To study these possibilities we focus on a fairly simple coupled system. The MM5 mesoscale numerical weather prediction (NWP) model has been coupled to the SCIPUFF atmospheric transport and dispersion (AT&D) model. Using a case from the Cross Appalachian Tracer Experiment (CAPTEX), we investigate the role of temporal frequency in MM5 output on the accuracy of SCIPUFF's predicted plume concentrations versus observations of an inert tracer gas measured downwind by a surface monitoring array over a distance of ~1200 km. Next, we examine concentration errors resulting from horizontal and vertical spatial interpolations between the native MM5 grid and that of SCIPUFF. Finally, we study the role of better physical coupling by modifying SCIPUFF to use more of the non-state variables predicted by MM5 for surface fluxes and turbulence processes in the atmospheric boundary layer. Each experiment uses the same 36-h MM5 4-km simulation of the CAPTEX case, obtained by dynamic analysis using four-dimensional data assimilation, to drive SCIPUFF.
Experimental evidence demonstrates that substantial errors can occur in predicted surface concentrations for all three elements of the coupling between MM5 and SCIPUFF. In this case, the greatest errors were found to be related to coupling of the physics between the two models.