Journal of Water and Climate Change (Sep 2021)

Changes in length of rainy season and rainfall extremes under moderate greenhouse gas emission scenario in the Vea catchment, Ghana

  • Isaac Larbi,
  • Bessah Enoch,
  • Clement Nyamekye,
  • Joshua Amuzu,
  • Gloria C. Okafor,
  • Daniel Kwawuvi,
  • Yaw Mensah Asare

DOI
https://doi.org/10.2166/wcc.2021.316
Journal volume & issue
Vol. 12, no. 6
pp. 2594 – 2607

Abstract

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The economic implications of extreme climate changes are found to impact sub-Saharan Africa negatively. This study aimed to analyze projected changes in length of rainy season (LRS), and rainfall extreme indices at the Vea catchment, Ghana. The analysis was performed using high-resolution simulated rainfall data from the Weather Research and Forecasting (WRF) model under moderate greenhouse gas emission scenario for the period 2020–2049 relative to the 1981–2010 period. LRS was computed from the difference between rainfall onset and cessation dates, and its trends were assessed using Mann–Kendall test and Sen's slope estimator. Annual rainfall intensity and frequency indices were computed. Results showed an increase in mean LRS from 168 to 177 days, which was at a rate of 1 day/year in the future (2020–2049). The LRS increase would be more significant at northern and south-western parts of the catchment. Rainfall intensity and frequency indices are projected to increase at spatial scale across the catchment. Projected changes in rainfall extremes could increase the frequency and intensity of drought and flood events. Thus, it is necessary to integrate suitable climate change adaptation measures such as rainwater harvesting, flood control measures, and development of early warning systems in the planning process by decision-makers at the catchment. HIGHLIGHTS The spatio-temporal changes in length of rainy season and rainfall extreme indices were analyzed under moderate greenhouse gas emission scenario for the vea catchment.; High resolution regional climate model was employed in this study.; Rainfall intensity and frequency indices are projected to increase at the spatial scale across the catchment.; Mann–Kendall test, onset and cessation of rainfall were used for the data analsysis.;

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