Crustal Thickness Variations Beneath the Western Indian Ocean Using Teleseismic P-Wave Coda Autocorrelations on Ocean-Bottom Seismic Data

Ali T S Saneesh, David Schlaphorst , Sandeep Gupta — Thu, 02 Jul 2026 00:00:00 -0400

The western Indian Ocean is a key region for investigating lithospheric evolution, as it records a complex interplay of tectonic, magmatic, and mantle processes. Constraining crustal thickness across this area is therefore essential for understanding how these processes interact and shape the region's geodynamic development. In this study, we apply teleseismic P-wave coda autocorrelation to map crustal thickness across the western Indian Ocean using data from 54 ocean-bottom seismometers (OBSs) and 7 land-based seismic stations. Our results reveal pronounced lateral variations in crustal thickness, ranging from ~4.3 km beneath young oceanic crust near the Central Indian Ridge (CIR) to ~25.85 km along the eastern margin of Madagascar. The oceanic domain exhibits a mean crustal thickness of ~7.01 ± 0.27 km, consistent with global oceanic averages. Volcanic islands within the Mozambique Channel show crustal thicknesses between ~11.21 and 23.98 km, whereas those in the Mascarene Basin display values of ~10.73 km and ~14.63 km. These localized zones of crustal thickening beneath volcanic islands likely reflect long-lived magmatic underplating and hotspot-related intrusions. Collectively, these findings provide new quantitative constraints on the tectono-magmatic processes that govern crustal formation, modification, and isostatic compensation in this geodynamically complex region.

Seismo-Acoustic Meteoroid Observation Recording Database (SMORD): A Global Dataset and Deep-Learning Phase Picker for Meteoroid-Generated Air-to-Ground Coupled Seismic Waves

Dario Eickhoff, Runa Ostermeier, Joachim Ritter — Fri, 03 Jul 2026 00:00:00 -0400

Meteoroids impacting Earth's atmosphere generate acoustic waves that can couple into the ground and can be recorded by dense, globally distributed seismic networks. Thus, these records complement optical and radar observations, especially since seismic stations also operate in cloudy weather conditions and during daytime. However, open datasets that link meteoroid events to labeled seismic waveforms are scarce, limiting the development of automated detectors for meteoroid-induced seismo-acoustic signals. We introduce the Seismo-acoustic Meteoroid Observation Recording Database (SMORD), compiled by cross-referencing public meteoroid catalogs (International Meteor Organization fireball reports; NASA CNEOS fireball catalog) with seismic archives. Continuous waveforms are manually labeled for the first clear meteoroid-related onset of air-to-ground coupled seismic waves using a three-level pick-quality scheme. SMORD v1.0 contains 310 meteoroid events and 3,295 labeled arrivals across a global station set. Using SMORD labels, we train a PhaseNet picker in SeisBench with station-level splits and augmentation. On test data, the model achieves 91% precision and 94% recall at a 0.5 decision threshold (area-under-curve value 0.89), with median absolute timing error of 0.02~s (90% within c. ±0.3 s). We demonstrate automated onset detection and trajectory reconstruction for an April 2025 Adriatic fireball, highlighting the values of SMORD for rapid post-event analysis.

Seismica

Crustal Thickness Variations Beneath the Western Indian Ocean Using Teleseismic P-Wave Coda Autocorrelations on Ocean-Bottom Seismic Data

Seismo-Acoustic Meteoroid Observation Recording Database (SMORD): A Global Dataset and Deep-Learning Phase Picker for Meteoroid-Generated Air-to-Ground Coupled Seismic Waves