To complement the new European Strong-Motion dataset and the ongoing efforts to update the seismic hazard and risk assessment of Europe and Mediterranean regions, we propose a new regionally adaptable ground-motion model (GMM). We present here the GMM capable of predicting the 5% damped RotD50 of PGA, PGV, and \( SA\left( {T = 0.01 - 8\,{\text{s}}} \right) \) from shallow crustal earthquakes of \( 3 \le M_{W} \le 7.4 \) occurring \( 0 < R_{JB} \le 545\,{\text{km}} \) away from sites with \( 90 \le V_{s30} \le 3000\,{\text{m}}\,{\text{s}}^{ - 1} \) or \( 0.001 \le slope \le 1\,{\text{m}}\,{\text{m}}^{ - 1} \). The extended applicability derived from thousands of new recordings, however, comes with an apparent increase in the aleatory variability (σ). Firstly, anticipating contaminations and peculiarities in the dataset, we employed robust mixed-effect regressions to down weigh only, and not eliminate entirely, the influence of outliers on the GMM median and σ. Secondly, we regionalised the attenuating path and localised the earthquake sources using the most recent models, to quantify region-specific anelastic attenuation and locality-specific earthquake characteristics as random-effects, respectively. Thirdly, using the mixed-effect variance–covariance structure, the GMM can be adapted to new regions, localities, and sites with specific datasets. Consequently, the σ is curtailed to a 7% increase at T < 0.3 s, and a substantial 15% decrease at T ≥ 0.3 s, compared to the RESORCE based partially non-ergodic GMM. We provide the 46 attenuating region-, 56 earthquake localities-, and 1829 site-specific adjustments, demonstrate their usage, and present their robustness through a 10-fold cross-validation exercise.

中文翻译：

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欧洲浅层地壳地震的区域适应地震动模型

为了补充新的欧洲强运动数据集，以及为更新欧洲和地中海地区的地震危险性和风险评估所做的持续努力，我们提出了一种新的区域适应性地面运动模型（GMM）。我们在这里展示的GMM能够从浅地壳中预测PGA，PGV和\（SA \ left（{T = 0.01-8 \，{\ text {s}}} \ right）\）的5％阻尼RotD 50 \（3 \ le M_ {W} \ le 7.4 \）发生的地震\（0 <R_ {JB} \ le 545 \，{\ text {km}} \）远离\（90 \ le V_ { s30} \ le 3000 \，{\ text {m}} \，{\ text {s}} ^ {-1} \）或\（0.001 \ lelope \ le 1 \，{\ text {m}} \\ ，{\ text {m}} ^ {-1} \）。然而，来自数千个新唱片的扩展适用性伴随着偶然变异性（σ）的明显增加。首先，为了预测数据集中的污染和特殊性，我们采用鲁棒的混合效应回归来仅权衡而非完全消除异常值对GMM中位数和σ的影响。其次，我们使用最新模型对衰减路径进行了区域划分并确定了震源，从而分别将区域特定的非弹性衰减和区域特定的地震特征量化为随机效应。第三，使用混合效应方差-协方差结构，可以将GMM调整为具有特定数据集的新区域，位置和地点。因此，σ被缩减到在增加了7％Ť  <0.3秒，并且在显着减少15％Ť  ≥0.3秒，与基于部分非遍历GMM的RESORCE。我们提供了46个衰减区域，56个地震区域和1829个站点特定的调整，展示了它们的用法，并通过10倍交叉验证练习展示了其稳健性。