Comment on “Detection of Marsquakes on InSight data using deep learning” by Huang et al. (2025)

Summary Huang et al. (2025) reported the detection of 67 teleseismic marsquakes identified by P and S wave arrivals. The authors used a deep learning phase picker trained on local earthquake data and applied it to narrow-bandpass filtered seismic data recorded by NASA’s InSight seismometer, making use of similarities between local earthquake and teleiseismic marsquake recordings when adjusting for sampling rate and S-P time scaling relations. We review all detections as similarly done for the Marsquake Service catalogue and other studies on this data set, using the complementary wind and pressure data recorded by InSight. As these auxiliary data were not recorded in the second half of the mission, we also infer wind contamination from bandwidths in the seismic data that contain wind-sensitive lander modes. Additionally, we analyse the signal polarisation to compare it with the expected characteristics of P and S waves and the background noise. Our review indicates that all 67 detections reported by the authors correspond to atmospheric noise. In most cases, the detections relate to the seismic signature of small wind bursts followed by larger wind bursts, onsets of which are interpreted as P and S waves by the authors. Further, we show that if these events were interpreted as genuine marsquakes, their inferred epicentral distance distribution would not match typical marsquake distances, while their magnitudes would make them the largest events of the catalogue. For future studies that deal with seismic event detection and interpretation from InSight, we recommend a careful consideration of the established event and noise signal markers described in this comment and in the literature to avoid misinterpretation of noise as event signals.