Uncovering Patterns of African Easterly Waves: A PCA and K-Means Clustering Approach

African Easterly Waves (AEWs) play a crucial role in sub-saharan weather and influencing Tropical Cyclogenesis across the Atlantic basin. This study presents a novel approach of analyzing common AEW structures through Principal Component Analysis (PCA) and k-means clustering. PCA is applied to ERA5 reanalysis data to extract dominant spatial patterns of AEWs, which are then clustered using k-means to categorize the wave structures into distinct groups. The analysis reveals several prominent AEW patterns each with unique evolutionary characteristics. The temporal evolution of these wave structures and their associated convective activity is examined using GPM IMERG precipitation data and MCS tracking datasets. The study finds that different AEW clusters exhibit distinct convection signatures, with certain structures associated with enhanced convection in different wave relative coordinates. This clustering approach not only clarifies the variability in AEW patterns but also improves understanding of their impact on tropical convection. The research contributes to a more nuanced understanding of AEW dynamics and their interactions with convection in the African region.