Abstract:
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.
Language:
English
Date of publication:
2015
Country:
Region Focus:
East Africa
University/affiliation:
Collection:
RUFORUM Theses and Dissertations
Agris Subject Categories:
Agrovoc terms:
Additional keywords:
Licence conditions:
Open Access
Access restriction:
Supervisor:
Diriba Korecha (PhD) and Lisanework Nigatu(PhD, Assoc. Prof)
Form:
Printed resource
Publisher:
ISSN:
E_ISSN:
Edition:
Extent:
xvi,105
Notes:
Msc. Thesis in Agrometeorology and natural risk management.