HR: 08:30h
AN: B51F-03    [Abstracts]
TI: Inverse Modeling of Atmospheric Methane Emissions Using 4D-Var
AU: * Meirink, J F
EM: j.f.meirink@phys.uu.nl
AF: Institute for Marine and Atmospheric research Utrecht, University of Utrecht, P.O. Box 80005, Utrecht, 3508 TA, Netherlands
AU: Bergamaschi, P
EM: peter.bergamaschi@jrc.it
AF: European Commission DG Joint Research Centre, IES CCU, TP 263, Via Fermi, Ispra, VA I-21020, Italy
AU: Krol, M C
EM: m.c.krol@phys.uu.nl
AF: Institute for Marine and Atmospheric research Utrecht, University of Utrecht, P.O. Box 80005, Utrecht, 3508 TA, Netherlands
AU: Krol, M C
EM: m.c.krol@phys.uu.nl
AF: Wageningen University and Research Centre, P.O. Box 47, Wageningen, 6700 AA, Netherlands
AU: Krol, M C
EM: m.c.krol@phys.uu.nl
AF: Netherlands Institute for Space Research, Sorbonnelaan 2, Utrecht, 3584 CA, Netherlands
AU: Dlugokencky, E J
EM: Ed.Dlugokencky@noaa.gov
AF: NOAA Earth System Research Laboratory, 325 Broadway, Boulder, CO 80305, United States
AU: Frankenberg, C
EM: C.Frankenberg@sron.nl
AF: Netherlands Institute for Space Research, Sorbonnelaan 2, Utrecht, 3584 CA, Netherlands
AU: Gatti, L V
EM: lvgatti@net.ipen.br
AF: Instituto de Pesquisas Energéticas e Nucleares, Av. Lineu Pretes 2242, São Paulo, SP 05508-900, Brazil
AU: Houweling, S
EM: s.houweling@sron.nl
AF: Institute for Marine and Atmospheric research Utrecht, University of Utrecht, P.O. Box 80005, Utrecht, 3508 TA, Netherlands
AU: Houweling, S
EM: s.houweling@sron.nl
AF: Netherlands Institute for Space Research, Sorbonnelaan 2, Utrecht, 3584 CA, Netherlands
AU: Miller, J B
EM: John.B.Miller@noaa.gov
AF: NOAA Earth System Research Laboratory, 325 Broadway, Boulder, CO 80305, United States
AU: Villani, M G
EM: maria-gabriella.villani@jrc.it
AF: European Commission DG Joint Research Centre, IES CCU, TP 263, Via Fermi, Ispra, VA I-21020, Italy
AB: A four-dimensional variational (4D-Var) data assimilation system for inverse modeling of atmospheric CH₄ emissions is presented. The system is based on the TM5 atmospheric transport model. It can be used for assimilating large volumes of CH₄ measurements, in particular satellite retrievals, and at the same time it enables the optimization of a large number of model parameters. We present the results of global inversions and coupled global-regional inversions, exploiting the zooming capability of the TM5 model. We assimilate observations from both surface stations and the SCIAMACHY instrument aboard ENVISAT, measuring column-averaged CH₄ mixing ratios globally with high sensitivity to near-surface CH₄. After application of a bias correction to the satellite retrievals, the assimilation system is able to closely fit the SCIAMACHY measurements, while retaining consistency with the surface network. Reductions in the uncertainty of emissions achieved by the different observation types, as estimated by our 4D- Var system, are discussed. Specific attention is given to tropical South America, where SCIAMACHY generally measures higher methane concentrations than simulated a priori by the model. Particularly in the period September to November 2003, the inversions suggest almost a doubling of South American emissions relative to the prior estimate. Independent aircraft observations support the presence of large methane emissions but suggest that enhancements may be smaller than estimated from the assimilation of SCIAMACHY observations.
DE: 0322 Constituent sources and sinks
DE: 0368 Troposphere: constituent transport and chemistry
DE: 3315 Data assimilation
DE: 3360 Remote sensing
SC: Biogeosciences [B]
MN: 2007 Fall Meeting