Carbon dioxide retrieval from reflected sunlight spectra in the presence of cirrus cloud: model studies

Andrey Bril; Sergey Oshchepkov; Tatsuya Yokota

doi:10.1117/12.737233

17 October 2007 Carbon dioxide retrieval from reflected sunlight spectra in the presence of cirrus cloud: model studies

Andrey Bril, Sergey Oshchepkov, Tatsuya Yokota

Proceedings Volume 6745, Remote Sensing of Clouds and the Atmosphere XII; 674502 (2007) https://doi.org/10.1117/12.737233
Event: SPIE Remote Sensing, 2007, Florence, Italy

Abstract

The results of model study for CO₂ retrievals from numerically synthesized GOSAT (Greenhouse gases Observing SATellite) observation data are presented. The GOSAT is scheduled to be launched in 2008 to monitor column amounts of CO₂ and CH₄. A nadir-looking Fourier-Transform Spectrometer (FTS) of Short Wavelength Infrared (SWIR, 1.6 μm and 2 μm) and 0.76 μm oxygen A-band regions will be mounted on GOSAT. To assess CO2 sources and sinks, the monthly averaged CO2 column amounts estimated by satellite-based measurements should have a precision of within 1% or better to provide an advantage over existing ground-based measurement networks. This study focuses on CO₂ retrievals in the presence of cirrus clouds. An important feature of this problem is to apply radiance data measured in several spectral channels. In particular, 1.58 μm spectral band was utilized for CO₂ total column amount retrievals. The cloud correction was performed using an original approach that is based on the application of the equivalence theorem with parameterization of photon path-length probability density function (PPDF). The PPDF parameters were estimated using nadir radiance in the oxygen A-band and in the H₂O-saturated area of the 2.0 μm spectral band.

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Andrey Bril, Sergey Oshchepkov, and Tatsuya Yokota "Carbon dioxide retrieval from reflected sunlight spectra in the presence of cirrus cloud: model studies", Proc. SPIE 6745, Remote Sensing of Clouds and the Atmosphere XII, 674502 (17 October 2007); https://doi.org/10.1117/12.737233

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KEYWORDS

Clouds

Carbon monoxide

Carbon dioxide

Atmospheric modeling

Satellites

Atmospheric optics

Data modeling

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