Identifying hotspots for the emergence of unprecedented precipitation extremes in Sub-Saharan Africa under climate change

Abstract

The likelihood of unprecedented precipitation extremes is increasing across Sub-Saharan Africa (SSA), yet where and when future events may exceed the full range of historical experience remains understudied. While previous studies have documented historical trends and projected changes in precipitation extremes across sub regions of Africa, integrated SSA-wide assessments explicitly identifying hotspots of record-breaking precipitation extremes remain limited.Here, we present a sub-continental, SSA-wide assessment of the emergence of unprecedented precipitation extremes under future climate change. Unprecedented extremes are defined as future events (2030-2100) that exceed the observed and simulated range during a historical reference period (1950-2014). Using precipitation-based extreme metrics relevant to water security (e.g., maximum 1-day rainfall, maximum 5-day rainfall, consecutive wet and dry days, maximum and minimum seasonal rainfall amount), derived from Coupled Model Intercomparison Project – Phase 6 (CMIP6) multi-model large-ensembles, we explicitly assess the future time and regional hotspot of emergence of record-breaking precipitation conditions. We also examine changes in the probability of emergence of unprecedented extremes and their potential large-scale ocean-atmospheric drivers (e.g., El Nino-Southern Oscillation, Atlantic Multidecadal Variability, and Indian Ocean Dipole), while accounting for uncertainties associated with both model physics and internal climate variability.By systematically identifying where and when observed and retrospectively simulated precipitation limits are exceeded, this study offers a new sub-continental perspective on the emergence of unprecedented hydroclimatic conditions and provides a robust foundation for assessing future water security risks and supporting climate-resilient planning in Sub-Saharan Africa under increasing hydroclimatic uncertainty.