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Buchwitz, Michael; Reuter, Maximilian; Schneising, Oliver; Noel, Stefan; Gier, Bettina; Bovensmann, Heinrich; Burrows, John P.; Bösch, Hartmut; Anand, Jasdeep; Parker, Robert J.; Somkuti, Peter; Detmers, Rob G.; Hasekamp, Otto P.; Aben, Ilse; Butz, Andre; Kuze, Akihiko; Suto, Hiroshi; Yoshida, Yukio; Crisp, David und O'Dell, Christopher (2018): Computation and analysis of atmospheric carbon dioxide annual mean growth rates from satellite observations during 2003-2016. In: Atmospheric Chemistry and Physics, Bd. 18, Nr. 23 [PDF, 3MB]

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Abstract

The growth rate of atmospheric carbon dioxide (CO2) reflects the net effect of emissions and uptake resulting from anthropogenic and natural carbon sources and sinks. Annual mean CO2 growth rates have been determined from satellite retrievals of column-averaged dry-air mole fractions of CO2, i.e. XCO2, for the years 2003 to 2016. The XCO2 growth rates agree with National Oceanic and Atmospheric Administration (NOAA) growth rates from CO2 surface observations within the uncertainty of the satellite-derived growth rates (mean difference +/- standard deviation: 0.0 +/- 0.3 ppm year(-1);R: 0.82). This new and independent data set confirms record-large growth rates of around 3 ppm year(-1) in 2015 and 2016, which are attributed to the 2015-2016 El Nino. Based on a comparison of the satellite-derived growth rates with human CO2 emissions from fossil fuel combustion and with El Nino Southern Oscillation (ENSO) indices, we estimate by how much the impact of ENSO dominates the impact of fossil-fuel-burning-related emissions in explaining the variance of the atmospheric CO2 growth rate. Our analysis shows that the ENSO impact on CO2 growth rate variations dominates that of human emissions throughout the period 2003-2016 but in particular during the period 2010-2016 due to strong La Nina and El Nino events. Using the derived growth rates and their uncertainties, we estimate the probability that the impact of ENSO on the variability is larger than the impact of human emissions to be 63 % for the time period 2003-2016. If the time period is restricted to 2010-2016, this probability increases to 94%.

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