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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/H003525/1
负责人：
Andrew Challinor
金额：
$ 62.29万
依托单位：
University of Leeds
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%2FH003525%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。可能产生影响的例子包括粮食生产的变化、热浪导致的死亡率上升以及我们海洋环境的变化。尽管有这样的新兴知识，但由于气候系统的根本混乱性质，以及我们对气候系统的理解、气候模拟模型和观测方面的不完善，对未来气候的准确预测是(并将继续)实现的。这种情况限制了我们采取有效适应行动的能力。然而，有效的适应仍然是可能的，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。再加上对我们知识局限性的评估，这种方法可以成为向决策者提供信息的强大工具。因此，气候及其影响预测中不确定性的量化显然是一个关键问题。关于气候变化研究的这个问题已经有了相当多的思考，尽管关于最佳方法的共识尚未出现。另一方面，气候影响研究主要集中在一组不同的问题上：气候变化可能通过哪些机制影响农业和健康，以及也需要考虑的非气候影响是什么？因此，气候影响的研究基础是可靠的，但在量化不确定性方面往往不如支持它的实际气候变化研究那么彻底。因此，关于气候变化影响的声明通常对风险和不确定性采取不那么复杂的方法。因此，气候影响研究的下一个合乎逻辑的阶段是学习用于气候变化预测的方法。由于气候及其影响都存在于一个更广泛的地球系统中，有许多相互关联的组成部分，因此下一阶段不是简单的技术转让。相反，这意味着对气候及其影响进行“端到端”的综合观察，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机制，还包括气候信息用户所做的决定。在装备中选择的气候影响已被选择从头到尾涵盖这一范围。除了有助于影响研究，端到端分析也是气候变化研究的下一个合乎逻辑的阶段，因为社会正是通过影响来经历气候变化的。该项目主要关注未来几十年，因为这是一个与适应气候变化的社会相关的时间尺度。这也是一个时间尺度，我们对温室气体排放的预测受到了相对较好的限制，因此不确定性比本世纪末的预测要小。还将开展更长时间的工作，以便更好地了解不确定性。装备研究将建立在迄今为止关于导致气候变化及其影响的机制和过程的工作的基础上，因为正是这种理解构成了预测能力的基础。这种知识的形式是观察和实验(例如，对作物的实验已经证明，即使是在作物开花时的短暂高温也会严重降低产量)，也可以通过模拟模型来实现。只有通过有效地使用和结合气候科学和影响科学，以及每个社区使用的模型，我们才能量化不确定性，评估风险，从而使社会有能力应对气候变化。