Modelling below-cloud scavenging of size resolved particles in GEM-MACHv3.1
Authors: Ghahreman Roya , Gong Wanmin , Makar Paul A. , Lupu Alexandru , Cole Amanda , Banwait Kulbir , Lee Colin , Akingunola Ayodeji 
Published: June 2023

Abstract. Below-cloud scavenging is the process of aerosol removal from the atmosphere between cloud-base and the ground by precipitation (e.g. rain or snow), and affects aerosol number/mass concentrations, lifetime and distributions. An accurate representation of precipitation phases is important in treating below-cloud scavenging as the efficiency of aerosol scavenging differs significantly between liquid and solid precipitation. The impact of different representations of below-cloud scavenging on existing model biases (Makar et al, 2018), was examined through implementing a new aerosol below-cloud scavenging scheme (from Wang et al., 2014) and comparing with the GEM-MACH’s existing scavenging scheme, based on Slinn (1984). Further, the current GEM-MACH employs a single-phase precipitation for below-cloud scavenging: total precipitation is treated as either liquid or solid depending on a fixed environment temperature threshold. Here, we consider co-existing liquid and solid precipitation phases as they are predicted by the GEM microphysics. GEM-MACH simulations are compared with - observed precipitation samples, with a focus on the particulate base cation NH4+, acidic anions NO3-, SO4=, HSO3- in precipitation, and ambient particulate sulfate, ammonium and nitrate. Overall, the precipitation-phase partitioning and Wang et al. (2014) scavenging scheme improve GEM-MACH performance relative to earlier approaches. Including multi-phase approach leads to a decrease in SO42- scavenging and impacts the below-cloud scavenging of SO2 into the aqueous phase over the domain. Sulphate biases improved from +46 % to -5 % relative to Alberta Precipitation Quality Monitoring Program wet sulphate observations. At Canadian Air and Precipitation Monitoring Network stations the biases became more negative, from -10 % to -30 % for the tests carried out here. These may be compared to previously published annual average biases of +200 % for SO42- from earlier versions of GEM-MACH (Makar et al, 2018), indicating an overall improvement in model performance relative to the prior results. Improvements in model performance (via scores for correlation coefficient, normalized mean bias, and/or fractional number of model values within a factor of two of observations) could also be seen, between the base case and the two simulations based on multiphase partitioning for NO3-, NH4+, and SO42. Whether or not these improvements corresponded to increases or decreases of NO3- and NH4+ wet deposition varied over the simulation region. The changes were episodic in nature – the most significant changes in wet deposition were likely at specific geographic locations and represent specific cloud precipitation events. The aerosol scavenging rates of the two schemes differ during liquid precipitation in the size range of 0.1–1 µm, mostly at high precipitation intensity. The two schemes aerosol scavenging diverges for aerosols smaller than 1 µm for solid precipitation at lower intensity (R=0.01 mm/h), while at higher precipitation intensities (R=10 mm/h), the two schemes show bigger differences for aerosols larger than 1 µm. The changes in wet scavenging resulted a higher formation rate and larger concentrations of atmospheric particle sulphate.