Abstract
Observed and simulated climate trends across South Africa in the period 1980–2014 are studied. Observed CRU3/CAMS (Climate Research Unit v3 / Climate Analysis and Monitoring System) air temperatures have increased by 0.02°C·yr−1 while NOAA/SODA sea temperatures have risen by 0.03°C·yr−1 in the Agulhas Current. A poleward expansion of the South Atlantic high in NCEP2/MERRA (National Center for Environmental Prediction v2 / Modern-Era Retrospective analysis for Research and Applications) has produced a trend toward south-easterly flow which contributes to a moist-east/dry-west pattern. Observed CHIRPS2 rainfall and NDVI vegetation fraction show no appreciable trend except near Cape Town where drier conditions in the period 1980–2014 correspond with enhanced coastal upwelling. CMIP5 model projections for rainfall up to 2050 reflect drying, except in the eastern coastal plains. While inter-annual fluctuations of South African rainfall overshadow linear trends, temperature increases account for 32% of observed variance.
Highlights
The semi-arid climate of South Africa is shaped by its plateau topography, sub-tropical latitude and the Agulhas and Benguela ocean currents
Rainfall and vegetation show no appreciable trend over the plateau, sensible heat has declined in the eastern lowlands
Instead the South Atlantic high did expand poleward into the mid-latitudes (Fig. 7), which corresponds with a positive trend in the Southern Annular Mode (0.025 hPa·yr−1, Marshall, 2003)
Summary
The semi-arid climate of South Africa is shaped by its plateau topography, sub-tropical latitude and the Agulhas and Benguela ocean currents. The low level zonal circulation alternates seasonally and rainfall fluctuations are influenced by the Pacific El Niño Southern Oscillation (ENSO) and adjacent South Atlantic and Indian Ocean sea surface temperatures (SST). Century-long meteorological measurements exist, coverage is uneven and instrument/station changes could affect trend estimates. Reanalysis systems that augment surface observations with other measurements and satellite estimates can limit the effects of station uncertainties and provide a more reliable means for evaluating trends since 1980. Data assimilation, historical reanalysis and coupled general circulation models (cGCM) are constantly improving (Meehl et al, 2007; Taylor et al, 2012); explorations of new data for observed and projected trends may provide new and better constrained information on which strategic adaptation and mitigating actions can be based
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