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| Titel |
Measuring atmospheric CO2 from space using Full Spectral Initiation (FSI) WFM-DOAS |
| VerfasserIn |
M. P. Barkley, U. Frieß, P. S. Monks |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1680-7316
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| Digitales Dokument |
URL |
| Erschienen |
In: Atmospheric Chemistry and Physics ; 6, no. 11 ; Nr. 6, no. 11 (2006-08-30), S.3517-3534 |
| Datensatznummer |
250004069
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| Publikation (Nr.) |
 copernicus.org/acp-6-3517-2006.pdf |
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| Zusammenfassung |
| Satellite measurements of atmospheric CO2 concentrations are a
rapidly evolving area of scientific research which can help reduce
the uncertainties in the global carbon cycle fluxes and provide
insight into surface sources and sinks. One of the emerging CO2
measurement techniques is a relatively new retrieval algorithm
called Weighting Function Modified Differential Optical Absorption
Spectroscopy (WFM-DOAS) that has been developed by
Buchwitz et al. (2000). This algorithm is designed to
measure the total columns of CO2 (and other greenhouse gases)
through the application to spectral measurements in the near
infrared (NIR), made by the SCIAMACHY instrument on-board ENVISAT.
The algorithm itself is based on fitting the logarithm of a model
reference spectrum and its derivatives to the logarithm of the ratio
of a measured nadir radiance and solar irradiance spectrum. In this
work, a detailed error assessment of this technique has been
conducted and it has been found necessary to include suitable a
priori information within the retrieval in order to minimize the
errors on the retrieved CO2 columns. Hence, a more flexible
implementation of the retrieval technique, called Full Spectral
Initiation (FSI) WFM-DOAS, has been developed which generates a
reference spectrum for each individual SCIAMACHY observation using
the estimated properties of the atmosphere and surface at the time
of the measurement. Initial retrievals over Siberia during the
summer of 2003 show that the measured CO2 columns are not biased
from the input a priori data and that whilst the monthly averaged
CO2 distributions contain a high degree of variability, they also
contain interesting spatial features. |
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