A further evaluation of the spatial and temporal variability of aerosols across North America: influence of lower tropospheric flow.

In previous work, we performed the first large-scale analysis of the role of the atmosphere in explaining the observed temporal and spatial variability in aerosols. In that research, the atmosphere's influence upon aerosol variability across North America was evaluated via the Spatial Synoptic Classification (SSC) scheme, which groups surface weather conditions at a particular location into one of several 'weather types'. We further our analysis here by utilizing the 850-hPa geopotential height field. Whereas the SSC classification is based upon surface weather at each individual location, and thus the classifications on a given day may change from location to location, the 850-hPa field on each day was classified into one of nine 'flow types' for the entire eastern two thirds of North America. The 850-hPa field was normalized to account for interseasonal variability before classification (via Principal Component Analysis and two-step Cluster Analysis) occurred. Aerosol data from 27 stations spanning two monitoring networks, AERONET and MFRSR, have been analyzed, with a period of record averaging 7.3 years. Both the aerosol optical depth (tau), a measure of the total amount of aerosols in the atmospheric column, and Angstrom's wavelength exponent (alpha), a measure of the size distribution of aerosols, have been compared to the 850-hPa flow types. Results show that, as with the SSC classification, the 850-hPa flow types differentiate days with statistically significant differences in tau more commonly than differences in alpha. However, with both variables, the 850- hPa flow types are associated with fewer statistically significant differences than with the SSC. Further, these differences are less consistent from place to place and season to season, as a particular flow pattern may be associated with higher values in one location and lower values in another. Thus, while it may be easier for climate models to predict larger-scale flow patterns than individual station-level data, this appears to be less favorable for aerosol estimation.