Statistical downscaling of global circulation models to assess future climate changes in the Black Volta basin of Ghana

• Published in: Environmental challenges (Amsterdam, Netherlands) Vol. 5; p. 100299
• Main Authors: Siabi, Ebenezer K., Kabobah, Amos T., Akpoti, Komlavi, Anornu, Geophery K., Amo-Boateng, Mark, Nyantakyi, Emmanuel K.
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01-12-2021; Elsevier
• Subjects: Black Volta basin; CanESM2; Climate change; Climate scenarios; HadCM3; SDSM; Statistical downscaling; Climate change; Statistical downscaling; CanESM2; Climate scenarios; Black Volta basin; HadCM3; SDSM
• ISSN: 2667-0100; 2667-0100
• DOI: 10.1016/j.envc.2021.100299

•Statistical downscaling of temperature and precipitation was performed for the Black Volta basin.•Warmer than reference period temperatures are expected throughout the 21st century.•Monthly increase and decrease in precipitation are dependent on the scenarios.•Considering the projected changes, local adaptation and mitigation strategies are required.
Statistical Downscaling Model (SDSM) is a powerful model for climate change assessment. However, its usage remains very gray with limited studies on climate change (CC) assessment in Ghana. This study explored the applicability and suitability of SDSM for CC assessment in the Black Volta section of Ghana. The hydro-climatic parameters of Hadley center Coupled Model, version 3 (HadCM3) under the A2 and B2 Emissions Scenarios and the second-generation Canadian Earth System Model (CanESM2) under the Representative Concentration Pathways (RCPs) 2.6, 4.5 and 8.5 of the Coupled Model Intercomparison Project Phase 5 were downscaled with SDSM over the Black Volta section in Ghana using 40-year ground station data. The R2, NSE, Pbias, RMSE, and KGE of the calibrated and validated results ranged from 64% to 99%, 50–99%, -0.30–21.1, 0.01 °C–1.48 °C and 49%–99%, respectively for both models indicating a good agreement between the historical and the simulated data. The future climate change showed an increase in average minimum temperature of 0.05 °C (2020s), 0.11 °C (2050s), 0.21 °C (2080s) under the A2 scenario, 0.05 °C (2020s), 0.13 °C (2050s), 0.19 °C (2080s) under the B2 scenario, 0.01 °C (2020s), 0.02 °C (2050s), 0.02 °C (2080s) under the RCP 2.6, 0.06 °C (2020s), 0.13 °C (2050s), 0.19 °C (2080s) under the RCP 4.5, and 0.06 °C (2020s), 0.15 °C (2050s), 0.32 °C (2080s) under the RCP 8.5. For Maximum temperature, the average changes showed an increase of 0.17 °C (2020s), 0.36 °C (2050s), 1.14 °C (2080s) under the A2 scenario, 0.18 °C (2020s), 0.39 °C (2050s), 1.01 °C (2080s) under the B2 scenario, 0.03 °C (2020s), 0.16 °C (2050s), 0.17 °C (2080s) under the RCP 2.6, 0.02 °C (2020s), 0.26 °C (2050s), 0.45 °C (2080s) under the RCP 4.5, and 0.03 °C (2020s), 0.29 °C (2050s), 0.61 °C (2080s) under the RCP 8.5. The change in precipitation is not uniform with increase and decrease depending on the months and the scenarios. Overall, A2, B2 scenarios showed higher decrease in precipitation compared to RCPs scenarios. The SDSM is suitable for CC assessment and impact studies. The results from this study are to support the Climate Action, goal 13 of the SDGs.