Aerosol and Clouds
Aerosol climatology over South Africa based on 10 years of Multiangle Imaging Spectroradiometer (MISR) data
Article first published online: 29 OCT 2011
Copyright 2011 by the American Geophysical Union.
Journal of Geophysical Research: Atmospheres (1984–2012)
Volume 116, Issue D20, 27 October 2011
How to Cite
2011), Aerosol climatology over South Africa based on 10 years of Multiangle Imaging Spectroradiometer (MISR) data, J. Geophys. Res., 116, D20216, doi:10.1029/2011JD016023., , , and (
- Issue published online: 29 OCT 2011
- Article first published online: 29 OCT 2011
- Manuscript Accepted: 12 AUG 2011
- Manuscript Revised: 23 JUN 2011
- Manuscript Received: 28 MAR 2011
- aerosol climatology
 In this paper, we present a detailed study of the spatial and seasonal aerosol climatology over South Africa (SA), based on Multiangle Imaging Spectroradiometer (MISR) data. We have used 10 years (2000–2009) of MISR monthly mean aerosol extinction (τext), absorption (τa) optical depths at 558 nm, Angstrom exponents in visible (VIS; 446–672 nm) and near-infrared (NIR; 672–866 nm) spectral bands, and the extracted spectral curvature. The study has shown that, in terms of aerosol load level spatial variation, SA can be classified into three parts: the upper, central, and lower, which illustrate high, medium, and low aerosol loadings, respectively. The results for the three parts of SA are presented in detail. The prevailing sources of aerosols are different in each part of SA. The lower part is dominated by the air mass transport from the surrounding marine environment and other SA or neighboring regions, while the central and upper parts are loaded through wind-ablated mineral dust and local anthropogenic activities. During the biomass burning seasons (July–September), the central part of SA is more affected than the rest of SA by the biomass-burning aerosols (based on τa, ∼20% higher than the rest of SA). In alignment with the observed higher values of τext, aerosol size distributions were found to be highly variable in the upper part of SA, which is due to the high population and the industrial/mining/agricultural activities in this area.