High-Resolution Long-Term and Short-Term Earthquake Forecasts for California
High-Resolution Long-Term and Short-Term Earthquake Forecasts for California
复制标题
加利福尼亚州高分辨率长期和短期地震预报
DOI：
10.1785/0120090340
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发表时间：
2011
影响因子：
3
通讯作者：
Y. Kagan
中科院分区：
文献类型：
--
作者：
M. Werner;A. Helmstetter;D. Jackson;Y. Kagan
我们提出了两个模型，用于估计加州未来地震的概率，将在地震可预报性研究合作实验室（CSEP）进行测试。第一个是我们根据Helmstetter等人（2007）修改的自适应平滑地震活动性的时间独立模型。该模型对M ≥ 4级地震提供了5年预报：95.我们表明大地震往往发生在M ≥ 2的小地震附近，因此，从众多小地震的位置可以得到未来大地震空间分布的高分辨率估计。我们进一步假设宇宙存在一个普遍的古滕贝格-里克特星等分布。在回顾性检验中，我们发现泊松分布不符合观测到的速率变异性，这与当前地震可预测性实验中的假设相反。因此，我们使用更适合的负二项分布对事件数量进行预测。第二个模型是我们从Helmstetter et al.（2006）改进而来的时变余震型余震序列（ETAS）模型，它提供了M ≥ 3：95的次日预报。在该模型中，预测率是背景率（与时间无关的模型率成比例）和由于所有先前地震引起的触发事件的预期率的总和。根据大森宇津定律，每次地震触发事件的速率随震级呈指数级增加，并随时间衰减。各向同性核模型的余震的空间密度为小（M ≤ 5：5）事件，而对于较大的地震，我们平滑早期的余震，以预测以后的事件。我们估计参数值，通过优化回顾性预测，发现短期模型实现了约6.0的概率增益每地震的时间无关的模型。在线材料：爆炸和ETAS参数的识别。
We present two models for estimating the probabilities of future earth- quakes in California, to be tested in the Collaboratory for the Study of Earthquake Predictability (CSEP). The first is a time-independent model of adaptively smoothed seismicity that we modified from Helmstetter et al. (2007). The model provides five- year forecasts for earthquakes with magnitudes M ≥ 4:95. We show that large earthquakes tend to occur near the locations of small M ≥ 2 events, so that a high- resolution estimate of the spatial distribution of future large quakes is obtained from the locations of the numerous small events. We further assume a universal Gutenberg- Richter magnitude distribution. In retrospective tests, we show that a Poisson distri- bution does not fit the observed rate variability, in contrast to assumptions in current earthquake predictability experiments. We therefore issued forecasts using a better- fitting negative binomial distribution for the number of events. The second model is a time-dependent epidemic-type aftershock sequence (ETAS) model that we modified from Helmstetter et al. (2006) and that provides next-day forecasts for M ≥ 3:95. In this model, the forecasted rate is the sum of a background rate (propor- tional to the time-independent model rate) and of the expected rate of triggered events due to all prior earthquakes. Each earthquake triggers events with a rate that increases exponentially with its magnitude and decays in time according to the Omori-Utsu law. An isotropic kernel models the spatial density of aftershocks for small (M ≤ 5:5) events, while for larger quakes, we smooth early aftershocks to forecast later events. We estimate parameter values by optimizing retrospective forecasts and find that the short-term model realizes a probability gain of about 6.0 per earthquake over the time-independent model. Online Material: Identification of explosions and ETAS parameters.