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The natural cycles of the surface-to-atmosphere fluxes of carbon dioxide (CO2) and other important greenhouse gases are changing in response to human influences. These changes need to be quantified to understand climate change and its impacts, but this is difficult to do because natural fluxes occur over large spatial and temporal scales and cannot be directly observed. Flux inversion is a technique that estimates the spatiotemporal distribution of a gas’ fluxes using observations of the gas’ mole fraction and a chemical transport model. To infer trends in fluxes and identify phase shifts ...

WOMBAT (the WOllongong Methodology for Bayesian Assimilation of Trace-gases) is a fully Bayesian hierarchical statistical framework for flux inversion of trace gases from flask, in situ, and remotely sensed data. WOMBAT extends the conventional Bayesian synthesis framework through the consideration of a correlated error term, the capacity for online bias correction, and the provision of uncertainty quantification on all unknowns that appear in the Bayesian statistical model. We show, in an observing system simulation experiment (OSSE), that these extensions are crucial when the data are indeed...