceborne multispectral imager.J. Geophys. Res., 114, D07206, doi: 07210.01029/02008JD010710.
8. Ishida, H., and T. Y. Nakjima,2011:Investigation of GOSAT TANSO-CAI cloud screening ability through an intersatellite comparison.J. Appl. Meteor. Climatol., 50, 1571-1586.
9. Liu, H.,W. Zhu,S. Yi,W. Li,L. Chen, and L. Bai,2003:Climatic analysis of the cloud over China.Acta Meteorologica Sinica, 61, 466-473. (in Chinese)
10. Min, M.,P. Wang, and X. Zong,2011:Cirrus cloud distribution over China from spaceborne lidar observations.Climatic and Environmental Research, 16, 301-309. (in Chinese)
11. Sabburg, J., and C. Long,2004:Improved sky imaging for studies of enhanced UV irradiance.Atmos. Chem. Phys, 4, 2543-2552.
12. Treut, L.,R. Somerville,U. Cubasch,Y. Ding,C. Mauritzen,A. Mokssit,T. Peterson, and M. Prather,2007: Historical overview of climate change. Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment report of the Intergovernmental Panel on Climate Change, Cambridge University Press, 996pp.
13. Xu, X., J. Qiu, S. Niu, and L. Tang, 2009. Optical depth of the atmospheric aerosol at 12 stations in China over the past 45 years. Acta Scientiae Circumstantiae, 29, 488-495. (in Chinese)
14. Yan, L. B., and X. D. Liu,2009:Seasonal variation of atmospheric aerosol and its relation to cloud faction over Beijing-Tianjin-Hebei region.Chinese Research of Environmental Sciences, 22, 924-931. (in Chinese)
15. Zhang, W.,D. Lu, and Y. Chang,2007:A feasibility study of cloud base height remote sensing by simulating ground-based thermal infrared brightness temperature measurements.Chinese Journal of Geophysics, 50, 339-350. (in Chinese)

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Examination of the Quality of GOSAT/CAI Cloud Flag Data over Beijing Using Ground-based Cloud Data

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