Abstract
Abstract. A parameter called the scavenging coefficient Λ is widely used in aerosol chemical transport models (CTMs) to describe below-cloud scavenging of aerosol particles by rain and snow. However, uncertainties associated with available size-resolved theoretical formulations for Λ span one to two orders of magnitude for rain scavenging and nearly three orders of magnitude for snow scavenging. Two recent reviews of below-cloud scavenging of size-resolved particles recommended that the upper range of the available theoretical formulations for Λ should be used in CTMs based on uncertainty analyses and comparison with limited field experiments. Following this recommended approach, a new semi-empirical parameterization for size-resolved Λ has been developed for below-cloud scavenging of atmospheric aerosol particles by both rain (Λrain) and snow (Λsnow). The new parameterization is based on the 90th percentile of Λ values from an ensemble data set calculated using all possible "realizations" of available theoretical Λ formulas and covering a large range of aerosol particle sizes and precipitation intensities (R). For any aerosol particle size of diameter d, a strong linear relationship between the 90th-percentile log10 (Λ) and log10 (R), which is equivalent to a power-law relationship between Λ and R, is identified. The log-linear relationship, which is characterized by two parameters (slope and y intercept), is then further parameterized by fitting these two parameters as polynomial functions of aerosol size d. A comparison of the new parameterization with limited measurements in the literature in terms of the magnitude of Λ and the relative magnitudes of Λrain and Λsnow suggests that it is a reasonable approximation. Advantages of this new semi-empirical parameterization compared to traditional theoretical formulations for Λ include its applicability to below-cloud scavenging by both rain and snow over a wide range of particle sizes and precipitation intensities, ease of implementation in any CTM with a representation of size-distributed particulate matter, and a known representativeness, based on the consideration in its development, of all available theoretical formulations and field-derived estimates for Λ (d) and their associated uncertainties.
Highlights
The removal of below-cloud aerosol particles by precipitation, either rain or snow, decreases the concentrations of particulate matter in the air and contributes to the wet deposition of toxic pollutants
Based on the conclusions listed above, we provided some recommendations regarding the applications of rain and snow parameterizations in chemical transport models (CTMs) (Wang et al, 2010, 2011; Zhang et al, 2013) as follows: 1. Empirical formulas should not be used in CTMs because some of the processes contributing to the fieldderived estimates of are treated in CTMs separately
The availability of a number of existing theoretical formulas for the size-resolved scavenging coefficient (d) requires somewhat arbitrary choices to be made when selecting amongst these schemes and their product terms for implementation in a chemical transport model followed by the coding and run-time solution of often complex algorithms
Summary
The removal of below-cloud aerosol particles by precipitation, either rain or snow, decreases the concentrations of particulate matter in the air and contributes to the wet deposition of toxic pollutants This process has been identified as one of the most efficient removal mechanisms for atmospheric particles and is a key process in aerosol chemical transport models (CTMs) (Textor et al, 2006). Simulating this process with reasonable accuracy in CTMs has important impacts when model results from CTMs are used to assess air quality, climate, or ecosystem issues. A parameter called the scavenging coefficient (s−1) serves this purpose (Seinfeld and Pandis, 2006).
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