Inverse Modeling Approaches to Infer Surface Trace Gas Fluxes from Observed Atmospheric Mixing Ratios

The accurate temporal and spatial quantification of sources and sinks of radiatively or chemically active atmospheric trace gases, constitutes a considerable scientific challenge. However, this quantification is needed for two purposes. Firstly, it provides critical data for the evaluation of process-based prognostic models, which are used to predict the evolution of the atmospheric composition as functions of anthropogenic impacts and environmental changes. Secondly, in the context of international negotiations to curb the emissions of greenhouse gases, an accurate quantification is indispensable to verify reduction targets claimed by individual nations or groups of nations. One approach to this problem involves the extrapolation of local flux measurements using geographically referenced databases of properties of the surface (e.g. vegetation cover, topography, soil properties etc.) in conjunction with climatic variables (e.g. temperature, precipitation, insolation etc.) and databases of anthropogenic activities (statistics of land-use, energy consumption, population, agricultural practices etc.). As sources and sinks of trace gases are also reflected in the spatial distribution and temporal variation of their atmospheric mixing ratio, an alternative approach consists of inverting atmospheric mixing ratio measurements into a spatial and temporal distribution of the trace gas sources. In order to do this, the atmospheric transport from the source regions to the observation sites has to be described using simulation models of atmospheric transport.