Seasonality of circulation in southern Africa using the Kohonen self-organising map

dc.contributor.advisorHewitson, Bruceen_ZA
dc.contributor.authorMain, Jeremy P Len_ZA
dc.date.accessioned2015-09-14T18:04:44Z
dc.date.available2015-09-14T18:04:44Z
dc.date.issued1997en_ZA
dc.descriptionBibliography: leaves 77-84.en_ZA
dc.description.abstractA technique employing the classification capabilities of the Kohonen self-organising map (SOM) is introduced into the body of computer-based techniques available to synoptic climatology. The SOM is one of many types of artificial neural networks (ANN) and is capable of unsupervised learning or non-linear classification. Components of the SOM are introduced and an application is then illustrated using observed daily sea level pressure (SLP) from the Australian Southern Hemisphere data set. To put the technique in the context of global climate change studies, a further example using simulated SLP from the GENESIS version 1.02 General Circulation Model (GCM) is illustrated, with the emphasis on the ability of the technique to highlight differences in seasonality between data sets. The SOM is found to be a robust technique for deducing the modes of variability of map patterns within a circulation data set, allowing variability to be expressed in terms of inter and intra-annual variability. The SOM is also found to be useful for comparing circulation data sets and finds particular application in the context of global climate change studies.en_ZA
dc.identifier.apacitationMain, J. P. L. (1997). <i>Seasonality of circulation in southern Africa using the Kohonen self-organising map</i>. (Thesis). University of Cape Town ,Faculty of Science ,Department of Environmental and Geographical Science. Retrieved from http://hdl.handle.net/11427/13889en_ZA
dc.identifier.chicagocitationMain, Jeremy P L. <i>"Seasonality of circulation in southern Africa using the Kohonen self-organising map."</i> Thesis., University of Cape Town ,Faculty of Science ,Department of Environmental and Geographical Science, 1997. http://hdl.handle.net/11427/13889en_ZA
dc.identifier.citationMain, J. 1997. Seasonality of circulation in southern Africa using the Kohonen self-organising map. University of Cape Town.en_ZA
dc.identifier.ris TY - Thesis / Dissertation AU - Main, Jeremy P L AB - A technique employing the classification capabilities of the Kohonen self-organising map (SOM) is introduced into the body of computer-based techniques available to synoptic climatology. The SOM is one of many types of artificial neural networks (ANN) and is capable of unsupervised learning or non-linear classification. Components of the SOM are introduced and an application is then illustrated using observed daily sea level pressure (SLP) from the Australian Southern Hemisphere data set. To put the technique in the context of global climate change studies, a further example using simulated SLP from the GENESIS version 1.02 General Circulation Model (GCM) is illustrated, with the emphasis on the ability of the technique to highlight differences in seasonality between data sets. The SOM is found to be a robust technique for deducing the modes of variability of map patterns within a circulation data set, allowing variability to be expressed in terms of inter and intra-annual variability. The SOM is also found to be useful for comparing circulation data sets and finds particular application in the context of global climate change studies. DA - 1997 DB - OpenUCT DP - University of Cape Town LK - https://open.uct.ac.za PB - University of Cape Town PY - 1997 T1 - Seasonality of circulation in southern Africa using the Kohonen self-organising map TI - Seasonality of circulation in southern Africa using the Kohonen self-organising map UR - http://hdl.handle.net/11427/13889 ER - en_ZA
dc.identifier.urihttp://hdl.handle.net/11427/13889
dc.identifier.vancouvercitationMain JPL. Seasonality of circulation in southern Africa using the Kohonen self-organising map. [Thesis]. University of Cape Town ,Faculty of Science ,Department of Environmental and Geographical Science, 1997 [cited yyyy month dd]. Available from: http://hdl.handle.net/11427/13889en_ZA
dc.language.isoengen_ZA
dc.publisher.departmentDepartment of Environmental and Geographical Scienceen_ZA
dc.publisher.facultyFaculty of Scienceen_ZA
dc.publisher.institutionUniversity of Cape Town
dc.subject.otherEnvironmental and Geographical Scienceen_ZA
dc.titleSeasonality of circulation in southern Africa using the Kohonen self-organising mapen_ZA
dc.typeMaster Thesis
dc.type.qualificationlevelMasters
dc.type.qualificationnameMScen_ZA
uct.type.filetypeText
uct.type.filetypeImage
uct.type.publicationResearchen_ZA
uct.type.resourceThesisen_ZA
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