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| Titel |
A global inverse model for estimating surface CO2 fluxes at a 0.1x0.1 degree resolution |
| VerfasserIn |
Shamil Maksyutov, Tomohiro Oda, Rajesh Janardanan, Alexey Yaremchuk, Johannes W. Kaiser, Akihiko Ito, Dmitry Belikov, Ruslan Zhuravlev, Alexander Ganshin, Vinu Valsala |
| Konferenz |
EGU General Assembly 2015
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 17 (2015) |
| Datensatznummer |
250105941
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| Publikation (Nr.) |
 EGU/EGU2015-5532.pdf |
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| Zusammenfassung |
| WeÂpropose an iterative inversion method for estimating surface CO2Âfluxes at
a high spatial resolution (0.1 degree) using atmospheric CO2Âdata collected by
the global in-situ network and GOSAT. The Lagrangian particle dispersion model
FLEXPART was coupled to the Eulerian atmospheric tracer transport model (NIES-TM)
and an adjoint of the coupled model was derived. The inverse model calculates
weekly corrections to given prior fluxes at a spatial resolution of the surface flux
footprints simulated by FLEXPART modelÂ(0.1 degrees). Prior fluxes are given at
different spatial resolutions in low and high resolution mode implementations. The
hourly terrestrial biosphere fluxes are simulated with VISIT model using CFSR
reanalysis. Ocean fluxes are calculated using a 4D-Var assimilation system of the surface
pCO2Âobservations. Fossil fuel (ODIAC) and biomass burning (GFASv1.1) emissions are
given at original model resolutions (0.1 degree), while terrestrial biosphere and
ocean fluxes are interpolated from a coarser resolution. Flux response functions
(footprints) for observations are first simulated with FLEXPART. The precalculated
flux response functions are then used in forward and adjoint runs of the coupled
transport model. We apply Lanczos process to obtain the truncated singular value
decomposition (SVD) of the scaled tracer transport operatorÂA = R-1/2HB1/2,
whereÂHÂ- tracer transport operator,ÂRÂandÂBÂ- error covariance matrices for
observations and fluxes, respectively. The square root of covariance matrixÂBÂis
constructed by directional splitting in latitude, longitude and time, with exponential
decay scales of 500 km on land, 1000 km over oceans and 2 weeks in time. Once
singular vectors ofÂAATÂare obtained, the prior and posterior flux uncertainties are
evaluated. Numerical experiments of inverting surface CO2Âfluxes showed that the
high-resolution (Lagrangian) part of the flux responses dominates the solution so that
spatial patterns from the coarser resolution NIES TM (10x10 degree) are not visible
in flux singular vectors and the optimized fluxes. The weekly flux uncertainties
at a resolution of 0.1 degree and flux uncertainty reduction due to assimilating
single shot GOSAT XCO2 data were estimated for a period of one year in 2010. We
demonstrated that our application of a coupled tracer transport model in adjoint-based
assimilation provides an efficient way to increase spatial resolution of the inverse model. |
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