{"id":{"repo_id":"cape-town","oai_identifier":"oai:open.uct.ac.za:11427/6500"},"canonical_url":"https://search.dev.ndltd.org/etd/cape-town/oai:open.uct.ac.za:11427/6500","repository":{"repo_id":"cape-town","name":"University of Cape Town","base_url":"https://open.uct.ac.za/oai/request"},"display":{"title":"Wind-stress variability over the Benguela upwelling system","abstract":"Regional wind-stress variability over the Benguela Upwelling System is described using 16 months (01 August 1999 29 November 2000) of satellite derived QuikSCA T wind data. The QuikSCA T data are compared to the climatologies presented by Kamstra (1985) and Bakun and Nelson (1991), as well as the long-term climatology (1968-1996) of the surface vector wind speed field off the coast of southern Africa, as derived from the 2.5° resolution NCEPINCAR reanalysis dataset. Broad scale similaritie\"s are found between the QuikSCA T and the long-term NCEPINCAR climatology (1968-1996) data sets. This allows one to have confidence in using this scatterometer data to investigate details of spatial and temporal variability over the Benguela System. During summer, wind-stress maxima are found at approximately 17, 29 and 34°S. These maxima strengthen in late summer. The seasonal northward migration of the South Atlantic Anticyclone becomes apparent in late autumn, when the strongest wind-stress occurs north of 28°S. A significant wind-stress minimum is observed to develop slightly north of Cape Columbine (33°S) during autumn. To the north (10-23.5°S) the Benguela is characterised by relatively strong south-easterly wind-stress during winter. To the south (24-35°S) the Benguela is characterised by relatively weak westerly to south-westerly wind-stress during winter. A southward migration of southeasterly wind-stress is observed during early spring. By November the entire Benguela Upwelling System is once again characterised by southerly to south-easterly wind stress. Wind-stress variability is investigated using both a type of artificial neural network, known as the Kohonen Self Organising Map (SOM), as well as a wavelet analysis. Two independent SOM studies are conducted. The first study produced a 6x4 SOM output array, which is used to examine seasonal variability as well as the temporal evolution of two synoptic-scale wind events. For the second study both a SOM and a wavelet analysis are applied to an extracted data set to find that the system can be divided into six discrete wind regimes, 10-15°S; 15.5-18.5°S; 19-23.5°S; 24-28.5°S; 29-32.5°S; and 33-35°S. The wavelet power spectra for these wind cells span a range of frequencies from 4 to 64 days, with each region appearing to contain distinct periodicities. To the north, 10-23.5°S, the majority of the power occurs during winter, with a 6-16 day periodicity. Further south, 24-35°S, the majority of the power occurs in the summer. Here a bi-modal distribution occurs, with peaks of 6-16 and 35-40 days. Lastly a case study sequence of the spatial distribution of wind-stress, windstress curl and SST, at a location off the west coast of southern Africa (25-300S and 12-17°E), is discussed in relation to an intense, upwelling favourable, wind event that occurred from 11-20 February 2000.","abstract_html":"Regional wind-stress variability over the Benguela Upwelling System is described using 16 months (01 August 1999 29 November 2000) of satellite derived QuikSCA T wind data. The QuikSCA T data are compared to the climatologies presented by Kamstra (1985) and Bakun and Nelson (1991), as well as the long-term climatology (1968-1996) of the surface vector wind speed field off the coast of southern Africa, as derived from the 2.5° resolution NCEPINCAR reanalysis dataset. Broad scale similaritie"s are found between the QuikSCA T and the long-term NCEPINCAR climatology (1968-1996) data sets. This allows one to have confidence in using this scatterometer data to investigate details of spatial and temporal variability over the Benguela System. During summer, wind-stress maxima are found at approximately 17, 29 and 34°S. These maxima strengthen in late summer. The seasonal northward migration of the South Atlantic Anticyclone becomes apparent in late autumn, when the strongest wind-stress occurs north of 28°S. A significant wind-stress minimum is observed to develop slightly north of Cape Columbine (33°S) during autumn. To the north (10-23.5°S) the Benguela is characterised by relatively strong south-easterly wind-stress during winter. To the south (24-35°S) the Benguela is characterised by relatively weak westerly to south-westerly wind-stress during winter. A southward migration of southeasterly wind-stress is observed during early spring. By November the entire Benguela Upwelling System is once again characterised by southerly to south-easterly wind stress. Wind-stress variability is investigated using both a type of artificial neural network, known as the Kohonen Self Organising Map (SOM), as well as a wavelet analysis. Two independent SOM studies are conducted. The first study produced a 6x4 SOM output array, which is used to examine seasonal variability as well as the temporal evolution of two synoptic-scale wind events. For the second study both a SOM and a wavelet analysis are applied to an extracted data set to find that the system can be divided into six discrete wind regimes, 10-15°S; 15.5-18.5°S; 19-23.5°S; 24-28.5°S; 29-32.5°S; and 33-35°S. The wavelet power spectra for these wind cells span a range of frequencies from 4 to 64 days, with each region appearing to contain distinct periodicities. To the north, 10-23.5°S, the majority of the power occurs during winter, with a 6-16 day periodicity. Further south, 24-35°S, the majority of the power occurs in the summer. Here a bi-modal distribution occurs, with peaks of 6-16 and 35-40 days. Lastly a case study sequence of the spatial distribution of wind-stress, windstress curl and SST, at a location off the west coast of southern Africa (25-300S and 12-17°E), is discussed in relation to an intense, upwelling favourable, wind event that occurred from 11-20 February 2000.","abstract_has_math":false,"creators":["Risien, Craig Miller"],"institution":"Department of Oceanography","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":["Reason, Chris","Shillington, Frank","Richardson, Anthony"],"committee_chairs":[],"committee_members":[],"year":2002,"date_issued":"2002","date_published":"2002","updated_at":"2026-07-22T22:23:39Z","subjects":[],"languages":["eng"],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/11427/6500","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Reason, Chris","Shillington, Frank","Richardson, Anthony"]},{"key":"dc:creator","label":"Author","values":["Risien, Craig Miller"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2014-08-13T19:52:05Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2014-08-13T19:52:05Z"]},{"key":"dc:date.issued","label":"Date","values":["2002"]},{"key":"dc:publisher.department","label":"Dc Publisher Department","values":["Department of Oceanography"]},{"key":"dc:publisher.institution","label":"Dc Publisher Institution","values":["University of Cape Town"]},{"key":"dc:type","label":"Dc Type","values":["Master Thesis"]},{"key":"dc:type.qualificationlevel","label":"Dc Type Qualificationlevel","values":["Masters"]},{"key":"dc:type.qualificationname","label":"Dc Type Qualificationname","values":["MSc"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["eng"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/11427/6500"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Bibliography: leaves 119-133."]},{"key":"dc:description.abstract","label":"Abstract","values":["Regional wind-stress variability over the Benguela Upwelling System is described using 16 months (01 August 1999 29 November 2000) of satellite derived QuikSCA T wind data. The QuikSCA T data are compared to the climatologies presented by Kamstra (1985) and Bakun and Nelson (1991), as well as the long-term climatology (1968-1996) of the surface vector wind speed field off the coast of southern Africa, as derived from the 2.5° resolution NCEPINCAR reanalysis dataset. Broad scale similaritie\"s are found between the QuikSCA T and the long-term NCEPINCAR climatology (1968-1996) data sets. This allows one to have confidence in using this scatterometer data to investigate details of spatial and temporal variability over the Benguela System. During summer, wind-stress maxima are found at approximately 17, 29 and 34°S. These maxima strengthen in late summer. The seasonal northward migration of the South Atlantic Anticyclone becomes apparent in late autumn, when the strongest wind-stress occurs north of 28°S. A significant wind-stress minimum is observed to develop slightly north of Cape Columbine (33°S) during autumn. To the north (10-23.5°S) the Benguela is characterised by relatively strong south-easterly wind-stress during winter. To the south (24-35°S) the Benguela is characterised by relatively weak westerly to south-westerly wind-stress during winter. A southward migration of southeasterly wind-stress is observed during early spring. By November the entire Benguela Upwelling System is once again characterised by southerly to south-easterly wind stress. Wind-stress variability is investigated using both a type of artificial neural network, known as the Kohonen Self Organising Map (SOM), as well as a wavelet analysis. Two independent SOM studies are conducted. The first study produced a 6x4 SOM output array, which is used to examine seasonal variability as well as the temporal evolution of two synoptic-scale wind events. For the second study both a SOM and a wavelet analysis are applied to an extracted data set to find that the system can be divided into six discrete wind regimes, 10-15°S; 15.5-18.5°S; 19-23.5°S; 24-28.5°S; 29-32.5°S; and 33-35°S. The wavelet power spectra for these wind cells span a range of frequencies from 4 to 64 days, with each region appearing to contain distinct periodicities. To the north, 10-23.5°S, the majority of the power occurs during winter, with a 6-16 day periodicity. Further south, 24-35°S, the majority of the power occurs in the summer. Here a bi-modal distribution occurs, with peaks of 6-16 and 35-40 days. Lastly a case study sequence of the spatial distribution of wind-stress, windstress curl and SST, at a location off the west coast of southern Africa (25-300S and 12-17°E), is discussed in relation to an intense, upwelling favourable, wind event that occurred from 11-20 February 2000."]},{"key":"dc:title","label":"Title","values":["Wind-stress variability over the Benguela upwelling system"]}]}],"canonical_facts":{"dc:contributor.advisor":["Reason, Chris","Shillington, Frank","Richardson, Anthony"],"dc:creator":["Risien, Craig Miller"],"dc:date.accessioned":["2014-08-13T19:52:05Z"],"dc:date.available":["2014-08-13T19:52:05Z"],"dc:date.issued":["2002"],"dc:description":["Bibliography: leaves 119-133."],"dc:description.abstract":["Regional wind-stress variability over the Benguela Upwelling System is described using 16 months (01 August 1999 29 November 2000) of satellite derived QuikSCA T wind data. The QuikSCA T data are compared to the climatologies presented by Kamstra (1985) and Bakun and Nelson (1991), as well as the long-term climatology (1968-1996) of the surface vector wind speed field off the coast of southern Africa, as derived from the 2.5° resolution NCEPINCAR reanalysis dataset. Broad scale similaritie\"s are found between the QuikSCA T and the long-term NCEPINCAR climatology (1968-1996) data sets. This allows one to have confidence in using this scatterometer data to investigate details of spatial and temporal variability over the Benguela System. During summer, wind-stress maxima are found at approximately 17, 29 and 34°S. These maxima strengthen in late summer. The seasonal northward migration of the South Atlantic Anticyclone becomes apparent in late autumn, when the strongest wind-stress occurs north of 28°S. A significant wind-stress minimum is observed to develop slightly north of Cape Columbine (33°S) during autumn. To the north (10-23.5°S) the Benguela is characterised by relatively strong south-easterly wind-stress during winter. To the south (24-35°S) the Benguela is characterised by relatively weak westerly to south-westerly wind-stress during winter. A southward migration of southeasterly wind-stress is observed during early spring. By November the entire Benguela Upwelling System is once again characterised by southerly to south-easterly wind stress. Wind-stress variability is investigated using both a type of artificial neural network, known as the Kohonen Self Organising Map (SOM), as well as a wavelet analysis. Two independent SOM studies are conducted. The first study produced a 6x4 SOM output array, which is used to examine seasonal variability as well as the temporal evolution of two synoptic-scale wind events. For the second study both a SOM and a wavelet analysis are applied to an extracted data set to find that the system can be divided into six discrete wind regimes, 10-15°S; 15.5-18.5°S; 19-23.5°S; 24-28.5°S; 29-32.5°S; and 33-35°S. The wavelet power spectra for these wind cells span a range of frequencies from 4 to 64 days, with each region appearing to contain distinct periodicities. To the north, 10-23.5°S, the majority of the power occurs during winter, with a 6-16 day periodicity. Further south, 24-35°S, the majority of the power occurs in the summer. Here a bi-modal distribution occurs, with peaks of 6-16 and 35-40 days. Lastly a case study sequence of the spatial distribution of wind-stress, windstress curl and SST, at a location off the west coast of southern Africa (25-300S and 12-17°E), is discussed in relation to an intense, upwelling favourable, wind event that occurred from 11-20 February 2000."],"dc:identifier.uri":["http://hdl.handle.net/11427/6500"],"dc:language.iso":["eng"],"dc:publisher.department":["Department of Oceanography"],"dc:publisher.institution":["University of Cape Town"],"dc:title":["Wind-stress variability over the Benguela upwelling system"],"dc:type":["Master Thesis"],"dc:type.qualificationlevel":["Masters"],"dc:type.qualificationname":["MSc"]},"updated_at":"2026-07-22T22:23:39Z"}