ASSESSING DISPERSION MODEL PERFORMANCE TO SIMULATE AVERAGE CENTERLINE CONCENTRATION VALUES

摘要

Most operational atmospheric simulation models are deterministic. They provide estimates of the average time- and space-variations in the conditions (e.g., mesoscale meteorological models), or they provide estimates of the average time- and space-variations of effects (e.g., air quality models). The observations used to test the performance of these models are individual realizations (which can be envisioned as coming from some ideal ensemble), and are affected by stochastic variations unaccounted for within the simulation model. If we believe this, then it makes sense to ask the models to replicate average patterns seen in the observations, but it does not make sense to ask the models to replicate the effects of stochastic variations unaccounted for within the simulation model (e.g., observed maxima, or total variance).