Computation and analysis of atmospheric carbon dioxide annual mean growth rates from satellite observations during 2003–2016

Abstract

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 Niño. Based on a comparison of the satellite-derived growth rates with human CO2 emissions from fossil fuel combustion and with El Niño 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 Niña and El Niño 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 %.

Comparison of Continuous In-Situ CO2 Measurements with Co-Located Column-Averaged XCO2 TCCON/Satellite Observations and CarbonTracker Model Over the Zugspitze Region

“…The STL-decomposed trend components were calculated into annual CO2 growth rates and overall mean growth rates (see Figure 4). These results perfectly matched those found by Buchwitz et al [27], who showed a mean difference between the satellite-derived and NOAA CO2 surface observation annual mean growth rates of 0.0 ± 0.3 ppm yr −1 (± 1 standard deviation). Their reported "record-large" growth rate over 2015-2016 of around 3 ppm yr −1 due to an El Niño event [43][44][45] was also clearly observed in all series of our study (ranging from 2.77 to 3.56 ppm yr −1 ).…”

“…The CO 2 annual growth rate was calculated from the STL-decomposed trend component based on the definition by NOAA [2], following the instructions in Buchwitz et al [27]. For each month, we calculated the difference in CO 2 or XCO 2 between this month and the same month from the previous year.…”

“…Satellite data were taken from a merged CO 2 satellite product described in Buchwitz et al [27] (available at https://cds.climate.copernicus.eu/) from the Scanning Imaging Absorption Spectrometer for Atmospheric Cartography sensor (SCIAMACHY) on the Environmental Satellite (ENVISAT) from 2002 to 2012, and the subunit Fourier Transform Spectrometer of the Thermal And Near-infrared Sensor for carbon Observation sensor (TANSO-FTS) on the GOSAT since 2009, referred to as XCO 2_SAT_Obs4MIPs . To make the satellite XCO 2 time-series more comparable with in-situ measurements on the temporal scale, measurements from the OCO-2 satellite launched and operated since July 2014 were further included [28].…”

“…A similar effect was also reported The levels of correlation coefficients were comparable with similar studies. Buchwitz et al [27] reported a correlation coefficient of 0.82 between the satellite-derived growth rates and the NOAA global growth rates over 2003-2016. This higher value is assumed to be due to the global averaging effect, while our results show a more specific signature of the Zugspitze region.…”

A methodology to constrain carbon dioxide emissions from coal-fired power plants using satellite observations of co-emitted nitrogen dioxide

“…Anthropogenic CO 2 emissions have been estimated from space-based CO 2 observations, but the existing satellite CO 2 sensors are designed to provide constraints on natural CO 2 sources and sinks (Basu et al, 2013;Houweling et al, 2015) and thus their capability for monitoring anthropogenic point sources is limited (Nassar et al, 2017). Observations from sensors, including the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIA-MACHY; Burrows et al, 1995), Greenhouse gases Observing SATellite (GOSAT; Yokota et al, 2009), and Orbiting Carbon Observatory-2 (OCO-2; Crisp, 2015), show statistically significant enhancements over metropolitan regions (Kort et al, 2012;Schneising et al, 2013;Janardanan et al, 2016;Buchwitz et al, 2018;Reuter et al, 2019;. However, very few studies have focused on individual point sources.…”