Spatial and Temporal Variability in Temperature and Rainfall over Mecha area, Ethiopia

Z. Meseret¹ , S. Belay²

Section:Research Paper, Product Type: Journal-Paper
Vol.5 , Issue.12 , pp.56-65, Dec-2019

Online published on Dec 31, 2019

Copyright © Z. Meseret, S. Belay . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
 

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Abstract :
Variability of temperature and rainfall and climatic hazards like droughts, floods, and windstorms affect agricultural activities. In the study area, the main livelihood of the people depends on rain-fed agriculture that would be affecting by the variation of rainfall and temperature. The study aims to analyze the recent spatiotemporal variability and trends of rainfall and temperature at seasonal and annual timescales over Mecha area where detail analysis of the two climate indicators does not exist, to inform development planners and improve the effectiveness of agricultural activities. In this study, we analyzed gridded monthly temperature and rainfall data from 1983 to 2014. The data were constructed to 154 points at a 10×10 km resolution and input into Geographic Information Systems (GIS) to model the spatial relationship of rainfall and temperature. Linear regression, standardized anomalies used to analyze temporal variation. Findings reveal that annual minimum and maximum temperature significantly increased at a rate of 0.11OC and 0.08OC per decade respectively. Seasonal warming trends for maximum temperature were significant in the winter and spring seasons (p = 0.05) whereas (p = 0.01) in winter and autumn for minimum temperature. Adjusted R-square values of the OLS method resulted in spatial relationships for annual rainfall, minimum and maximum temperature are 0.41, 0.44 and 0.68 respectively. The mean annual and seasonal rainfall distribution shows statistically non-significant increasing trends. These results call a need to develop local level and context-specific climate change adaptation strategies.

Key-Words / Index Term :
trend, spatial variability, temporal variability, climate factors

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