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Uncertainty & environmental process modelling

Uncertainty & environmental process modelling
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批准号:
5241-2011
负责人:
Zidek, James
金额:
$1.17万
依托单位国家:
加拿大
项目类别:
Discovery Grants Program - Individual
财政年份:
2015
资助国家:
加拿大
项目状态:
已结题
起止时间:
2015-01-01 至 2016-12-31

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中文摘要
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英文摘要
Summary Much of this proposal concerns environmental processes such as weather that evolve over large spatial domains such as an ocean. Two very different modelling cultures have developed, one based on deterministic models that attempt to replicate reality and the other, based on stochastic models that try to summarize it. This proposal explores ways of combining those approaches, to overcome their individual deficiencies where forecasts are needed. In fact, the research proposed would apply when a number of different deterministic models and measurement methods need to be integrated, as in weather forecasting. Part of the proposal concerns better statistical models for environmental processes, ones whose parameters can change gradually over time and space. Approaches are presented for handling the very large domains and datasets involved. (One application we discuss involves a statistical model with more than 3mi parameters.) Monitoring environmental processes such as air pollution to protect human health and welfare entails siting a newtwork of monitors. These may then be purpose built to detect non compliance regulatory standards. We will consider both how to adjust the measurements to remove bias and also how to site them for other purposes such as the getting accurate estimates of the processes impact on health. Climate change has put emphasis on developing tools to better manage risk in Canadian agriculture. How should insurance and futures contracts be priced. We will continue work in this area and produce models covering space and time to forecast the duration of a drought and the first night frost at the level of a local farm. Further work will be done on forecasting crop yields as a function of soil moisture. Finally the proposal addresses theoretical issues. In particular, I will explore further how information impacts on uncertainty. Does more of the first always lead to less of the second? The answer is no in general, but under what circumstances does an increase in uncertainty occur. Such issues have not been much explored.
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Spatio-temporal modelling, network design, health effects, and dimensional analysis
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Design, measurement and modelling in spatio-temporal analysis
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