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The Greenhouse Gas Climate Change Initiative (GHG-CCI) : Comparison and quality assessment of near-surface-sensitive satellite-derived CO2 and CH4 global data sets

Buchwitz, M.; Reuter, M.; Schneising, O.; Boesch, H.; Guerlet, S.; Dils, B.; Aben, I.; Armante, R.; Bergamaschi, P. and Blumenstock, T., et al. (2015) In Remote Sensing of Environment 162. p.344-362
Abstract

The GHG-CCI project is one of several projects of the European Space Agency's (ESA) Climate Change Initiative (CCI). The goal of the CCI is to generate and deliver data sets of various satellite-derived Essential Climate Variables (ECVs) in line with GCOS (Global Climate Observing System) requirements. The "ECV Greenhouse Gases" (ECV GHG) is the global distribution of important climate relevant gases - atmospheric CO2 and CH4 - with a quality sufficient to obtain information on regional CO2 and CH4 sources and sinks. Two satellite instruments deliver the main input data for GHG-CCI: SCIAMACHY/ENVISAT and TANSO-FTS/GOSAT. The first order priority goal of GHG-CCI is the further development of... (More)

The GHG-CCI project is one of several projects of the European Space Agency's (ESA) Climate Change Initiative (CCI). The goal of the CCI is to generate and deliver data sets of various satellite-derived Essential Climate Variables (ECVs) in line with GCOS (Global Climate Observing System) requirements. The "ECV Greenhouse Gases" (ECV GHG) is the global distribution of important climate relevant gases - atmospheric CO2 and CH4 - with a quality sufficient to obtain information on regional CO2 and CH4 sources and sinks. Two satellite instruments deliver the main input data for GHG-CCI: SCIAMACHY/ENVISAT and TANSO-FTS/GOSAT. The first order priority goal of GHG-CCI is the further development of retrieval algorithms for near-surface-sensitive column-averaged dry air mole fractions of CO2 and CH4, denoted XCO2 and XCH4, to meet the demanding user requirements. GHG-CCI focuses on four core data products: XCO2 from SCIAMACHY and TANSO and XCH4 from the same two sensors. For each of the four core data products at least two candidate retrieval algorithms have been independently further developed and the corresponding data products have been quality-assessed and inter-compared. This activity is referred to as "Round Robin" (RR) activity within the CCI. The main goal of the RR was to identify for each of the four core products which algorithms should be used to generate the Climate Research Data Package (CRDP). The CRDP will essentially be the first version of the ECV GHG. This manuscript gives an overview of the GHG-CCI RR and related activities. This comprises the establishment of the user requirements, the improvement of the candidate retrieval algorithms and comparisons with ground-based observations and models. The manuscript summarizes the final RR algorithm selection decision and its justification. Comparison with ground-based Total Carbon Column Observing Network (TCCON) data indicates that the "breakthrough" single measurement precision requirement has been met for SCIAMACHY and TANSO XCO2 (<3ppm) and TANSO XCH4 (<17ppb). The achieved relative accuracy for XCH4 is 3-15ppb for SCIAMACHY and 2-8ppb for TANSO depending on algorithm and time period. Meeting the 0.5ppm systematic error requirement for XCO2 remains a challenge: approximately 1ppm has been achieved at the validation sites but also larger differences have been found in regions remote from TCCON. More research is needed to identify the causes for the observed differences. In this context GHG-CCI suggests taking advantage of the ensemble of existing data products, for example, via the EnseMble Median Algorithm (EMMA).

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@article{78bcee13-384e-462a-956b-6f99dfc28c54,
  abstract     = {<p>The GHG-CCI project is one of several projects of the European Space Agency's (ESA) Climate Change Initiative (CCI). The goal of the CCI is to generate and deliver data sets of various satellite-derived Essential Climate Variables (ECVs) in line with GCOS (Global Climate Observing System) requirements. The "ECV Greenhouse Gases" (ECV GHG) is the global distribution of important climate relevant gases - atmospheric CO<sub>2</sub> and CH<sub>4</sub> - with a quality sufficient to obtain information on regional CO<sub>2</sub> and CH<sub>4</sub> sources and sinks. Two satellite instruments deliver the main input data for GHG-CCI: SCIAMACHY/ENVISAT and TANSO-FTS/GOSAT. The first order priority goal of GHG-CCI is the further development of retrieval algorithms for near-surface-sensitive column-averaged dry air mole fractions of CO<sub>2</sub> and CH<sub>4</sub>, denoted XCO<sub>2</sub> and XCH<sub>4</sub>, to meet the demanding user requirements. GHG-CCI focuses on four core data products: XCO<sub>2</sub> from SCIAMACHY and TANSO and XCH<sub>4</sub> from the same two sensors. For each of the four core data products at least two candidate retrieval algorithms have been independently further developed and the corresponding data products have been quality-assessed and inter-compared. This activity is referred to as "Round Robin" (RR) activity within the CCI. The main goal of the RR was to identify for each of the four core products which algorithms should be used to generate the Climate Research Data Package (CRDP). The CRDP will essentially be the first version of the ECV GHG. This manuscript gives an overview of the GHG-CCI RR and related activities. This comprises the establishment of the user requirements, the improvement of the candidate retrieval algorithms and comparisons with ground-based observations and models. The manuscript summarizes the final RR algorithm selection decision and its justification. Comparison with ground-based Total Carbon Column Observing Network (TCCON) data indicates that the "breakthrough" single measurement precision requirement has been met for SCIAMACHY and TANSO XCO<sub>2</sub> (&lt;3ppm) and TANSO XCH<sub>4</sub> (&lt;17ppb). The achieved relative accuracy for XCH<sub>4</sub> is 3-15ppb for SCIAMACHY and 2-8ppb for TANSO depending on algorithm and time period. Meeting the 0.5ppm systematic error requirement for XCO<sub>2</sub> remains a challenge: approximately 1ppm has been achieved at the validation sites but also larger differences have been found in regions remote from TCCON. More research is needed to identify the causes for the observed differences. In this context GHG-CCI suggests taking advantage of the ensemble of existing data products, for example, via the EnseMble Median Algorithm (EMMA).</p>},
  author       = {Buchwitz, M. and Reuter, M. and Schneising, O. and Boesch, H. and Guerlet, S. and Dils, B. and Aben, I. and Armante, R. and Bergamaschi, P. and Blumenstock, T. and Bovensmann, H. and Brunner, D. and Buchmann, B. and Burrows, J. P. and Butz, A. and Chédin, A. and Chevallier, F. and Crevoisier, C. D. and Deutscher, N. M. and Frankenberg, C. and Hase, F. and Hasekamp, O. P. and Heymann, J. and Kaminski, T. and Laeng, A. and Lichtenberg, G. and De Mazière, M. and Noël, S. and Notholt, J. and Orphal, J. and Popp, C. and Parker, R. and Scholze, M. and Sussmann, R. and Stiller, G. P. and Warneke, T. and Zehner, C. and Bril, A. and Crisp, D. and Griffith, D. W.T. and Kuze, A. and O'Dell, C. and Oshchepkov, S. and Sherlock, V. and Suto, H. and Wennberg, P. and Wunch, D. and Yokota, T. and Yoshida, Y.},
  issn         = {0034-4257},
  keyword      = {Carbon dioxide,Climate change,GOSAT,Greenhouse gases,Methane,SCIAMACHY},
  language     = {eng},
  month        = {06},
  pages        = {344--362},
  publisher    = {Elsevier},
  series       = {Remote Sensing of Environment},
  title        = {The Greenhouse Gas Climate Change Initiative (GHG-CCI) : Comparison and quality assessment of near-surface-sensitive satellite-derived CO<sub>2</sub> and CH<sub>4</sub> global data sets},
  url          = {http://dx.doi.org/10.1016/j.rse.2013.04.024},
  volume       = {162},
  year         = {2015},
}