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Titel |
Sensitivity analysis of methane emissions derived from SCIAMACHY observations through inverse modelling |
VerfasserIn |
J. F. Meirink, H. J. Eskes, A. P. H. Goede |
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. 5 ; Nr. 6, no. 5 (2006-04-24), S.1275-1292 |
Datensatznummer |
250003729
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Publikation (Nr.) |
copernicus.org/acp-6-1275-2006.pdf |
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Zusammenfassung |
Satellite observations of trace gases in the atmosphere offer a promising
method for global verification of emissions and improvement of global
emission inventories. Here, an inverse modelling approach based on
four-dimensional variational (4D-var) data assimilation is presented and
applied to synthetic measurements of atmospheric methane. In this approach,
emissions and initial concentrations are optimised simultaneously, thus
allowing inversions to be carried out on time scales of weeks to months,
short compared with the lifetime of methane. Observing System Simulation
Experiments (OSSEs) have been performed to demonstrate the feasibility of the
method and to investigate the utility of SCIAMACHY observations for methane
source estimation. The impact of a number of parameters on the error in the
methane emission field retrieved has been analysed. These parameters include
the measurement error, the error introduced by the presence of clouds, and
the spatial resolution of the emission field. It is shown that 4D-var is an
efficient method to deal with large amounts of satellite data and to retrieve
emissions at high resolution. Some important conclusions regarding the
SCIAMACHY measurements can be drawn. (i) The observations at their estimated
precision of 1.5 to 2% will contribute considerably to uncertainty reduction
in monthly, subcontinental (~500 km) methane source strengths. (ii)
Systematic measurement errors well below 1% have a dramatic impact on the
quality of the derived emission fields. Hence, every effort should be made to
identify and remove such systematic errors. (iii) It
is essential to take partly cloudy pixels into account in order to achieve
sufficient spatial coverage. (iv) The uncertainty in measured cloud
parameters may at some point become the limiting factor for methane emission
retrieval, rather than the uncertainty in measured methane itself. |
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