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Reuter, M.; Bovensmann, H.; Buchwitz, M.; Burrows, J. P.; Connor, B. J.; Deutscher, N. M.; Griffith, D. W. T.; Heymann, J.; Keppel-Aleks, G.; Messerschmidt, J.; Notholt, J.; Petri, C.; Robinson, J.; Schneising, O.; Sherlock, V.; Velazco, V.; Warneke, T.; Wennberg, P. O.; Wunch, D.
Journal of Geophysical Research: Atmospheres, 27 February 2011, Letnik: 116, Številka: D4Journal Article
The Bremen Optimal Estimation differential optical absorption spectroscopy (DOAS) (BESD) algorithm for satellite based retrievals of XCO2 (the column‐average dry‐air mole fraction of atmospheric CO2) has been applied to Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY) data. It uses measurements in the O2‐A absorption band to correct for scattering of undetected clouds and aerosols. Comparisons with precise and accurate ground‐based Fourier transform spectrometer (FTS) measurements at four Total Carbon Column Observing Network (TCCON) sites have been used to quantify the quality of the new SCIAMACHY XCO2 data set. Additionally, the results have been compared to NOAA's assimilation system CarbonTracker. The comparisons show that the new retrieval meets the expectations from earlier theoretical studies. We find no statistically significant regional XCO2 biases between SCIAMACHY and the FTS instruments. However, the standard error of the systematic differences is in the range of 0.2 ppm and 0.8 ppm. The XCO2 single‐measurement precision of 2.5 ppm is similar to theoretical estimates driven by instrumental noise. There are no significant differences found for the year‐to‐year increase as well as for the average seasonal amplitude between SCIAMACHY XCO2 and the collocated FTS measurements. Comparison of the year‐to‐year increase and also of the seasonal amplitude of CarbonTracker exhibit significant differences with the corresponding FTS values at Darwin. Here the differences between SCIAMACHY and CarbonTracker are larger than the standard error of the SCIAMACHY values. The difference of the seasonal amplitude exceeds the significance level of 2 standard errors. Therefore, our results suggest that SCIAMACHY may provide valuable additional information about XCO2, at least in regions with a low density of in situ measurements.
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