Verification of gridded seasonal wind speed forecasts over South Africa.

Simple item page
dc.contributor.advisorMarquard, Andrewen_ZA
dc.contributor.advisorLennard, Chrisen_ZA
dc.contributor.authorNchaba, Tebohoen_ZA
dc.date.accessioned2014-07-31T10:22:20Z
dc.date.available2014-07-31T10:22:20Z
dc.date.issued2013en_ZA
dc.descriptionIncludes abstract.
dc.descriptionIncludes bibliographical references.
dc.description.abstractThe 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.en_ZA
dc.identifier.apacitationNchaba, T. (2013). <i>Verification of gridded seasonal wind speed forecasts over South Africa</i>. (Thesis). University of Cape Town ,Faculty of Engineering & the Built Environment ,Energy Research Centre. Retrieved from http://hdl.handle.net/11427/4970en_ZA
dc.identifier.chicagocitationNchaba, Teboho. <i>"Verification of gridded seasonal wind speed forecasts over South Africa."</i> Thesis., University of Cape Town ,Faculty of Engineering & the Built Environment ,Energy Research Centre, 2013. http://hdl.handle.net/11427/4970en_ZA
dc.identifier.citationNchaba, T. 2013. Verification of gridded seasonal wind speed forecasts over South Africa. University of Cape Town.en_ZA
dc.identifier.ris TY - Thesis / Dissertation AU - Nchaba, Teboho AB - 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. DA - 2013 DB - OpenUCT DP - University of Cape Town LK - https://open.uct.ac.za PB - University of Cape Town PY - 2013 T1 - Verification of gridded seasonal wind speed forecasts over South Africa TI - Verification of gridded seasonal wind speed forecasts over South Africa UR - http://hdl.handle.net/11427/4970 ER - en_ZA
dc.identifier.urihttp://hdl.handle.net/11427/4970
dc.identifier.vancouvercitationNchaba T. Verification of gridded seasonal wind speed forecasts over South Africa. [Thesis]. University of Cape Town ,Faculty of Engineering & the Built Environment ,Energy Research Centre, 2013 [cited yyyy month dd]. Available from: http://hdl.handle.net/11427/4970en_ZA
dc.language.isoengen_ZA
dc.publisher.departmentEnergy Research Centreen_ZA
dc.publisher.facultyFaculty of Engineering and the Built Environment
dc.publisher.institutionUniversity of Cape Town
dc.subject.otherEnergy and Development Studiesen_ZA
dc.titleVerification of gridded seasonal wind speed forecasts over South Africa.en_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
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
thesis_ebe_2013_nchaba_teboho.pdf
Size:
1.18 MB
Format:
Adobe Portable Document Format
Description:
Download
Collections
Masters