Downscaled Climate Change Projections in Urban Centers of Southwest Ethiopia Using CORDEX Africa Simulations

Abstract

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.

Impact of urbanization on exposure to extreme warming in megacities

“…In addition to the geographical bias, the review also pointed out that only 14% of reviewed articles examined the combined effect of climate change and urban heat island and only 16% examined consequences to urban population. Recently, more studies [27] , [28] have been done to address the geographical bias; however, the aforementioned issues (e.g., lack of consideration of urbanization and/or anthropogenic heat) persist.…”

Evaluation of climate change, urbanization, and low-impact development practices on urban flooding

“…Thirty years of daily recorded rainfall data (1980–2020) were obtained from the National Meteorological Agency of Ethiopia. However, after signing up for the CORDEX research, fine resolution (0.44°×0.44°) future projected rainfall data of the global climate models: EC-EARTH, MPI-ES-LR, CanESM2, HadGEM2-ES, and CNRM-CM5 were downloaded [ 35 , 36 ]. The daily rainfall data from each GCM was downscaled for the study area using the RACMO22T, REMO2009, RCA4, and RACMO22T RCMs for the Representative Concentration Pathway of RCP 4.5 and RCP 8.5.…”

Assessment of the effects of climate change on water balance components in the upper Erer subbasin, Ethiopia

“…[ 7 , [9] , [10] , [11] , [12] , [13] , [14] ] indicate that their effect increases water shortage in the system. The increase in temperature and rainfall variability expected in the future [ [15] , [16] , [17] , [18] ]; [ 19 ]] aggravate the water resources stress. Hence, climate change studies are remarkable in the sustainability of water sources and the effects can touch different parts of the world [ 20 , 21 ].…”

“…Today many researchers such as [ [25] , [26] , [27] , [28] , [29] , [30] ] rank the importance of water resource challenge by climate change effects. But, most of these analyses were implemented on large basins with coarser data [ 18 ]. So, high-resolution data are required to efficiently quantify climate change impacts at local scale.…”

“…Several hydrological models have been in use to model hydrological processes using spatially distributed information and time series data [ [45] , [46] , [47] , [48] ] under data scarce. The Soil and Water Assessment Tool (SWAT) model is implemented to quantify hydrological response and climate change studies under data scarce regions [ 17 , 18 , 38 , [49] , [50] , [51] , [52] ] and also used in this study.…”