We analyze the potential effect of global warming levels (GWLs) of 1.5 • C and 2 • C above pre-industrial levels (1861−1890) on mean temperature and precipitation as well as intra-seasonal precipitation extremes over the Greater Horn of Africa. We used a large, 25-member regional climate model ensemble from the Coordinated Regional Downscaling Experiment and show that, compared to the control period of 1971−2000, annual mean near-surface temperature is projected to increase by more than 1 • C and 1.5 • C over most parts of the Greater Horn of Africa, under GWLs of 1.5 • C and 2 • C respectively. The highest temperature increases are projected in the northern region, covering most parts of Sudan and northern parts of Ethiopia, and the lowest temperature increases are projected over the coastal belt of Tanzania. However, the projected mean surface temperature difference between 2 • C and 1. 5 • C GWLs is higher than 0.5 • C over nearly all land points, reaching 0.8 • C over Sudan and northern Ethiopia. This implies that the Greater Horn of Africa will warm faster than the global mean.While projected changes in precipitation are mostly uncertain across the Greater Horn of Africa, there is a substantial decrease over the central and northern parts of Ethiopia. Additionally, the length of dry and wet spells is projected to increase and decrease respectively. The combined effect of a reduction in rainfall and the changes in the wet and dry spells will likely impact negatively on the livelihoods of people within the coastal cities, lake regions, highlands as well as arid and semi-arid lands of Kenya, Tanzania, Somalia, Ethiopia and Sudan. The probable impacts of these changes on key sectors such as agriculture, water, energy and health sectors, will likely call for formulation of actionable policies geared towards adaptation and mitigation of the impacts of 1.5 • C and 2 • C warming.

The study evaluates the ability of ten regional climate models (RCMs) to simulate the present-day rainfall over Uganda within the Coordinated Regional Downscaling Experiment (CORDEX) for the period 1990-2008. The models' ability to reproduce the space-time variability of annual, seasonal, and interannual rainfall has been diagnosed. A series of metrics have been employed to quantify the RCM-simulated rainfall pattern discrepancies and biases compared to three gridded observational datasets. It is found that most models underestimate the annual rainfall over the country; however, the seasonality of rainfall is properly reproduced by the RCMs with a bimodal component over the major part of the country and a unimodal component over the north. Models reproduce the interannual variability of the dry season (December-February) but fail with the long and short rains seasons even if the ENSO and IOD signal is correctly simulated by most models. In many aspects, the UQAM-CRCM5 RCM is found to perform best over the region. Overall, the ensemble mean of the ten RCMs reproduces the rainfall climatology over Uganda with reasonable skill.

The study was conducted in the districts of Nakaseke and Nakasongola stratified into four farming systems of crop dominancy, pastoralists, mixed crop and livestock and fishing. The study was guided by two research questions: (1) how do community residents perceive climate change/variability? (2) What is the trend and nature of climate variability and how does it compare with people's perceptions? Ninety eight percent (98%) of the respondents reported that the routine patterns of weather and climate had changed in the last 5 to 10 years and it has become less predictable with sunshine hours being extended and rainfall amounts being reduced. This compared well with the analyzed secondary data. Over 78% respondents perceived climate change and variability to be caused by tree cutting other than the known scientific reasons like increase in industrial fumes or increased fossil fuel use. Climate data showed that over the period 1961 to 2010 the number of dry spells within a rainfall season had increased with the most significant increase observed in the first rainfall season of March to May as compared to the season of September to November. The first dry season of June/July to August is short while the second dry season of December to February is long during the study period. The two rainfall seasons of March to May and September to November seem to be merging into one major season from May to November. Temperature data shows a significant increasing trend in mean annual temperatures with the most increase observed in the mean annual minimum temperatures than the maximum temperatures.

This study examines the effects of 1.5°C and 2°C global warming levels (GWLs) on intra-seasonal rainfall characteristics over the Greater Horn of Africa. The impacts are analysed based on the outputs of a 25-member regional multi-model ensemble from the Coordinated Regional Climate Downscaling Experiment project. The regional climate models were driven by Coupled Model Intercomparison Project Phase 5 Global Climate Models for historical and future (RCP8.5) periods. We analyse the three major seasons over the region, namely March-May, June-September, and October-December. Results indicate widespread robust changes in the mean intra-seasonal rainfall characteristics at 1.5°C and 2°C GWLs especially for the June-September and October-December seasons. The March-May season is projected to shift for both GWL scenarios with the season starting and ending early. During the June-September season, there is a robust indication of delayed onset, reduction in consecutive wet days and shortening of the length of rainy season over parts of the northern sector under 2°C GWL. During the October-December season, the region is projected to have late-onset, delayed cessation, reduced consecutive wet days and a longer season over most of the equatorial region under the 2°C GWL. These results indicate that it is crucial to limit the GWL to below 1.5°C as the differences between the 1.5°C and 2°C GWLs in some cases exacerbates changes in the intra-seasonal rainfall characteristics over the Greater Horn of Africa.

Understanding variations in rainfall in tropical regions is important due to its impacts on water resources, health and agriculture. This study assessed the dekadal rainfall patterns and rain days to determine intra-seasonal rainfall variability during the March-May season using the Mann-Kendall (MK) trend test and simple linear regression (SLR) over the period 2000-2015. Results showed an increasing trend of both dekadal rainfall amount and rain days (third and seventh dekads). The light rain days (SLR = 0.181; MK = 0.350) and wet days (SLR = 0.092; MK = 0.118) also depict an increasing trend. The rate of increase of light rain days and wet days during the third dekad (light rain days: SLR = 0.020; MK = 0.279 and wet days: SLR = 0.146; MK = 0.376) was slightly greater than during the seventh dekad (light rain days: SLR = 0.014; MK = 0.018 and wet days: SLR = 0.061; MK = 0.315) dekad. Seventy-four percent accounted for 2-4 consecutive dry days, but no significant trend was detected. The extreme rainfall was increasing over the third (MK = 0.363) and seventh (MK = 0.429) dekads. The rainfall amount and rain days were highly correlated (r: 0.43-0.72).