A stochastic model for daily climate

 

Show simple item record

dc.contributor.advisor Zucchini, Walter en_ZA
dc.contributor.author Brandão, Anabela de Gusmão en_ZA
dc.date.accessioned 2016-01-12T11:19:30Z
dc.date.available 2016-01-12T11:19:30Z
dc.date.issued 1986 en_ZA
dc.identifier.citation Brandão, A. 1986. A stochastic model for daily climate. University of Cape Town. en_ZA
dc.identifier.uri http://hdl.handle.net/11427/16348
dc.description Includes bibliography. en_ZA
dc.description.abstract This thesis describes the results of a study to establish whether climate variables could be usefully modelled on a daily basis. Three stochastic models are considered for the description of daily climate sequences, which can then be used to generate artificial sequences. The climate variables under consideration are rainfall, maximum and minimum temperature, evaporation, sunshine duration, windrun and maximum and minimum humidity. A simple Markov chain-Weibull model is proposed to model rainfall. Three multivariate models (one proposed by Richardson (1981), two new) are suggested for modelling the remaining climate variables. The model parameters are allowed to vary seasonally, while the error term is assumed to follow an autoregressive process. The models were validated and their general performance·was found to be satisfactory. Some weaknesses were identified and are discussed. The. main conclusion of this study is that daily climate sequences can indeed be usefully described by means of stochastic models. en_ZA
dc.language.iso eng en_ZA
dc.subject.other Mathematical Statistics en_ZA
dc.title A stochastic model for daily climate en_ZA
dc.type Master 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 Mathematics and Applied Mathematics en_ZA
dc.type.qualificationlevel Masters
dc.type.qualificationname MSc en_ZA
uct.type.filetype Text
uct.type.filetype Image
dc.identifier.apacitation Brandão, A. d. G. (1986). <i>A stochastic model for daily climate</i>. (Thesis). University of Cape Town ,Faculty of Science ,Department of Mathematics and Applied Mathematics. Retrieved from http://hdl.handle.net/11427/16348 en_ZA
dc.identifier.chicagocitation Brandão, Anabela de Gusmão. <i>"A stochastic model for daily climate."</i> Thesis., University of Cape Town ,Faculty of Science ,Department of Mathematics and Applied Mathematics, 1986. http://hdl.handle.net/11427/16348 en_ZA
dc.identifier.vancouvercitation Brandão AdG. A stochastic model for daily climate. [Thesis]. University of Cape Town ,Faculty of Science ,Department of Mathematics and Applied Mathematics, 1986 [cited yyyy month dd]. Available from: http://hdl.handle.net/11427/16348 en_ZA
dc.identifier.ris TY - Thesis / Dissertation AU - Brandão, Anabela de Gusmão AB - This thesis describes the results of a study to establish whether climate variables could be usefully modelled on a daily basis. Three stochastic models are considered for the description of daily climate sequences, which can then be used to generate artificial sequences. The climate variables under consideration are rainfall, maximum and minimum temperature, evaporation, sunshine duration, windrun and maximum and minimum humidity. A simple Markov chain-Weibull model is proposed to model rainfall. Three multivariate models (one proposed by Richardson (1981), two new) are suggested for modelling the remaining climate variables. The model parameters are allowed to vary seasonally, while the error term is assumed to follow an autoregressive process. The models were validated and their general performance·was found to be satisfactory. Some weaknesses were identified and are discussed. The. main conclusion of this study is that daily climate sequences can indeed be usefully described by means of stochastic models. DA - 1986 DB - OpenUCT DP - University of Cape Town LK - https://open.uct.ac.za PB - University of Cape Town PY - 1986 T1 - A stochastic model for daily climate TI - A stochastic model for daily climate UR - http://hdl.handle.net/11427/16348 ER - en_ZA


Files in this item

This item appears in the following Collection(s)

Show simple item record