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Published July 2006 | Published
Book Section - Chapter Open

Satellite Chartography of Atmospheric Methane and carbon monoxide from SCIAMACHY onboard ENVISAT

Abstract

The UV/Vis/near infrared spectrometer SCIAMACHY on board the European ENVISAT satellite enables total column retrieval of atmospheric methane with high sensitivity to the lower troposphere. The vertical column density of methane is converted to column averaged mixing ratio by using carbon dioxide retrievals as proxy for the probed atmospheric column. For this purpose, we apply concurrent total column measurements of CO_2 in combination with modeled column-averaged CO_2 mixing ratios. Possible systematic errors are discussed in detail while the precision error is 1.8% on average. This paper focuses on methane retrievals from January 2003 through December 2004. The measurements with global coverage over continents are compared with model results from the chemistry–transport model TM4. In the retrievals, the north-south gradient as well as regions with enhanced methane levels can be clearly identified. The highest abundances are found in the Red Basin of China, followed by northern South America, the Gangetic plains of India and central parts of Africa. Especially the abundances in northern South America and the Red Basin are generally higher than modeled. Further, we present the seasonal variations within the investigated time period. Peak values in Asia due to rice emissions are observed from August through October. We expand earlier investigations that suggest underestimated emissions in the tropics. It is shown that these underestimations show a seasonal behavior that peaks from August through December. The global measurements may be used for inverse modeling and are thus an important step towards better quantification of the methane budget.

Additional Information

© 2006 European Space Agency. Most importantly the authors would like to thank all scientists and engineers involved in the European Space Agency's ENVISAT/SCIAMACHY mission, especially John Burrows and his team from the University of Bremen. We thank the Netherlands SCIAMACHY Data Center, in particular Ankie Piters and John van de Vegte from KNMI, for their invaluable assistance in transferring the data set to Heidelberg. We wish to acknowledge the European Commission for supporting the 5th Framework Programme RTD project EVERGREEN (contract number EVG1-CT-2002-00079). We further acknowledge exchange of information within the EU 6th FP Network of Excellence ACCENT (http://www.accent-network.org/).

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