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Keywords:

  • TOMS and OMI AI;
  • mean annual cycle;
  • rotated EOF

[1] Absorbing aerosols, especially mineral dust and black carbon, play key roles in climate change by absorbing solar radiation, heating the atmosphere, and contributing to global warming. In this paper, we first examine the consistency of the Aerosol Index (AI) product as measured by the Total Ozone Mapping Spectrometer (TOMS) and Ozone Monitoring Instrument (OMI) instruments and then analyze these AI data sets to investigate the temporal and spatial variability of UV absorbing aerosols. In contrast to the trend in aerosol optical depth found in the advanced very high-resolution radiometer data, no obvious long-term trend in absorbing aerosols is observed from the time series of AI records. The comparison between the mean annual cycle in the two data sets shows that the cycles agree very well both globally and regionally, indicating a consistency between the AI products from TOMS and OMI. Varimax rotated Empirical Orthogonal Function (EOF) analysis of detrended, deseasonalized AI data proves to be successful in isolating major dust and biomass burning source regions, as well as dust transport. Finally, we find that large, individual events, such as the Kuwait oil fire and Australian smoke plum, are isolated in individual higher-order principal components.