Potential contributions of process modeling to understanding and constraining the global methane budget

The global methane budget is fairly well-constrained in aggregate, but the partitioning of global emissions into the various natural and anthropogenic sources is not. Direct measurements of emissions are essential for quantifying the various terms, but alone are not up to the task as some important source terms are widely distributed across the planet and often remote, and emissions can be highly variable in space and time. The various components of global methane emissions can also be estimated by inverse modeling, which can be constrained by the network of atmospheric concentration and isotopic measurements, but has coarse spatial resolution, and is not so useful for prognostic modeling. Process-based modeling can also help to constrain and evaluate the global methane budget. Using the DNDC model as an example, we review both strengths (e.g., spatial and temporal extrapolation), weaknesses (e.g., incomplete representations; generalization), and challenges (e.g., adequate ancillary data) of process models as a scientific tool for understanding the global methane budget.