Consequence forecasting: A rational framework for predicting the consequences of approaching storms
Consequence forecasting: A rational framework for predicting the consequences of approaching storms
复制标题
后果预测：预测即将到来的风暴后果的合理框架
DOI：
10.1016/j.crm.2022.100412
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发表时间：
2022
影响因子：
4.4
通讯作者：
Wilkinson S
中科院分区：
文献类型：
--
作者：
Wilkinson S
由于我们的气候继续对人为强迫作出反应，个别天气事件的规模和频率以及与之相关的极端天气的强度仍然高度不确定。这对我们的基础设施网络来说是一个特别令人关切的问题，因为对这些重要生命线的风暴破坏日益严重，对我们的社区产生了重大影响。因此，有效的第一反应正在成为基础设施系统管理的一个日益重要的部分。在这里，我们提出了一个新的和合理的框架，“后果预测”，使概率，事件前的决策，为第一响应者有效地针对资源之前，极端天气事件，从而减少社会后果。我们的方法是独特的，它最大限度地减少模型偏差，使用相同的数值天气预报模型的故障归因和故障预测。我们的框架可以提前24小时预测超过50%的事件的故障率在真实值的50%以内，因此表明它可以通过减少恢复时间来提高社会气候适应力。
As our climate continues to respond to anthropogenic forcing, the magnitude and frequency of individual weather events and the intensity of the weather extremes associated with these, remains highly uncertain. This is a particular concern for our infrastructure networks, as increasing storm-related damage to these vital lifelines has significant consequences for our communities. Effective first response is hence becoming an increasingly important part of the management of infrastructure systems. Here, we propose a novel and rational framework for ‘consequence forecasting’ that enables probabilistic, pre-event decision-making for first responders to effectively target resources prior to an extreme weather event and thus reduce the societal consequences. Our method is unique in that it minimises model bias by using the same numerical weather prediction model for both fault attribution and fault prediction. Our framework can predict failure rates that are within 50% of the true value for more than 50% of the events considered, some 24 h in advance, therefore demonstrating that it can be an important part of increasing societal climate resilience by reducing reinstatement times.