On the attribution of the impacts of extreme weather events to anthropogenic climate change
On the attribution of the impacts of extreme weather events to anthropogenic climate change
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DOI：
10.1088/1748-9326/ac44c8
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发表时间：
2022-02-01
影响因子：
6.7
通讯作者：
Wehner, M.
中科院分区：
文献类型：
--
作者：
Perkins-Kirkpatrick, S. E.;Stone, D. A.;Wehner, M.
对人为气候变化在极端天气事件中的作用的调查现在开始扩展到分析人为对非气候（例如社会经济）系统的影响。然而，在进行这种扩展时需要谨慎，因为在考虑事件的影响时，关于极端天气归因的方法选择可能至关重要。归因风险分数（FAR）方法，在极端天气归因研究中很有用，对一类事件有非常具体的解释，有可能误解天气事件分析的结果适用于特定的事件及其影响结果。使用两个案例研究的极端气象及其影响，我们认为，FAR是不适当的，一般估计的人为信号背后的具体影响的幅度。除了评估相关的气象事件外，还应始终进行影响归因评估，因为由于影响系统对天气作出反应的过程存在滞后和非线性，因此不能假定天气背后的人为信号等同于影响背后的信号。虽然在有些情况下，使用FAR来理解一类影响背后的气候变化信号是有用的（例如“系统破坏”事件），但如果重新定义关于具体影响的归因问题，以关注实际和反事实气候模型和影响模拟的大样本中影响回报值和幅度的变化，通常会产生更有用的结果。我们主张不断开展跨学科合作，这对于有效和强有力的影响归因评估至关重要。
Investigations into the role of anthropogenic climate change in extreme weather events are now starting to extend into analysis of anthropogenic impacts on non-climate (e.g. socio-economic) systems. However, care needs to be taken when making this extension, because methodological choices regarding extreme weather attribution can become crucial when considering the events' impacts. The fraction of attributable risk (FAR) method, useful in extreme weather attribution research, has a very specific interpretation concerning a class of events, and there is potential to misinterpret results from weather event analyses as being applicable to specific events and their impact outcomes. Using two case studies of meteorological extremes and their impacts, we argue that FAR is not generally appropriate when estimating the magnitude of the anthropogenic signal behind a specific impact. Attribution assessments on impacts should always be carried out in addition to assessment of the associated meteorological event, since it cannot be assumed that the anthropogenic signal behind the weather is equivalent to the signal behind the impact because of lags and nonlinearities in the processes through which the impact system reacts to weather. Whilst there are situations where employing FAR to understand the climate change signal behind a class of impacts is useful (e.g. 'system breaking' events), more useful results will generally be produced if attribution questions on specific impacts are reframed to focus on changes in the impact return value and magnitude across large samples of factual and counterfactual climate model and impact simulations. We advocate for constant interdisciplinary collaboration as essential for effective and robust impact attribution assessments.