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Proceedings Paper

Assessment of uncertainty in CO2 concentrations retrieved from thermal infrared spectra of GOSAT satellite
Author(s): N. Saitoh; Y. Ota; S. Taguchi; R. Imasu
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Paper Abstract

The Greenhouse Gases Observing Satellite (GOSAT) will be launched in 2008 for global observations of greenhouse gases such as CO2 and methane. This study examines the feasibility of retrieving CO2 concentrations from the infrared spectra of the GOSAT/Thermal and near infrared Sensor for Carbon Observation (TANSO)-FTS. Retrieval simulations in which the maximum a posteriori (MAP) method was applied to pseudo-spectra at 700-800 cm-1 from TANSO-FTS ("CO2 15-?m band") showed that retrieved CO2 profiles agreed with true CO2 profiles to within the total errors throughout the troposphere above 700-800 hPa when atmospheric conditions such as temperature used in the computation of the spectra were known. In contrast, discrepancies between retrieved CO2 and true CO2 concentrations increased if temperatures used in the retrieval included random errors; a random scatter of ±0.5 K caused a discrepancy that was 12 times larger at ~750 hPa. However, appropriate channel selection based on CO2 and temperature information could reduce the effect of temperature uncertainty on CO2 retrievals in this spectral region: the discrepancy between retrieved and true concentrations at ~750 hPa in the case with channel selection was about one-third of the discrepancy without any channel selection.

Paper Details

Date Published: 22 December 2006
PDF: 10 pages
Proc. SPIE 6405, Multispectral, Hyperspectral, and Ultraspectral Remote Sensing Technology, Techniques, and Applications, 640508 (22 December 2006); doi: 10.1117/12.693803
Show Author Affiliations
N. Saitoh, The Univ. of Tokyo (Japan)
Y. Ota, National Institute for Environmental Studies (Japan)
S. Taguchi, National Institute of Advanced Industrial Science and Technology (Japan)
R. Imasu, The Univ. of Tokyo (Japan)

Published in SPIE Proceedings Vol. 6405:
Multispectral, Hyperspectral, and Ultraspectral Remote Sensing Technology, Techniques, and Applications
William L. Smith; Allen M. Larar; Tadao Aoki; Ram Rattan, Editor(s)

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