Correction of Rayleigh scattering effects in cloud optical thickness retrievals

Wang, Menghua; King, Michael D.

doi:10.1029/97jd02225

Cited by 32 publications

(21 citation statements)

References 12 publications

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“…Excellent reviews of these and other relevant issues, however, are available elsewhere Kobayashi, 1993;Cahalan et al, 1994;Pincus et al, 1995;Wang and King, 1997;Asano et al, 2000].…”

Section: à2mentioning

confidence: 99%

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A semianalytical cloud retrieval algorithm using backscattered radiation in 0.4–2.4 μm spectral region

et al. 2003

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[1] This study is devoted to the development of a semianalytical algorithm for the determination of the optical thickness, the liquid water path, and the effective size of droplets from spectral measurements of the intensity of light reflected from water clouds with large optical thickness. The probability of photon absorption by droplets in the visible and near-infrared spectral regions is low. This allows us to simplify and modify wellknown asymptotic equations of the radiative transfer theory, taking into account the fact that the single scattering albedo is close to one. Modified asymptotic equations are used to develop the inverse algorithm. We also avoid the use of the Mie theory, applying parametrizations and geometrical optics results with account for wave corrections. The main advantage of the method proposed lays in the fact that the equations derived not only provide a valuable alternative to the numerical radiative transfer solution but also are much more simple than equations of a conventional asymptotic theory. This simplicity allows both the simplification of the cloud retrieval algorithm and, even more important, the insight into various factors involved in a retrieval scheme.

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“…Excellent reviews of these and other relevant issues, however, are available elsewhere Kobayashi, 1993;Cahalan et al, 1994;Pincus et al, 1995;Wang and King, 1997;Asano et al, 2000].…”

Section: à2mentioning

confidence: 99%

“…However, corrections can be easily taken into account if needed [Bucholtz, 1995;Wang and King, 1997;Goloub et al, 2000]. The influence of the surface reflection on the cloud reflection function, assuming that the surface is Lambertian with albedo A, is taken into account.…”

Section: The Two-channel Inversion Algorithmmentioning

confidence: 99%

A semianalytical cloud retrieval algorithm using backscattered radiation in 0.4–2.4 μm spectral region

et al. 2003

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“…The LUTs do not include the additional contributions from Rayleigh scattering, which are added to the atmospherically corrected ASTER reflectances before a retrieval is attempted. The added amount of Rayleigh scattering is a function of cloud top pressure and is accounted for dynamically, using the retrieved value of cloud top pressure as described in Wang and King (1997). For both MODIS and ASTER, the retrieved τ is scaled to the respective 0.65 µm band (i.e., band 1 for MODIS and band 2 for ASTER).…”

Section: Cloud Optical and Microphysical Propertiesmentioning

confidence: 99%

Marine boundary layer cloud property retrievals from high-resolution ASTER observations: case studies and comparison with Terra MODIS

et al. 2016

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Abstract.A research-level retrieval algorithm for cloud optical and microphysical properties is developed for the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) aboard the Terra satellite. It is based on the operational MODIS algorithm. This paper documents the technical details of this algorithm and evaluates the retrievals for selected marine boundary layer cloud scenes through comparisons with the operational MODIS Data Collection 6 (C6) cloud product. The newly developed, ASTERspecific cloud masking algorithm is evaluated through comparison with an independent algorithm reported in Zhao and Di Girolamo (2006). To validate and evaluate the cloud optical thickness (τ ) and cloud effective radius (r eff ) from ASTER, the high-spatial-resolution ASTER observations are first aggregated to the same 1000 m resolution as MODIS. Subsequently, τ aA and r eff, aA retrieved from the aggregated ASTER radiances are compared with the collocated MODIS retrievals. For overcast pixels, the two data sets agree very well with Pearson's product-moment correlation coefficients of R > 0.970. However, for partially cloudy pixels there are significant differences between r eff, aA and the MODIS results which can exceed 10 µm. Moreover, it is shown that the numerous delicate cloud structures in the example marine boundary layer scenes, resolved by the high-resolution ASTER retrievals, are smoothed by the MODIS observations. The overall good agreement between the research-level ASTER results and the operational MODIS C6 products proves the feasibility of MODIS-like retrievals from ASTER reflectance measurements and provides the basis for future studies concerning the scale dependency of satellite observations and three-dimensional radiative effects.

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“…The Rayleigh scattering correction is based on Wang and King (1997) and is only performed in the VIS channel. Next to the viewing geometry, it depends on cloud albedo α c , which in turn depends on COT and REF, and Rayleigh optical thickness from cloud top to the top of the atmosphere, τ r .…”

Section: Cloud Optical and Microphysical Propertiesmentioning

confidence: 99%

“…Next to the viewing geometry, it depends on cloud albedo α c , which in turn depends on COT and REF, and Rayleigh optical thickness from cloud top to the top of the atmosphere, τ r . The Rayleigh optical thickness is determined assuming a total column Rayleigh optical thickness of 0.044 at surface pressure 1013 hPa (Wang and King, 1997) and scaling it by an estimated cloud top pressure p c . The atmospheric transmittance above the cloud is determined considering absorption by water vapor (total column water vapor above cloud) and ozone (total ozone in Dobson units) in the VIS channel and only absorption by water vapor in the NIR channel.…”

Section: Cloud Optical and Microphysical Propertiesmentioning

confidence: 99%

FAME-C: cloud property retrieval using synergistic AATSR and MERIS observations

et al. 2014

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Abstract.A newly developed daytime cloud property retrieval algorithm, FAME-C (Freie Universität Berlin AATSR MERIS Cloud), is presented. Synergistic observations from the Advanced Along-Track Scanning Radiometer (AATSR) and the Medium Resolution Imaging Spectrometer (MERIS), both mounted on the polar-orbiting Environmental Satellite (Envisat), are used for cloud screening. For cloudy pixels two main steps are carried out in a sequential form. First, a cloud optical and microphysical property retrieval is performed using an AATSR near-infrared and visible channel. Cloud phase, cloud optical thickness, and effective radius are retrieved, and subsequently cloud water path is computed. Second, two cloud top height products are retrieved based on independent techniques. For cloud top temperature, measurements in the AATSR infrared channels are used, while for cloud top pressure, measurements in the MERIS oxygen-A absorption channel are used. Results from the cloud optical and microphysical property retrieval serve as input for the two cloud top height retrievals. Introduced here are the AATSR and MERIS forward models and auxiliary data needed in FAME-C. Also, the optimal estimation method, which provides uncertainty estimates of the retrieved property on a pixel basis, is presented. Within the frame of the European Space Agency (ESA) Climate Change Initiative (CCI) project, the first global cloud property retrievals have been conducted for the years [2007][2008][2009]. For this time period, verification efforts are presented, comparing, for four selected regions around the globe, FAME-C cloud optical and microphysical properties to cloud optical and microphysical properties derived from measurements of the Moderate Resolution Imaging Spectroradiometer (MODIS) on the Terra satellite. The results show a reasonable agreement between the cloud optical and microphysical property retrievals. Biases are generally smallest for marine stratocumulus clouds: −0.28, 0.41 µm and −0.18 g m −2 for cloud optical thickness, effective radius and cloud water path, respectively. This is also true for the root-mean-square deviation. Furthermore, both cloud top height products are compared to cloud top heights derived from ground-based cloud radars located at several Atmospheric Radiation Measurement (ARM) sites. FAME-C mostly shows an underestimation of cloud top heights when compared to radar observations. The lowest bias of −0.3 km is found for AATSR cloud top heights for single-layer clouds, while the highest bias of −3.0 km is found for AATSR cloud top heights for multilayer clouds. Variability is low for MERIS cloud top heights for low-level clouds, and high for MERIS cloud top heights for mid-level and high-level single-layer clouds, as well as for both AATSR and MERIS cloud top heights for multilayer clouds.

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Correction of Rayleigh scattering effects in cloud optical thickness retrievals

Cited by 32 publications

References 12 publications

A semianalytical cloud retrieval algorithm using backscattered radiation in 0.4–2.4 μm spectral region

A semianalytical cloud retrieval algorithm using backscattered radiation in 0.4–2.4 μm spectral region

Marine boundary layer cloud property retrievals from high-resolution ASTER observations: case studies and comparison with Terra MODIS

FAME-C: cloud property retrieval using synergistic AATSR and MERIS observations

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