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Titel |
Long-term analysis of carbon dioxide and methane column-averaged mole fractions retrieved from SCIAMACHY |
VerfasserIn |
Oliver Schneising, Michael Buchwitz, Maximilian Reuter, Jens Heymann, Heinrich Bovensmann, John P. Burrows |
Konferenz |
EGU General Assembly 2010
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Medientyp |
Artikel
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Sprache |
Englisch
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Digitales Dokument |
PDF |
Erschienen |
In: GRA - Volume 12 (2010) |
Datensatznummer |
250033491
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Zusammenfassung |
Carbon dioxide (CO2) and methane (CH4) are the two most important anthropogenic
greenhouse gases contributing to climate change. Despite their importance our knowledge
about their variable natural and anthropogenic sources and sinks has significant gaps.
Satellite observations can add important global scale information on greenhouse
gas sources and sinks provided the data are accurate and precise enough and are
sensitive to the lowest atmospheric layers where the variability is largest. High
sensitivity to near-surface greenhouse gas concentration changes can be achieved
using reflected solar radiation in the near-infrared/shortwave-infrared (NIR/SWIR)
spectral region. SCIAMACHY onboard ENVISAT (launch 2002) was the first and is
now besides TANSO onboard GOSAT (launch 2009) the only satellite instrument
currently in space covering important absorption bands of both gases in this spectral
range.
Global SCIAMACHY nadir observations from the time period 2003-2009 have been used
to retrieve carbon dioxide and methane column-averaged mole fractions (which are the
quantities needed for inverse modelling to get information on the sources and sinks)
constituting seven years of greenhouse gas information derived from European EO data
and offering temporal overlap with GOSAT. These new improved WFM-DOAS
multi-year global data sets extending afore existing retrievals will be presented and
discussed including an analysis of the long-term characteristics and comparison of the
retrieved mole fractions with independent data, e.g., a first analysis of how the
SCIAMACHY results compare with GOSAT retrievals for the overlapping time period. |
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