South Africa - Inkaba.org

Downscaling climate change scenarios to daily maximum
temperatures over Bloemfontein, South Africa
P.C. Tharaga and A.S. Steyn
Department of Soil Crop and Climate Science, University of the Free State, South Africa,
2005162884@ufs4life.ac.za
ABSTRACT
Climate change refers to a change in the state of the climate that can be recognised by changes in the mean and/or
the variability of its properties and that continues for an extended period, typically decades or longer. Climate
change may be limited to a specific region, or may occur across continents or the whole planet. Global Circulation
Models (GCMs) are the main source of climate projections under varying greenhouse gas emission scenarios, but
their output needs to be downscaled before it can be interpreted for point stations. The main objective of this study
was to downscale and quantify the projected changes in maximum temperatures that can be expected in
Bloemfontein within the 21 st century.
A statistical downscaling model (SDSM) was employed. SDSM reduces the task of statistical downscaling into the
following discrete steps: quality control, predictor screening, model calibration, generation of ensembles of future
data for the baseline climatic period using observed predictors, statistical analysis, generating of ensembles of
future weather data using GCM-derived predictors, and time series analysis. The model was calibrated and tested
with the use of observed datasets of daily temperature as the predictand and normalised NCEP variables as the
predictors. SDSM was then used to construct downscaled daily temperature projections under the A2 and B2
emission scenarios as obtained from the HadCM3 model. The projected changes for the future climate were
assessed by means of delta statistics.
Predictor screening revealed that the most important predictors for maximum temperature were mean sea level
pressure and 500 hPa height, probably because of the relationship to column thickness (which were not available as
a predictor variable). Wind direction was also included as a predictor variable because of its apparent influence on
temperatures in mid-latitudes. Preliminary results of the downscaling model will be presented.
KEYWORDS: climate change, statistical downscaling, maximum temperature
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