Meteorological data trend analysis and local community perception towards climate change: a case study of Jimma City, Southwestern Ethiopia

This study examines the trends of temperature and rainfall as an evidence of climate change and variability in Jimma city, southwestern Ethiopia. Historical rainfall and temperature data of forty years (1978-2017) obtained from Ethiopian Meteorological Agency and household questionnaire survey (n=150) were used to assess the climate trend of Jimma city. Descriptive statistics have been used to assess people's perceptions towards climate change. Rainfall and temperature variability were analyzed using standard deviations, coefficient of variation (CV), rainfall anomaly index and standard precipitation index. The magnitude of the linear trends is estimated using the Sen's slope estimator, and Mann-Kendall test to check the statistical significance of the trends. Findings revealed that average maximum and minimum temperature showed statistically significant trend. The magnitude of increasing trends of monthly maximum temperature varies between 0.033 and 0.045 degrees C/year in January and April, respectively. For minimum temperature the magnitude of trends vary between 0.081 degrees C/year in November and 0.025 degrees C/year in April. Annual rainfall variability is relatively stable with 11% CV, while monthly rainfall variability was found to be very high in December, January, and February with CV 115, 80, and 75, respectively. The result from household survey shows that 85% perceived the increasing trends of temperature. The community perceived that climate change is having an impact on vector-borne diseases. Our results indicate that climate-borne disease and pests, food insecurity, frequent drought and flooding appear to have a significant relationship with climate change withpvalue 0.000, 0.029, 0.010, and 0.047, respectively. Thus, it is crucial to plan for climate change adaptation and mitigation strategies to minimize the potential impacts of climate change in the study area.