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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Variability and long-term trends of climate extremes over the Limpopo, South Africa

Sikhwari, Thendo 20 September 2019 (has links)
MENVSC / Department of Geography and Geo-Information Sciences / Climate change has a crucial impact on livelihoods, economy, and water resources due to the occurrence of weather and climate extreme events such as floods, droughts and heat waves. Extreme weather has been increasing worldwide, hence the need to understand their nature and trends. The aim of this study was to analyse the spatial variability and long-term trends of climate extremes over the Limpopo in South Africa from 1960 to 2014. Rainfall, temperature, and circulation fields were analysed to understand the extent, nature of climate extremes over the Limpopo. Extreme value theory (EVT) is a powerful method that was also employed in this study to provide statistical models for events rarely observed. R statistical software was used for clustering analysis which has a variety of functions for cluster analysis. Any station whose value is larger than 95th for any day of the season was considered as a widespread extreme event. The results show that the study area is highly vulnerable to extreme events due to its latitudinal location and low altitude. Anomalous cut-off lows, tropical cyclones and tropical storms are the major extreme producing systems affecting the Limpopo province whilst the Botswana High becomes dominant during heat waves and drought. Extreme weather events are common in Limpopo during summertime and often coincide with mature phases of the El Nino Southern Oscillation. In this study, after the suitable model for data was chosen, the interest was in deriving return levels of extreme maximum rainfall. The computed data for return levels predicted that the 5-year return period’s return level is approximately 223.89 mm, which suggests that rainfall of 223.89 mm or more per month should occur at that station or location on the average of once every five years. / NRF / http://hdl.handle.net/11602/1485

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