Optimal application of climate data to the development of design wind speeds
The simultaneous development of the REWC and revision of the extreme wind statistics of South Africa created an opportunity to bring together a range of expertise that could contribute to the optimal development of design wind speed information. These include the knowledge of the statistical extraction of extreme wind observations from reanalysis and model data, the quality control and extreme value analysis of measured wind data, the reliability basis of statistical results, and the principles of wind action on structures and its standardization.
Methods with reanalysis and model data
In the case of the reanalysis data, the extreme wind quantiles are estimated using the Annual Maximum Method (AMM), with the Gumbel distribution (Gumbel 1958). The annual maximum winds of the standard conditions are derived using two approaches, namely the application of the geostrophic wind (Larsén and Mann 2009), as well as the surface wind and a generalization procedure (Badger et al. 2010 and Larsén et al. 2012a). Spectral correction is then applied (Larsén et al. 2012b) in order to augment the wind variability in a certain range of frequency, to the modeled time series. The variability is missed out by the smoothing effect embedded in the numerical modeling.
Analysis of measured data
South Africa is, in some regions, dominated by a mixed strong wind climate (Kruger et al. 2010). The methodologies using reanalysis of the data can become inappropriate for shorter time scales, as these were developed for strong wind climates dominated by synoptic-scale systems. Therefore, the extreme value analysis of the measured data serves as the major input in the development of extreme wind statistics. Here, various factors are considered which influence the appropriate analysis of the data, including record lengths, relevant strong wind mechanisms, and types of instrumentation and measuring environments (Kruger 2010).
The probability models applied in the reliability analysis should represent both the natural variability of strong winds and the uncertainties resulting from the phenomenological and statistical bases of the models. In converting the probability models into operational design procedures, provision needs to be made in terms of regional characteristics on the one hand and a range of design conditions and situations.
Based on standardized structural design procedures strong wind, at a given location, is typically defined in terms of a 50-year return period quantile. Regional distribution is obtained by mapping the results from the network of observations with sufficient resolution to capture geographical trends, but also sufficiently simplified to be used for operational design (Retief et al 2013). Normalized probability models per strong wind sub-region are used to derive design values from the characteristic value wind map.
Investigations so far addressed the unique limitations of both the estimation of the REWC and design wind speeds with measured or reanalysis/model. For the measured data these mainly refer to the quality of the data, the density of the observation network and the significant spatial and regional tendencies of the strong wind climate. For the reanalysis/model approach in South Africa, these refer to the different strong wind mechanisms, prevalence of thunderstorms as a source of strong winds, and the dominance of mixed strong wind climate conditions in some parts of the country. The optimal consideration of these associated strengths and limitations is required in the integration of the results of different approaches.
Eventually, strong wind probability models for the optimal design of the built environment are developed. These take into consideration the inherent uncertainty associated with the occurrence of strong winds, as well as the simplification required to characteristic and design values for use by practitioners in the built environment on the basis of reliability analysis. The process of integrating REWC probability models into the wind engineering and reliability calibration has been initiated as part of the comprehensive approach taken.
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