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

 

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dc.contributor.advisor Abiodun, Babatunde Joseph en_ZA
dc.contributor.advisor Stone, Dáithí A en_ZA
dc.contributor.author Lawal, Kamoru Abiodun en_ZA
dc.date.accessioned 2016-01-26T11:01:13Z
dc.date.available 2016-01-26T11:01:13Z
dc.date.issued 2015 en_ZA
dc.identifier.citation Lawal, 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.uri http://hdl.handle.net/11427/16556
dc.description Includes bibliographical references en_ZA
dc.description.abstract 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. en_ZA
dc.language.iso eng en_ZA
dc.subject.other Environmental Studies en_ZA
dc.subject.other Climatology en_ZA
dc.title Understanding the variability and predictability of seasonal climates over West and Southern Africa using climate models en_ZA
dc.type Doctoral Thesis
uct.type.publication Research en_ZA
uct.type.resource Thesis en_ZA
dc.publisher.institution University of Cape Town
dc.publisher.faculty Faculty of Science en_ZA
dc.publisher.department Department of Environmental and Geographical Science en_ZA
dc.type.qualificationlevel Doctoral
dc.type.qualificationname PhD en_ZA
uct.type.filetype Text
uct.type.filetype Image
dc.identifier.apacitation Lawal, 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/11427/16556 en_ZA
dc.identifier.chicagocitation Lawal, 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/11427/16556 en_ZA
dc.identifier.vancouvercitation Lawal 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/11427/16556 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


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