ResearchSpace

Strong winds in South Africa, part 1: application of estimation methods

Show simple item record

dc.contributor.author Kruger, A
dc.contributor.author Retief, J
dc.contributor.author Goliger, Adam M
dc.date.accessioned 2013-11-19T05:40:35Z
dc.date.available 2013-11-19T05:40:35Z
dc.date.issued 2013-08
dc.identifier.citation Kruger, A, Retief, J and Goliger, A. 2013. Strong winds in South Africa, part 1: application of estimation methods. Journal of the South African Institution of Civil Engineering, vol. 55(2), pp 29-45 en_US
dc.identifier.issn 1021-2019
dc.identifier.uri http://www.scielo.org.za/scielo.php?pid=S1021-20192013000200005&script=sci_arttext
dc.identifier.uri http://hdl.handle.net/10204/7074
dc.description Copyright: 2013 South African Institution of Civil Engineering. Published in Journal of the South African Institution of Civil Engineering, vol. 55(2), pp 29-45 en_US
dc.description.abstract The accurate estimation of strong winds is of cardinal importance to the built environment, particularly in South Africa, where wind loading represents the dominant environmental action to be considered in the design of structures. While the Gumbel method remains the most popular applied method to estimate strong wind quantiles, several factors should influence the consideration of alternative approaches. In South Africa, the most important factors influencing the choice of method are the mixed strong wind climate and the lengths of available wind measurement records. In addition, the time-scale of the estimations (in this case one hour and 2–3 seconds) influences the suitability of some methods. The strong wind climate is dominated by synoptic scale disturbances along the coast and adjacent interior, and mesoscale systems, i.e. thunderstorms, in the biggest part of the interior. However, in a large part of South Africa more than one mechanism plays a significant role in the development of strong winds. For these regions the application of a mixed-climate approach is recommended as more appropriate than the Gumbel method. In South Africa, reliable wind records are in most cases shorter than 20 years, which makes the application of a method developed for short time series advisable. In addition it is also recommended that the shape parameter be set to zero, which translates to the Gumbel method when only annual maxima are employed. In the case of the Peak-Over-Threshold (POT) method, one of several methods developed for short time series, the application of the Exponential Distribution instead of the Generalised Pareto Distribution is recommended. However, the POT method is not suitable for estimations over longer time scales, e.g. one hour averaging, due to the high volumes of dependent strong wind values in the data sets to be utilised. The results of an updated assessment, or the present strong wind records reported in this paper, serve as input to revised strong wind maps, as presented in the accompanying paper. en_US
dc.language.iso en en_US
dc.publisher South African Institution of Civil Engineering (SAICE) en_US
dc.relation.ispartofseries Workflow;11709
dc.subject Strong wind climate en_US
dc.subject South African winds en_US
dc.subject Extreme-value distributions en_US
dc.subject Wind statistics en_US
dc.title Strong winds in South Africa, part 1: application of estimation methods en_US
dc.type Article en_US
dc.identifier.apacitation Kruger, A., Retief, J., & Goliger, A. M. (2013). Strong winds in South Africa, part 1: application of estimation methods. http://hdl.handle.net/10204/7074 en_ZA
dc.identifier.chicagocitation Kruger, A, J Retief, and Adam M Goliger "Strong winds in South Africa, part 1: application of estimation methods." (2013) http://hdl.handle.net/10204/7074 en_ZA
dc.identifier.vancouvercitation Kruger A, Retief J, Goliger AM. Strong winds in South Africa, part 1: application of estimation methods. 2013; http://hdl.handle.net/10204/7074. en_ZA
dc.identifier.ris TY - Article AU - Kruger, A AU - Retief, J AU - Goliger, Adam M AB - The accurate estimation of strong winds is of cardinal importance to the built environment, particularly in South Africa, where wind loading represents the dominant environmental action to be considered in the design of structures. While the Gumbel method remains the most popular applied method to estimate strong wind quantiles, several factors should influence the consideration of alternative approaches. In South Africa, the most important factors influencing the choice of method are the mixed strong wind climate and the lengths of available wind measurement records. In addition, the time-scale of the estimations (in this case one hour and 2–3 seconds) influences the suitability of some methods. The strong wind climate is dominated by synoptic scale disturbances along the coast and adjacent interior, and mesoscale systems, i.e. thunderstorms, in the biggest part of the interior. However, in a large part of South Africa more than one mechanism plays a significant role in the development of strong winds. For these regions the application of a mixed-climate approach is recommended as more appropriate than the Gumbel method. In South Africa, reliable wind records are in most cases shorter than 20 years, which makes the application of a method developed for short time series advisable. In addition it is also recommended that the shape parameter be set to zero, which translates to the Gumbel method when only annual maxima are employed. In the case of the Peak-Over-Threshold (POT) method, one of several methods developed for short time series, the application of the Exponential Distribution instead of the Generalised Pareto Distribution is recommended. However, the POT method is not suitable for estimations over longer time scales, e.g. one hour averaging, due to the high volumes of dependent strong wind values in the data sets to be utilised. The results of an updated assessment, or the present strong wind records reported in this paper, serve as input to revised strong wind maps, as presented in the accompanying paper. DA - 2013-08 DB - ResearchSpace DP - CSIR KW - Strong wind climate KW - South African winds KW - Extreme-value distributions KW - Wind statistics LK - https://researchspace.csir.co.za PY - 2013 SM - 1021-2019 T1 - Strong winds in South Africa, part 1: application of estimation methods TI - Strong winds in South Africa, part 1: application of estimation methods UR - http://hdl.handle.net/10204/7074 ER - en_ZA


Files in this item

This item appears in the following Collection(s)

Show simple item record