{"id":{"repo_id":"cape-town","oai_identifier":"oai:open.uct.ac.za:11427/4970"},"canonical_url":"https://search.dev.ndltd.org/etd/cape-town/oai:open.uct.ac.za:11427/4970","repository":{"repo_id":"cape-town","name":"University of Cape Town","base_url":"https://open.uct.ac.za/oai/request"},"display":{"title":"Verification of gridded seasonal wind speed forecasts over South Africa.","abstract":"The Climate System Analysis Group (CSAG) at the University of Cape Town produces provisional global and Southern African seasonal wind forecasts generated using the United Kingdom Meteorological Office Atmospheric General Circulation Model (AGCM) HadAM3P (non-standard version of HadAM3). This study examines the quality of the seasonal wind speed forecasts through a forecast verification process for continuous variables using reanalysis products of the National Centers for Environmental Prediction and the Department of Energy (NCEP-DOE) as observations data. The verification analyses are performed using summary measures Mean Error (ME), Mean Absolute Error (MAE), Mean Squared Error (MSE), correlation coefficients, Linear Error in Probability Space (LEPS) and exploratory methods, scatter and conditional quantile plots. These methods are used to determine the aspects of forecast quality namely, bias, accuracy, reliability, resolution, and skill over a 20 year period (1991 to 2010). The results of the study have determined that the use of both accuracy and skill measures for the verification analyses provide more information about the quality of the forecasts, as opposed only one of these. In all provinces, the highest quality seasonal wind speed forecasts are made at 500 hPa and the lowest quality forecasts at 1000 hPa. Furthermore regions, pressure levels, and seasons with the highest forecast quality share the common characteristic that their wind speeds are relatively high. The forecasts add value to the climatology and thus are a useful tool for wind assessment at a seasonal scale. It is suggested that adding spatial resolution to the forecasts through downscaling may prepare them for use in applications such as wind power output forecasting.","abstract_html":"The Climate System Analysis Group (CSAG) at the University of Cape Town produces provisional global and Southern African seasonal wind forecasts generated using the United Kingdom Meteorological Office Atmospheric General Circulation Model (AGCM) HadAM3P (non-standard version of HadAM3). This study examines the quality of the seasonal wind speed forecasts through a forecast verification process for continuous variables using reanalysis products of the National Centers for Environmental Prediction and the Department of Energy (NCEP-DOE) as observations data. The verification analyses are performed using summary measures Mean Error (ME), Mean Absolute Error (MAE), Mean Squared Error (MSE), correlation coefficients, Linear Error in Probability Space (LEPS) and exploratory methods, scatter and conditional quantile plots. These methods are used to determine the aspects of forecast quality namely, bias, accuracy, reliability, resolution, and skill over a 20 year period (1991 to 2010). The results of the study have determined that the use of both accuracy and skill measures for the verification analyses provide more information about the quality of the forecasts, as opposed only one of these. In all provinces, the highest quality seasonal wind speed forecasts are made at 500 hPa and the lowest quality forecasts at 1000 hPa. Furthermore regions, pressure levels, and seasons with the highest forecast quality share the common characteristic that their wind speeds are relatively high. The forecasts add value to the climatology and thus are a useful tool for wind assessment at a seasonal scale. It is suggested that adding spatial resolution to the forecasts through downscaling may prepare them for use in applications such as wind power output forecasting.","abstract_has_math":false,"creators":["Nchaba, Teboho"],"institution":"Energy Research Centre","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":["Marquard, Andrew","Lennard, Chris"],"committee_chairs":[],"committee_members":[],"year":2013,"date_issued":"2013","date_published":"2013","updated_at":"2026-07-22T22:22:37Z","subjects":[],"languages":["eng"],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/11427/4970","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Marquard, Andrew","Lennard, Chris"]},{"key":"dc:creator","label":"Author","values":["Nchaba, Teboho"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2014-07-31T10:22:20Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2014-07-31T10:22:20Z"]},{"key":"dc:date.issued","label":"Date","values":["2013"]},{"key":"dc:publisher.department","label":"Dc Publisher Department","values":["Energy Research Centre"]},{"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/11427/4970"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Includes abstract.","Includes bibliographical references."]},{"key":"dc:description.abstract","label":"Abstract","values":["The Climate System Analysis Group (CSAG) at the University of Cape Town produces provisional global and Southern African seasonal wind forecasts generated using the United Kingdom Meteorological Office Atmospheric General Circulation Model (AGCM) HadAM3P (non-standard version of HadAM3). This study examines the quality of the seasonal wind speed forecasts through a forecast verification process for continuous variables using reanalysis products of the National Centers for Environmental Prediction and the Department of Energy (NCEP-DOE) as observations data. The verification analyses are performed using summary measures Mean Error (ME), Mean Absolute Error (MAE), Mean Squared Error (MSE), correlation coefficients, Linear Error in Probability Space (LEPS) and exploratory methods, scatter and conditional quantile plots. These methods are used to determine the aspects of forecast quality namely, bias, accuracy, reliability, resolution, and skill over a 20 year period (1991 to 2010). The results of the study have determined that the use of both accuracy and skill measures for the verification analyses provide more information about the quality of the forecasts, as opposed only one of these. In all provinces, the highest quality seasonal wind speed forecasts are made at 500 hPa and the lowest quality forecasts at 1000 hPa. Furthermore regions, pressure levels, and seasons with the highest forecast quality share the common characteristic that their wind speeds are relatively high. The forecasts add value to the climatology and thus are a useful tool for wind assessment at a seasonal scale. It is suggested that adding spatial resolution to the forecasts through downscaling may prepare them for use in applications such as wind power output forecasting."]},{"key":"dc:title","label":"Title","values":["Verification of gridded seasonal wind speed forecasts over South Africa."]}]}],"canonical_facts":{"dc:contributor.advisor":["Marquard, Andrew","Lennard, Chris"],"dc:creator":["Nchaba, Teboho"],"dc:date.accessioned":["2014-07-31T10:22:20Z"],"dc:date.available":["2014-07-31T10:22:20Z"],"dc:date.issued":["2013"],"dc:description":["Includes abstract.","Includes bibliographical references."],"dc:description.abstract":["The Climate System Analysis Group (CSAG) at the University of Cape Town produces provisional global and Southern African seasonal wind forecasts generated using the United Kingdom Meteorological Office Atmospheric General Circulation Model (AGCM) HadAM3P (non-standard version of HadAM3). This study examines the quality of the seasonal wind speed forecasts through a forecast verification process for continuous variables using reanalysis products of the National Centers for Environmental Prediction and the Department of Energy (NCEP-DOE) as observations data. The verification analyses are performed using summary measures Mean Error (ME), Mean Absolute Error (MAE), Mean Squared Error (MSE), correlation coefficients, Linear Error in Probability Space (LEPS) and exploratory methods, scatter and conditional quantile plots. These methods are used to determine the aspects of forecast quality namely, bias, accuracy, reliability, resolution, and skill over a 20 year period (1991 to 2010). The results of the study have determined that the use of both accuracy and skill measures for the verification analyses provide more information about the quality of the forecasts, as opposed only one of these. In all provinces, the highest quality seasonal wind speed forecasts are made at 500 hPa and the lowest quality forecasts at 1000 hPa. Furthermore regions, pressure levels, and seasons with the highest forecast quality share the common characteristic that their wind speeds are relatively high. The forecasts add value to the climatology and thus are a useful tool for wind assessment at a seasonal scale. It is suggested that adding spatial resolution to the forecasts through downscaling may prepare them for use in applications such as wind power output forecasting."],"dc:identifier.uri":["http://hdl.handle.net/11427/4970"],"dc:language.iso":["eng"],"dc:publisher.department":["Energy Research Centre"],"dc:publisher.institution":["University of Cape Town"],"dc:title":["Verification of gridded seasonal wind speed forecasts over South Africa."],"dc:type":["Master Thesis"],"dc:type.qualificationlevel":["Masters"],"dc:type.qualificationname":["MSc"]},"updated_at":"2026-07-22T22:22:37Z"}