Sensitivity Study of Cloud Cover and Ozone Modeling to Microphysics Parameterization

Cloud cover is a significant meteorological parameter influencing the amount of solar radiation reaching the ground surface, and therefore affecting the formation of photochemical pollutants, most of all tropospheric ozone (O3). Because cloud amount and type in meteorological models are resolved by microphysics schemes, adjusting this parameterization is a major factor determining the accuracy of the results. However, verification of cloud cover simulations based on surface data is difficult and yields significant errors. Current meteorological satellite programs provide many high-resolution cloud products, which can be used to verify numerical models. In this study, the Weather Research and Forecasting model (WRF) has been applied for the area of Poland for an episode of June 17th–July 4th, 2008, when high ground-level ozone concentrations were observed. Four simulations were performed, each with a different microphysics parameterization: Purdue Lin, Eta Ferrier, WRF Single-Moment 6-class, and Morrison Double-Moment scheme. The results were then evaluated based on cloud mask satellite images derived from SEVIRI data. Meteorological variables and O3 concentrations were also evaluated. The results show that the simulation using Morrison Double-Moment microphysics provides the most and Purdue Lin the least accurate information on cloud cover and surface meteorological variables for the selected high ozone episode. Those two configurations were used for WRF-Chem runs, which showed significantly higher O3 concentrations and better model-measurements agreement of the latter.