“区域-时间-长度算法”及其在华北中强地震中短期前兆特征研究中的应用
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摘要
引入并改进了“区域 时间 长度算法”(region time lengthalgorithm) ,较之原来的定义更加强调了地震破裂尺度函数对VRTL的贡献 ,同时保证了震中距函数、时间函数及破裂尺度函数对VRTL影响的权系数相等 .华北 5级以上地震的回顾性预测研究结果表明 ,改进的RTL算法所得到的异常大多具有短期或中短期特征 .震前VRTL变化型态可分为两类 :Ⅰ类具有相对完整的变化形态 ,大多呈现从 0开始的“上升—转折下降”或“下降—转折上升”形态 ;Ⅱ类变化形态不完整 ,一般从 0开始急剧上升或下降 ,无明显转折 ,主震发生在VRTL极值附近 .VRTL上升表征地震活动水平相对于背景变化率的增高 ,意味着地震活动增强 ;VRTL下降则意味着地震活动相对于背景变化率的降低 ,在一定程度上表征了地震活动的平静 .据此给出由RTL算法进行中、短期异常识别并粗略估计发震时间的方法 .该方法Ⅰ ,Ⅱ类异常 3个月内发震的R值评分分别为 0 .6及 0 .3左右 ,6个月内的R评分分别为 0 .7及 0 .4左右 .对特征时间跨度、特征距离、震级下限等对VRTL的影响 ,以及其它一些实际应用中的重要问题进行了初步讨论 .
The Region Time Length Algorithm (RTL algorithm) is introduced and improved in the paper. Compared with the original definition, the influence of rupture length on RTL function is emphasized and the weights of epicentral distance function, time function, and rupture length function are ensured to be equal. The retrospective examinations of RTL algorithm in North China have indicated that the anomalies obtained by the improved RTL algorithm show the short or intermediate short term precursory features in most cases. There are two types of RTL anomalous patterns before the main shock. For the I type, the variation pattern of the V RTL , numerical values of the V RTL (x, y, z, t) function, is complete and most of them have shown the changing pattern of "rising from 0turningdropping" or "dropping from 0turningrising". For the II type, the variation pattern of V RTL is not complete, which increases or decreases quickly from 0 and there is no evident turning, the main shock generally occurs in the short period around the peak V RTL . The rising of V RTL indicates an increase of seismic activity relative to the background level, which means the enhancement of seismic activity, while the dropping of V RTL indicates the decrease of seismic activity relative to the background level, which represents the seismic quiescence to a certain extent. According to statistical examination results of RTL algorithm in North China, the methods to distinguish the intermediate and short term anomalies and to estimate the occurrence time of the coming main shock are given in the paper. For both I and II type RTL anomalies, the R value, i.e., the forecasting score, is about 0.6 and 0.3 for the 3 months forecasting period and about 0.7 and 0.4 for the 6 months forecasting period. The preliminary discussion is also made for the influences of characteristic time span t 0, characteristic distance r 0, and threshold magnitude M 0 on computation of V RTL , as well as some other significant problems in application.
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