Optical Characterization of Atmospheric Aerosols via Airborne Spectral Imaging and Self-Organizing Map for Climate Change Diagnostics

Abstract

Self-Organizing Map (SOM) analysis is used to perform optical characterization of both Aerosol Optical Depth (AOD) and Ångström Exponent (ÅE) retrieved from Moderate-resolution Imaging Spectroradiometer (MODIS) in relation to Precipitation Rate (PR) from Tropical Rainfall Measurement Mission (TRMM) over selected East African sites from 2000 to 2014 and further diagnose climate change over the region if any. SOM reveals a marked spatial variability in AOD and ÅE that is associated to changing aerosol transport, urban heat islands, diffusion, direct emission, hygroscopic growth and their scavenging from the atmosphere specific to each site. Temporally, all sites except Mbita and Kampala indicate two clusters in AOD that are associated to prevailing dry and wet seasons over East Africa. Moreover, all sites except Mbita and Mount Kilimanjaro show two clusters in ÅE that are related to aerosol mode of generation and composition over the region. The single cluster in AOD and ÅE over Mbita indicate that aerosol characteristics over the site are influenced by biomass burning and local air circulation rather than the monsoon precipitation throughout the study period.