Masters Degrees (Soil, Crop and Climate Sciences)
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Browsing Masters Degrees (Soil, Crop and Climate Sciences) by Advisor "Engelbrecht, Francois A."
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Item Open Access Downscaling of global circulation model predictions to daily rainfall over the upper Olifants River catchment(University of the Free State, 2008) Steyn, Abraham Stephanus; Walker, Sue; Engelbrecht, Francois A.English: Climate change could have far reaching consequences for all spheres of life. Continued greenhouse gas (GHG) emissions at or above current rates will cause further warming and induce further changes in the global climate system. This is particularly true for southern Africa where an ever-increasing population is already causing an increase in the demand for fresh water and much of the agricultural food production depends on rain. Global Circulation Models (GCMs) are the main source of climate projections under varying GHG emission scenarios. The spatial resolution of GCMs is too coarse to resolve sub-grid processes such as convection and precipitation. However, agrohydrological application models often require information at a network of point locations, implying the need to downscale the GCM output. Downscaling approaches have subsequently emerged as a means of employing large-scale atmospheric predictor variables (such as the 500 hPa meridional velocity) to develop station-scale meteorological series. Variables such as daily rainfall, which are not always accurately represented by the GCMs, can be derived using statistical approaches to build relationships between the required forecast parameter and variables that are simulated more accurately. Previous investigators have used the statistical downscaling model (SDSM) to downscale climate projections of daily rainfall over North America and Europe. A similar methodology was adopted to downscale daily rainfall projections under the A2 and B2 emission scenarios at five selected quaternary catchments (QCs) within the Upper Olifants River catchment. The downscaling was performed for the summer months of December, January and February (DJF). The set of generic predictors which were identified across all five QCs included surface airflow strength, vorticity, divergence and specific humidity, 850 hPa wind direction and relative humidity as well as 500 hPa relative humidity and meridional wind velocity. Generally, all the predictors exhibited a reasonably low explanatory power. The considerable variation in the resultant correlations between the large-scale predictors and the observed daily precipitation at the selected QCs may very well have stemmed from the convective nature of the rainfall patterns, being irregularly distributed in space and time. Generally, the downscaling model results were not very encouraging as the model failed to produce satisfactory results for four of the five QCs. For one of the QCs, namely Groblersdal, the projected changes for the future climate were assessed by calculating several delta-statistics. Only a few of the indices revealed a clear change, while most indices exhibited inconsistent changes for DJF across three future periods centred on the 2020s, 2050s and 2080s. Similar changes in the characteristics of the daily rainfall series are projected for the early and mid 21st century under the A2 and B2 scenarios. Differences in the expected GHG forcing under the B2 scenario does not seem to affect any of the rainfall indices differently from the A2 scenario until the late 21st century. It should however be noted that the projected changes are often smaller than the model errors which implies that the downscaling model is simply not sensitive enough for the projected changes to be taken at face value. Therefore the results should only be used with caution. The fact that the downscaling procedure provides similar results for the A2 and B2 scenarios suggests that it is at least to some extent robust and stable.