Inverse modeling of methane sources and sinks using the adjoint of a global transport model

An inverse modeling method is presented to evaluate the sources and sinks o f atmospheric methane. An adjoint version of a global transport model has b een used to estimate these fluxes at a relatively high spatial and temporal resolution. Measurements from 34 monitoring stations and 11 locations alon g two ship cruises by the National Oceanographic and Atmospheric Administra tion have been used as input. Recent estimates of methane sources, includin g a number of minor ones, have been used as a priori constraints. For the t arget period 1993-1995 our inversion reduces the a priori assumed global me thane emissions of 528 to 505 Tg(CH4) yr(-1) a posteriori. Further, the rel ative contribution of the Northern Hemispheric sources decreases from 77% a priori to 67% a posteriori. In addition to making the emission estimate mo re consistent with the measurements, the inversion helps to reduce the unce rtainties in the sources, Uncertainty reductions vary from 75% on the globa l scale to similar to 1% on the grid-scale (8 degrees x10 degrees), indicat ing that the grid scale variability is not resolved by the measurements. La rge scale features such as the interhemispheric methane concentration gradi ent are relatively well resolved and therefore impose strong constraints on the estimated fluxes. The capability of the model to reproduce this gradie nt is critically dependent on the accuracy at which the interhemispheric tr acer exchange and the large-scale hydroxyl radical distribution are represe nted. As a consequence, the inversion-derived emission estimates are sensit ive to errors in the transport model and the calculated hydroxyl radical di stribution. In fact, a considerable contribution of these model errors cann ot be ignored. This underscores that source quantification by inverse model ing is limited by the extent to which the rate of interhemispheric transpor t and the hydroxyl radical distribution can be validated. We show that the use of temporal and spatial correlations of emissions may significantly imp rove our results; however, at present the experimental support for such cor relations is lacking. Our results further indicate that uncertainty reducti ons reported in previous inverse studies of methane have been overestimated .