September 2007
Comparison of adjoint and analytical Bayesian inversion methods for constraining Asian sources of carbon monoxide using satellite (MOPITT) measurements of CO columns

We applied the adjoint of GEOS-Chem CTM to constrain Asian sources of carbon monoxide (CO) with 2° x 2.5° spatial resolution using MOPITT satellite observations of CO columns in Feb-Apr 2001. We compared the results to the more common analytical method for solving the same Bayesian inverse problem and applied to the same data set. We find that the correction factors to the a priori CO emission inventory from the adjoint inversion are consistent with those of the analytical inversion when averaged over the large regions of the latter. The adjoint solution also reveals fine-scale variability that the analytical inversion cannot resolve.

The figures above show correction factors to a priori Asian CO sources for Feb 1 - Apr 10, 2001 as optimized in (left) the analytical inversion and (right) the adjoint inversion. Boxes in the left panel refer to the individual regions (state vector elements) used by Heald et al. [2004]. An example of the fine-scale variability in the adjoint solution can be found in India, which shows both large emissions underestimates in the densely populated Ganges Valley and large overestimates in the eastern part of the country where springtime emissions are dominated by biomass burning.

For more information see Kopacz et al [2007].