Magma flow during volcanic eruptions causes surface deformation that can be used to constrain the location, geometry and internal pressure evolution of the underlying magmatic source 1 . The height of the volcanic plumes during explosive eruptions also varies with magma flow rate, in a nonlinear way 2,3 . In May 2011, an explosive eruption at Grímsvötn Volcano, Iceland, erupted about 0.27 km 3 denserock equivalent of basaltic magma in an eruption plume that was about 20 km high. Here we use Global Positioning System (GPS) and tilt data, measured before and during the eruption at Grímsvötn Volcano, to show that the rate of pressure change in an underlying magma chamber correlates with the height of the volcanic plume over the course of the eruption. We interpret ground deformation of the volcano, measured by geodesy, to result from a pressure drop within a magma chamber at about 1.7 km depth. We estimate the rate of magma discharge and the associated evolution of the plume height by differentiating the co-eruptive pressure drop with time. The time from the initiation of the pressure drop to the onset of the eruption was about 60 min, with about 25% of the total pressure change preceding the eruption. Near-real-time geodetic observations can thus be useful for both timely eruption warnings and for constraining the evolution of volcanic plumes.

[1] We find strong correlation between seasonal variation in CGPS time series and predicted response to annual snow load in Iceland. The load is modeled using Green's functions for an elastic halfspace and a simple sinusoidal load history on Iceland's four largest ice caps. We derive E = 40 ± 15 GPa as a minimum value for the effective Young's modulus in Iceland, increasing with distance from the Eastern Volcanic Zone. We calculate the elastic response over all of Iceland to maximum snow load at the ice caps using E = 40 GPa. Predicted annual vertical displacements are largest under the Vatnajökull ice cap with a peak-to-peak seasonal displacement of $37 mm. CGPS stations closest to the ice cap experience a peak-to-peak seasonal displacement of $16 mm, consistent with our model. East and north of Vatnajökull we find the maximum of annual horizontal displacements of $6 mm resulting in apparent modulation of plate spreading rates in this area. Citation: Grapenthin, R.,

Moment magnitudes for large earthquakes (M w ≥ 7.0) derived in real time from near-field seismic data can be underestimated due to instrument limitations, ground tilting, and saturation of frequency/amplitude-magnitude relationships. Real-time high-rate GPS resolves the buildup of static surface displacements with the S wave arrival (assuming nonsupershear rupture), thus enabling the estimation of slip on a finite fault and the event's geodetic moment. Recently, a range of high-rate GPS strategies have been demonstrated on off-line data. Here we present the first operational system for real-time GPS-enhanced earthquake early warning as implemented at the Berkeley Seismological Laboratory (BSL) and currently analyzing real-time data for Northern California. The BSL generates real-time position estimates operationally using data from 62 GPS stations in Northern California. A fully triangulated network defines 170+ station pairs processed with the software trackRT. The BSL uses G-larmS, the Geodetic Alarm System, to analyze these positioning time series and determine static offsets and preevent quality parameters. G-larmS derives and broadcasts finite fault and magnitude information through least-squares inversion of the static offsets for slip based on a priori fault orientation and location information. This system tightly integrates seismic alarm systems (CISN-ShakeAlert, ElarmS-2) as it uses their P wave detections to trigger its processing; quality control runs continuously. We use a synthetic Hayward Fault earthquake scenario on real-time streams to demonstrate recovery of slip and magnitude. Reanalysis of the M w 7.2 El Mayor-Cucapah earthquake tests the impact of dynamic motions on offset estimation. Using these test cases, we explore sensitivities to disturbances of a priori constraints (origin time, location, and fault strike/dip).