The 2019 Ridgecrest sequence provides the first opportunity to evaluate Uniform California Earthquake Rupture Forecast v.3 with epidemic‐type aftershock sequences (UCERF3‐ETAS) in a pseudoprospective sense. For comparison, we include a version of the model without explicit faults more closely mimicking traditional ETAS models (UCERF3‐NoFaults). We evaluate the forecasts with new metrics developed within the Collaboratory for the Study of Earthquake Predictability (CSEP). The metrics consider synthetic catalogs simulated by the models rather than synoptic probability maps, thereby relaxing the Poisson assumption of previous CSEP tests. Our approach compares statistics from the synthetic catalogs directly against observations, providing a flexible approach that can account for dependencies and uncertainties encoded in the models. We find that, to the first order, both UCERF3‐ETAS and UCERF3‐NoFaults approximately capture the spatiotemporal evolution of the Ridgecrest sequence, adding to the growing body of evidence that ETAS models can be informative forecasting tools. However, we also find that both models mildly overpredict the seismicity rate, on average, aggregated over the evaluation period. More severe testing indicates the overpredictions occur too often for observations to be statistically indistinguishable from the model. Magnitude tests indicate that the models do not include enough variability in forecasted magnitude‐number distributions to match the data. Spatial tests highlight discrepancies between the forecasts and observations, but the greatest differences between the two models appear when aftershocks occur on modeled UCERF3‐ETAS faults. Therefore, any predictability associated with embedding earthquake triggering on the (modeled) fault network may only crystalize during the presumably rare sequences with aftershocks on these faults. Accounting for uncertainty in the model parameters could improve test results during future experiments.

中文翻译：

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2019年Ridgecrest序列中UCERF3-ETAS预报的拟假评估

2019年的Ridgecrest序列提供了第一个机会，可以从假性的角度评估具有流行型余震序列（UCERF3-ETAS）的加利福尼亚统一地震破裂预报v.3。为了进行比较，我们提供了一个没有显式故障的模型版本，该版本更类似于传统的ETAS模型（UCERF3-NoFaults）。我们使用在地震可预测性研究（CSEP）协作实验室内开发的新指标来评估预测。度量标准考虑的是模型模拟的综合目录，而不是概要概率图，从而放宽了先前CSEP测试的泊松假设。我们的方法将综合目录中的统计信息直接与观察结果进行比较，从而提供了一种灵活的方法，可以解决模型中编码的依赖性和不确定性。我们发现 首先，UCERF3-ETAS和UCERF3-NoFaults大致捕获了Ridgecrest序列的时空演化，从而增加了越来越多的证据表明ETAS模型可以作为信息预报工具。但是，我们还发现，这两个模型在评估期内平均略微高估了地震活动率。更为严格的测试表明，过高的预测经常发生，以至于观测值与模型在统计上无法区分。数量级测试表明，模型在预测的数量级分布中没有包含足够的可变性以匹配数据。空间测试突出了预报和观测值之间的差异，但是，当模拟的UCERF3-ETAS断层发生余震时，两个模型之间的最大差异就会出现。因此，与将地震触发因素嵌入（建模的）断层网络有关的任何可预测性都只能在这些断层上带有余震的假定稀有序列中结晶。考虑模型参数的不确定性可以在将来的实验中改善测试结果。