Multi-Scale ARMA Residual Correction Model for Detecting Pre-earthquake Ionospheric Anomalies
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摘要: 为提高电离层总电子含量（total electronic content，TEC）扰动探测参考背景值的预测精度，提出了多尺度自回归移动平均（autoregressive moving average，ARMA）残差修正模型。通过对比该方法、ARMA模型、四分位距法（inter quartile range，IQR）及滑动时窗法对TEC背景值的预测精度，结果显示修正模型预测的TEC背景值平均相对精度为89.78%，分别比ARMA模型、IQR及滑动时窗法高5.18%、1.41%和1.42%，且预测值的残差绝对值小于等于3.0 TECU的百分比为91.67%，明显优于其他3种方法，说明修正模型探测震前TEC异常是可行的。利用该方法探测2013-04-20芦山县Mw7.0级地震震前电离层TEC扰动情况，验证了该方法的有效性。实验结果表明，震前第9天和第13天电离层明显的正异常和震前第1~4天明显的负异常极可能是孕育地震引起的，且正异常主要出现在08：00-10：00 UT，而负异常主要集中在0：00-14：00 UT。Abstract: To improve the prediction accuracy of the background values of the ionospheric total electronic content (TEC) disturbance, we have proposed multi-scale autoregressive moving average (ARMA) residual correction model (MARCM) by comparing the precision of this method, ARMA model, inter quartile range(IQR)and sliding window method in predicting the ionospheric total electronic content reference background values. The results show that the average relative accuracy of TEC background value predicted by MARCM is 89.78%, which is higher than the ARMA model, IQR and sliding window method with values of 5.18%, 1.41% and 1.42% respectively and show that the percentage of absolute residual values less than or equal to 3.0 TECU predicted by MARCM is 91.67%, significantly better than the other three methods, It is demorstrated that using MARCM to detect pre-earthquake ionospheric anomalies is feasible. We use this method to detect pre-earthquake ionospheric anomalies of the earthquake happened in Lushan on April 20, 2013, and prove the effectiveness of the proposed method. The results show that obviously ionospheric positive anomalies on 9 and 13 days before the earthquake and apparently ionospheric negative anomalies on 1 to 4 days before the earthquake, are most likely to be caused by the earthquake. And positive anomalies mainly emerge in the 08:00 UT to 10:00 UT, the negative anomalies are mainly concentrated in 00:00 UT to 14:00 UT
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Keywords:
- multi-scale /
- ARMA /
- residual correction /
- earthquake /
- ionospheric TEC anomaly
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图 1 4种方法背景值预测结果对比
Figure 1. Comparison of Background Value Prediction Results of the Four Methods
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图 2 平静状态下3种方法探测结果
Figure 2. Detection Results of Three Methods Under Quiescent Conditions
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图 3 2013-04-05-2013-04-20的F10.7、DST指数和Kp指数
Figure 3. The F10.7 Index, DST Index and Kp Index in April 5 to April 20, 2013
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图 6 MARCM探测的异常值分布情况
Figure 6. Distribution of Anomalies Detected by Multi-scale ARMA Residual Correction Model
表 1 4种方法背景值预测精度统计
Table 1 Prediction Accuracy Statistics of Background Values of Four Methods
日期 MARCM ARMA模型 IQR 滑动窗口法 Δ/TECU σ/TECU P/% Δ/TECU σ/TECU P/% Δ/TECU σ/TECU P/% Δ/TECU σ/TECU P/% 2013-02-21 -0.61 1.47 90.55 1.25 1.18 89.96 1.99 0.87 87.70 2.06 1.05 87.55 2013-02-22 0.54 1.43 90.86 2.05 1.69 82.73 2.09 1.22 84.87 2.13 1.14 85.13 2013-02-23 0.12 1.56 90.85 2.57 1.09 83.48 2.82 2.21 83.91 2.79 2.24 83.77 2013-02-24 -0.77 1.48 90.95 2.02 1.73 81.68 2.13 0.87 85.77 2.11 0.81 86.01 2013-02-25 0.29 1.65 89.48 1.89 1.63 82.90 2.04 0.92 86.81 2.05 0.94 86.65 2013-02-26 -0.61 2.51 88.04 0.31 3.00 82.01 0.82 1.08 92.17 0.87 1.11 91.44 2013-02-27 -0.28 2.67 86.59 0.81 2.83 82.91 1.11 1.54 89.86 1.19 1.44 89.41 2013-02-28 -0.59 1.92 90.92 -0.41 2.07 91.10 -0.21 0.80 95.86 -0.18 0.58 96.95 平均值 -0.24 1.84 89.78 1.31 1.90 84.60 1.60 1.19 88.37 1.63 1.16 88.36 
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表 2 4种方法预报残差分类百分比统计/%
Table 2 Percentage Statistics of Forecast Residual Classification of Four Methods/%
方法 绝对残差分布/ TECU |Δ|≤3.0 3.0 < |Δ|≤4.0 4.0 < |Δ|≤5.0 5.0 < |Δ|≤6.0 |Δ|>6.0 MARCM 91.67 3.13 4.16 1.04 0 ARMA模型 72.92 14.58 10.42 2.08 0 IQR 84.37 10.42 3.13 0 2.08 滑动窗口法 85.42 10.42 2.08 1.04 1.04
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