Anomaly recording station detection process

According to Figure S1, the detection process of abnormal recording stations is as follows:
Step1, acquisition of repeating earthquake event data. We prepare a list of repeating earthquakes and retrieve the waveform data of the station to be detected from the NEDBC database (Chai et al., 2020).
Step 2, calculation of the correlation coefficient. We retrieved relevant event waveforms, and performed waveform pre-processing such as demean, detrend, band-pass filtering (0.01-0.05 Hz), and normalization. Then, we calculated the CC and σSF (variance of scale factor) with a sliding window method. The statistical parameter hypothesis testing method is used to obtain the confidence interval thresholds ηCC and ηSF of CC and σSF, respectively.
Step3, filtering of potentially anomalous stations. After determining the detection threshold of each channel, if the CC of the channel falls outside the confidence interval, the station is recorded as a potential abnormal station. While for cases where the CC values fall in the confidence area, the variance σSF of the 3-channel scale factor SF is calculated to determine whether the σSFfalls within the confidence interval. If the σSF falls within the confidence interval, the station is recorded as a normal record station, otherwise it will be considered as a candidate abnormal station.
Step 4, confirmation of abnormal recording station. Combining the original waveforms and the PSD curve characteristics, we verified the anomalous stations and classified them into four categories.