A Method for Forecasting Cloud Condensation Nuclei Using Predictions of Aerosol Physical and Chemical Properties from WRF/Chem

Abstract

odel investigations of aerosol?cloud interactions across spatial scales are necessary to advance basic understanding of aerosol impacts on climate and the hydrological cycle. Yet these interactions are complex, involving numerous physical and chemical processes. Models capable of combining aerosol dynamics and chemistry with detailed cloud microphysics are recent developments. In this study, predictions of aerosol characteristics from the Weather Research and Forecasting Model with Chemistry (WRF/Chem) are integrated into the Regional Atmospheric Modeling System microphysics package to form the basis of a coupled model that is capable of predicting the evolution of atmospheric aerosols from gas-phase emissions to droplet activation. The new integrated system is evaluated against measurements of cloud condensation nuclei (CCN) from a land-based field campaign and an aircraft-based field campaign in Colorado. The model results show the ability to capture vertical variations in CCN number concentration within an anthropogenic pollution plume. In a remote continental location the model-forecast CCN number concentration exhibits a positive bias that is attributable in part to an overprediction of the aerosol hygroscopicity that results from an underprediction in the organic aerosol mass fraction. In general, the new system for predicting CCN from forecast aerosol fields improves on the existing scheme in which aerosol quantities were user prescribed.