The Application of a Generalized Hygroscopicity Parameterization for Climate Modeling

Kanishk Gohil, Andrew Gettelman, AKUA ASA-AWUKU, University of Maryland

     Abstract Number: 614
     Working Group: Aerosols, Clouds and Climate

Abstract
The indirect effect of aerosols on clouds, including that due to organic aerosols, is a significant source of uncertainties in climate modeling. One of the uncertainties in understanding aerosol-cloud interaction is a systematic misrepresentation of the water uptake behavior (hygroscopicity) of dust and carbonaceous aerosols – including primary organic matter (POM), secondary organic aerosols (SOAs), and black carbon (BC). The hygroscopicity of aerosol species in large-scale models, such as the Community Atmosphere Model (CAM), is prescribed based on the traditional Köhler theory (KT). Since KT assumes aerosols to be infinitely soluble in water, KT-based hygroscopicities are regularly found to have uncertainties for several organic aerosols that have low water solubility. These uncertainties can then translate into the predicted aerosol-cloud interactions. In this work, we implemented the hygroscopicity parameterization based on the novel Hybrid Activity Model (HAM) within CAM6. The HAM framework explicitly treats the water solubility of any given compound coupled with adsorption-based droplet growth to predict the Cloud Condensation Nuclei (CCN) activity. Recently, CCN activity analysis using HAM for laboratory measurements indicated that solubility-partitioned, water adsorption-based hygroscopicity may be an improved representation of the water uptake by effectively water-insoluble species. The complex HAM hygroscopicity is represented as a function of particle size by simplification into a power law for implementation within CAM6. We investigate the changes in CCN and droplet properties from HAM-based hygroscopicity parameterization using sensitivity tests as well as full 3D climate simulations. This work is the first to provide a computationally efficient treatment of size-dependent aerosol hygroscopicity for cloud droplet formation for climate modeling. The results suggest that accounting for complex aerosol chemistry for hygroscopicity parameterization can improve estimates of the physical and radiative properties of aerosols and clouds. Similar extensive hygroscopicity treatment of atmospherically relevant aerosols can be considered in other global and regional climate models.