Stochastic modelling of the weather : selected aspects

Stochastic weather models facilitate the simulation of long weather sequences, statistically similar to the observed series, from summary statistics or short sequences of recorded meteorological data. Long weather records are often required for the design and management of agricultural systems, water resources, solar energy conversion systems and other environmental resources. Stochastic weather models are also useful for assessing the impact of global warming on agriculture, ecology and hydrology on a regional scale. Four inter-related topics in stochastic modelling of the weather were chosen for research: 0 the development of a daily weather data set for Australia suitable for calibrating and testing stochastic weather models, 0 the development of a new conceptual framework for the stochastic modelling of daily weather sequences at a single site, 0 the development of a stochastic model of daily cloud duration, and 0 the conversion of daily cloud duration to daily solar radiation using the Angstrom-Prescott equation. Daily cloud duration is defined as the period of daylight duration not receiving bright sunshine. The first objective is to collate a daily weather data set, representing the major tropical and temperate climatic zones in Australia, for the development and testing of stochastic weather models. The database developed, named AUSSET, comprises daily records of rainfall, minimum temperature, maximum temperature, sunshine duration, and solar radiation from eleven major weather stations operated by the Australian Bureau of Meteorology. The records were edited for errors, inconsistencies, missing values, and data homogeneity. The data were shown to be of high quality. The second objective is the development of a new conceptual framework for the stochastic modelling of daily weather sequences at a single site. The author proposed a new class of stochastic weather models based on daily cloud duration. The key advantage of this approach is that it

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