中强地震前地震频次－震级关系式拟合优度变化的研究
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摘要
根据著名的Ｇｕｔｅｎｂｅｒｇ－Ｒｉｃｈｔｅｒ（以下简写成Ｇ－Ｒ）地震频次－震级统计关系式研究了我国东部地区（１０８°Ｅ以东）部分Ｍｓ≥５．０中强地震前一定时空尺度内中小地震频次与震级线性拟合优度（线性相关系数ｒ）随时间变化的特征。结果表明，利用中强地震前震中区一定范围内的中小地震进行Ｇ－Ｒ关系式拟合时，其线性拟合优度在地震前出现不同程度的异常现象。其变化特点是：在中强地震发生前期，震源区及其附近中小地震的发生在能级上分配均匀，线性拟合优度接近１；随着中强地震的临近，该区中小地震在能级上的分配存在着较显著的不均匀现象，表现为线性拟合优度明显下降。这种拟合优度的异常变化具有中期异常性质，有可能为中强地震的中期判定提供依据。
In this paper, characteristics of spacial and temperal variation of linear goodness of fit before some strong earthquakes (Ms≥5.0) in east part of China (longtitude>180°) are studied according to the famous Gutenberg-Richter's relation expression 1gN=a-bM by means of moderate and small events occurred in and around source area. The results show that the linear goodness of fit varies abnormaly prior to these strong earthquakes. In early stage of earthquake preparatory process, distribution of the energy released by small events in and around source area is isostatic and the goodness of fit approximates to 1,while the distribution of the energy turns to be anisostaic before strong earthquakes, leading to the obvious abatement of the linear goodness of fit. This phenomenon could be a middle term anomaly and a middle term criterion for strong earthquake prediction.
In this paper, characteristics of spacial and temperal variation of linear goodness of fit before some strong earthquakes (Ms≥5.0) in east part of China (longtitude>180°) are studied according to the famous Gutenberg-Richter's relation expression 1gN=a-bM by means of moderate and small events occurred in and around source area. The results show that the linear goodness of fit varies abnormaly prior to these strong earthquakes. In early stage of earthquake preparatory process, distribution of the energy released by small events in and around source area is isostatic and the goodness of fit approximates to 1,while the distribution of the energy turns to be anisostaic before strong earthquakes, leading to the obvious abatement of the linear goodness of fit. This phenomenon could be a middle term anomaly and a middle term criterion for strong earthquake prediction.
引文
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