The critical role of trace gases in global change makes an improved understanding of these gases imperative. Measurements of the distributions of these gases in space and time provide important information, but the interpretation of these data requires modeling of the atmospheric transport as well as inversion techniques. Whereas inverse modeling of the sources of atmospheric trace gases on global scale with low spatial and temporal resolution is an established technique, there are many fewer applications to smaller scales. Additional challenges are created for regional modelers because they must deal with limited domains. The inflow fluxes across lateral boundaries are usually several orders of magnitude higher than the surface fluxes from the regional domains. Another difficulty appears when the trace gas emission has a strong diurnal cycle that cannot be neglected at these scales, as in the case of CO2.

We have been developing a set of techniques to combine the use of numerical models with regional CO2 measurements. The regional inversion framework is built around CSU RAMS (Regional Atmospheric Modeling System) and the Lagrangian Particle Dispersion (LPD) model. The LPD model is used in adjoint mode to trace particles backward in time to derive influence functions for each concentration sample. The influence function provides information on potential contributions both from surface sources and inflow fluxes that make their way through the modeling domain boundaries into the CO2 concentration sample. Then the Bayesian inversion technique is applied in an attempt to estimate unknown surface emissions. CO2 flux is treated as a sum of respiration flux and assimilation (uptake by vegetation). Additional constrains are formulated for these fluxes using information from RAMS output (shortwave radiation, soil temperature, vegetation type) traced by Lagrangian particles.

The modeling framework is being applied to estimate CO2 fluxes within 500 km radius from WLEF TV tower in northern Wisconsin instrumented with continuous measurements of CO2 concentration at 6 levels from 11 to 396m. Additional CO2 measurements include five 76 m communication towers operating during summer season of 2004. These towers form a ring around the WLEF tower with 100-150 km radius. The preliminary tests of the modeling framework were performed with the aid of model generated concentration pseudo-data for August 2000. Different configurations of source areas and different assumptions concerning expected model-data mismatch error were investigated. The results for CO2 flux estimation using concentration data form the ring of towers are very promising as long as the inflow CO2 flux is known or if its good a-priori estimation is available. For this purpose we are going to link our regional inversion system to a global transport model based on PCTM (Parameterized Chemical Transport Model) driven by CO2 fluxes provided by SiB3 (Simple Biosphere Model). Further inversion experiments using pseudo-data are being performed in parallel with a preparation for inversions using real CO2 observations for the summer of 2004.