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

Kokhanovsky, Alexander A.; Розанов, В. В.; Zege, Eleonora P.; Bovensmann, H.; Burrows, J. P.

doi:10.1029/2001jd001543

Cited by 102 publications

(140 citation statements)

References 45 publications

(115 reference statements)

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“…The equations given above are easily generalized for the case of finite optically thick layers having the geometrical thickness L. Then we have [Kokhanovsky et al, 2003] …”

Section: Theorymentioning

confidence: 99%

Spectral reflectance of whitecaps

Kokhanovsky

2004

J. Geophys. Res.

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[1] Spectral properties of whitecaps are of importance for color ocean remote sensing and aerosol optical thickness probing from satellite-based instruments. They also influence planetary albedo and climate. In particular, whitecaps may affect the response of the climate system to changes in greenhouse gases and other atmospheric constituents. Several experimental measurements of whitecap spectral reflectance have been performed both in the surf zone and in the open ocean, which indicate that oceanic foam cannot be considered as a gray body (e.g., for satellite remote sensing techniques). This paper is devoted to the interpretation of experiments performed in terms of the radiative transfer theory. Only the case of a semi-infinite foam is studied in detail. However, results can be easily extended to the case of finite foamed media having large optical thickness. The model introduced is capable of explaining main features observed, like a sharp decrease of the foam spectral reflectance in the infrared as compared with the visible part of the electromagnetic spectrum and a high correlation of the foam reflectance R and the water absorption coefficient a. A simple method to retrieve the spectral dependence of a from the spectral foam reflectance R is proposed.

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“…The equations given above are easily generalized for the case of finite optically thick layers having the geometrical thickness L. Then we have [Kokhanovsky et al, 2003] …”

Section: Theorymentioning

confidence: 99%

Spectral reflectance of whitecaps

Kokhanovsky

2004

J. Geophys. Res.

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“…The high variability of ship tracks results in a high variation of their radiative behavior. Therefore, in the third step the cloud optical properties like effective radius and cloud optical thickness are calculated for each individual pixel using a combination of the SACURA method (Semi-Analytical Cloud Retrieval Algorithm [Kokhanovsky et al, 2003]) and a look-up-tableapproach calculated with the libRadtran package [Mayer and Kylling, 2005] as described by Schreier et al [2006]. Using these cloud optical parameters, the backscattered radiative flux at TOA is calculated for the possible solar zenith angles, depending on the latitude and season, within the ship tracks and in the surrounding region.…”

Section: Radiative Forcingmentioning

confidence: 99%

Global ship track distribution and radiative forcing from 1 year of AATSR data

Schreier¹,

Mannstein²,

Eyring³

et al. 2007

Geophysical Research Letters

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One year of ENVISAT‐AATSR (Advanced Along Track Scanning Radiometer) satellite data is analyzed to derive a global distribution of ship tracks and their radiative forcing (RF). Ship tracks are changes in cloud reflectance, visible in satellite data, and result from the emission of aerosols and their precursors by ships into the clean marine boundary layer. An algorithm is presented that extracts scenes dominated by low clouds over the oceans that are susceptible to be affected by ship emissions. These selected cloud scenes are used to examine ship tracks on a global scale via visual analysis. The results show a high temporal variability of ship track occurrence with peak values in July. They also show a high spatial variability with peak values in the North Pacific Ocean and on the west coast of southern Africa, correlated with high ship traffic and frequent low cloud occurrence in regions of cold upwelling ocean currents. The analysis of backscattered radiation at top of the atmosphere (TOA) compared to the surrounding area reveals enhanced backscattering with values between 0 and 100 Wm−2. For particular regions on the west coast of North America, the annual mean RF due to ship tracks estimated by the changes in backscattered radiation at TOA can be up to −50 mWm−2. The global annual mean RF due to ship tracks is small (−0.4 to −0.6 mWm−2) and negligible compared to previous global model estimates on the total indirect aerosol effect and RF contributions of other ship emissions.

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“…In SACURA, the CGT is constrained to an upper limit of 11 km. Additionally, due to the SCIAMACHY spectral coverage of the shortwave infrared, SACURA can also differentially exploit the absorption features of water and ice and retrieve the effective radius of cloud droplets (Kokhanovsky et al, 2003) as well as the thermodynamic phase from measurements at 1.55 and 1.67 µm (Kokhanovsky et al, 2006a,c). However, in the present paper, the focus is only on cloud products derived from Vis-NIR channels.…”

Section: Inversion Of the Measurementsmentioning

confidence: 99%

Evaluation of SCIAMACHY ESA/DLR Cloud Parameters Version 5.02 by Comparisons to Ground-Based and Other Satellite Data

Lelli

Weber

Burrows

2016

Front. Environ. Sci.

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This paper reports on the evaluation of long-term cloud products as retrieved from measurements of the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) instrument with the DLR/ESA processor in its version 5.02 and the operational implementation of the Semi-Analytical CloUd Retrieval Algorithm SACURA. The comparison is performed against spaceborne and ground-based cloud data. The satellite records are the SCIAMACHY/SACURA in its scientific implementation and the Global retrieval of ATSR cloud parameters and evaluation (GRAPE) data set, in its version 3.2, generated for the nadir view of the Advanced Along-Track Scanning Radiometer (AATSR) instrument onboard ENVISAT. Ground-based data are derived from profiles of micro-pulse lidars, continuously operated at three Atmospheric Radiation Measurement (ARM) research facilities. They are, namely, North Slope Alaska, Southern Great Plains and Tropical Western Pacific-Nauru, located in three different latitude belts. It has been found that SCIAMACHY cloud top heights, inferred in the visible-near infrared, have a seasonal dependent overestimation in range 0.6-1.0 km when compared to the thermal infrared-derived AATSR cloud top heights. The comparison with the in-situ cloud retrievals reveals that SCIAMACHY cloud altitudes are more accurate for local cloud cover values > 0.6.

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

Cited by 102 publications

References 45 publications

Spectral reflectance of whitecaps

Spectral reflectance of whitecaps

Global ship track distribution and radiative forcing from 1 year of AATSR data

Evaluation of SCIAMACHY ESA/DLR Cloud Parameters Version 5.02 by Comparisons to Ground-Based and Other Satellite Data

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