Aerosols play a critical role in Earth’s climate system. They influence cloud formation, atmospheric dynamics and Earth’s energy balance. This study presents a comprehensive spatiotemporal analysis of aerosol optical depth (AOD), Angstrom Exponent (AE), Single scattering Albedo (SSA) and their associations with primary climate variables such as Surface Air Temperature (SAT) and Rainfall Rates (RR). The present study derived its data from both satellites based remote sensing data and ground based observation, i.e. , Moderate Resolution Imaging Spectrometer (MODIS), Modern Era Retrospective Analysis for Research and Application 2 (MERRA-2) and Tropical Rainfall Mission (TRMM) between the years 2000 to 2022. These data platforms are run and maintained by National Aeronautics and Space Administration (NASA). The researcher examined monthly and annual trends. Hidden Markov models were employed to determine the patterns and potential cause of variabilities and the link between aerosol optical properties and climate variables. The researcher determined trends in AOP and evaluated the trends in climate variables using HMM. Satellite-based dataset provided enhanced spatial resolution, accurate and observation. The findings gave more insight into aerosol dynamics and accurate climate modelling; the researcher addressed critical gaps in understanding the interactions between aerosols and climate variables in Kenya, a region highly vulnerable to the impacts of climate change and air quality degradation, hence better environment planning policy. Identified hidden patterns and transitions that were often overlooked by traditional methods. The methodological innovation is not only relevant for Kenya but also adaptable to other regions facing similar environmental challenges, thereby contributing to the broader field of atmospheric sciences.
KeywordsMODISMERRA-2TRMMHMMKenya
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