Hypocenter Determination and Clustering of Volcano-tectonic Earthquakes in Gede Volcano 2015

Gede volcano is an active volcano in West Java, Indonesia. Research about determination the volcano-tectonic earthquake source positions has given results using volcano-tectonic earthquakes data from January until November 2015. Volcano-tectonic earthquakes contained deep (VT-A) have frequency (maximum amplitude) range 5 – 15 Hz. Furthermore, they contain shallow earthquake, VT-B have range 3-5 Hz and LF have range 1-3 Hz. Geiger's Adaptive Damping (GAD) methods used for determining the hypocenter of these volcano-tectonic (VT) events. Hypocenter distribution divided into 4 clusters. Cluster I located in the crater of Gede volcano dominated by VT-B earthquakes their depth range 2 km below MSL to 2 km above MSL including the VT-B swarm. The seismic sources in cluster I indicated dominant due to the volcanic fluid or gas filled in conduit pipes. Cluster II located at the west of Gede volcano caused by Gede-Pangrango fault-line dominated by VT-A earthquakes with depths range 1.5 km below MSL to 700 m above MSL. Cluster III located in the North of Gede volcano dominated by VT-A events there caused by graben fault area with those depths range 7.5 – 1.65 km below MSL. Cluster IV located in South West of Gede volcano contained VT-A earthquakes with depth range at 10 km below MSL and VT-B earthquakes this depth 2 km below MSL. Due to magma intrusion filled into fractures of the fault in the West of Gede volcano this shallow magma filling-fractures and degassing in subsurface assumed dominates the volcano-tectonic events from January to November 2015 due to faults extends from North to South occured in the West of Gede volcano

Application of Volcano Plots in Analyses of mRNA Differential Expressions with Microarrays

Volcano plot displays unstandardized signal (e.g. log-fold-change) against noise-adjusted/standardized signal (e.g. t-statistic or -log10(p-value) from the t test). We review the basic and an interactive use of the volcano plot, and its crucial role in understanding the regularized t-statistic. The joint filtering gene selection criterion based on regularized statistics has a curved discriminant line in the volcano plot, as compared to the two perpendicular lines for the "double filtering" criterion. This review attempts to provide an unifying framework for discussions on alternative measures of differential expression, improved methods for estimating variance, and visual display of a microarray analysis result. We also discuss the possibility to apply volcano plots to other fields beyond microarray.Comment: 8 figure

Models of Hawaiian volcano growth and plume structure: Implications of results from the Hawaii Scientific Drilling Project

The shapes of typical Hawaiian volcanoes are simply parameterized, and a relationship is derived for the dependence of lava accumulation rates on volcano volume and volumetric growth rate. The dependence of lava accumulation rate on time is derived by estimating the eruption rate of a volcano as it traverses the Hawaiian plume, with the eruption rate determined from a specified radial dependence of magma generation in the plume and assuming that a volcano captures melt from a circular area centered on the volcano summit. The timescale of volcano growth is t = 2 R/ν_plate where R is the radius of the melting zone of the (circular) plume and νplate is the velocity of the Pacific plate. The growth progress of a volcano can be described by a dimensionless time t′ = tν_plate/2R, where t′ = 0 is chosen to be the start of volcano growth and t′ = 1 approximates the end of “shield” growth. Using a melt generation rate for the whole plume of 0.2 km^(3)/yr, a plume diameter of 50 km, and a plate velocity of 10 cm/yr, we calculate that the lifetime of a typical volcano is 1000 kyr. For a volcano that traverses the axis of the plume, the “standard” dimensions are a volume of 57,000 km^3, a summit thickness of 18 km, a summit elevation of 3.6 km, and a basal radius of 60 km. The volcano first breaches the sea surface at t′ ≈ 0.22 when it has attained only 5% of its eventual volume; 80% of the volume accumulates between t′ = 0.3 and t′ = 0.7. Typical lava accumulation rates start out over 50 m/kyr in the earliest stages of growth from the seafloor, and level out at ∼35 m/kyr from t′ ≈ 0.05 until t′ = 0.4. From t′ = 0.4 to t′ = 0.9, the submarine lava accumulation rates decrease almost linearly from 35 m/kyr to ∼0; subaerial accumulation rates are about 30% lower. The lava accumulation rate is a good indicator of volcano age. A volcano that passes over the plume at a distance 0.4R off to the side of the plume axis is predicted to have a volume of about 60% of the standard volcano, a lifetime about 8% shorter, and lava accumulation rates about 15–20% smaller. The depth-age data for Mauna Kea lavas cored by the Hawaii Scientific Drilling Project are a good fit to the model parameters used, given that Mauna Kea appears to have crossed the plume about 15–20 km off-axis. The lifetime of Mauna Kea is estimated to be 920 kyr. Mauna Loa is predicted to be at a stage corresponding to t′ ≈ 0.8, Kilauea is at t′ ≈ 0.6, and Loihi is at t′ ≈0.16. The model also allows the subsurface structure of the volcanoes (the interfaces between lavas from different volcanoes) to be modeled. Radial geochemical structure in the plume may be blurred in the lavas because the volcanoes capture magma from a sizeable cross-sectional area of the plume; this inference is qualitatively born out by available isotopic data. The model predicts that new Hawaiian volcanoes are typically initiated on the seafloor near the base of the next older volcano but generally off the older volcano's flank

Geology of Tindfjallajökull volcano, Iceland

The geology of Tindfjallajökull volcano, southern Iceland, is presented as a 1:50,000 scale map. Field mapping was carried out with a focus on indicators of past environments. A broad stratocone of interbedded fragmental rocks and lavas was constructed during Tindfjallajökull’s early development. This stratocone has been dissected by glacial erosion and overlain by a variety of mafic to silicic volcanic landforms. Eruption of silicic magma, which probably occurred subglacially, constructed a thick pile of breccia and lava lobes in the summit area. Mafic to intermediate flank eruptions continued through to the end of the last glacial period, producing lavas, hyaloclastite-dominated units and tuyas that preserve evidence of volcano-ice interactions. The Thórsmörk Ignimbrite, a regionally important chronostratigraphic marker, is present on the SE flank of the volcano. The geological mapping of Tindfjallajökull gives insights into the evolution of stratovolcanoes in glaciated regions and the influence of ice in their development

Predictability of Volcano Eruption: lessons from a basaltic effusive volcano

Volcano eruption forecast remains a challenging and controversial problem despite the fact that data from volcano monitoring significantly increased in quantity and quality during the last decades.This study uses pattern recognition techniques to quantify the predictability of the 15 Piton de la Fournaise (PdlF) eruptions in the 1988-2001 period using increase of the daily seismicity rate as a precursor. Lead time of this prediction is a few days to weeks. Using the daily seismicity rate, we formulate a simple prediction rule, use it for retrospective prediction of the 15 eruptions,and test the prediction quality with error diagrams. The best prediction performance corresponds to averaging the daily seismicity rate over 5 days and issuing a prediction alarm for 5 days. 65% of the eruptions are predicted for an alarm duration less than 20% of the time considered. Even though this result is concomitant of a large number of false alarms, it is obtained with a crude counting of daily events that are available from most volcano observatoriesComment: 4 pages, 4 figure

Sensitivity to lunar cycles prior to the 2007 eruption of Ruapehu volcano

A long-standing question in Earth Science is the extent to which seismic and volcanic activity can be regulated by tidal stresses, a repeatable and predictable external excitation induced by the Moon-Sun gravitational force. Fortnightly tides, a similar to 14-day amplitude modulation of the daily tidal stresses that is associated to lunar cycles, have been suggested to affect volcano dynamics. However, previous studies found contradictory results and remain mostly inconclusive. Here we study how fortnightly tides have affected Ruapehu volcano (New Zealand) from 2004 to 2016 by analysing the rolling correlation between lunar cycles and seismic amplitude recorded close to the crater. The long-term (similar to 1-year) correlation is found to increase significantly (up to confidence level of 5-sigma) during the similar to 3 months preceding the 2007 phreatic eruption of Ruapehu, thus revealing that the volcano is sensitive to fortnightly tides when it is prone to explode. We show through a mechanistic model that the real-time monitoring of seismic sensitivity to lunar cycles may help to detect the clogging of active volcanic vents, and thus to better forecast phreatic volcanic eruptions