| Abstract: |
| Climate-related environmental and humanitariancrisis are important challenges in the Great Horn of Africa (GHA). In theabsence of long-term past climate records in the region, tree-rings arevaluable climate proxies, reflecting past climate variations and complementingclimate records prior to the instrumental era. We established annually resolvedmulti-century tree-ring chronology from Juniperusproceratrees in northern Ethiopia,the longest series yet for the GHA. The chronology correlates significantlywith wet-season (r = .64,p <.01)and annual (r= .68,p <.01)regional rainfall. Reconstructed rainfall since A.D. 1811 revealed significantinterannual variations between 2.2 and 3.8 year periodicity, with significantdecadal and multidecadal variations during 1855–1900and 1960–1990.The duration of negative and positive rainfall anomalies varied between 1–7years and 1–8 years. Approximately78.4% (95%) of reconstructed dry (extreme dry) and 85.4% (95%) of wet (extremewet) events lasted for 1 year only and corresponded to historical records offamine and flooding, suggesting that future climate change studies should beboth trend and extreme event focused. The average return periods for dry(extreme dry) and wet (extreme wet) events were 4.1 (8.8) years and 4.1 (9.5)years. Extreme-dry conditions during the 19th century were concurrent withdrought episodes in equatorial eastern Africa that occurred at the end of theLittle Ice Age. El Ni~no and La Ni~na eventsmatched with 38.5% and 50% of extreme-dry and extreme-wet events. Equivalentmatches for positive and negative Indian Ocean Dipole events were weaker,reaching 23.1 and 25%, respectively. Spatial correlations revealed that reconstructedrainfall represents wet-season rainfall variations over northern Ethiopia andlarge parts of the Sahel belt. The data presented are useful for backcasting climateand hydrological models and for developing regional strategic plans to manage scarceand contested water resources. Historical perspectives on long-term regionalrainfall variability improve the interpretation of recent climate trends. |
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