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Strong winds in South Africa : part 2 : mapping of updated statistics

Kruger, A. C. ; Retief, J. V. ; Goliger, A. M. (2013-08)

CITATION: Kruger, A. C., Retief, J. V. & Goliger, A. M. 2013. Strong winds in South Africa : part 2 : mapping of updated statistics. Journal of the South African Institution of Civil Engineering, 55(2)46-58.

The original publication is available at


Although wind is the most important environmental action on buildings and structures in South Africa, the last comprehensive strong wind analysis was conducted in 1985. The current wind loading code is still based on the strong wind quantiles forthcoming from that analysis. Wind data available for strong wind analysis has increased about five-fold, due to the employment of automatic weather station (AWS) technology by the South African Weather Service. This makes an updated assessment of strong winds in South Africa imperative. Based on the estimation of strong winds as reported in the accompanying paper (see page 29 in this volume), the spatial interpolation of 50-year characteristic strong wind values to provide updated design wind speed maps is reported in this paper. In addition to taking account of short recording periods and the effects of the mixed strong wind climate, the exposure of the weather stations was considered and correction factors applied. Quantile values were adjusted to compensate for the small data samples. The resultant design maps reveal regions of relatively high and low quantiles, but with an improved relationship with physical conditions compared to the previous analyses. Consequently some significant differences in quantiles between the present and previous analyses were found. The complexity of the resulting strong wind maps is not only the result of the improved resolution of the larger number of weather stations, but also due to an improved identification of the effects of physical factors such as the mixed strong wind climate and topography. Guidance can also be derived for future updating, such as incorporating accumulated observations and improved coverage by additional AWS in critical regions.

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