TEMPERATURE AND PRECIPITATION TREND ANALYSIS USING THE CMIP6 MODEL IN THE UPPER EAST REGION OF GHANA

Abstract

The aim of this study was to assess the historical and projected climate trend analysis in the Upper East Region, Ghana, using time series and modelled climate data under shared socio economic pathways scenarios. Due to the climate data scarcity challenge in Ghana, there is a need to rely on high-resolution satellite-based climate products for climate change studies. Accordingly, temperature and precipitation data of six stations were obtained from Ghana meteorological stations; in addition, precipitation data of five satellite stations were obtained from CHIRPS data with 0.05’ (5 km) resolution to complement the in-situ datasets; and the temperature data for the satellite station obtained from the NASA power project were extracted. Modelled climate data were obtained from five GCMs in the CMIP data portal on the WCRP website. R software was used to extract NetCDF-format GCM data to Excel format and CMhyd was used for downscaling GCM data. The variance scaling method and local intensity scaling methods were used for temperature and precipitation bias correction, respectively. The Mann-Kendall (MK) method was used to determine the statistical significance of a change and identify trends in temperature and precipitation. The results of historical temperatures were significantly increased, while historical precipitation was significantly decreased. The projected mean annual temperature will increase significantly, peaking at 1.80°C by 2065, precipitation will, conversely, show significant spatial variability and seasonal dependency. For instance, by 2065, precipitation is projected to decrease between 10.05% and 12.66%. The results concluded by recommending policymakers develop climate change adaptation strategies guided by future climate scenarios.