Estimating the uncertainty of a Lagrangian photochemical air quality simulation model caused by inexact meteorological input data

A deterministic Lagrangian photochemical air quality simulation model was developed at the Institute of Meteorology and Physics in Vienna. As the analysis of model uncertainty is an important part of the validation strategy, a local sensitivity and a global uncertainty analysis for model output was done. The effects of meteorological input and physical parameterisations on the model output were studied, whereas uncertainties arising from emissions and chemistry will be studied in a later stage of the model validation. As a result of the analysis, distribution density functions and vertical distributions of uncertainty in the model boxes for the chemical species ozone (O₃), nitrogen dioxide (NO₂), hydrogen peroxide (H₂O₂) and peroxiacetylnitrate (PAN) were obtained. It turned out that ozone is one of the least sensitive and uncertain species in the model. Only as far as nighttime simulations in the lowest two model boxes are concerned were the uncertainty of simulated ozone concentrations considerable. A clear weather pattern dependence of uncertainty has been detected. Highest model output variations for ozone, nitrogen dioxides and hydrogen peroxide are observed during weather situations with strong westerly winds.