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2020年牙买加M_W7.7地震前蜂群卫星磁场的时变背景场与异常分析
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作者 朱凯光 贺小丹 +4 位作者 樊蒙璇 Dedalo Marchetti 王婷 温佳咪 张逸群 《地震学报》 CSCD 北大核心 2023年第2期315-327,共13页
蜂群卫星磁场数据受地磁活动和地方时的影响,本文先通过变分模态分解去除地磁活动对数据的影响,再建立时变背景场以消除地方时对数据的影响。基于建立的时变背景场,我们利用蜂群卫星磁场数据对2020年牙买加M_W7.7地震进行震前异常分析,... 蜂群卫星磁场数据受地磁活动和地方时的影响,本文先通过变分模态分解去除地磁活动对数据的影响,再建立时变背景场以消除地方时对数据的影响。基于建立的时变背景场,我们利用蜂群卫星磁场数据对2020年牙买加M_W7.7地震进行震前异常分析,计算地震影响区域内轨道数据的能量值,利用时变背景场设置阈值提取异常。结果表明:牙买加地震影响区域内的异常轨道累计数量在震前50天至震前43天出现加速增长的现象。此外,基于时变背景场与昼、夜侧背景场提取异常的结果对比显示:由于昼、夜侧背景场的建立混合了多个当地时间的磁场数据,高值背景场会被低值背景场拉低,导致部分非异常的轨道被错误地识别为异常轨道;而低值背景场会被高值背景场抬高,导致部分异常轨道不能被识别。而时变背景场针对每一个地方时建立了更为准确的背景,其时间分辨率高,能凸显出不同地方时卫星磁场数据的背景值差异,这对异常轨道的准确提取十分重要。进一步对岩石层、大气层和电离层多圈层的参量进行了震前异常分析,并对三个圈层的异常出现时间进行解释,证明了这些异常可能与牙买加地震的孕育有关。 展开更多
关键词 蜂群卫星磁场 时变背景场 牙买加地 震前异常提取 变分模态分解
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Short-term Earthquake Prediction in the Sichuan-Yunnan Region Using the Method of Modulated Earthquakes
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作者 Wang Cuizhi Cao Jingquan Guo Hongli Zhang Lei Xue Na 《Earthquake Research in China》 2011年第1期101-110,共10页
By scanning modulated or un-modulated earthquakes spatio-temporally in the region of Sichuan-Yunnan,short-term non-stationary seismic precursory patterns were extracted with significant difference and the characterist... By scanning modulated or un-modulated earthquakes spatio-temporally in the region of Sichuan-Yunnan,short-term non-stationary seismic precursory patterns were extracted with significant difference and the characteristic of non-stationary short-term seismic anomalies were analyzed as well as prediction efficiency of modulated small earthquakes before a strong earthquake. Besides,small earthquake modulation ratios near the region of the epicenter were calculated and sorted by time. The results indicated that there were significant effects using the modulated earthquake method to predict earthquakes greater than MS6. 0 in a short time. Before the MS8. 0 Wenchuan earthquake,there were obvious short-term precursory seismicity gap patterns of modulated small earthquakes. 展开更多
关键词 Modulated earthquake Non-steady-state Modulation ratio Short-term earthquake prediction
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