Abstract:
Rainfall is undoubtedly the most significant factor for life’s continuity. South Africa is prone to future climate uncertainties due to global climate change. The aim of this study is to investigate rainfall variability and change in South Africa on a present day (1976-2005), near-future (2006-2035) and far-future (2036-2065) climate. For the study, 3 RCMs (REMO2009, RCA4 and CCLM4-8-17), forming part of CORDEX-Africa project were nested within 5 different CIMP5_GCMs of low resolution. GPCC precipitation, NOAA GHCN_CAMS Land Temperature and other NCEP reanalysis products were useful in validating models in simulations of present-day climate. RCP4.5 and RCP8.5 emission scenarios from IPCC-AR5 were used for future climate projections. On the validation, each regional climate model displayed different signature on simulations, rainfall in particular because this is a variable that is affected most by sub-grid process. Simulations nested within MIROC5 simulated more precipitation than simulations forced with other GCMs, due to more large-scale moisture convergence into the nested domain. There were differences in projections of RCM nested within the same GCM, as well as with the same RCM nested within different GCMs, on the future. Models nested within MPI project wetter conditions over the eastern parts of Limpopo, while the other two projected drier conditions in the same area. REMO2009 forced on MPI uniquely projected drying of Western Cape throughout the seasons on both RCPs and futures. Simulations conducted with the RCP8.5 scenario forcing are generally found to be associated with either a larger increase in temperature, or an increase in area associated with higher temperature increases. CCLM4-8-17 forced on HadGEM2 projected below average temperatures over the northwest parts of the country under the RCP8.5 scenarios. MPI driving model projected a general reduction of evaporation values, with lowest over northeast, northwest parts and south coastal parts of South Africa, in contrary to adjacent oceans. In this study, we have sought to identify the sources of uncertainties amongst model simulations between either the RCMs or the driving GCMs.
