Abstract
Abstract. The source-oriented Weather Research and Forecasting chemistry model (SOWC) was modified to include warm cloud processes and was applied to investigate how aerosol mixing states influence fog formation and optical properties in the atmosphere. SOWC tracks a 6-D chemical variable (X, Z, Y, size bins, source types, species) through an explicit simulation of atmospheric chemistry and physics. A source-oriented cloud condensation nuclei module was implemented into the SOWC model to simulate warm clouds using the modified two-moment Purdue Lin microphysics scheme. The Goddard shortwave and long-wave radiation schemes were modified to interact with source-oriented aerosols and cloud droplets so that aerosol direct and indirect effects could be studied. The enhanced SOWC model was applied to study a fog event that occurred on 17 January 2011, in the Central Valley of California. Tule fog occurred because an atmospheric river effectively advected high moisture into the Central Valley and nighttime drainage flow brought cold air from mountains into the valley. The SOWC model produced reasonable liquid water path, spatial distribution and duration of fog events. The inclusion of aerosol–radiation interaction only slightly modified simulation results since cloud optical thickness dominated the radiation budget in fog events. The source-oriented mixture representation of particles reduced cloud droplet number relative to the internal mixture approach that artificially coats hydrophobic particles with hygroscopic components. The fraction of aerosols activating into cloud condensation nuclei (CCN) at a supersaturation of 0.5 % in the Central Valley decreased from 94 % in the internal mixture model to 80 % in the source-oriented model. This increased surface energy flux by 3–5 W m−2 and surface temperature by as much as 0.25 K in the daytime.
Highlights
Atmospheric aerosols are complex mixtures of particles emitted from many different anthropogenic and natural sources suspended in the atmosphere
The primary goal of this research is to quantify the effect of assumptions about particle mixing state on predicted cloud droplet formation within the Weather Research and Forecasting (WRF)/Chem model
This paper presents the development of the CLDAQC treatment within the source-oriented Weather Research and Forecasting chemistry model (SOWC) model to ensure that the model performs properly
Summary
Atmospheric aerosols are complex mixtures of particles emitted from many different anthropogenic and natural sources suspended in the atmosphere. In contrast to greenhouse gases, aerosols have large spatial and temporal variability in the troposphere because of their short lifetimes (about 1 week) before coagulation, dry deposition or wet scavenging processes remove them from the atmosphere (Ramanathan et al, 2001). Aerosol particles can influence human health (McMichael et al, 2006), ecological health (over land and ocean) (Griffin et al, 2001), visible range through the atmosphere (Dick et al, 2000), cloud/precipitation formation (Chen et al, 2008) and the net radiation budget of the earth (IPCC, 2007). Some chemical components of aerosol particles are important to direct radiative forcing of the climate due to their optical properties (Tegen et al, 1996). Particulate sulfate scatters incoming solar radiation, leading to an estimated direct forcing of −0.95 W m−2 (Adams et al, 2001). Particulate black carbon strongly absorbs incoming shortwave radiation, which warms the mid-level of the at-
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