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Title: Consistent satellite XCO2 retrievals from SCIAMACHY and GOSAT using the BESD algorithm

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 (IFS). 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,more » GOSAT and TCCON). The comparison results demonstrate the good consistency between the SCIAMACHY and the 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° × 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 using also data from other missions (e.g., OCO-2, GOSAT-2, CarbonSat) in the future.« less
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  1. University of Bremen, Bremen (Germany)
  2. Japan Aerospace Exploration Agency (JAXA), Tsukuba (Japan)
  3. University of Bremen, Bremen (Germany); Univ. of Wollongong, Wollongong (Australia)
  4. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
  5. University of Wollongong, Wollongong(Australia)
  6. IMK-ASF, Karlsruhe Institute of Technology (KIT), Karlsruhe (Germany)
  7. Finnish Meteorological Institute, Sodankylä (Finland)
  8. National Institute for Environmental Studies (NIES), Tsukuba (Japan)
  9. California Institute of Technology, Pasadena, CA (United States)
  10. National Institute of Water and Atmospheric Research, Wellington (New Zealand); Lab. de Meteorologie Dynamique, Palaiseau (France)
  11. IMK-IFU, Karlsruhe Institute of Technology (KIT), Garmisch-Partenkirchen (Germany)
Publication Date:
OSTI Identifier:
Grant/Contract Number:
Accepted Manuscript
Journal Name:
Atmospheric Measurement Techniques Discussions (Online)
Additional Journal Information:
Journal Name: Atmospheric Measurement Techniques Discussions (Online); Journal Volume: 8; Journal Issue: 2; Journal ID: ISSN 1867-8610
European Geosciences Union
Research Org:
Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
Sponsoring Org:
Country of Publication:
United States