Rainfall is the most critical and key variable both in atmospheric and hydrological cycle. Its patterns usually have spatial and temporal variability. Its variability is assumed to be the main cause for the frequently occurring climate extreme events such as drought and flood. In this study, spectrum analysis, cross-spectral analysis as well as seasonal auto-regressive integrated moving average (SARIMA) model were used in intending to predict the pattern and its extreme event frequency of rainfall in Dire Dawa Region based on data obtained from Dire Dawa and adjacent stations: Dengego and Haramaya. The result indicated that the amount of rainfall at Dengego and Haramaya are more or less the same on average in all seasons and much higher than that of Dire Dawa during last 30 year study period. The variability of annual rainfall in Dire Dawa during the study period is a bit larger than neighboring station's rainfall (Dengego and Haramaya), indicating that climate instability is high in Dire Dawa than other nearby stations. The result also indicates that relatively there is a tendency of increasing pattern in average annual rainfall of Dire Dawa in forecasted period. In the region, the rainfall extreme event like flood predicts or inferred to be recurring at about 4.17 years. Moreover, the rainfall periodicities of Dengego and Dire Dawa are found to be more likely associated, which implies that rainfall extreme event frequency in two districts is statistical significantly associated. It is proposed that assessing the factors that cause the fluctuation in the pattern and frequency of rainfall distribution in the region is needed to be study. The impacts of climate variability and climate change are evident on almost all socio-economic sectors. The output of this study can play an important role in the design of hydrological structures in the area of study and help the policy makers in improve their decisions by taking into consideration the available and future water resources. Prediction of Long-term Pattern and its Extreme Event Materials and Methods Data and variable of the studyA time series of monthly 30 years rainfall data in mm for the period January, 1984 to January, 2014 collected by the National Meteorological Agency of Ethiopia were used in the study. The data were collected from the synoptic stations of Dire Dawa and adjacent station: Dengego and Haramaya for further investigation. MethodologyThe development of climatology as a science has given rise to growing statistical applications on climatic information. Conducting investigations using standard statistical methodologies is an essential step in the development of climatology [13]. For instance, time series analysis is used in order to evaluate the temporal and spatial behavior of rainfall [14]. In this study a univariate Box-Jenkins Methods, in particular, Seasonal Autoregressive Integrated Moving Average (SARIMA) methods and spectral analysis and cross-spectral analysis are employed [15].Seasonal autoregressive integrated moving average (SA...