Oceanic intraplate explosive eruptions fed directly from the mantle.

Constraining the volatile content of magmas is critical to our understanding of eruptive processes and their deep Earth cycling essential to planetary habitability [R. Dasgupta, M. M. Hirschmann, Earth Planet. Sci. Lett. 298, 1 (2010)]. Yet, much of the work thus far on magmatic volatiles has been dedicated to understanding their cycling through subduction zones. Further, studies of intraplate mafic volcanism have disproportionately focused on Hawaii [P. E. Wieser et al., Geochem. Geophys. Geosyst. 22, e2020GC009364 (2021)], making assessments of the overall role of intraplate volcanoes in the global volatile cycles a challenge. Additionally, while mafic volcanoes are the most common landform on Earth and the Solar System [C. A. Wood, J. Volcanol. Geotherm. Res. 7, 387-413 (1980)], they tend to be overlooked in favor of silicic volcanoes when it comes to their potential for explosivity. Here, we report primitive (olivine-hosted, with host Magnesium number - Mg# 78 to 88%) melt inclusion (MI) data from Fogo volcano, Cabo Verde, that suggest that oceanic intraplate silica-undersaturated explosive eruptions sample volatile-rich sources. Primitive MI (melt Mg# 70 to 71%) data suggest that these melts are oxidized (NiNiO to NiNiO+1) and very high in volatiles (up to 2 wt% CO2, 2.8 wt% H2O, 6,000 ppm S, 1,900 ppm F, and 1,100 ppm Cl) making Fogo a global endmember. Storage depths calculated from these high volatile contents also imply that magma storage at Fogo occurs at mantle depths (~20 to 30 km) and that these eruptions are fed from the mantle. Our results suggest that oceanic intraplate mafic eruptions are sustained from the mantle by high volatile concentrations inherited from their source and that deep CO2 exsolution (here up to ~800 MPa) drives their ascent and explosivity.

High-resolution precipitation monitoring with a dense seismic nodal array.

Accurate precipitation monitoring is crucial for understanding climate change and rainfall-driven hazards at a local scale. However, the current suite of monitoring approaches, including weather radar and rain gauges, have different insufficiencies such as low spatial and temporal resolution and difficulty in accurately detecting potentially destructive precipitation events such as hailstorms. In this study, we develop an array-based method to monitor rainfall with seismic nodal stations, offering both high spatial and temporal resolution. We analyze seismic records from 1825 densely spaced, high-frequency seismometers in Oklahoma, and identify signals from nine precipitation events that occurred during the one-month station deployment in 2016. After removing anthropogenic noise and Earth structure response, the obtained precipitation spatial pattern mimics the one from a nearby operational weather radar, while offering higher spatial (~ 300 m) and temporal (< 10 s) resolution. We further show the potential of this approach to monitor hail with joint analysis of seismic intensity and independent precipitation rate measurements, and advocate for coordinated seismological-meteorological field campaign design.