Sergey Oshchepkov, Andrey Bril, Tatsuya Yokota, Paul O. Wennberg, Nicholas M. Deutscher, Debra Wunch, Geoffrey C. Toon, Yukio Yoshida, Christopher W. O'Dell, David Crisp, Charles E. Miller, Christian Frankenberg, André Butz, Ilse Aben, Sandrine Guerlet, Otto Hasekamp, Hartmut Boesch, Austin Cogan, Robert Parker, David Griffith, Ronald Macatangay, Justus Notholt, Ralf Sussmann, Markus Rettinger, Vanessa Sherlock, John Robinson, Esko Kyrö, Pauli Heikkinen, Dietrich G. Feist, Isamu Morino, Nikolay Kadygrov, Dmitry Belikov, Shamil Maksyutov, Tsuneo Matsunaga, Osamu Uchino, Hiroshi Watanabe
- This report is the second in a series of companion papers describing the effects of atmospheric light scattering in observations of atmospheric carbon dioxide (CO2) by the Greenhouse gases Observing SATellite (GOSAT), in orbit since 23 January 2009. Here we summarize the retrievals from six previously published algorithms; retrieving column-averaged dry air mole fractions of CO2 (XCO2) during 22 months of operation of GOSAT from June 2009. First, we compare data products from each algorithm with ground-based remote sensing observations by Total Carbon Column Observing Network (TCCON). Our GOSAT-TCCON coincidence criteria select satellite observations within a 5° radius of 11 TCCON sites. We have compared the GOSAT-TCCON XCO2 regression slope, standard deviation, correlation and determination coefficients, and global and station-to-station biases. The best agreements with TCCON measurements were detected for NIES 02.xx and RemoTeC. Next, the impact of atmospheric light scattering onThis report is the second in a series of companion papers describing the effects of atmospheric light scattering in observations of atmospheric carbon dioxide (CO2) by the Greenhouse gases Observing SATellite (GOSAT), in orbit since 23 January 2009. Here we summarize the retrievals from six previously published algorithms; retrieving column-averaged dry air mole fractions of CO2 (XCO2) during 22 months of operation of GOSAT from June 2009. First, we compare data products from each algorithm with ground-based remote sensing observations by Total Carbon Column Observing Network (TCCON). Our GOSAT-TCCON coincidence criteria select satellite observations within a 5° radius of 11 TCCON sites. We have compared the GOSAT-TCCON XCO2 regression slope, standard deviation, correlation and determination coefficients, and global and station-to-station biases. The best agreements with TCCON measurements were detected for NIES 02.xx and RemoTeC. Next, the impact of atmospheric light scattering on XCO2 retrievals was estimated for each data product using scan by scan retrievals of light path modification with the photon path length probability density function (PPDF) method. After a cloud pre-filtering test, approximately 25% of GOSAT soundings processed by NIES 02.xx, ACOS B2.9, and UoL-FP: 3G and 35% processed by RemoTeC were found to be contaminated by atmospheric light scattering. This study suggests that NIES 02.xx and ACOS B2.9 algorithms tend to overestimate aerosol amounts over bright surfaces, resulting in an underestimation of XCO2 for GOSAT observations. Cross-comparison between algorithms shows that ACOS B2.9 agrees best with NIES 02.xx and UoL-FP: 3G while RemoTeC XCO2 retrievals are in a best agreement with NIES PPDF-D.…
