Coupled models: Expert Judgement, Emulators and Model Uncertainty

该项目将侧重于将模拟器的新技术应用于风险评估中一些密切相关的问题。模拟器本质上是对模型进行统计构建的近似值，其运行速度比原始模型快得多。在风险评估中，将复杂的计算机模型链接在一起以生成决策者感兴趣的情景信息是很常见的。在这个项目中，链模拟器的使用将与一些研究课题一起研究。首先是探索如何使用仿真器来支持专家对不确定性的判断，当专家对模型链不同阶段可能观察到的可测量量有意见时，以便我们可以获得更好的量化参数不确定性的方法。其次是探索模型的参数不确定性如何取决于使用它的建模环境（在这种情况下，它形成的模型链的一部分）。第三个也是最后一个问题认识到，通常有几个不同的模型可以被选择来模拟某种行为，因此寻求探索使用来自这些不同模型替代品的模拟器来评估模型链对这些建模选择的结构敏感性的可能性。

The project will focus on applications of the new technique of emulators to a number of closely related problems in risk assessment. An emulator is essentially a statistically built approximation for a model, which is much faster to run than the original model. It is common in risk assessment to chain complex computer models together to generate information about scenario's of interest to the decision makers. In this project the use of chained emulators will be studied with a number of research topics in mind. First is to explore how emulators can be used to support expert judgements about uncertainties, when experts have opinions about measurable quantities that might be observed at different stages of the model chain, so that we might obtain a better way of quantifying parameter uncertainties. Second is to explore how parameter uncertainty for a model depends on the modelling context in which it is used (in this case, the chain of models it forms a part of). The third and final question recognizes that there are often several different models that could have been chosen to model some kind of behaviour, and therefore seeks to explore the possibilities of using emulators from those different model alternatives to assess the structural sensitivity of a model chain to those modelling choices.