Projections of future climate change trends in four urban centers of southwest Ethiopia were examined under a high Representative Concentration Pathways (RCP8.5) scenario for near- (2030), mid- (2050), and long-term (2080) periods based on high-resolution (0.22⁰) Coordinated Regional Climate Downscaling Experiment (CORDEX) for Africa data. The multi-model ensemble projects annual maximum and minimum temperatures increasing by 0.047 °C per year (R² > 0.3) and 0.038 °C per year (R² > 0.7), respectively, with the rates increased by a factor of 10 for decadal projections between the 2030s and 2080s. The monthly maximum temperature increase is projected to be 1.41 °C and 2.82 °C by 2050 and 2080, respectively. In contrast, the monthly minimum temperature increase is projected to reach +3.2 °C in 2080. The overall seasonal multi-model ensemble average shows an increment in maximum temperature by +1.1 °C and +1.9 °C in 2050 and 2080, with the highest change in the winter, followed by spring, summer, and autumn. Similarly, the future minimum temperature is projected to increase across all seasons by 2080, with increases ranging from 0.4 °C (2030s) to 3.2 °C (2080s). All models consistently project increasing trends in maximum and minimum temperatures, while the majority of the models projected declining future precipitation compared to the base period of 1971–2005. A two-tailed T-test (alpha = 0.05) shows a significant change in future temperature patterns, but no significant changes in precipitation were identified. Changes in daily temperature extremes were found in spring, summer, and autumn, with the largest increases in extreme heat in winter. Therefore, our results support proactive urban planning that considers suitable adaptation and mitigation strategies against increasing air temperatures in urban centers in southwest Ethiopia. Future work will examine the likely changes in temperature and precipitation extremes.

Rainfall is one of the most important climate elements for agricultural production throughout the world. This study analyzes the seasonal and annual rainfall variability and its implications on agriculture production in the East Hararghe Zone of Oromia, Ethiopia. Rainfall is a critical factor influencing agricultural productivity and water resource management in this region, where agriculture serves as the mainstay of the economy and livelihood for millions. Utilizing historical precipitation data from meteorological stations across East Hararghe from 1981 to 2023, we employed statistical methods to analyze trends, patterns, and anomalies in both seasonal (Kiremt and Belg) and annual rainfall totals. This study used GeoCLIM version 1.2.1, ArcGIS version 10.3.1, and QGIS 3.12.1, and Python version for data analysis. The findings revealed that significant seasonal and inter-annual variability characterized by periods of extreme weather events that have profound implications for food security. There are two main rainy seasons, the Belg (February, March, April, and May; short rains) and the Kiremt (June, July, August, and September; long rains), and one dry season, the Bega (October, November, December, and January; no rain). The Kiremt season (June to September), essential for crop cultivation, exhibits distinct fluctuations linked to regional climate phenomena such as El Niño/La Niña–Southern Oscillation. Moreover, our results indicated an increasing trend of Kiremt rainfall standardized anomaly during 2007, 2014, 2019, and 2020 but also highlighted concerning patterns of erratic distribution within the Belg season. Based on the results, we underscore the necessity for adaptive agricultural practices to mitigate risks associated with climate variability. Understanding these dynamics is vital for concerned sectors, policymakers, and researchers aiming to enhance resilience among vulnerable communities dependent on rain-fed agriculture.

This study identified the practices of adaptation strategies to climate change in Jimma, Bedelle, Bonga, and Sokorru urban centers using a survey of 384 households, 55 key informant interviews, 4 focus group discussions, and field observations. A cross-sectional study design was employed from 2019 to 2021. The adaptive capacity of municipalities to reduce climate extreme events was rated as poor by the majority (51%), mostly reactive measures (76%). The climate hazards identified in four urban centers were riverine and flash floods, urban heat waves, landslides, and windstorms. The urban households practiced lifestyle modification, reduce paved surfaces, the use of air conditioner, planting trees, and multiple windows. The adaptation strategies practiced by municipalities include the relocation of prone areas, the support of basic amenities, the construction of protection walls, diversion ditches, the clearance of waterways and rivers, greenery, and park development. The adaptation actions were constrained by a lack of awareness, commitment, cooperation and coordination, adaptive capacity, and participation. Gray/physical infrastructures (costly but important) as adaptation actions were hampered by the low municipal capacity. We recommend that urban authorities should incorporate climate change adaptation strategies into urban planning and development proactively to ensure future resilient climate smart urban centers of southwest Ethiopia.

East Africa is dependent on rain, and experiences two major rainy seasons from March to May and October to December. The main objective is to investigate the strong signal characteristics of rainfall systems and variability of wind patterns using the empirical orthogonal function (EOF) Mode 1 across different pressure levels over East Africa. This study utilized multiple datasets to analyze rainfall variability over East Africa, using monthly rainfall data from the Climate Hazards Group Infrared Precipitation with Station data (CHIRPS) and others from 1991 to 2020. EOF analysis, the North test, and assessments of variance and correlation were analyzed using MATLAB R2023a. The result revealed that the northern regions demonstrated pronounced variability influenced by seasonal monsoons and jet streams, while the southern regions exhibited unique wind patterns. The vertical velocity analysis in EOF1 interactions between atmospheric dynamics in baroclinic and barotropic zones shows that temperature gradients drive notable vertical motions of rising and sinking air. The vertical cross-sectional analysis during EOF1 emphasized the importance of water vapor below 850 hPa, with specific humidity of 10 g/kg, which is essential for rainfall formation. Eastward water vapor condensation was associated with decreased precipitation, while higher humidity from the south led to increased rainfall. These findings underscore the need for regional circulation system monitoring to improve seasonal weather forecasts and future research.

Ethiopia is a country that heavily relies on rainfall-aided cultivation which is carried out by small-scale landowners, leaving it very vulnerable to climate change and fluctuation. The primary goal of this research is to investigate how climate change affects maize yield in Wolaita zone of Ethiopia. The authors were employed a linear regression method to evaluate the relationship between climate parameters and maize yield. Sen's slope magnitude estimator and the Mann-Kendal trend test were used to assess the significance of climate change. The outcome demonstrated that the temperature extreme indices of warm days and the length of warm days were considerably higher by 37.5% and 3.7% of days per year, however, cold days and cold spells were significantly decreased. Over the 1981-2021 periods, there was a significant upward pattern in TXx and TNn at an average of 0.033°C and 0.034°C. There was a considerable decline of 2.3% in the simple daily precipitation intensity index and 33% decreased in extremely heavy precipitation, respectively. The correlation analysis's findings indicated that growing period precipitation and maize outputs were positively correlated, but negatively correlated with maximum and minimum temperatures. Extreme temperature and precipitation were more explained a maize yield than average climate patterns. 12.4%, 14.76%, 13.08%, and 7.95% of maize output variability was attributed by the growing season mean climate conditions, which include precipitation, mean, minimum, and maximum temperature. The variability of maize output was explained by combined impact of precipitation and temperature extremes were 67.7% and 45.0%, respectively. Therefore, livelihood diversification and relevant policy formulation are suggested to adapt inevitable climate change by implementing irrigation and resistant varieties to improve maize yield production.

Climate change is becoming a global threat to human well-being and the sustainability of the planet Earth. The central cores of urban centers are significantly observed warmer than their surrounding outskirts or rural areas, which is identified as the urban heat island (UHI) effect fueled by massive Land Use Land Cover (LULC) change. The main research aim was to examine the Spatio-temporal variation of UHI dynamics based on the land surface temperature (LST), Normalized Difference Vegetation Index (NDVI) and built-up density in the urban centers (Jimma, Bedelle, Bonga, and Sokorru) landscape using techniques of remote sensing. In this study, Landsat thematic mapper (TM) for 1987 and Landsat Operational Imagery (OLI) for 2018 in the extraction of LST were used for examining UHI. Also, LULC, NDVI and built-up density of the urban centers were analyzed. The results of the study showed that the urban core had greater LST and UHI values, due to an increase of built-up density and a decline of green space. The result of LST mean value range rose from 20.1 ℃ (Bonga) to 23.3 ℃ (Sokorru) in 1987 and 22.67 ℃ (Bedelle) to 24.74 ℃ (Bonga), and 24.72 ℃ (Sokorru) in 2018, while the maximum observed LST value range from 28.97 ℃ (Jimma) in 1987 to 32.61 ℃ (Bonga) in 2018. The maximum range of UHI mean value was from 11.23 ℃ (1987) to 14.04 ℃ (2018), while the maximum observed UHI value ranged from 19.63 ℃ in 1987 to 23.32 ℃ in 2018 over Jimma city. The computed correlation at 5% significance results showed LULC change has a significant association with surface air temperature (r = 0.621, Sig. (2-tailed) = 0.031) accompanied by UHI impacts. We recommended urban authorities, policymakers, and urban planners should consider the effects of LST and UHI in urban planning to realize climate-smart urban centers of tomorrow in urban centers of southwest Ethiopia. Climate change is becoming a global threat to human well-being and the sustainability of the planet Earth. The central cores of urban centers are significantly observed warmer than their surrounding outskirts or rural areas, which is identified as the urban heat island (UHI) effect fueled by massive Land Use Land Cover (LULC) change. The main research aim was to examine the Spatio-temporal variation of UHI dynamics based on the land surface temperature (LST), Normalized Difference Vegetation Index (NDVI) and built-up density in the urban centers (Jimma, Bedelle, Bonga, and Sokorru) landscape using techniques of remote sensing. In this study, Landsat thematic mapper (TM) for 1987 and Landsat Operational Imagery (OLI) for 2018 in the extraction of LST were used for examining UHI. Also, LULC, NDVI and built-up density of the urban centers were analyzed. The results of the study showed that the urban core had greater LST and UHI values, due to an increase of built-up density and a decline of green space. The result of LST mean value range rose from 20.1 ℃ (Bonga) to 23.3 ℃ (Sokorru) in 1987 and 22.67 ℃ (Bedelle) to 24.74 ℃ (Bonga), and 24.72 ℃ (Sokorru) in 2018, while the maximum observed LST value range from 28.97 ℃ (Jimma) in 1987 to 32.61 ℃ (Bonga) in 2018. The maximum range of UHI mean value was from 11.23 ℃ (1987) to 14.04 ℃ (2018), while the maximum observed UHI value ranged from 19.63 ℃ in 1987 to 23.32 ℃ in 2018 over Jimma city. The computed correlation at 5% significance results showed LULC change has a significant association with surface air temperature (r = 0.621, Sig. (2-tailed) = 0.031) accompanied by UHI impacts. We recommended urban authorities, policymakers, and urban planners should consider the effects of LST and UHI in urban planning to realize climate-smart urban centers of tomorrow in urban centers of southwest Ethiopia.