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A stochastic model for daily climate
Includes bibliography.
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| Main Author: | |
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| Other Authors: | |
| Format: | Thesis |
| Language: | English |
| Published: |
Department of Mathematics and Applied Mathematics
2016
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| _version_ | 1867613307489222656 |
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| access_status_str | Open Access |
| author | Brandão, Anabela de Gusmão |
| author2 | Zucchini, Walter |
| author_browse | Brandão, Anabela de Gusmão Zucchini, Walter |
| author_facet | Zucchini, Walter Brandão, Anabela de Gusmão |
| author_sort | Brandão, Anabela de Gusmão |
| collection | Thesis |
| description | Includes bibliography. |
| format | Thesis |
| id | oai:open.uct.ac.za:11427/16348 |
| institution | University of Cape Town (South Africa) |
| language | eng |
| last_indexed | 2026-06-10T12:34:03.682Z |
| license_str | Not specified — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UCTD — University of Cape Town Open Access Repository |
| publishDate | 2016 |
| publishDateRange | 2016 |
| publishDateSort | 2016 |
| publisher | Department of Mathematics and Applied Mathematics |
| publisherStr | Department of Mathematics and Applied Mathematics |
| record_format | dspace |
| source_str | UCTD — University of Cape Town Open Access Repository |
| spelling | oai:open.uct.ac.za:11427/16348 A stochastic model for daily climate Brandão, Anabela de Gusmão Zucchini, Walter Mathematical Statistics Includes bibliography. 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. 2016-01-12T11:19:30Z 2016-01-12T11:19:30Z 1986 Master Thesis Masters MSc http://hdl.handle.net/11427/16348 eng application/pdf Department of Mathematics and Applied Mathematics Faculty of Science University of Cape Town |
| spellingShingle | Mathematical Statistics Brandão, Anabela de Gusmão A stochastic model for daily climate |
| thesis_degree_str | Master's |
| title | A stochastic model for daily climate |
| title_full | A stochastic model for daily climate |
| title_fullStr | A stochastic model for daily climate |
| title_full_unstemmed | A stochastic model for daily climate |
| title_short | A stochastic model for daily climate |
| title_sort | stochastic model for daily climate |
| topic | Mathematical Statistics |
| url | http://hdl.handle.net/11427/16348 |
| work_keys_str_mv | AT brandaoanabeladegusmao astochasticmodelfordailyclimate AT brandaoanabeladegusmao stochasticmodelfordailyclimate |