This study investigated the trends and variability of seasonal and annual rainfall and temperature data over southern Ethiopia using time series analysis for the period 1983–2016. Standard Anomaly Index (SAI), Coefficient of Variation (CV), Precipitations Concentration Index (PCI), and Standard Precipitation Index (SPI) were used to examine rainfall variability and develop drought indices over southern Ethiopia. Temporal changes of rainfall trends over the study period were detected using Mann Kendall (MK) trend test and Sen’s slope estimator. The results showed that the region experienced considerable rainfall variability and change that resulted in extended periods of drought and flood events within the study period. Results from SAI and SPI indicated an inter-annual rainfall variability with the proportions of years with below and above normal rainfall being estimated at 56% and 44% respectively. Results from the Mann Kendall trend test indicated an increasing trend of annual rainfall, Kiremt (summer) and Bega (dry) seasons whereas the Belg (spring) season rainfall showed a significant decreasing trend (p < 0.05). The annual rate of change for mean, maximum and minimum temperatures was found to be 0.042 °C, 0.027 °C, and 0.056 °C respectively. The findings from this study can be used by decision-makers in taking appropriate measures and interventions to avert the risks posed by changes in rainfall and temperature variability including extremes in order to enhance community adaptation and mitigation strategies in southern Ethiopia.

Rivers in the Lake Victoria Basin support a multitude of ecosystem services, and the economies of the riparian countries (Kenya, Tanzania, Uganda, Rwanda, and Burundi) rely on their discharge, but projections of their future discharges under various climate change scenarios are not available. Here, we apply Vector Autoregressive Moving Average models with eXogenous variables (VARMAX) statistical models to project hydrological discharge for 23 river catchments for the 2015–2100 period, under three representative concentration pathways (RCPs), namely RCPs 2.6, 4.5, and 8.5. We show an intensification of future annual rainfall by 25% in the eastern and 5–10% in the western part of the basin. At higher emission scenarios, the October to December season receives more rainfall than the March to May season. Temperature projections show a substantial increase in the mean annual minimum temperature by 1.3–4.5 °C and warming in the colder season (June to September) by 1.7–2.9 °C under RCP 4.5 and 4.9 °C under RCP 8.5 by 2085. Variability in future river discharge ranges from 5–267%, increases with emission intensity, and is the highest in rivers in the southern and south eastern parts of the basin. The flow trajectories reveal no systematic trends but suggest marked inter-annual variation, primarily in the timing and magnitude of discharge peaks and lows. The projections imply the need for coordinated transboundary river management in the future.

Variability in rainfall and temperature results in different impacts on agricultural practices. Assessesment of variability and trend of rainfall and temperature for the district of Musanze in Rwanda was conducted using six meteorological stations for a period of 37 years, ranging from 1981 to 2018, and data were obtained from Rwanda Meteorology Agency. Musanze district is located in highland areas of Rwanda, understanding the variability and trend in rainfall and temperature is paramount to increase the uptake of climate information and support strategic orientation. The Mann–Kendall nonparametric test and modified Mann–Kendall were used to assess the trend in rainfall and temperature, whereas Sen’s slope estimator was used to assess the magnitude of change. The results from both methods showed much similarity and consistency. The assessment of variability and trend in rainfall and temperature in Musanza district indicated that increasing temperature and decreasing rainfall trends gave an indication of changes in variability and trend in rainfall and temperature. The annual pattern revealed a substantial downward tendency of −25.7% for Nyange, the only station with constant decreasing trend over all seasons, DJF, −61.4%, SON, −12.2%, JJA, −40.3%, and MAM, −4.35. Temperature analysis for both maximum and minimum indicated increasing trend which was signal for constant warming up in the area. The results from coefficient of variation indicated a high disparity in rainfall variation from June to August which ranged between 51 and 74%, and other seasons changes were moderate.

The Kenya Meteorological Society (KMS) is a non-profit making professional/ scientific society, in a bid to promote the understanding of meteorology and its applications, among other functions, in Kenya and beyond.