Three Ingredients for Improved Global Aftershock Forecasts: Tectonic Region, Time‐Dependent Catalog Incompleteness, and Intersequence Variability
Three Ingredients for Improved Global Aftershock Forecasts: Tectonic Region, Time‐Dependent Catalog Incompleteness, and Intersequence Variability
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改进全球余震预报的三个要素：构造区域、时变目录不完整性和层序间变异性
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发表时间：
2015
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通讯作者：
A. Michael
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作者：
M. Page;N. V. Elst;J. Hardebeck;K. Felzer;A. Michael
在大地震之后，由于余震触发，地震危险性可能比长期平均水平高出几个数量级。由于这种危险性的增加，应急管理人员和公众需要快速、权威和可靠的余震预报。过去，美国地质调查局（USGS）在全球大地震后发布的余震预报是临时发布的，方法不一致，在某些情况下余震参数来自加州。为了解决这个问题，美国地质勘探局目前正在根据Reasenberg和Jones（1989）的方法开发一种自动余震产品，这种产品将产生更准确的预报。为了更好地捕捉空间变化的余震生产力和衰减，我们估计区域余震参数序列内的加西亚等人。（2012）构造区。我们发现，平均余震生产力的区域变化几乎达到10倍。我们还开发了一种方法来解释目录中大事件之后的完整性随时间变化的幅度。除了估计区域内的平均序列参数，我们开发了一种逆方法来估计序列间参数的变异性。这允许预测不确定性的更完整量化和预测的贝叶斯更新，因为序列特异性信息变得可用。
在线资料：大森参数置信限、考虑到B-值变化的替代大森拟合、更大的构造区域和更长的时间拟合窗口以及合成测试结果。
Following a large earthquake, seismic hazard can be orders of magnitude higher than the long‐term average as a result of aftershock triggering. Because of this heightened hazard, emergency managers and the public demand rapid, authoritative, and reliable aftershock forecasts. In the past, U.S. Geological Survey (USGS) aftershock forecasts following large global earthquakes have been released on an ad hoc basis with inconsistent methods, and in some cases aftershock parameters adapted from California. To remedy this, the USGS is currently developing an automated aftershock product based on the Reasenberg and Jones (1989) method that will generate more accurate forecasts. To better capture spatial variations in aftershock productivity and decay, we estimate regional aftershock parameters for sequences within the Garcia et al. (2012) tectonic regions. We find that regional variations for mean aftershock productivity reach almost a factor of 10. We also develop a method to account for the time‐dependent magnitude of completeness following large events in the catalog. In addition to estimating average sequence parameters within regions, we develop an inverse method to estimate the intersequence parameter variability. This allows for a more complete quantification of the forecast uncertainties and Bayesian updating of the forecast as sequence‐specific information becomes available.
Online Material: Omori parameter confidence limits, alternative Omori fits taking into account b ‐value variation, larger tectonic regions, and a longer temporal fitting window, and synthetic test results.