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A joint effort to deliver satellite retrieved atmospheric CO[subscript 2] concentrations for surface flux inversions: the ensemble median algorithm EMMA

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posted on 2013-10-15, 15:29 authored by M. Reuter, H. Bösch, H. Bovensmann, A. Bril, M. Buchwitz, A. Butz, J.P. Burrows, C.W. O'Dell, S. Guerlet, O. Hasekamp, J. Heymann, N. Kikuchi, S. Oshchepkov, R. Parker, S. Pfeifer, O. Schneising, T. Yokota, Y. Yoshida
We analyze an ensemble of seven XCO[subscript 2] retrieval algorithms for SCIAMACHY (scanning imaging absorption spectrometer of atmospheric chartography) and GOSAT (greenhouse gases observing satellite). The ensemble spread can be interpreted as regional uncertainty and can help to identify locations for new TCCON (total carbon column observing network) validation sites. Additionally, we introduce the ensemble median algorithm EMMA combining individual soundings of the seven algorithms into one new data set. 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 0.3–0.9 ppm) and seasonal amplitudes (by 1.5–2.0 ppm).

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Citation

Atmospheric Chemistry and Physics, 2013, 13 (4), 1771-1780

Version

  • VoR (Version of Record)

Published in

Atmospheric Chemistry and Physics

Publisher

Copernicus GmbH (Copernicus Publications) on behalf of the European Geosciences Union (EGU)

issn

1680-7316

eissn

1680-7324

Copyright date

2013

Available date

2013-10-15

Publisher version

http://www.atmos-chem-phys.net/13/1771/2013/acp-13-1771-2013.html

Language

en

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