A joint effort to deliver satellite retrieved atmospheric CO<sub>2</sub> concentrations for surface flux inversions: the ensemble median algorithm EMMA
Author:
Reuter M.,Bösch H.,Bovensmann H.,Bril A.,Buchwitz M.,Butz A.,Burrows J. P.,O'Dell C. W.,Guerlet S.,Hasekamp O.,Heymann J.,Kikuchi N.,Oshchepkov S.,Parker R.,Pfeifer S.,Schneising O.,Yokota T.,Yoshida Y.
Abstract
Abstract. We analyze an ensemble of seven XCO2 retrieval algorithms for SCIAMACHY and GOSAT. The ensemble spread can be interpreted as regional uncertainty and can help to identify locations for new TCCON validation sites. Additionally, we introduce the ensemble median algorithm EMMA combining individual soundings of the seven algorithms into one new dataset. The ensemble takes advantage of the algorithms' independent developments. We find ensemble spreads being often <1 ppm but rising up to 2 ppm especially in the tropics and East Asia. On the basis of gridded monthly averages, we compare EMMA and all individual algorithms with TCCON and CarbonTracker model results (potential outliers, north/south gradient, seasonal (peak-to-peak) amplitude, standard deviation of the difference). Our findings show that EMMA is a promising candidate for inverse modeling studies. Compared to CarbonTracker, the satellite retrievals find consistently larger north/south gradients (by 0.3 ppm–0.9 ppm) and seasonal amplitudes (by 1.5 ppm–2.0 ppm).
Funder
European Commission
Publisher
Copernicus GmbH
Reference37 articles.
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