研究目的
Investigating aerosol optical, microphysical, and radiative properties over three environmentally distinct AERONET sites in Kenya, East Africa, to understand their influence on regional climate effects.
研究成果
The study provides comprehensive insights into aerosol properties over East Africa, showing significant seasonal and spectral variations dominated by mixed and biomass burning aerosols. Coarse-mode particles contribute significantly to pollution episodes. Radiative forcing indicates surface cooling and atmospheric warming, with heating rates up to 1.02 K day-1. Findings support improved climate modeling in the region, highlighting the need for further investigation into atmospheric stability and dynamic effects.
研究不足
Uncertainties in aerosol property retrievals due to assumptions in models (e.g., spherical aerosols in King's inversion), limited data availability for certain parameters (e.g., SSA only when AOD440 > 0.4), and potential underestimation from non-spherical dust aerosols. Use of Level 1.5 data for inversion products as a compromise. Dependencies on input variables like surface albedo and atmospheric profiles may introduce errors.
1：Experimental Design and Method Selection:
The study utilized ground-based remote sensing data from AERONET Cimel Sunphotometers to measure aerosol properties. Methods included aerosol type discrimination using AOD vs. AE and FMF vs. SSA clustering, King's inversion technique for columnar size distribution retrieval, and the SBDART radiative transfer model for simulating direct aerosol radiative forcing.
2：Sample Selection and Data Sources:
Data from three AERONET sites in Kenya (CRPSM_Malindi, Nairobi, ICIPE_Mbita) during 2006-2015 were used. Level
3：0 and Level 5 data products were employed, including spectral AOD, AE, SSA, ASY, RI, and VSD. Meteorological data from ECMWF, CRU, and TRMM were also sourced. List of Experimental Equipment and Materials:
Cimel Sunphotometer (CE-318) for aerosol measurements.
4：Experimental Procedures and Operational Workflow:
Measurements taken every 15-30 minutes at specific wavelengths. Data processed using AERONET algorithms, King's inversion for CSD, and SBDART model inputs including aerosol optical properties, surface albedo, solar zenith angle, and atmospheric profiles.
5：Data Analysis Methods:
Statistical analysis (e.g., Box-Whisker plots), correlation coefficients, and seasonal averaging. Radiative forcing calculated using SBDART, with integration over 24 hours for daily means.
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