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dc.contributor.authorDE BEEK Ruedigeren_GB
dc.contributor.authorBUCHWITZ Michaelen_GB
dc.contributor.authorNOEL Stefanen_GB
dc.contributor.authorBURROWS Johnen_GB
dc.contributor.authorBOVENSMANN Heinrichen_GB
dc.contributor.authorBRUNS M.en_GB
dc.contributor.authorBREMER Holgeren_GB
dc.contributor.authorBERGAMASCHI PETERen_GB
dc.contributor.authorKOERNER Stefanen_GB
dc.contributor.authorHEIMANN Martinen_GB
dc.contributor.authorSCHNEISING O.en_GB
dc.contributor.authorKHLYSTOVA I.en_GB
dc.date.accessioned2010-02-25T17:01:51Z-
dc.date.available2006-02-20en_GB
dc.date.available2010-02-25T17:01:51Z-
dc.date.issued2006en_GB
dc.date.submitted2006-02-16en_GB
dc.identifier.citationATMOSPHERIC CHEMISTRY AND PHYSICS vol. 6 no. Atmospheric carbon gases retrieved from SCIAMACHY by WFM-DOAS: version 0.5 CO and CH4 and impact of calibration improvements on CO2 retrieval p. 363-399en_GB
dc.identifier.urihttp://publications.jrc.ec.europa.eu/repository/handle/JRC32688-
dc.description.abstractThe three carbon gases carbon monoxide (CO), carbon dioxide (CO2), and methane (CH4) are important atmospheric constituents affecting air quality and climate. The nadir spectra of reflected and scattered solar radiation in the near-infrared region, as observed by SCIAMACHY/ENVISAT, contain information on the vertical 5 columns of these gases. A modified DOAS algorithm (WFM–DOAS) has been developed to retrieve this information. The main SCIAMACHY/WFM–DOAS data products are CO vertical columns and dry-air column averaged mixing ratios of methane and CO2, denoted XCH4 and XCO2, respectively. For CO and methane we present new results 10 obtained with an improved version of WFM–DOAS (v0.5). The SCIAMACHY data products have been compared with global reference data (MOPITT for CO, TM5 model simulations for XCH4). The comparisons indicate that major problems of the previous version of WFM–DOAS (v0.4x) related to the varying ice-layer on the SCIAMACHY channel 8 detector have been solved. On average, the SCIAMACHY CO agrees within 15 10% (standard deviation 30%) with MOPITT but regionally, especially over northern South America, large differences have been found (up to about 80%). For methane we present global and regional maps which are compared to TM5 model simulations performed using standard emission inventories. Overall, there is good agreement but regionally there are substantial differences, e.g., due to limitations of current methane 20 emission inventories. It still needs to be assessed by how much emission inventories can be improved by using the SCIAMACHY data. Concerning CO2 we present a comparison of SCIAMACHY XCO2 (WFM-DOAS v0.4) with TM3 model simulations over Park Falls, Wisconsin, USA. The peak-to-peak XCO2 variability as measured by SCIAMACHY (seasonal cycle of year 2003–2005 data) is _13 ppmv, in good agree25 ment with preliminary analysis of ground-based Fourier Transform Spectrometer (FTS) measurements, which is a factor of 2.3 larger than the XCO2 variability of TM3 model simulation for 2003. Park Falls is one of the few FTS ground stations which measure column averaged CO2 and detailed comparison with these measurements (after data release) will help identifying the reason for the observed differences between SCIAMACHY and global (atmospheric) carbon models such as TM3 as reported here and in previous studies. For all three carbon gases we present regional results including seasonal variation focusing on China.en_GB
dc.description.sponsorshipJRC.H.2-Climate changeen_GB
dc.format.mediumOnlineen_GB
dc.languageENGen_GB
dc.publisherEUROPEAN GEOSCIENCES UNIONen_GB
dc.relation.ispartofseriesJRC32688en_GB
dc.titleAtmospheric Carbon Gases Retrieved from SCIAMACHY by WFM-DOAS: Version 0.5 CO and CH4 and Impact of Calibration Improvements on CO2 Retrievalen_GB
dc.typeArticles in periodicals and booksen_GB
JRC Directorate:Sustainable Resources

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