Understanding the variability and predictability of seasonal climates over West and Southern Africa using climate models

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dc.contributor.advisorAbiodun, Babatunde Josephen_ZA
dc.contributor.advisorStone, Dáithí Aen_ZA
dc.contributor.authorLawal, Kamoru Abiodunen_ZA
dc.date.accessioned2016-01-26T11:01:13Z
dc.date.available2016-01-26T11:01:13Z
dc.date.issued2015en_ZA
dc.descriptionIncludes bibliographical referencesen_ZA
dc.description.abstractA good understanding of seasonal climate and the limit to which it can be predicted is crucial in addressing various socio-economic challenges in Africa. However, how to improve the capability of the dynamical models of the climate system in reproducing the regional seasonal climate variability and in replicating the role of various atmospheric circulation anomalies on the regional variability remains a major challenge. Thus far, understanding of seasonal climate over these regions, as well as the ability of climate models to predict them, has focused on the agreement of simulations of dynamical models of the climate system, rather than considering outliers as potentially vital contributors to understanding and predictability. This thesis uses discrepancy in a large ensemble of climate simulations as a tool to investigate variability in dominant seasonal rainfall and temperature patterns (i.e. classes) over West and Southern Africa, to examine the capability of climate models in reproducing the variability, and to study the predictability of the seasonal climates over South Africa. The dominant classes of variability (of rainfall and maximum temperature fields) in both regions are examined based on the Self-Organizing Map (SOM) classifications. The sequences in which each class occurs cannot be linked simply to a single common index of global scale atmospheric circulation anomalies, implying that the chaotic regional atmospheric circulations that modulate the global scale modes of variability are indispensable. The climate model examined adequately reproduces the dominant classes of seasonal climate over West and Southern Africa.en_ZA
dc.identifier.apacitationLawal, K. A. (2015). <i>Understanding the variability and predictability of seasonal climates over West and Southern Africa using climate models</i>. (Thesis). University of Cape Town ,Faculty of Science ,Department of Environmental and Geographical Science. Retrieved from http://hdl.handle.net/11427/16556en_ZA
dc.identifier.chicagocitationLawal, Kamoru Abiodun. <i>"Understanding the variability and predictability of seasonal climates over West and Southern Africa using climate models."</i> Thesis., University of Cape Town ,Faculty of Science ,Department of Environmental and Geographical Science, 2015. http://hdl.handle.net/11427/16556en_ZA
dc.identifier.citationLawal, K. 2015. Understanding the variability and predictability of seasonal climates over West and Southern Africa using climate models. University of Cape Town.en_ZA
dc.identifier.ris TY - Thesis / Dissertation AU - Lawal, Kamoru Abiodun AB - A good understanding of seasonal climate and the limit to which it can be predicted is crucial in addressing various socio-economic challenges in Africa. However, how to improve the capability of the dynamical models of the climate system in reproducing the regional seasonal climate variability and in replicating the role of various atmospheric circulation anomalies on the regional variability remains a major challenge. Thus far, understanding of seasonal climate over these regions, as well as the ability of climate models to predict them, has focused on the agreement of simulations of dynamical models of the climate system, rather than considering outliers as potentially vital contributors to understanding and predictability. This thesis uses discrepancy in a large ensemble of climate simulations as a tool to investigate variability in dominant seasonal rainfall and temperature patterns (i.e. classes) over West and Southern Africa, to examine the capability of climate models in reproducing the variability, and to study the predictability of the seasonal climates over South Africa. The dominant classes of variability (of rainfall and maximum temperature fields) in both regions are examined based on the Self-Organizing Map (SOM) classifications. The sequences in which each class occurs cannot be linked simply to a single common index of global scale atmospheric circulation anomalies, implying that the chaotic regional atmospheric circulations that modulate the global scale modes of variability are indispensable. The climate model examined adequately reproduces the dominant classes of seasonal climate over West and Southern Africa. DA - 2015 DB - OpenUCT DP - University of Cape Town LK - https://open.uct.ac.za PB - University of Cape Town PY - 2015 T1 - Understanding the variability and predictability of seasonal climates over West and Southern Africa using climate models TI - Understanding the variability and predictability of seasonal climates over West and Southern Africa using climate models UR - http://hdl.handle.net/11427/16556 ER - en_ZA
dc.identifier.urihttp://hdl.handle.net/11427/16556
dc.identifier.vancouvercitationLawal KA. Understanding the variability and predictability of seasonal climates over West and Southern Africa using climate models. [Thesis]. University of Cape Town ,Faculty of Science ,Department of Environmental and Geographical Science, 2015 [cited yyyy month dd]. Available from: http://hdl.handle.net/11427/16556en_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 Studiesen_ZA
dc.subject.otherClimatologyen_ZA
dc.titleUnderstanding the variability and predictability of seasonal climates over West and Southern Africa using climate modelsen_ZA
dc.typeDoctoral Thesis
dc.type.qualificationlevelDoctoral
dc.type.qualificationnamePhDen_ZA
uct.type.filetypeText
uct.type.filetypeImage
uct.type.publicationResearchen_ZA
uct.type.resourceThesisen_ZA
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