Abstract

SUMMARYWe present the first 16 months of data returned from a mobile array of 16 freely floating diving instruments, named mermaid for Mobile Earthquake Recording in Marine Areas by Independent Divers, launched in French Polynesia in late 2018. Our 16 are a subset of the 50 mermaid deployed over a number of cruises in this vast and understudied oceanic province as part of the collaborative South Pacific Plume Imaging and Modeling (SPPIM) project, under the aegis of the international EarthScope-Oceans consortium. Our objective is the hydroacoustic recording, from within the oceanic water column, of the seismic wavefield generated by earthquakes worldwide, and the nearly real-time transmission by satellite of these data, collected above and in the periphery of the South Pacific Superswell. This region, characterized by anomalously elevated oceanic crust and myriad seamounts, is believed to be the surface expression of deeply rooted mantle upwellings. Tomographically imaging Earth’s mantle under the South Pacific with data from these novel instruments requires a careful examination of the earthquake-to-mermaid traveltimes of the high-frequency P-wave detections within the windows selected for reporting by the discrimination algorithms on board. We discuss a workflow suitable for a fast-growing mobile sensor database to pick the relevant arrivals, match them to known earthquakes in global earthquake catalogues, calculate their traveltime residuals with respect to global seismic reference models, characterize their quality and estimate their uncertainty. We detail seismicity rates as recorded by mermaid over 16 months, quantify the completeness of our catalogue and discuss magnitude–distance relations of detectability for our network. The projected lifespan of an individual mermaid is 5 yr, allowing us to estimate the final size of the data set that will be available for future study. To prove their utility for seismic tomography we compare mermaid data quality against ‘traditional’ land seismometers and their low-cost Raspberry Shake counterparts, using waveforms recovered from instrumented island stations in the geographic neighbourhood of our floats. Finally, we provide the first analyses of traveltime anomalies for the new ray paths sampling the mantle under the South Pacific.

Highlights

  • The EarthScope-Oceans consortium was founded in 2016, and counts members from the US (Princeton and Stanford University, Incorporated Research Institutions for Seismology [IRIS] Seattle, DBV Technology North Kingstown, RI), Japan (Kobe University, Japan Agency for Marine-Earth Science and Technology [JAMSTEC], Earthquake Research Institute [ERI]), France (Géoazur Sophia Antipolis, École et Observatoire des Sciences de la Terre [EOST] Strasbourg, Institut Français de Recherche pour l’Exploitation de la Mer [IFREMER] Plouzané, OSEAN SAS Le Pradet), South Korea (Korea Institute of Geoscience and Mineral Resources [KIGAM] Daejeon), New Zealand (GNS Science, Te Pu Ao, Lower Hutt), the UK (Universities of Oxford and Bristol), and China (Southern University of Science and Technology [SUSTech], Shenzhen)

  • Quoted in the inset boxes are the corresponding signal-to-noise ratios (SNRs), defined to be the ratio of the maximum-likelihood estimates of the variances of the signal and noise segments, the “signal” being the segment after the AIC pick, and the “noise” the segment preceding it. This definition of the SNR is the same as that in the main text, the signal and noise segments are not—there, we focus on the first arrival within a single frequency band (1–5 Hz) and a short time window (30 s); here we consider the complete time series (⇠200–300 s) at each subspace projection (x1–x5) resulting in five SNRs per seismogram

  • We note that the picks shown here are not influenced by the edges, whose treatment we describe in Simon et al (2020), so users need not necessarily be wary of an arrival pick near an edge

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Summary

Introduction

The second step of the matching procedure involves manual review to sort the seismograms into two classes: “identified” and “unidentified.” Those in the former class will have been assessed to contain energies consistent with phase arrivals corresponding to known earthquakes in global seismic catalogs, both by visual inspection and by considering their travel-time residuals with respect to the AIC picks. Regardless, because of the agreement between the theoretical arrival time of the p wave corresponding to the largest event and the AIC picks at low scales (high frequencies) in Fig. S1, this seismogram would be counted among the identified category.

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