Search

Abstract Background Understanding the climate variability at local scale could help suggest local adaptation responses to manage climate associated risks. This paper analyzed the variability and trend of climate in semi-arid Borana zone of southern Ethiopia over the period 1981–2018 using Mann–Kendall (MK) test, Sen’s Slope Estimator (SEE) and inverse distance weighted (IDW) interpolation technique. Gridded (4 km * 4 km) climate data (daily precipitation, daily maximum temperature (Tmax) and minimum temperature (Tmin)) were collected from National Meteorology Agency (NMA) of Ethiopia. Results The results revealed the study area received a mean monthly precipitation of 39.19 mm and a monthly mean Tmax and Tmin of 29.66 °C and 16.31 °C were observed respectively. Rainfall shows a significant increasing trend during August, October and November and extremely variable during December, January and February where CV > 100%. Tmax shows a significant warming trend during August but January, February, August and October exhibited similar trend for Tmin. Rainfall and Tmin shows a significant trend during Meher and no trend for the rest of the seasons. Mean annual rainfall shows a significant increase where no trend observed for both Tmax and Tmin at this timescale. Decadal rainfall and Tmin exhibited no trend but Tmax show significant warming trend during 2001–2010 decade. Better rainfall and cooler temperature were observed in the north central, northeastern and northwestern whereas the southeastern and southwestern regions were drier and warmer. Conclusion Rainfall is highly variable than temperature both at temporal and spatial scales in Borana. The intensity of rainfall decreases from the northeastern and northwestern parts towards the southwest while temperature increased from the north central parts towards the southwest for Tmax and the southeast for Tmin. The effect of topography is substantial for the local scale variability observed in the study area. Internal variability is observed at temporal and spatial scales and therefore any adaptation responses to local climate variability should consider the microscale climate.