An Air Quality Simulation Model over Complex Terrain by Taylor-Galerkin with Forester Filter Method
This study is aimed to improve a predictive performance of the air quality simulation model over complex terrain which was proposed in our previous study. Taylor Galerkin method for three-dimensional numerical model is attractive due to very small artificial (or numerical) diffusion. However, the most important weak point may be the occurrence of computational ripples. To suppress these ripples (or noise), the Forester filter was incorporate into our model and this Forester filter method is a kind of nonlinear filtering for smoothing the computational noise. An air quality simulation model by Taylor Galerkin with Forester filter (TGF) method was proposed.
In order to evaluate the performance of the proposed air quality model, a simulation by this TGF model for Tochigi area was carried out. The filtering coefficient in this model was determined empirically by preliminary calculations. The simulation result was compared with the data of air tracer diffusion experiment.
The statistical evaluation scores, such as correlation coefficient between the observed and simulated SF6 concentrations showed high predictive performance of this proposed model. Although the consistency nearly peak concentration area was not necessarily sufficient, this proposed model seems to have sufficient performance for an air quality simulation.