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Seasonality of circulation in southern Africa using the Kohonen self-organising map
Bibliography: leaves 77-84.
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| Other Authors: | |
| Format: | Thesis |
| Language: | English |
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Department of Environmental and Geographical Science
2015
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| _version_ | 1867613165315948544 |
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| access_status_str | Open Access |
| author | Main, Jeremy P L |
| author2 | Hewitson, Bruce |
| author_browse | Hewitson, Bruce Main, Jeremy P L |
| author_facet | Hewitson, Bruce Main, Jeremy P L |
| author_sort | Main, Jeremy P L |
| collection | Thesis |
| description | Bibliography: leaves 77-84. |
| format | Thesis |
| id | oai:open.uct.ac.za:11427/13889 |
| institution | University of Cape Town (South Africa) |
| language | eng |
| last_indexed | 2026-06-10T12:31:48.735Z |
| license_str | Not specified — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UCTD — University of Cape Town Open Access Repository |
| publishDate | 2015 |
| publishDateRange | 2015 |
| publishDateSort | 2015 |
| publisher | Department of Environmental and Geographical Science |
| publisherStr | Department of Environmental and Geographical Science |
| record_format | dspace |
| source_str | UCTD — University of Cape Town Open Access Repository |
| spelling | oai:open.uct.ac.za:11427/13889 Seasonality of circulation in southern Africa using the Kohonen self-organising map Main, Jeremy P L Hewitson, Bruce Environmental and Geographical Science Bibliography: leaves 77-84. 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. 2015-09-14T18:04:44Z 2015-09-14T18:04:44Z 1997 Master Thesis Masters MSc http://hdl.handle.net/11427/13889 eng application/pdf Department of Environmental and Geographical Science Faculty of Science University of Cape Town |
| spellingShingle | Environmental and Geographical Science Main, Jeremy P L Seasonality of circulation in southern Africa using the Kohonen self-organising map |
| thesis_degree_str | Master's |
| title | Seasonality of circulation in southern Africa using the Kohonen self-organising map |
| title_full | Seasonality of circulation in southern Africa using the Kohonen self-organising map |
| title_fullStr | Seasonality of circulation in southern Africa using the Kohonen self-organising map |
| title_full_unstemmed | Seasonality of circulation in southern Africa using the Kohonen self-organising map |
| title_short | Seasonality of circulation in southern Africa using the Kohonen self-organising map |
| title_sort | seasonality of circulation in southern africa using the kohonen self organising map |
| topic | Environmental and Geographical Science |
| url | http://hdl.handle.net/11427/13889 |
| work_keys_str_mv | AT mainjeremypl seasonalityofcirculationinsouthernafricausingthekohonenselforganisingmap |