Abstract:
This study Characterizes seasonal climate Variability and compares with Communities perception and explores Indigenous climate risk prediction methods over Jigjiga District, using Qualitative data collected from 96 households comprising both pastoralist and agro-pastoralist. Also FGDs and KII were utilized to triangulate and substantiate the findings from household survey. Besides, daily rainfall and temperature data of the period of 1980-2015 were obtained from NMA of Ethiopia. Data were analyzed by descriptive statistics using SPSS. INSTAT plus were used to analyze the onset and cessation of the rainy season and Dry spell, in addition to this first order Markov chain model was used to summarize and analyze the station based data. The result indicated that 93.5% of the interviewed households perceived climate change and variability with a declining rainfall and increasing temperature trend. The analysis of coefficient of variation revealed that Dira’ (MAM) rainfall has shown high inter-annual variability with a CV of 33.6% than Karan (JAS) and annual with a CV of 23.8%. The result indicated that there is significant increment of maximum and minimum temperature. The findings indicated that before 15 April was identified as the starting of rain for 24 years (66.7%) and before 30 April for 28 years (77.8%), For (JAS) before August-15 for 24 years (68.6%), also in the last decade the onset of rainfall shift from March to the April for MAM season and for JAS it shifts from July to August, it shows also short rainy (MAM) ends in the first 10-May the water balance for long rainy season (JAS) completed before 20-September. The finding also indicated that the maximum dry day length was highest in March for short rainy season and July for long rainy season, respectively. The main indigenous forecasting mechanisms follows Islamic calendar called “Hijri”; Astronomical observation and wind direction are the main in this Finding. Lastly the retrospective relationships between these indigenous forecasting systems and scientific forecasting system had a synergy/positive relationship.
