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

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、热浪造成的死亡率上升以及海洋环境的变化。尽管有了这些新兴的知识，但由于气候系统的基本混沌性质以及我们对气候系统的理解、气候模拟模型和观测的不完善，对未来气候的精确预测是（并且将继续）无法实现的。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有力工具。显然，对气候及其影响预测中的不确定性进行量化是一个关键问题。在气候变化研究方面，人们对这个问题进行了相当多的思考，尽管尚未就最佳方法达成共识。另一方面，气候影响研究主要集中在一系列不同的问题上：气候变化可能影响（例如农业和健康）的机制是什么，哪些非气候影响也需要考虑在内？因此，气候影响的研究基础是健全的，但在量化不确定性方面往往不如支持它的物理气候变化研究那么彻底。因此，关于气候变化影响的声明往往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，下一阶段不是简单的技术转让。相反，它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，还包括气候信息使用者所作的决定。在EQUIP中选择的气候影响已被选择覆盖这个范围从端到端。除了有助于影响研究之外，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，因为这是一个与社会适应气候变化相关的时间尺度。在这个时间尺度上，我们对温室气体排放的预测受到了相对较好的约束，因此不确定性比本世纪末的预测要小。也将进行更长时间尺度的工作，以便对不确定性有更深入的了解。EQUIP研究将以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为基础，因为正是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存在（例如，对作物的实验表明，即使作物开花附近的短暂高温也会严重降低产量）以及模拟模型。只有通过有效地利用和结合气候科学和影响科学，以及每个社区使用的模型，我们才能够量化不确定性，评估风险，从而使社会有能力应对气候变化。

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.