 |
| Titel |
SCIAMACHY WFM-DOAS XCO2: comparison with CarbonTracker XCO2 focusing on aerosols and thin clouds |
| VerfasserIn |
J. Heymann, O. Schneising, M. Reuter, M. Buchwitz, V. V. Rozanov, V. A. Velazco, H. Bovensmann, J. P. Burrows |
| Medientyp |
Artikel
|
| Sprache |
Englisch
|
| ISSN |
1867-1381
|
| Digitales Dokument |
URL |
| Erschienen |
In: Atmospheric Measurement Techniques ; 5, no. 8 ; Nr. 5, no. 8 (2012-08-13), S.1935-1952 |
| Datensatznummer |
250003048
|
| Publikation (Nr.) |
 copernicus.org/amt-5-1935-2012.pdf |
|
|
|
|
|
| Zusammenfassung |
Carbon dioxide (CO2) is the most important greenhouse gas whose
atmospheric loading has been significantly increased by anthropogenic
activity leading to global warming. Accurate measurements and models
are needed in order to reliably predict our future climate. This,
however, has challenging requirements. Errors in measurements and
models need to be identified and minimised.
In this context, we present a comparison between satellite-derived
column-averaged dry air mole fractions of CO2, denoted XCO2,
retrieved from SCIAMACHY/ENVISAT using the WFM-DOAS (weighting function modified differential optical
absorption spectroscopy) algorithm, and
output from NOAA's global CO2 modelling and assimilation system
CarbonTracker. We investigate to what extent differences between these
two data sets are influenced by systematic retrieval errors due to
aerosols and unaccounted clouds. We analyse seven years of SCIAMACHY
WFM-DOAS version 2.1 retrievals (WFMDv2.1) using CarbonTracker version
2010.
We investigate to what extent the difference between SCIAMACHY and
CarbonTracker XCO2 are temporally and spatially correlated with
global aerosol and cloud data sets. For this purpose, we use a global
aerosol data set generated within the European GEMS project, which
is based on assimilated MODIS satellite data. For clouds, we use a
data set derived from CALIOP/CALIPSO.
We find significant correlations of the SCIAMACHY minus CarbonTracker
XCO2 difference with thin clouds over the Southern Hemisphere.
The maximum temporal correlation we find for Darwin, Australia (r2 = 54%).
Large temporal correlations with thin clouds are also observed
over other regions of the Southern Hemisphere (e.g. 43% for South
America and 31% for South Africa). Over the Northern Hemisphere the
temporal correlations are typically much lower. An exception is India,
where large temporal correlations with clouds and aerosols have also
been found. For all other regions the temporal correlations with aerosol
are typically low. For the spatial correlations the picture is less
clear. They are typically low for both aerosols and clouds, but depending
on region and season, they may exceed 30% (the maximum value of 46%
has been found for Darwin during September to November).
Overall we find that the presence of thin clouds can potentially explain
a significant fraction of the difference between SCIAMACHY WFMDv2.1
XCO2 and CarbonTracker over the Southern Hemisphere. Aerosols
appear to be less of a problem. Our study indicates that the quality
of the satellite derived XCO2 will significantly benefit from
a reduction of scattering related retrieval errors at least for the
Southern Hemisphere. |
| |
|
| Teil von |
|
|
|
|
|
|
|
|