Validation of CORDEX regional climate models to simulate climate trends and variability across various agro-ecological zones of North Shewa, Ethiopia
•Accurate information on climate variability is a front line of agriculture.•There is both temporal and spatial variability of temperature and rainfall in the three AEZs of North Shewa.•The use of well-validated RCM provides efficient climate data which capture the patterns, and predict future varia...
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Veröffentlicht in: | Water-Energy Nexus 2024-12, Vol.7, p.87-102 |
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Sprache: | eng |
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Zusammenfassung: | •Accurate information on climate variability is a front line of agriculture.•There is both temporal and spatial variability of temperature and rainfall in the three AEZs of North Shewa.•The use of well-validated RCM provides efficient climate data which capture the patterns, and predict future variability of climate.•It is better to use the ensemble average of the output from the RCMs for precise estimation of data than specific RCMs.
Climate variability significantly affects the overall agricultural production and productivity over space and time. To quantify the effect of climate variability on natural systems on Earth in the future, the use of regional climate models (RCMs) as a tool is mandatory. Thus, the use of well-validated RCM provides efficient climate data, and predicts future climate variability over agroecological zones (AEZs). Eleven RCMs from CORDEX-Ethiopia were evaluated to simulate maximum temperature (Tmax), minimum temperature (Tmin) and rainfall variability over space and time, to validate their performance and to select the best-fit models. The temporal variability Tmax and rainfall was smaller with a CV of 10 %, indicating uniform distribution over stations. However, CV for Tmin over stations shows satisfactory distributions. Most of the evaluated RCMs have a better capability to capture the spatial variability of rainfall,Tmax, and Tmin in some stations. However, some of the RCMs can handle the spatial variability of Tmax while others are not. None of the RCMs can handle the spatial variability of Tmin in Debre Birhan, Majete, and Kewat AEZs. In general, most RCMs can capture the spatial and temporal variability of rainfall and temperature. It might be better to use the ensemble average of the output from these RCMs for precise estimation of data than specific RCMs. Therefore, this work could suggest the use of high-resolution RCMs for the projection of temperature and rainfall over different AEZs. |
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ISSN: | 2588-9125 2588-9125 |
DOI: | 10.1016/j.wen.2024.01.001 |