Abstract
AbstractIn the framework of Aerosol Robotic Network (AERONET), the aerosol optical, microphysical, and radiative properties were investigated over three sites (CRPSM_Malindi, Nairobi, and ICIPE_Mbita) in Kenya, East Africa, during 2006–2015. The annual mean (±σ) aerosol optical depth at 440 nm (AOD440) was found high at Mbita (0.27 ± 0.09) followed by Malindi (0.26 ± 0.07), and low at Nairobi (0.19 ± 0.04). Whereas the seasonal mean AOD440 noticed high (low) values during the local dry (wet) seasons. The aerosol optical properties: AOD, single scattering albedo, asymmetry parameter, and complex aerosol refractive index exhibited significant temporal and spectral heterogeneities illustrating the complexity of aerosol types with an abundance of fine‐mode aerosols during the local dry (June–July–August) season. Characterization of major aerosol types revealed the dominance of mixed‐type followed by biomass burning aerosols. The aerosol volume size distribution revealed that the coarse‐ over fine‐mode aerosols showed a significant contribution to the total volume particle concentration, especially at high (>0.3) AOD440. Further, the aerosol columnar number size distribution retrieved from the King's inversion of spectral AOD exhibited a power law distribution affirming multiplicity of aerosol sources. The direct aerosol radiative forcing values simulated in the shortwave region using the Santa Barbara DISORT Atmospheric Radiative Transfer model showed good correlation (r = >0.85) with the AERONET‐derived ones at the top‐of‐atmosphere, bottom‐of‐atmosphere, and within the atmosphere. The annual mean (±σ) top‐of‐atmosphere, bottom‐of‐atmosphere, and within the atmosphere forcing values were found in the range from −8.10 ± 3.75 to −13.23 ± 4.87, −34.54 ± 4.86 to −46.11 ± 10.27, and 26.63 ± 6.43 to 36.24 ± 7.26 W/m2, respectively, with an atmospheric heating rate of 0.74 ± 0.12–1.02 ± 0.20 K/day. The Santa Barbara DISORT Atmospheric Radiative Transfer‐derived direct aerosol radiative forcing exhibited significant temporal heterogeneity with high (low) during the local dry (wet) seasons. Results derived from the present study forms a basis for regional climate change studies and could increase the accuracy of climate models over this unexplored region of Africa.
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