Long Term Characterization of Dust and Its Radiative Forcing over Kenya Using Satellite and Model-Based Data

Abstract

Dust aerosols play a critical role in atmospheric processes, influencing air quality, climate, and weather patterns through their interactions with radiation and cloud formation. This study aimed at characterizing the spatiotemporal distribution of dust and quantifying its radiative forcing over Kenya using a combination of satellite observations and model-based measurements. Multi-year datasets from MERRA-2 and MODIS were utilized to analyze dust loading and spatial variability. Additionally, radiative forcing (RF) derived from MERRA-2 and satellite observations was estimated to assess dust-induced changes in surface of-atmosphere (BOA), top-of-atmosphere (TOA) and within atmosphere (ATM). The findings on spatiotemporal variability of dust over Kenya, highlight high concentrations in northern regions during dry months and reductions during wet seasons (MAM and OND). While on particle size distribution, the analysis shows coarse-mode dominance in dry periods, depicting dominance of dust. On the other hand, dust mass concentrations peak in the northwest part of the study domain. Further, RF analysis indicates dust induces BOA and TOA cooling but atmospheric heating, with peak heating in June to July, local dry months. This study therefore recommends an enhanced integrated dust monitoring and modeling system, especially during dry seasons, to capture Dust AOD, size, and mass concentration. Further, targeted mitigation measures like afforestation, land-use planning and early warning systems should be prioritized to reduce dust emissions, improve climate model accuracy, and protect public health in vulnerable regions.