Temperature Forecasting as a Means of Mitigating Climate Change and Its Effects: A Case Study of Mali

Temperature forecasts and trend analyzes were carried out for several locations in Mali as an important tool for warning of potentially threatening weather events such as severe heat waves, storms, droughts and floods, which could pose a great risk to humans and their environment. Five locations (Segou, Sikasso, Kayes, Gao and Taoudenni) across Mali (170 00’N – 40 00’W) were chosen for this research work. Satellite data of annual temperature obtained from the European Centre for Medium-Range Weather Forecast (ECMWF) database for 35 years (1985-2019) was used for this work. The Mann-Kendall trend test was carried out for various locations to observe and study the trend. Four Models including Auto Regressive and Integrated Moving Average (ARIMA), Exponential smoothening (ETS), TBATS (Trigonometric seasonality, Box-Cox transformation, ARMA errors, Trend and Seasonal components) and the linear model were employed to forecast average temperature for 10 years for all the locations. The model that produces the best forecast at the 95% confidence level is expected to have the lowest Root Mean Square Error (RMSE) value. The results showed that no significant trends were recorded at the considered locations. The linear model produced the best forecast for Segou, Kayes and Taoudenni, while the TBATS model produced the best forecast for Gao and the ARIMA model produced the best forecast for Sikasso.Citation: Billy, U., Udo, S., Ewona, I., Umoh, M., & Mfongang, A. (2023). Temperature Forecasting as a Means of Mitigating Climate Change and Its Effects: A Case Study of Mali. Trends in Renewable Energy, 9(2), 167-179. doi:http://dx.doi.org/10.17737/tre.2023.9.2.0015

Effects of Angstrom-Prescott and Hargreaves-Samani Coefficients on Climate Forcing and Solar PV Technology Selection in West Africa

We evaluated and compared the performance of simulated Angström-Prescott (AP) and Hargreaves-Samani (HS) models on monthly and annual timescales using generalized datasets covering the entire West African region. The fitted AP model yielded more efficient parameters of a = 0.366 and b = 0.459, whereas the HS model produced a 0.216 coefficient based on an annual timescale, which is more suitable in the region compared to coefficients recommended by the Food and Agriculture Organization (FAO) (a = 0.25 and b = 0.5) and HS (0.17), respectively. Employing the FAO and HS recommended coefficients will introduce a relative percentage error (RPE) of 18.388% and 27.19% compared to the RPEs of 0.0014% and 0.1036% obtained in this study, respectively. When considering time and resource availability in the absence of ground-measured datasets, the coefficients obtained in this study can be used for predicting global solar radiation within the region. According to the AP and HS coefficients, the polycrystalline module (p-Si) is more reliable than the monocrystalline module (m-Si) because the p-Si module has a higher tendency to withstand the high temperatures projected to affect the region due to its higher intrinsic properties based on the AP and HS coefficients assessment in the region.Citation: Agbor, M. E., Udo, S. O., Ewona, I. O., Nwokolo, S. C., Ogbulezie, J. C., Amadi, S. O., and Billy, U. A. (2023). Effects of Angstrom-Prescott and Hargreaves-Samani Coefficients on Climate Forcing and Solar PV Technology Selection in West Africa. Trends in Renewable Energy, 9, 78-106. DOI: 10.17737/tre.2023.9.1.0015

Potential impacts of climate change on global solar radiation and PV output using the CMIP6 model in West Africa

In this study, six different PV power technology models from similar climatic environments in West Africa were used to estimate the potential of PV generation and apply the model to evaluate the effects of climate change on PV output in the region. This was achieved by using historical and projected satellite datasets obtained from the ECMWF database. It was found that, compared to other technologies, poly-crystalline silicon (p-Si) technology yielded the highest increase in solar PV output compared to other modules in both best-case and moderate-case scenarios. However, in the worst-case scenario, amorphous silicon (a-Si) technology produces less than a 1% increase in solar PV production, while other technologies produce less than a 1% decrease in solar PV output. The CMIP6 climate model was also used to assess the effects of climate change on the region's global solar radiation. With the exception of the near- and far-future Boreal winter seasons (DJF), as the impact of climate change intensifies, there may be a corresponding decrease in solar radiation in the moderate- and worst-case scenarios in different seasons between 2015-2050 and 2051–2100, as well as in the annual resolution implying that solar energy should be the main contributor to renewable energy and low-carbon economic planning in the region. In addition, the authors used historical datasets to develop and test 171 theoretical models to estimate West Africa's solar radiation potential. According to the error metrics, the CARIMA-LG hybrid surpassed other models developed in this study as well as those obtained from the literature