Trend analysis of atmospheric aerosols enhances confidence in the evaluation of both direct and indirect effects of aerosols on regional climate change. To comprehensively achieve this over East Africa, it's important to understand aerosols temporal characteristics over well selected sites namely Nairobi (1˚S, 36˚E), Mbita (0˚S, 34˚E), Mau Forest (0.0˚S -0.6˚S; 35.1˚E -35.7˚E), Malindi (2˚S, 40˚E), Mount Kilimanjaro (3˚S, 37˚E) and Kampala (0˚N, 32.1˚E). In this context, trend analysis (annual (in Aerosol Optical Depth (AOD) at 550 nm and Ångström Exponent Anomaly (ÅEA) at 470 -660 nm) and seasonal (AOD)) from Moderate Resolution Imaging Spectroradiometer (MODIS) were performed following the weighted least squares (WLS) fitting method for the period 2000 to 2013. The MODIS AOD annual trends were ground-truthed by AErosol RObotic NETwork (AERONET) data. Tropical Rainfall Measurement Mission (TRMM) was utilized to derive rainfall rates (RR) in order to assess its influence on the observed aerosol temporal characteristics. The derived annual AOD trends utilizing MODIS and AERONET data were consistent with each other. However, monthly AOD and RR were found to be negatively correlated over Nairobi, Mbita, Mau forest complex and Malindi. There was no clear relationship between the two trends over Kampala and Mount Kilimanjaro, which may imply the role of aerosols in cloud modulation and hence RR received. Seasonality is evident between AOD and ÅEA annual trends as these quantities were observed to be modulated by RR. AOD was observed to decrease over East Africa except Nairobi during the study period as a result of RR during the study period. Unlike the other study sites, Nairobi shows positive trends in AOD that may be attributed to increasing populace and fossil fuel, vehicular-industrial emission and biomass and refuse burning during the study period. Negative trends over the rest of the study sites were associated to rain washout. The AOD and ÅEA derived annual trends were found to meet the statistical significance of 95% confidence level over each How to cite this paper: Makokha,

Atmospheric aerosols have contributed to radiative forcing through direct and indirect mechanisms. Aerosol effects are important in computing radiative forcing estimates for the past, current and future climate. In this study, a comprehensive assessment of regional aerosol radiative forcing, Optical , respectively. This corresponds to an increment in net atmospheric forcing at a heating rate of about 0.55 ± 0.05 K/day (0.41 ± 0.03 to 0.78 ± 0.03 K/day) in the lower troposphere. The study points out the significant role played by atmospheric aerosols in climate modification over the area of study. It is recommended that a further assessment be done in view of uncertainties that may impact on the findings and which were not within the scope of this research.

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.

Neural network analysis based on Growing Hierarchical Self-Organizing Map (GHSOM) is used to examine Spatial-Temporal characteristics in Aerosol Optical Depth (AOD), Ångström Exponent (ÅE) and Precipitation Rate (PR) over selected East African sites from 2000 to 2014. The selected sites of study are Nairobi (1˚S, 36˚E), Mbita (0˚S, 34˚E), Mau Forest (0.0˚-0.6˚S; 35.1˚E-35.7˚E), Malindi (2˚S, 40˚E), Mount Kilimanjaro (3˚S, 37˚E) and Kampala (0˚N, 32.1˚E). GHSOM analysis reveals a marked spatial variability in AOD and ÅE that is associated to changing PR, urban heat islands, diffusion, direct emission, hygroscopic growth and their scavenging from the atmosphere specific to each site. Furthermore, spatial variability in AOD, ÅE and PR is distinct since each variable corresponds to a unique level of classification. On the other hand, GHSOM algorithm efficiently discriminated by means of clustering between AOD, ÅE and PR during Long and Short rain spells and dry spell over each variable emphasizing their temporal evolution. The utilization of GHSOM therefore confirms the fact that regional aerosol characteristics are highly variable be it spatially or temporally and as well modulated by PR received over each variable.

Atmospheric aerosols are posing a great threat to the already stressed climate with the effects being felt more on African continent. Their presence and interaction with the clouds contribute to the strongest uncertainty in aerosol characteristics and Earth's energy budget hence; calling for a long term assessment to be done. The present study analyses long term spatiotemporal microphysical aerosol characteristics (namely: effective radius (eff r) and surface-area concentration), using AErosolROboticNETwork (AERONET) framework over Kenyan urban atmosphere (Nairobi-1˚S, 36˚E), rural atmosphere (ICIPE-Mbita-0˚S, 34˚E) and maritime atmosphere (CRPSM-Malindi-2˚S, 40˚E). AERONET framework was used due to its availability over the selected sites; it is also located in sites that provided contrasting aerosols type, source and characteristics and due to its synergism with other frameworks. The findings indicated a spatial and temporal variability in microphysical properties over CRPSM-Malindi, Nairobi and ICIPE-Mbita. CRPSM-Malindi is dominated with coarse aerosols in all seasons while Nairobi with coarse mode in the DJF and MAM seasons. ICIPE-Mbita is on the other hand dominated with fine aerosols in all season. In terms of size distribution, the three AERONET sites displayed a bimodal distribution inflecting at 0.44 µm and fine mode radius of 0.15 µm while CRPSM-Malindi recorded a coarse mode of 3.86 µm and Nairobi and ICIPE-Mbita with 5.06 µm. The coarse aerosols have a higher concentration than the fine aerosols in all AERONET sites because of aerosol coagulation and dominance of certain type of aerosols that are coarse in nature.