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Real-time forecasts of tomorrow's earthquakes in California

机译：加利福尼亚明天地震的实时预报

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摘要

Despite a lack of reliable deterministic earthquake precursors, seismologists have significant predictive information about earthquake activity from an increasingly accurate understanding of the clustering properties of earthquakes(1-4). In the past 15 years, time-dependent earthquake probabilities based on a generic short-term clustering model have been made publicly available in near-real time during major earthquake sequences. These forecasts describe the probability and number of events that are, on average, likely to occur following a mainshock of a given magnitude, but are not tailored to the particular sequence at hand and contain no information about the likely locations of the aftershocks. Our model builds upon the basic principles of this generic forecast model in two ways: it recasts the forecast in terms of the probability of strong ground shaking, and it combines an existing time-independent earthquake occurrence model based on fault data and historical earthquakes(5) with increasingly complex models describing the local time-dependent earthquake clustering(1,2). The result is a time-dependent map showing the probability of strong shaking anywhere in California within the next 24 hours. The seismic hazard modelling approach we describe provides a better understanding of time-dependent earthquake hazard, and increases its usefulness for the public, emergency planners and the media.
机译：尽管缺乏可靠的确定性地震前兆，但地震学家通过对地震的聚类性质的日益准确的了解，对地震活动具有重要的预测信息（1-4）。在过去的15年中，在重大地震序列中，基于通用短期聚类模型的随时间变化的地震概率已近实时公开。这些预测描述了在给定大小的主震后平均可能发生的事件的概率和数量，但并未针对眼前的特定顺序进行调整，并且不包含有关余震可能位置的信息。我们的模型基于以下两种通用的预测模型的基本原理：根据强地面震动的可能性重新构建了预测，并结合了基于断层数据和历史地震的现有独立于时间的地震发生模型（5） ），其模型越来越复杂，描述了当地随时间变化的地震聚类（1,2）。结果是一张随时间变化的地图，显示了未来24小时内加利福尼亚任何地方发生强烈晃动的可能性。我们描述的地震灾害建模方法可以更好地了解随时间变化的地震灾害，并提高其对公众，应急计划人员和媒体的实用性。

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