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)

• 批准号: NE/H003487/1
• 负责人: Andrew Morse
• 金额: $ 2.14万
• 依托单位: University of Liverpool
• 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%2FH003487%2F1
• 关键词: End; end; Quantification; Uncertainty; Impacts

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。尽管有这些新的知识，但由于气候系统的根本混沌性质以及我们的理解、气候模拟模型和气候系统观测的不完善，对未来气候的精确预测仍然是（并将继续是）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确程度，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。因此，很明显，在预测气候及其影响时量化不确定性是一个关键问题。在气候变化研究方面，人们对这一问题进行了大量思考，尽管尚未就最佳方法达成共识。另一方面，气候影响研究主要侧重于一系列不同的问题：气候变化可能影响农业和健康等的机制是什么？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，这意味着对气候及其影响进行“端到端”的综合审视，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作出的决定。在EQUIP中选择的气候影响已经被选择为从端到端覆盖这一范围。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阶段，因为社会正是通过影响经历气候变化的。该项目主要侧重于未来几十年，因为这是一个与社会适应气候变化相关的时间表。这也是一个时间尺度，在这个时间尺度上，我们对温室气体排放的预测相对受到很好的限制，因此不确定性比世纪末要小。还将开展较长时间尺度的工作，以便更好地了解不确定性。EQUIP研究将建立在迄今为止对导致气候变化及其影响的机制和过程的研究基础上，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，对作物的实验表明，即使在作物开花时出现短暂的高温，也会严重减产）以及模拟模型。正是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。

项目成果

Visualizing the uncertainty in the relationship between seasonal average climate and malaria risk.

• DOI: 10.1038/srep07264
• 发表时间: 2014-12-02
• 期刊: Scientific reports
• 影响因子: 4.6
• 作者: MacLeod DA;Morse AP
• 通讯作者: Morse AP

Demonstration of successful malaria forecasts for Botswana using an operational seasonal climate model

• DOI: 10.1088/1748-9326/10/4/044005
• 发表时间: 2015-04-01
• 期刊: ENVIRONMENTAL RESEARCH LETTERS
• 影响因子: 6.7
• 作者: MacLeod, Dave A.;Jones, Anne;Morse, Andrew P.
• 通讯作者: Morse, Andrew P.

The Biosurveillance Analytics Resource Directory (BARD): Facilitating the Use of Epidemiological Models for Infectious Disease Surveillance.

• DOI: 10.1371/journal.pone.0146600
• 发表时间: 2016
• 期刊: PloS one
• 影响因子: 3.7
• 作者: Margevicius KJ;Generous N;Abeyta E;Althouse B;Burkom H;Castro L;Daughton A;Del Valle SY;Fairchild G;Hyman JM;Kiang R;Morse AP;Pancerella CM;Pullum L;Ramanathan A;Schlegelmilch J;Scott A;Taylor-McCabe KJ;Vespignani A;Deshpande A
• 通讯作者: Deshpande A

Equipped to deal with uncertainty in climate and impacts predictions: lessons from internal peer review

有能力应对气候和影响预测的不确定性：内部同行评审的经验教训

• DOI: 10.1007/s10584-014-1213-1
• 发表时间: 2014
• 期刊: Climatic Change
• 影响因子: 4.8
• 作者: Wesselink A