Spatiotemporal Variability and Trend Analysis of Solar Radiation in North-Central Nigeria (Federal Capital Territory, Abuja and Nasarawa State), using Non-parametric Statistical Methods
DOI:
https://doi.org/10.33003/fjs-2026-1019-6163Keywords:
Solar radiation, Spatiotemporal variability, Mann-Kendall test, Sen's slope, Innovative Trend Analysis, Radiation Anomaly Index, Federal Capital Territory, Nasarawa StateAbstract
This study assessed the spatiotemporal variability and temporal trends of mean daily global solar radiation in the Federal Capital Territory (FCT), Abuja, and Nasarawa State (NS), Nigeria, using complementary nonparametric methods. Monthly average daily global solar radiation data for 2014–2023 were analyzed using descriptive statistics, coefficient of variation, Radiation Anomaly Index (RAI), Mann-Kendall (M-K) test, Sen's slope estimator, Spearman rank correlation, and Innovative Trend Analysis (ITA). The results revealed pronounced seasonal and interannual variability at both locations. FCT recorded its highest and lowest monthly mean radiation in February (17.56 MJm-2day-1) and August (10.12 MJm-2day-1), respectively, whereas NS recorded corresponding values of 24.87 MJm-2day-1 in January and 15.64 MJm-2day-1 in July. NS generally exhibited higher radiation levels, while FCT showed greater relative variability. The strongest positive RAI occurred in 2021 at both locations, with values of 2.00 for FCT and 1.27 for NS; the strongest negative anomalies were recorded in 2014 for FCT (−1.22) and 2018 for NS (−1.69). Annual M-K results indicated no statistically significant trend in FCT (Z = 1.43, p = 0.156; Sen's slope = 0.1083) or NS (Z = 0.54, p = 0.601; Sen's slope = 0.0094). Following adjustment for multiple monthly tests using the Holm-Bonferroni correction, the previously identified significant monthly trends did not remain statistically significant. ITA further indicated month-dependent changes rather than a uniform temporal pattern. Overall, both locations possess favorable solar resources, although seasonal and interannual variability should be incorporated into photovoltaic resource assessment, system design, and renewable-energy planning.
References
Abdullahi, N. I., Mohammed, S., Owoseni, Y., Ijimdiya, S., & Suleiman, K. (2023). A non-parametric Mann-Kendall and Sen's slope estimate as a method for detecting trend within hydro-meteorological time series: A review. Academy Journal of Science and Engineering.
Adelakun, A. O., & Adelakun, F. O. (2024). Mathematical modeling and seasonal solar radiation variability in Nigeria's geopolitical zones. Solar Energy/related journal publication.
Agbo, E. P. (2021). Forecasting of meteorological variables using statistical methods and tools. arXiv.
Agbo, E. P., Edet, C. O., Magu, T. O., Njok, A. O., Ekpo, C. M., & Louis, H. (2021). Solar energy: A panacea for the electricity generation crisis in Nigeria. Heliyon, 7(5), e07016. https://doi.org/10.1016/j.heliyon.2021.e07016.
Amadi, S., Dike, T., & Nwokolo, S. (2020). Global solar radiation characteristics at Calabar and Port Harcourt cities in Nigeria. Trends in Renewable Energy, 6(2), 111–130. https://doi.org/10.17737/tre.2020.6.2.00114.
Andah, M., Ibrahim, U., Idris, M. M., Mundi, A. A., & Sarki, M. U. (2020). Solar radiation modelling and measurement techniques in Lafia Zone, Nasarawa State, Nigeria. EDUCATUM Journal of Science, Mathematics and Technology, 7(1). https://doi.org/10.37134/ejsmt.vol7.1.6.2020.
Carpentieri, A., Folini, D., Wild, M., Vuilleumier, L., & Meyer, A. (2022). Satellite-derived solar radiation for intra-hour and intra-day applications: Biases and uncertainties by season and altitude. Atmospheric Measurement Techniques.
Carpentieri, A., Pulkkinen, S., Nerini, D., Folini, D., & Meyer, A. (2023). Intraday probabilistic forecasts of solar resources with cloud scale-dependent autoregressive advection. Atmospheric/solar-resource forecasting literature.
Chanchangi, Y. N., Adu, F., Ghosh, A., Sundaram, S., & Mallick, T. K. (2023). Nigeria's energy review: Focusing on solar energy potential and penetration. Environment, Development and Sustainability, 25, 5755–5796. https://doi.org/10.1007/s10668-022-02308-4.
Garba, H., & Udokpoh, U. U. (2023). Analysis of trend in meteorological and hydrological time-series using Mann-Kendall and Sen's slope estimator statistical test in Akwa Ibom State, Nigeria. International Journal of Environment and Climate Change, 13(10), 1017–1035. https://doi.org/10.9734/IJECC/2023/v13i102748.
International Energy Agency (IEA). (2024). Renewables 2024. Paris: IEA.
International Renewable Energy Agency (IRENA). (2023). Renewable Energy Market Analysis: Africa and Its Regions. Abu Dhabi: IRENA.
International Renewable Energy Agency (IRENA). (2024). Renewable Capacity Statistics 2024. Abu Dhabi: IRENA.
Mamman, A., Ibrahim, U., Dauda, Y. S., Idris, M. M., & Paul, B. (2020). Variation of solar radiation in Akwanga, Nasarawa State, Nigeria. Journal of Energy Research and Reviews, 5(2), 17–24. https://doi.org/10.9734/jenrr/2020/v5i230144.
Okono, M. A., Agbo, E. P., Ekah, B. J., Ekah, U. J., Ettah, E. B., & Edet, C. O. (2022). Statistical analysis and distribution of global solar radiation and temperature over Southern Nigeria. Journal of the Nigerian Society of Physical Sciences, 4, 588. https://doi.org/10.46481/jnsps.2022.588.
Serinaldi, F., Chebana, F., & Kilsby, C. G. (2020). Dissecting innovative trend analysis. Stochastic Environmental Research and Risk Assessment, 34, 733–754. https://doi.org/10.1007/s00477-020-01797-x.
Vrac, M., et al. (2020). Effects of prewhitening method, time granularity and time segmentation on Mann–Kendall trend detection and associated Sen's slope. Atmospheric Measurement Techniques, 13, 6945–6960.
Wang, F., Shao, W., Yu, H., Kan, G., He, X., Zhang, D., Ren, M., & Wang, G. (2020). Re-evaluation of the power of the Mann-Kendall test for detecting monotonic trends in hydrometeorological time series. Frontiers in Earth Science, 8, 14. https://doi.org/10.3389/feart.2020.00014.
Montgomery, Douglas C., & Runger, George C. (2018). Applied Statistics and Probability for Engineers (7th ed.). John Wiley & Sons.
Kendall, M. G. (1975). Rank Correlation Methods (4th ed.). Charles Griffin.
Sen, P. K. (1968). Estimates of the regression coefficient based on Kendall's tau. Journal of the American Statistical Association, 63(324), 1379–1389. https://doi.org/10.1080/01621459.1968.10480934
National Aeronautics and Space Administration. (2024). Climate and Earth’s energy budget. NASA Science. NASA Science: Climate and Earth’s Energy Budget
World Meteorological Organization. (2024). The Sun’s impact on the Earth. World Meteorological Organization. WMO: The Sun’s Impact on the Earth
Ohunakin, O. S., Adaramola, M. S., Oyewola, O. M., & Fagbenle, R. O. (2015). Solar radiation variability in Nigeria based on multiyear RegCM3 simulations. Renewable Energy, 74, 195–207. https://doi.org/10.1016/j.renene.2014.07.057
Isikwue, B. C., Akiishi, M., & Utah, E. U. (2014). Investigation of the seasonal variations in the solar radiation balance and other solar energy parameters in some cities in Nigeria. Earth Science Research, 3(2), 59–67. https://doi.org/10.5539/esr.v3n2p59.
Ajayi, O. O., Ohijeagbon, O. D., Nwadialo, C. E., & Olasope, O. (2023). Solar radiation potential and energy availability in Southwest Nigeria. Renewable Energy, 205, 1126–1138.
Zar, J. H. (2005). Spearman rank correlation. In P. Armitage & T. Colton (Eds.), Encyclopedia of biostatistics. John Wiley & Sons. https://doi.org/10.1002/0470011815.b2a15150
Şen, Z. (2012). Innovative trend analysis methodology. Journal of Hydrologic Engineering, 17(9), 1042–1046. https://doi.org/10.1061/(ASCE)HE.1943-5584.0000556
Soneye, O. O., Ayoola, M. A., Ajao, I. A., & Jegede, O. O. (2019). Diurnal and seasonal variations of the incoming solar radiation flux at a tropical station, Ile-Ife, Nigeria. Heliyon, 5(5), e01673. https://doi.org/10.1016/j.heliyon.2019.e01673
Wilks, D. S. (2019). Statistical methods in the atmospheric sciences (4th ed.). Elsevier. https://doi.org/10.1016/C2017-0-03921-6.
Downloads
Published
Issue
Section
Categories
License
Copyright (c) 2026 Medina Umar, Terkimbi Tor, George Gala Nyam, Damilola Oluwafemi Samson, Omolara Victoria Oyelade
This work is licensed under a Creative Commons Attribution 4.0 International License.
