Browsing by Author "Wanjala, Dennis W."

Filter results by typing the first few letters
Now showing 1 - 2 of 2
  • No Thumbnail Available
    Item
    Anomaly Detection in Selected Aerosol Optical Properties and Associated Climate Variables Using a Multivariate Hidden Markov Model: A Case Study over Kenya
    (Open Access Library Journal, 2025-10-23) Wanjala, Dennis W.; Makokha, John Wanjala; Khamala, Geoffrey W.
    Understanding aerosol climate interactions is crucial for monitoring atmospheric changes and supporting climate resilience efforts, particularly in vulnerable regions such as Kenya. This study applies a Multivariate Hidden Markov Model (HMM) to detect anomalies in key Aerosol Optical Properties (AOP) i.e., Aerosol Optical Depth (AOD), Single Scattering Albedo (SSA), and Ångström Exponent (AE) alongside associated climate variables; Surface Air Temperature (SAT) and Rainfall Rate (RR), over the period 2000-2022. Satellitebased datasets from MODIS, MERRA-2, and TRMM were used to derive monthly means, and descriptive statistics and linear regression were initially employed to characterize long-term variability. The objectives of this study were to examine the temporal and spatial variability of key aerosol and climate parameters over Kenya, detect and classify anomalies in the multivariate dataset using HMM and to interpret the climatic and environmental implications of detected anomalies and their possible causes. The HMM approach successfully identified temporal patterns and hidden states, enabling the detection of significant anomalous periods, particularly between 2010 and 2016, which aligned with regional biomass burning events and transboundary pollution episodes. Results indicate that AOD and SSA anomalies correspond with periods of elevated temperature and reduced rainfall, highlighting potential climate-aerosol feedbacks. The findings demonstrate the utility of multivariate HMMs in capturing the complex dynamics of aerosol-climate interactions and provide a foundation for improved air quality monitoring and climate impact assessments in Kenya which is critical for improving environmental monitoring and enhancing regional climate adaptation strategies.
  • No Thumbnail Available
    Item
    Spatiotemporal Analysis of Aerosol Optical Properties and Their Associations Using Satellite and Ground-Based Observations
    (Atmospheric and Climate Sciences, 2025-09-29) Wanjala, Dennis W.; Makokha, John Wanjala; Khamala, Geoffrey W.
    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.