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A 21 F - 0901 A 21 F - 0901 Parameterization of Aerosol and Cirrus Cloud Effects on Reflected Sunlight Spectra Measured From Space: Application of the.

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Presentation on theme: "A 21 F - 0901 A 21 F - 0901 Parameterization of Aerosol and Cirrus Cloud Effects on Reflected Sunlight Spectra Measured From Space: Application of the."— Presentation transcript:

1 A 21 F - 0901 A 21 F - 0901 Parameterization of Aerosol and Cirrus Cloud Effects on Reflected Sunlight Spectra Measured From Space: Application of the Equivalence Theorem Andrey Bril *, Sergey Oshchepkov, Tatsuya Yokota, and Gen Inoue National Institute for Environmental Studies, Environment Ministry of Japan 16-2 Onogawa, Tsukuba-Shi Ibaraki 305-8506, JAPAN http://www.jaxa.jp/missions/projects/sat/eos/gosat/ A novel approach is proposed to estimate the aerosol and cirrus cloud effect on reflected sunlight radiance spectra measured with spaceborne sensors. This approach does not require detailed information on aerosol and cloud microphysical and optical properties. The proposed method is based on application of the equivalence theorem and photon path length statistics with further parameterization of the of photon path-length probability density function (PPDF). A limited set of the parameters could permit their simultaneous retrievals with gas amount. Monte Carlo simulations were utilized to validate this parameterization for the vertically non-homogeneous atmosphere including aerosol layer and cirrus cloud. Abstract This study concerns algorithms for greenhouse gas retrievals from satellite radiance observations in the near infrared spectral regions. The present paper focuses on the correction of aerosol and cirrus cloud effects that would be available using spectral channels and spectral resolution provided by the Greenhouse Gases Observing Satellite (GOSAT) instrument. Introduction to the problem A traditional way to account for thin cloud effects Geometry of the problem Monte Carlo simulations GOSAT SWIR channels The GOSAT spectral instrument is a nadir- looking Fourier-transform spectrometer (FTS) of short wavelength infrared (SWIR) that includes 1.6 µm, 2.0 µm CO 2 bands, and 0.76 µm oxygen A-band. Spectral resolution is 0.2 cm -1. Cloud information is consideration of Cloud optical depth Cloud scattering phase function Cloud single-scattering albedo Pressure top of scattering layer However: Background and strategy for the inverse modeling 1.These parameters are highly variable to be a priori prescribed 2.Observation data contain not enough information to retrieve them 3.Radiative transfer calculations are very time consuming to simulate high spectral resolution measurements Advantages to apply pathlength statistics Pathlength formalism enables us to accumulate scattering effects in PPDF Effects of scattering and absorption can be separated by applying the equivalence theorem The equivalence theorem Gas Particles Particles + Gas Cloud information The retrieval strategy includes Parameterization of the Photon Pathlength Distribution Function (PPDF) with validation by Monte Carlo technique Retrieval of PPDF parameters from 0.76  m oxygen band and 2.0  m saturation area the problem becomes very complicated for inhomogeneous multilayered atmosphere when the joint probability density function incorporates the PPDF for each individual layer as well as the interlayer photon path-length correlations PPDF and transmittance parameterization The simplified atmosphere consists of two layers (above and under cirrus) The pathlength above cloud is L 2 L 1 G is “under the cloud” pathlength for the photons that come to the detector without scattering Single light scattering by the cloud could both decrease and increase the pathlength Dashed lines show trajectories due to double light scattering The above considerations imply bi- modal form of the PPDF presented in the diagram. H e - the effective cloud height,  - cloud relative, reflectance, and  - two additional factors to account for photon pathlength distribution under the cloud These parameters have been retrieved from oxygen A-band and 2.0  m band. The accuracy of the H e,  and retrievals was validated with Monte Carlo simulations of these parameters. Impact of rural aerosol and Rayleigh scattering (symbols) on cloud relative reflectance and on relative average pathlength Aerosol and cirrus corrections in NIR bands The photon trajectories are identical for both cases and the only difference is in the amount of radiation that is attenuated by the gas As a result, scattering and absorption effects can be separated in the transmittance PPDF under the cloud Cloud with optical thickness of 0.5 is located between 11 and 12 km. Cloud. The data are presented for oxygen band at 12,980 cm-1. Surface albedo is 0.2 Conclusions An original methodology to account for aerosol and cloud effects in reflected sunlight transmittance has been developed on the basis of photon pathlength statistics analysis. The aerosol/cloud photon pathlength probability density function was represented by four parameters which can be retrieved from the nadir radiance measured in the O 2 -A band and from the saturated area of the CO 2 2.0 µm band. The efficiency of the PPDF approach for the correction of the CO 2 retrievals is demonstrated No aerosol and cloud correction Only cloud relative reflectance from 2.0 μm band is taken into account All PPDF parameters from 0.76 μm and 2.0 μm band are taken into account Potential errors in CO2column retrievals before of aerosol and cloud effects are of 16% (albedo 0.1) and 7% (0.2) After the correction these errors reduce to 0.9% and to 0.6%, correspondingly. Error of CO 2 retrievals according to DOAS WFT for 1.6  m band (no cirrus correction) To obtain PPDF parameters at 1.6  m, the interpolation of those retrieved from oxygen band and 2.0  m has to be utilized As a first approximation, DOAS Weighting Function Technique were utilized for the CO 2 retrievals (baseline was approximated by 2 nd order polynomial) Correction of the effective transmittance in 2.0  m band (4950 to 5050 cm-1) The model atmosphere includes cirrus clouds between 11 and 12 km with optical depth τ = 0.5, and rural aerosol with optical depth τ = 0.2. By computing the weighting functions using the PPDF the above errors were reduced to below 1% under the following conditions: Surface Albedo 0.1 - 0.5; Cirrus Optical Depth 0.1 - 0.3; Aerosol Optical Depth 0.01-0.2; Solar Zenith Angle 30 0 - 60 0


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