Comparing Methods to Constrain Future European Climate Projections Using a Consistent Framework
Comparing Methods to Constrain Future European Climate Projections Using a Consistent Framework
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DOI：
10.1175/jcli-d-19-0953.1
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发表时间：
2020-10-15
影响因子：
4.9
通讯作者：
Undorf, Sabine
中科院分区：
文献类型：
--
作者：
Brunner, Lukas;McSweeney, Carol;Undorf, Sabine
政治决策、适应规划和影响评估需要对未来气候变化和相关不确定性进行可靠的估计。为了提供这些估计，已经提出了不同的方法来约束、过滤或加权气候模型预测到概率分布。然而，对多种这类方法的评估往往因缺乏协调而受阻，这些方法侧重于各种变量、时间段、区域或模型库。在这里，建立了一个一致的框架，以便能够对八种不同的方法进行定量比较；重点是2041-60年欧洲三个空间区域相对于1995-2014年夏季温度和降水的变化。该分析利用了几个大型合奏、CMIP5多模合奏和扰动物理合奏的预测，所有这些都使用了高排放情景RCP8.5。总结了这些方法的主要特点，讨论了假设条件，给出了结果的约束分布。研究发现，方法一致性取决于调查区域，但中位数变化的一致性一般高于不确定范围。因此，这项研究强调了提供关于不同方法如何影响评估的不确定性的明确背景的重要性--特别是对规避风险的利益攸关方感兴趣的上限和下限百分比。这种比较还暴露了不同证据路线导致不同限制的情况；还需要开展额外的工作，以了解方法之间的根本差异如何导致这种分歧，并向用户提供明确的指导。
Political decisions, adaptation planning, and impact assessments need reliable estimates of future climate change and related uncertainties. To provide these estimates, different approaches to constrain, filter, or weight climate model projections into probabilistic distributions have been proposed. However, an assessment of multiple such methods to, for example, expose cases of agreement or disagreement, is often hindered by a lack of coordination, with methods focusing on a variety of variables, time periods, regions, or model pools. Here, a consistent framework is developed to allow a quantitative comparison of eight different methods; focus is given to summer temperature and precipitation change in three spatial regimes in Europe in 2041-60 relative to 1995-2014. The analysis draws on projections from several large ensembles, the CMIP5 multimodel ensemble, and perturbed physics ensembles, all using the high-emission scenario RCP8.5. The methods' key features are summarized, assumptions are discussed, and resulting constrained distributions are presented. Method agreement is found to be dependent on the investigated region but is generally higher for median changes than for the uncertainty ranges. This study, therefore, highlights the importance of providing clear context about how different methods affect the assessed uncertainty-in particular, the upper and lower percentiles that are of interest to risk-averse stakeholders. The comparison also exposes cases in which diverse lines of evidence lead to diverging constraints; additional work is needed to understand how the underlying differences between methods lead to such disagreements and to provide clear guidance to users.