Environmental Challenges 6 (2022) 100439 Contents lists available at ScienceDirect Environmental Challenges journal homepage: www.elsevier.com/locate/envc Assessing climate change projections in the Volta Basin using the CORDEX-Africa climate simulations and statistical bias-correction Kofi A. Yeboah a,∗ , Komlavi Akpoti b , Amos T. Kabo-bah a , Eric A. Ofosu a,b , Ebenezer K. Siabi c , Eric M. Mortey c,d , Samuel A. Okyereh b a Department of Civil and Environmental Engineering, University of Energy and Natural Resources, P. O. Box 214, Sunyani, Ghana b Regional Center for Energy and Environmental Sustainability (RCEES), University of Energy and Natural Resources (UENR), P. O. Box 214, Sunyani, Ghana c Earth Observation Research and Innovation Center (EORIC), University of Energy and Natural Resources, P. O. Box 214, Sunyani, Ghana d Faculty of Science and Techniques, Doctoral Research Program in Climate Change and Energy (DRP-CCE) of the West African Science Service Center on Climate Change and Adapted Land Use (WASCAL), Université Abdou Moumouni, P.O. Box 10662, Niamey 8000, Niger a r t i c l e i n f o Keywords: Climate change CMIP5 simulations RCPs scenarios Volta Basin CMhyd Bias-correction a b s t r a c t Climate change potential impacts are evaluated through the changes in the local and regional climate. However, Global and Regional Climate simulated outputs do not often capture these changes well, hampering their direct applicability. Impact studies using coarse resolution data require bias-correction of climate variables, a process that minimizes the discrepancy between observed and simulated climate variables. This study assessed climate projections in the Volta Basin using an ensemble of 4 Regional Climate Models under the Representative Concen- tration Pathways-RCPs 4.5 and 8.5 scenarios in the CORDEX-Africa datasets. These datasets were bias-corrected using the Climate Model data for hydrologic modeling tool (CMhyd) and 27-years of Climate Forecast System Reanalysis data. The performances of the ensemble bias-corrected precipitation ranged from 97-99%, 93-99%, 70-485mm, and -9-5% for R 2 , NSE, RMSE, and PBIAS respectively. TMAX bias-correction performances ranged from 65-99%, 27-99%, 0-4°C and -2-7% for R 2 , NSE, RMSE and PBIAS respectively. For TMIN, the performances ranged from 91–99%, 91–99%, 0-1°C and 0-1% for R 2 , NSE, RMSE and PBIAS respectively. The annual projected change in precipitation under RCP4.5 and 8.5 indicated a decrease in precipitation for the near (the 2020s), the mid-century (2050s), and the end far (2080s) with a relative increase from late November to January, a pe- riod currently part of dry season period in the Volta Basin. This suggests that the basin could expect a potential shift in the rainy season. The 12-month standard precipitation index suggests more frequent and longer drought periods in the future. Changes in annual mean monthly maximum temperature revealed an increase under all scenarios and throughout the century with an intensified increase by the end of the century under the higher CO 2 concentration scenario (RCP 8.5). The study showed that under RCP 4.5 and 8.5 scenarios, the Volta Basin will experience frequent drought and extreme precipitation events, warmer days, and nights temperatures although RCP 4.5 showed a relatively lower magnitude of these extremes. It is therefore important to emphasize the need for strong adaptation to preserve water resources, limit negative impacts on energy and agricultural production, and other ecosystems services in the Volta Basin. 1. Introduction Anthropogenic activities have influenced our environment for cen- turies. These impacts from the industrial revolution have extended through global to local scales (Baede et al., 2001; Dai, 2011). Primarily, land use and land cover change and burning of fossil fuel are respon- sible for the increase of greenhouse gases concentration in the atmo- sphere (De Matteis, 2019; Wuebbles and Jain, 2001). This distorts en- ergy balances and increases the atmospheric temperature which results ∗ Corresponding author. E-mail address: quophius@gmail.com (K.A. Yeboah). in changes in the climate. Africa is likely to have a greater mean annual warming than the global annual average warming in all seasons with the subtropics getting drier than the moist tropics (Anwar Al-Gamal et al., 2009; Nikulin et al., 2018; James et al., 2013). Thus, climate change impacts are widespread and are mostly the outcome of interlinked nat- ural and anthropogenic activities which influence natural phenomena in the atmosphere and the oceanic ecology (IPCC, 2014), presenting di- verse consequences on climatic conditions and distribution worldwide. Since a lot of factors including land surface, polar ice sheets, and the sun, among others, instigate global climate conditions, it becomes im- perative for computer programs to be built so that adequate data can be harnessed, stored, and employed in simulating these complex pro- cesses. Therefore, the advent of climate models serves an important role https://doi.org/10.1016/j.envc.2021.100439 Received 31 August 2021; Received in revised form 31 December 2021; Accepted 31 December 2021 2667-0100/© 2022 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)