This study examines seasonal climate prediction method and evaluates its social and economic values in reducing climate-related hazards on livestock productivity over Borana Zone using monthly rainfall and temperature data recorded over Borana Zone for the period of 1983-2014 as well as regional and global oceanic and atmospheric indices. The predictive potential of March-May, June-August and September-November rainfall in Borana Zone also examined using mainly statistical methods and identified traditional climate prediction indicators. Multivariate statistical techniques would have applied to analyze and predict seasonal rainfall. Global and regional processes have distinct impact long rainy (MAM) and short rainy (SON) climate patterns over Borana Zone. This is also reflected in a relatively in regional and local climate drivers. Result indicates that two to three distinct homogenous rainfall zones in the region. In addition, the study shows that long rainy (MAM) has declined and while temperature over all season has risen throughout the past consecutive decades. ENSO predictability skill for JJA season has less potential to provide seasonal rainfall forecasts one or two months in advance. Altogether, the results as generated from this study indicates a prevailing of recurrent droughts, particularly during the main rainy season, which has been predicted in advance using integrating scientific climate prediction and a wisdom of indigenous knowledge of Borana Community. Seasonal climate prediction is a promising tool to enhance societal exposure to climate-relate calamities by availing timely and local-specific weather and climate forecasts.
Date of publication:
RUFORUM Theses and Dissertations
Agris Subject Categories:
Diriba Korecha (PhD) and Lisanework Nigatu(PhD, Assoc. Prof)
Msc. Thesis in Agrometeorology and natural risk management.