Methane mixing ratios measured at a tall tower are compared to model predictions to estimate surface emissions of CH₄ in Central California for October–December 2007 using an inverse technique. Predicted CH₄ mixing ratios are calculated based on spatially resolved a priori CH₄ emissions and simulated atmospheric trajectories. The atmospheric trajectories, along with surface footprints, are computed using the Weather Research and Forecast (WRF) coupled to the Stochastic Time-Inverted Lagrangian Transport (STILT) model. An uncertainty analysis is performed to provide quantitative uncertainties in estimated CH₄ emissions. Three inverse model estimates of CH₄ emissions are reported. First, linear regressions of modeled and measured CH₄ mixing ratios obtain slopes of 0.73 ± 0.11 and 1.09 ± 0.14 using California-specific and Edgar 3.2 emission maps, respectively, suggesting that actual CH₄ emissions were about 37 ± 21% higher than California-specific inventory estimates. Second, a Bayesian “source” analysis suggests that livestock emissions are 63 ± 22% higher than the a priori estimates. Third, a Bayesian “region” analysis is carried out for CH₄ emissions from 13 subregions, which shows that inventory CH₄ emissions from the Central Valley are underestimated and uncertainties in CH₄ emissions are reduced for subregions near the tower site, yielding best estimates of flux from those regions consistent with “source” analysis results. The uncertainty reductions for regions near the tower indicate that a regional network of measurements will be necessary to provide accurate estimates of surface CH₄ emissions for multiple regions.