End-to-end Quantification of Uncertainty for Impacts Prediction (EQUIP)

影响预测不确定性的端到端量化 (EQUIP)

基本信息

批准号：
NE/H003533/1
负责人：
Gabriele Hegerl
金额：
$ 25.95万
依托单位：
University of Edinburgh
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2010
资助国家：
英国
起止时间：
2010 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=NE%2FH003533%2F1
关键词：
End end Quantification Uncertainty Impacts

项目摘要

Society is becoming increasingly aware of climate change and its consequences for us. Examples of likely impacts are changes in food production, increases in mortality rates due to heat waves, and changes in our marine environment. Despite such emerging knowledge, precise predictions of future climate are (and will remain) unattainable owing to the fundamental chaotic nature of the climate system and to imperfections in our understanding, our climate simulation models and our observations of the climate system. This situation limits our ability to take effective adaptation actions. However, effective adaptation is still possible, particularly if we assess the level of precision associated with predictions, and thus quantify the risk posed by climate change. Coupled with assessments of the limitations on our knowledge, this approach can be a powerful tool for informing decision makers. Clearly, then, the quantification of uncertainty in the prediction of climate and its impacts is a critical issue. Considerable thought has gone into this issue with regard to climate change research, although a consensus on the best methods is yet to emerge. Climate impacts research, on the other hand, has focussed primarily on a different set of problems: what are the mechanisms through which climate change is likely to affect for example, agriculture and health, and what are the non-climatic influences that also need to be accounted for? Thus the research base for climate impacts is sound, but tends to be less thorough in its quantification of uncertainty than the physical climate change research that supports it. As a result, statements regarding the impacts of climate change often take a less sophisticated approach to risk and uncertainty. The logical next stage for climate impacts research is therefore to learn from the methods used for climate change predictions. Since climate and its impacts both exist within a broader earth system, with many interrelated components, this next stage is not a simple transfer of technology. Rather, it means taking an 'end-to-end' integrated look at climate and its impacts, and assessing risk and uncertainty across whole systems. These systems include not only physical and biological mechanisms, but also the decisions taken by users of climate information. The climate impacts chosen in EQUIP have been chosen to cover this spectrum from end to end. As well as aiding impacts research, end-to-end analyses are also the logical next stage for climate change research, since it is through impacts that society experiences climate change. The project focuses primarily on the next few decades, since this is a timescale of relevance for societies adapting to climate change. It is also a timescale at which our projections of greenhouse gas emissions are relatively well constrained, thus uncertainty is smaller than for, say, the end of the century. Work on longer timescales will also be carried out in order to gain a greater understanding of uncertainty. EQUIP research will build on work to date on the mechanisms and processes that lead to climate change and its impacts, since it is this understanding that forms the basis of predictive power. This knowledge is in the form of observations and experiments (e.g. experiments on crops have demonstrated that even brief episodes of high temperatures near the flowering of the crop can seriously reduce yield) and also simulation models. It is through effective use and combination of climate science and impacts science, and the models used by each community, that we will be able to quantify uncertainty, assess risk, and thus equip society to deal with climate change.

社会越来越意识到气候变化及其对我们的影响。可能影响的例子是粮食生产的变化，由于热浪而导致的死亡率增加以及我们的海洋环境变化。尽管有如此新兴的知识，但由于气候系统的基本混乱性以及我们的理解，我们的气候模拟模型和对气候系统的观察，对未来气候的精确预测是（并且将仍然是）无法实现的。这种情况限制了我们采取有效适应措施的能力。但是，仍然可以进行有效的适应，特别是如果我们评估与预测相关的精度水平，从而量化气候变化带来的风险。再加上对我们知识的局限性的评估，这种方法可以成为告知决策者的强大工具。显然，在气候及其影响的预测中对不确定性的量化是一个关键问题。关于气候变化研究，尽管尚未出现关于最佳方法的共识，但在气候变化研究方面已经有很多思想。另一方面，气候影响研究主要集中在不同的问题上：气候变化可能影响的机制是什么，例如农业和健康，以及还需要考虑的非气候影响是什么？因此，对气候影响的研究基础是合理的，但是与支持它的物理气候变化研究相比，其不确定性量化的量化往往不太透彻。结果，关于气候变化影响的陈述通常会采取不太复杂的风险和不确定性方法。因此，气候影响研究的逻辑下阶段是从用于气候变化预测的方法中学习。由于气候及其影响都存在于更广泛的地球系统中，并且具有许多相互关联的组成部分，因此下一阶段并不是技术的简单转移。相反，这意味着对气候及其影响进行“端到端”的综合研究，并评估整个系统的风险和不确定性。这些系统不仅包括物理和生物学机制，还包括气候信息用户做出的决定。选择了设备中选择的气候影响以覆盖从头到尾的范围。除了有助于影响研究外，端到端分析也是气候变化研究的逻辑下阶段，因为社会经历了气候变化的影响。该项目主要关注接下来的几十年，因为这是适应气候变化的社会的时间表。这也是一个时间表，我们对温室气体排放的预测相对较好，因此不确定性比本世纪末的不确定性小。还将在更长的时间尺度上进行工作，以便对不确定性有更深入的了解。设备研究将基于迄今为止的工作，基于导致气候变化及其影响的机制和过程，因为这种理解构成了预测能力的基础。这些知识以观察和实验的形式形式（例如，在农作物上进行的实验表明，即使是在作物开花附近的高温发作也可以严重降低产量）和模拟模型。我们将能够量化不确定性，评估风险，从而使社会能够应对气候变化，从而有效地使用和结合了气候科学和影响科学的模型。