What does this research mean for the field?

Despite the use of GPS timestamping, seismic arrays can experience significant, quantized timing errors that can be detected, modeled, and corrected using multi-channel cross-correlation of teleseismic recordings. Novelty: ClaimNovelty.METHODOLOGICAL. Consensus alignment: ConsensusAlignment.NEUTRAL.

What question did this study set out to answer?

To detect, model, and correct relative in situ timing errors among individual sensors in seismic arrays using teleseismic wave arrivals.

September 3, 2026Seismological Research LettersOpen Access

Detection and Modeling of Timing Errors at Seismic Arrays

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Authors

NANick Ackerley

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Overview

Cross-correlation analysis reveals quantized datalogger timing errors across seismic array stations, indicating that firmware anomalies can systematically corrupt waveform timestamps until reset.

Key Points

To detect, model, and correct relative in situ timing errors among individual sensors in seismic arrays using teleseismic wave arrivals.
Applied multi-channel cross-correlation to teleseismic waveforms recorded across array stations.
Calculated inter-station relative timing offsets via empirical moveout correction on data recorded between 2014 and 2020.
Detected quantized timing errors up to a maximum of 0.4 s, occurring in discrete base increments of 0.125 s (exactly five samples at 40 samples per second).
Identified that errors began at random times and grew monotonically until datalogger reset, with zero errors observed after an April 8, 2020 firmware update.

Cite This Study

Nick Ackerley (2026) studied this question.

synapsesocial.com/papers/6a993474636c6408cfa7c260 https://doi.org/10.1785/0220260111

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September 3, 2026Seismological Research LettersOpen Access

Detection and Modeling of Timing Errors at Seismic Arrays

View Full Paper

Ask AI

Bookmark

Authors

NANick Ackerley

Discussion

Member takes

Overview

Cross-correlation analysis reveals quantized datalogger timing errors across seismic array stations, indicating that firmware anomalies can systematically corrupt waveform timestamps until reset.

Key Points

To detect, model, and correct relative in situ timing errors among individual sensors in seismic arrays using teleseismic wave arrivals.
Applied multi-channel cross-correlation to teleseismic waveforms recorded across array stations.
Calculated inter-station relative timing offsets via empirical moveout correction on data recorded between 2014 and 2020.
Detected quantized timing errors up to a maximum of 0.4 s, occurring in discrete base increments of 0.125 s (exactly five samples at 40 samples per second).
Identified that errors began at random times and grew monotonically until datalogger reset, with zero errors observed after an April 8, 2020 firmware update.

Cite This Study

Nick Ackerley (2026) studied this question.

synapsesocial.com/papers/6a993474636c6408cfa7c260 https://doi.org/10.1785/0220260111

View Full Paper

Ask AI

Bookmark