Abstract
Identifying GCMs that represent the climate of a specific area is crucial for climate change studies. However, the uncertainties in GCMs caused by computational constraints, such as coarser resolution, physical parameterizations, initializations, and model structures, make it imperative to identify a representative individual or group of GCM for a climate impact study. An advanced envelope-based multi-criteria selection approach was used to identify a subset of the most appropriate future GCMs in the Upper Awash Basin. The skill accounting is based on (1) the range of projected mean changes of climate variables, (2) range of variability in climate extremes and, (3) model run performance to represent historical climate data. Statistical downscaling and bias correction were made for the selected model runs. The downscaled and bias-corrected monthly values for precipitation are expected to increase from 0.42% to 2.82% in mid-century and 0.15% to 3.79% by the end century considering the SSP4.5 scenario. For SSP8.5, it increases from 1.45% to 5.51% and 2.57% to 9.78% in the respective periods. Likewise, under the SSP4.5 forcing scenario, the monthly average air temperature projected to be warmer, which increased from 0.68°C to 1.55°C during mid-century and 0.09°C to 1.92°C end-of-century. Meanwhile, for SSP8.5, the projection indicates an increment of 0.19°C to 1.98°C under mid-century and 2.37°C to 7.00°C end-century. The projected change of future precipitation and temperature in the study basin increases the precipitation intensities, wet days and dry spells due to high-temperature increment.
Agricultural landscape change impact on the quality of land: An African continent-wide assessment in gained and displaced agricultural lands