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| Titel |
Consistent satellite XCO2 retrievals from SCIAMACHY and GOSAT using the BESD algorithm |
| VerfasserIn |
J. Heymann, M. Reuter, M. Hilker, M. Buchwitz, O. Schneising, H. Bovensmann, J. P. Burrows, A. Kuze, H. Suto, N. M. Deutscher, M. K. Dubey, D. W. T. Griffith, F. Hase, S. Kawakami, R. Kivi, I. Morino, C. Petri, C. Roehl, M. Schneider, V. Sherlock, R. Sussmann, V. A. Velazco, T. Warneke, D. Wunch |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1867-1381
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| Digitales Dokument |
URL |
| Erschienen |
In: Atmospheric Measurement Techniques ; 8, no. 7 ; Nr. 8, no. 7 (2015-07-24), S.2961-2980 |
| Datensatznummer |
250116491
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| Publikation (Nr.) |
 copernicus.org/amt-8-2961-2015.pdf |
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| Zusammenfassung |
| Consistent and accurate long-term data sets of global atmospheric
concentrations of carbon dioxide (CO2) are required for carbon cycle and
climate-related research. However, global data sets based on satellite
observations may suffer from inconsistencies originating from the use of
products derived from different satellites as needed to cover a long enough
time period. One reason for inconsistencies can be the use of different
retrieval algorithms. We address this potential issue by applying the same
algorithm, the Bremen Optimal Estimation DOAS (BESD) algorithm, to different
satellite instruments, SCIAMACHY on-board ENVISAT (March 2002–April 2012) and
TANSO-FTS on-board GOSAT (launched in January 2009), to retrieve XCO2, the
column-averaged dry-air mole fraction of CO2. BESD has been initially
developed for SCIAMACHY XCO2 retrievals. Here, we present the first
detailed assessment of the new GOSAT BESD XCO2 product. GOSAT BESD XCO2
is a product generated and delivered to the MACC project for assimilation
into ECMWF's Integrated Forecasting System. We describe the
modifications of the BESD algorithm needed in order to retrieve XCO2 from
GOSAT and present detailed comparisons with ground-based observations of
XCO2 from the Total Carbon Column Observing Network (TCCON). We discuss
detailed comparison results between all three XCO2 data sets (SCIAMACHY,
GOSAT and TCCON). The comparison results demonstrate the good consistency
between SCIAMACHY and GOSAT XCO2. For example, we found a mean
difference for daily averages of −0.60 ± 1.56 ppm (mean
difference ± standard deviation) for GOSAT–SCIAMACHY (linear
correlation coefficient r=0.82), −0.34 ± 1.37 ppm (r = 0.86)
for GOSAT–TCCON and 0.10 ± 1.79 ppm (r = 0.75) for
SCIAMACHY–TCCON. The remaining differences between GOSAT and SCIAMACHY are
likely due to non-perfect collocation (± 2 h,
10° x 10° around TCCON sites), i.e. the observed air
masses are not exactly identical but likely also due to a still non-perfect
BESD retrieval algorithm, which will be continuously improved in the future.
Our overarching goal is to generate a satellite-derived XCO2 data set
appropriate for climate and carbon cycle research covering the longest
possible time period. We therefore also plan to extend the existing SCIAMACHY
and GOSAT data set discussed here by also using data from other missions
(e.g. OCO-2, GOSAT-2, CarbonSat) in the future. |
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