Abstract
Abstract. 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.
Highlights
Space-based observations of carbon dioxide (CO2) can contribute to the elimination of important knowledge gaps related to the regional sources and sinks of CO2 (Rayner and O’Brien, 2001; Hungershoefer et al, 2010; Schneising et al, 2013, 2014; Reuter et al, 2014b, c)
In order to evaluate the consistency of the satellite data products, we compare the data products with Total Carbon Column Observing Network (TCCON) data for the same time period and perform a direct comparison of the satellite data, i.e. validation results from the overlapping observation years 2010–2011 of SCIAMACHY and gases Observing SATellite (GOSAT) are presented and compared, and a direct comparison of daily means of the data sets and an additional comparison to daily TCCON data are performed
The number of collocations are higher for SCIAMACHY/TCCON compared to GOSAT/TCCON as the time series of Bremen Optimal Estimation DOAS (BESD) SCIAMACHY is longer and more measurements per day were performed by SCIA
Summary
Space-based observations of carbon dioxide (CO2) can contribute to the elimination of important knowledge gaps related to the regional sources and sinks of CO2 (Rayner and O’Brien, 2001; Hungershoefer et al, 2010; Schneising et al, 2013, 2014; Reuter et al, 2014b, c). Near-surface sensitive measurements of column-averaged dry-air mole fractions of CO2 (XCO2) in the short-wave infrared spectral region (SWIR) are well suited for this application. These observations can complement measurements from existing surfacebased greenhouse gas monitoring networks, especially in data-poor regions, by providing data with dense spatial coverage. The SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) on-board the European Space Agency’s (ESA) Environmental Satellite (ENVISAT) (Burrows et al, 1995; Bovensmann et al, 1999), launched in 2002, was in the time period before mid-2009 the only satellite instrument measuring XCO2 with high surface sensitivity. SCIAMACHY had observed the Earth’s atmosphere until the loss of ENVISAT in April 2012
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