Assessing and Modelling the Impacts of Temperature, Cloud Cover and Relative Humidity on Global Solar Radiation: A Case Study in Ethiopia

International Journal of Electrical and Electronics Engineering

© 2025 by SSRG - IJEEE Journal

Volume 12 Issue 10

Year of Publication : 2025

Authors : Abera Jote Lidate, A Venkata Ramayya, Getachew Biru Worku, and Tefera Terefe Yetayew

10.14445/23488379/IJEEE-V12I10P112

How to Cite?

Abera Jote Lidate, A Venkata Ramayya, Getachew Biru Worku, and Tefera Terefe Yetayew, "Assessing and Modelling the Impacts of Temperature, Cloud Cover and Relative Humidity on Global Solar Radiation: A Case Study in Ethiopia," SSRG International Journal of Electrical and Electronics Engineering, vol. 12,  no. 10, pp. 157-169, 2025. Crossref, https://doi.org/10.14445/23488379/IJEEE-V12I10P112

Abstract:

Understanding the influence of climatological factors on solar energy is crucial for optimizing solar potential assessment, power generation, and load variation analysis. Despite Ethiopia's significant solar energy potential, the impacts of key climatic variables such as temperature (TΔ, Ta, Tmax), Cloud Cover (CC), and Relative Humidity (RH) fluctuations on Global Horizontal Irradiance (GHI) remain understudied, particularly in remote regions. This research bridges this gap by evaluating how these factors affect GHI distribution across Ethiopia. The study employs a multiple linear regression model, integrating seasonal climatic parameters with a Prescott sunshine-based model to predict GHI. Additionally, spatial interpolation via ArcGIS mapping analyzes the variations in cloud cover (35 sites of NASA data and nine sites from meteorological data), and relative humidity of (26 sites of meteorological data) against 73 sites' solar radiation patterns. Key uniqueness includes the integration of multi-climatic predictors on solar modeling and a spatially explicit assessment of Ethiopia’s solar potential under varying weather conditions. Results reveal that monthly average solar irradiance ranges from 3.56 kWh/m²/day (July, Awasa) to 6.78 kWh/m²/day (February, Mekele). When climatic factors (Ta, RH, CC) are incorporated, predicted GHI varies between 3.81 kWh/m²/day (July, Jimma) and 6.59 kWh/m²/day (February, Bahir Dar). The model demonstrates high accuracy, with a multiple correlation coefficient of R = 0.999 Awasa. Statistical validation confirms robustness, showing minimal errors. Mean Bias Error (MBE: (-0.65 to -0.48) kWh/m²/day; Mean Absolute Percentage Error MAPE: (0.004–0.344%). Spatial analysis indicates that cloud cover and RH reduce GHI in western, southwestern, and central highlands, whereas drier northeastern/southeastern regions receive higher radiation. The discussion underscores the implications for PV system sizing, energy demand management, and equipment selection based on climate-solar relationships. In conclusion, this study provides critical insights into Ethiopia’s solar energy dynamics, emphasizing the need for climate-informed solar planning. The findings support policymakers and energy developers in optimizing solar resource utilization under varying meteorological conditions.

Keywords:

Climatological impacts, Solar radiation, Prediction, Multiple linear regressions, Spatial interpolation.

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