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Delayed Mode Monitoring of Greenhouse Gases

Delayed mode monthly mean fields
Delayed mode monthly mean fields Monthly mean pressure level fields for CH4 and CO2 from the delayed-mode production stream. The delayed-mode stream is running about 5 months behind real-time to make maximum use of satellite and in-situ observations that are currently not provided in real-time. The output of the delayed-mode monitoring is used in the delayed-mode flux inversions.

Delayed mode monthly mean total columns
Delayed mode monthly mean total columns Monthly mean total column fields for CH4 and CO2 from the delayed-mode production stream. The delayed-mode stream is running about 5 months behind real-time to make maximum use of satellite and in-situ observations that are currently not provided in real-time. The output of the delayed-mode monitoring is used in the delayed-mode flux inversions.

Delayed mode methane flux inversions
Delayed mode methane flux inversions

These monthly mean plots illustrate the flux inversion from the MACC delayed-mode analysis of CH4 concentrations, based on the TM5-4DVAR inverse modeling system [Bergamaschi et al., 2009]. While the MACC delayed-mode analysis assimilates SCIAMACHY CH4 retrievals into the IFS model, we use in addition also high accuracy surface measurements from the NOAA global cooperative air sampling network in the inversion. The latter constrain significantly the surface mixing ratios in remote regions (ocean) and allow deriving corrections for potential small latitudinal or seasonal biases of the satellite data. 3D fields of CH4 mixing ratios from the TM5-4DVAR inversion are available upon request.

While the results shown here present our first best effort, using NRT delayed-mode observations with some preliminary quality control, the inversion set-up is still being improved and therefore results should not be taken as final.

Acknowledgments

We thank Ed Dlugokencky for provision of surface measurements from the NOAA Earth System Research Laboratory (ESRL) global cooperative air sampling network.

References

Bergamaschi, P., C. Frankenberg, J. F. Meirink, M. Krol, M. G. Villani, S. Houweling, F. Dentener, E. J. Dlugokencky, J. B. Miller, L. V. Gatti, A. Engel, and I. Levin, Inverse modeling of global and regional CH4 emissions using SCIAMACHY satellite retrievals, J. Geophys. Res., 114, doi:10.1029/2009JD012287, 2009.