Search

As one of the dominant sinks of aerosol particles, wet scavenging greatly influences aerosol lifetime and interactions with clouds, precipitation, and radiation. However, wet scavenging remains highly uncertain in models, hindering accurate predictions of aerosol spatiotemporal distributions and downstream interactions. In this study, we present a flexible, computationally inexpensive method to identify meteorological variables relevant for estimating wet scavenging using a combination of aircraft, satellite, and reanalysis data augmented by trajectory modeling to account for air mass history. We assess the capabilities of an array of meteorological variables to predict the transport efficiency of black carbon (TE BC) using a combination of nonlinear regression, curve fitting, and k -fold cross-validation. We find that accumulated precipitation along trajectories (APT) – treated as a wet scavenging indicator across multiple studies – does poorly when predicting TE BC. Among different precipitation characteristics (amount, frequency, intensity), precipitation intensity was the most effective at estimating TE BC but required longer trajectories (>48 h) and including only intensely precipitating grid cells. This points to the contribution of intense precipitation to aerosol scavenging and the importance of accounting for air mass history. Predictors that were most able to predict TE BC were related to the distribution of relative humidity (RH) or the frequency of humid conditions along trajectories, suggesting that RH is a more robust way to estimate TE BC than APT. We recommend the following alternatives to APT when estimating aerosol scavenging: (1) the 90th percentile of RH along trajectories, (2) the fraction of hours along trajectories with either water vapor mixing ratios >15 g kg -1 or RH >95 %, and (3) precipitation intensity along trajectories at least 48 h along and filtered for grid cells with precipitation >0.2 mm h -1. Future scavenging parameterizations should consider these meteorological variables along air mass histories. This method can be repeated for different regions to identify region-specific factors influencing wet scavenging. [ABSTRACT FROM AUTHOR]