Kristin S. Vogfjord

P wave velocity of Proterozoic upper mantle beneath central and southern Asia

P wave velocity structure of Proterozoic upper mantle beneath central and southern Africa was investigated by forward modeling of Pnl waveforms from four moderate size earthquakes. The source-receiver path of one event crosses central Africa and lies outside the African superswell while the source-receiver paths for the other events cross Proterozoic lithosphere within southern Africa, inside the African superswell. Three observables (Pn waveshape, PL-Pn time, and Pn/PL amplitude ratio) from the Pnl waveform were used to constrain upper mantle velocity models in a grid search procedure. For central Africa, synthetic seismograms were computed for 5880 upper mantle models using the generalized ray method and wavenumber integration; synthetic seismograms for 216 models were computed for southern Africa. Successful models were taken as those whose synthetic seismograms had similar waveshapes to the observed waveforms, as well as PL-Pn times within 3 s of the observed times and Pn/PL amplitude ratios within 30% of the observed ratio. Successful models for central Africa yield a range of uppermost mantle velocity between 7.9 and 8.3 km s−1, velocities between 8.3 and 8.5 km s−1 at a depth of 200 km, and velocity gradients that are constant or slightly positive. For southern Africa, successful models yield uppermost mantle velocities between 8.1 and 8.3 km s−1, velocities between 7.9 and 8.4 km s−1 at a depth of 130 km, and velocity gradients between −0.001 and 0.001 s−1. Because velocity gradients are controlled strongly by structure at the bottoming depths for Pn waves, it is not easy to compare the velocity gradients obtained for central and southern Africa. For central Africa, Pn waves turn at depths of about 150–200 km, whereas for southern Africa they bottom at ∼100–150 km depth. With regard to the origin of the African superswell, our results do not have sufficient resolution to test hypotheses that invoke simple lithospheric reheating. However, our models are not consistent with explanations for the African superswell invoking extensive amounts of lithospheric thinning. If extensive lithospheric thinning had occurred beneath southern Africa, as suggested previously, then upper mantle P wave velocities beneath southern Africa would likely be lower than those in our models.

AN ANALYSIS OF THE NONLINEAR MAGMA‐EDIFICE COUPLING AT GRIMSVÖTN VOLCANO (ICELAND)

Continuous monitoring of seismicity and surface displacement of active volcanoes can reveal important features of the eruptive cycle. Here, high-quality GPS and earthquake data recorded at Grimsvotn volcano by the Icelandic Meteorological Office during the 2004-2011 inter-eruptive period are analyzed. These showed a characteristic pattern, with an initial ∼2-year-long exponential decay followed by ∼3-year-long constant surface-displacement inflation rate. We model it by using a one magma-reservoir model in an elastic damaging edifice, with incompressible magma and constant pressure at the base of the magma conduit. Seismicity rate and damage were first modeled, and simple analytical expressions were derived for the magma reservoir overpressure and surface displacement as functions of time. Very good fits of the seismicity and surface displacement data were obtained by fitting only three phenomenological parameters. Characteristic time and power strain show maxima from which reference times were inferred that split the inter-eruptive period into five periods. After the pressurization periods, damage occurring in the third period induced weakly nonlinear variations in magma overpressure and flow, and surface displacement. During the fourth period, the damage dominated and variations became more strongly nonlinear, the reservoir overpressure decreased and magma flow increased. This process lasted until the power strain reached its second maximum, where instability was generalized. This maximum is a physical limit, the occurrence of which shortly precedes rupture, and eventually eruption. This analysis allows characterization of the state of the volcanic edifice during the inter-eruptive period, and supports medium-term prediction of rupture and eruption.