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Data Quality Analysis of China Permanent Seismic Network by Repeating Earthquakes | Seismological Research Letters | GeoScienceWorld
Source: pubs.geoscienceworld.org
Article summary:
1. This article presents a data quality detection model based on repeating earthquakes to evaluate the waveform quality of large-scale station data.
2. The model was verified using waveforms from 109 stations in the Global Seismographic Network and 842 permanent broadband seismic stations in mainland China.
3. Repeating earthquakes can be used to analyze waveform quality, circumventing the need for extensive forward calculations and reducing the influence of source parameter uncertainties and structural complexity on seismograms.
Article analysis:
This article provides an interesting approach to assessing seismic data quality by utilizing repeating earthquakes as a metric for waveform similarity detection. The authors present a hypothesis testing method to establish a data quality detection model based on repeating earthquakes, which is then verified using waveforms from 109 stations in the Global Seismographic Network and 842 permanent broadband seismic stations in mainland China.
The article is generally well-written and provides clear explanations of the methods used, as well as detailed results from their analysis. However, there are some potential biases that should be noted when evaluating this article's trustworthiness and reliability. Firstly, the authors do not provide any evidence or discussion regarding possible risks associated with their proposed method, such as potential errors due to inaccurate earthquake locations or incorrect focal mechanisms being used for comparison purposes. Additionally, while they discuss how their approach can reduce the influence of source parameter uncertainties and structural complexity on seismograms, they do not explore any counterarguments or alternative approaches that could be taken to address these issues.
Furthermore, it is unclear whether all possible sources of bias have been considered when conducting their analysis; for example, it is not stated whether any particular station was excluded from their evaluation due to calibration errors or instrument noise issues that may have affected its recordings. Additionally, while they mention that 18 anomalies were found mainly attributed to calibration, instrument noise, mass recentering, and regional long‐period interference issues, they do not provide any further details about these anomalies or how they were addressed in order to ensure accurate results from their analysis.
In conclusion, this article provides an interesting approach for assessing seismic data quality using repeating earthquakes as a metric for waveform similarity detection; however, there are some potential biases that should be noted when evaluating its trustworthiness and reliability.