Unsupervised segmentation and clustering time series approach to Southern Africa rainfall regime changes
Analysis of hydro-climatological time series and spatiotemporal dynamics of meteorological variables has become critical in the context of climate change, especially in Southern African countries where rain-fed agriculture is predominant. In this work, we compared modern unsupervised time series and segmentation approaches and commonly used time series models to analyse rainfall regime changes in the coastal, sub-humid and semi-arid regions of Southern Africa.