Aerosol Awareness In A Convective Parameterization For Deep and Shallow Convection: Comparison To Cloud Resolving Simulations (invited Presentation)

Abstract

A convective parameterization is applied and evaluated that may be used in high resolution non-hydrostatic mesoscale models for weather and air quality prediction, as well as in modeling system with unstructured varying grid resolutions and for convection aware simulations. This scheme is based on a stochastic approach originally implemented by Grell and Devenyi (2002) and described in more detail in Grell and Freitas (2014, ACP). It was expanded to include PDF's for vertical mass flux in deep and shallow convection, and additional closures and aerosol dependence in the shallow scheme. Interactions with aerosols have been implemented through a CCN dependent autoconversion of cloud water to rain as well as an aerosol dependent evaporation of cloud drops. Initial tests with this newly implemented aerosol approach showed plausible results with a decrease in predicted precipitation in some areas, caused by the changed autoconversion mechanism. Here we compare and evaluate performance over a 10-day period using the SAMBBA test case of the Working Group for Numerical Experimentation (WGNE) on aerosol impacts on numerical weather prediction. A shorter period is also compared to fully cloud-resolving simulations using WRF-Chem.