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构建区域气候变化信息的情景方法

Storyline approach to the construction of regional climate change information.

作者信息

Shepherd Theodore G

机构信息

Department of Meteorology, University of Reading, PO Box 243, Earley Gate, Whiteknights, Reading RG6 6BB, UK.

出版信息

Proc Math Phys Eng Sci. 2019 May;475(2225):20190013. doi: 10.1098/rspa.2019.0013. Epub 2019 May 15.

Abstract

Climate science seeks to make statements of confidence about what has happened, and what will happen (conditional on scenario). The approach is effective for the global, thermodynamic aspects of climate change, but is ineffective when it comes to aspects of climate change related to atmospheric circulation, which are highly uncertain. Yet, atmospheric circulation strongly mediates climate impacts at the regional scale. In this way, the confidence framework, which focuses on avoiding type 1 errors (false alarms), raises the prospect of committing type 2 errors (missed warnings). This has ethical implications. At the regional scale, however, where information on climate change has to be combined with many other factors affecting vulnerability and exposure-most of which are highly uncertain-the societally relevant question is not 'What will happen?' but rather 'What is the impact of particular actions under an uncertain regional climate change?' This reframing of the question can cut the Gordian knot of regional climate change information, provided one distinguishes between epistemic and aleatoric uncertainties-something that is generally not done in climate projections. It is argued that the storyline approach to climate change-the identification of physically self-consistent, plausible pathways-has the potential to accomplish precisely this.

摘要

气候科学试图对已经发生的事情以及将会发生的事情(取决于情景)做出有把握的陈述。这种方法对于气候变化的全球热力学方面是有效的,但在涉及与大气环流相关的气候变化方面却无效,而大气环流相关方面具有高度不确定性。然而,大气环流在区域尺度上对气候影响起着强有力的调节作用。这样一来,专注于避免一类错误(误报)的置信度框架增加了犯二类错误(漏报)的可能性。这具有伦理意义。然而,在区域尺度上,气候变化信息必须与许多其他影响脆弱性和暴露度的因素相结合——其中大多数因素具有高度不确定性——与社会相关的问题不是“将会发生什么?”,而是“在区域气候变化不确定的情况下,特定行动会产生什么影响?” 只要区分认知不确定性和偶然不确定性,对问题的这种重新表述就能解开区域气候变化信息的难题——而这在气候预测中通常是做不到的。有人认为,气候变化的情景线方法——确定物理上自洽、合理的路径——有潜力恰恰做到这一点。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0679/6545051/ec923e743d20/rspa20190013-g1.jpg

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