A stochastic model for daily climate

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.

Grantor dc:publisher.institution

Department of Mathematics and Applied Mathematics

Year dc:date.issued

1986

Author dc:creator

• Brandão, Anabela de Gusmão

Advisor dc:contributor.advisor

• Zucchini, Walter

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/11427/16348

OAI identifier oai:identifier

oai:open.uct.ac.za:11427/16348