[ Real-Time/High-Rate GPS
| Volcano Sources
| Crustal Loading
This is an overview of my broad research interest and respective projects
I have been working on over the last years (up to 2013). It is not exhaustive and
I am always interested to apply some of the techniques described here
to new problems, or learn something new to look at old data in a different
way. If you're interested in collaboration, send me an email!
Real-Time and high-rate GPS for Early Warning and Hazard Mitigation (top)
The work focusing on producing quality real-time GPS data for near instantaneous
hazard assessment and mitigation is an emerging field. It benefits tremendously
from high-rate (post-processed) GPS studies, as these identify worthwhile applications
at a high signal to noise ratio. Major areas of research involve earthquake early
warning and rapid response, eruption early warning and (near) real-time monitoring,
and tsunami monitoring. The problems in real-time applications are rather technical
as methods to reduce real-time noise must be developed, and strategies for handling and
analyzing the resulting large volumes of data in minimum time need to be adapted.
Currently, in my post-doc work, I focus on the integration of real-time GPS into an
existing seismic system for California. We want to enable reliable magnitude estimation
for large events (M>6.5), and rapid estimation of distributed slip along a fault. I use
simulated static offsets and real past events to test the system and estimate the
timing of warnings / rapid response.
I have been also exploring the use of sub-daily GPS for volcanic plume detection
at Redoubt and Okmok
volcanoes. Below I show an example for Redoubt.
Skyplot (or azimuth-elevation plot; code I used for plotting here
) of phase residuals per satellite for Redoubt stations RVBM and AC17.
The outer circle marks azimuths for the satellites and also indicates 0° of elevation above the horizon as seen from the
station. The two inner circles mark 30°, 60° of elevation. 90° of elevation is directly above the station.
Thin black lines indicate the tracks of the GPS satellites. The gray traces along these lines are
the time series of phase residuals (mismatch between recorded and modeled satellite signal phases) for this satellite.
The red sections indicate the eruption time from 14:00-14:40 UTC on April 4, 2009.
The volcano summit is about 6 km to the east of station RVBM and about 28 km southwest of site AC17.
The impact of the plume is clearly seen at satellite PRN 10 for RVBM, whereas AC17 shows no misfit for this
Volcanic Source Modeling (top)
Knowledge about the plumbing system of volcanoes is important for
hazard assessments and our general understanding of how these land
creators work. Geodetic data (InSAR, GPS, Leveling, Tilt, Gravity)
are phenomenal tools to infer knowledge about the plumbing
system of volcanoes. The results depend highly on the kind of volcano (open / closed system, magma
compressibility, ...), depth of the source and its volume change. The expected pattern, however, is that of
inflation of the edifice when the magma source is recharged and co-eruptive deflation; much
like a ballon.
Cycle of Volcano Deformation from unpressurized magma reservoir to overpressure and
associated inflation to eruption with lava flow and deflation (Background: Bezymianny
and Kamen with a bit of a plume from Klyuchevskoy in Kamchatka).
During my dissertation I was fortunate enough to conduct the first in-depth, GPS based
geodetic studies of Redoubt Volcano in
Alaska and Bezymianny Volcano in
Velocity field at Bezymianny volcano (horizontal: blue, vertical: red) for data
from August 2005-August 2010. Lower portion is blow-up of the black rectangle in the
regional map. Tectonics model (Bürgmann et al, 2005, indicated by grey rectangles in regional map)
is removed from data, horizontal is with respect to ES1. Note the wide ranging
subsidence signal in vertical and incoherent horizontal (Grapenthin et al., JVGR, 2013a
Co-eruptive displacement field (not velocity!) at Redoubt showing displacements
from March 22-April 4 2009 relative to a site about 100 km SW (horizontal: blue, vertical: red).
Note the horizontals pointing to the vent indicating the map location of the deflation source
(Grapenthin et al., JVGR, 2013b
Redoubt erupted in 2009 and was equipped with a small monitoring network. We found an interesting
aseismic pre-eruptive inflation period starting about 6 months before deep long period seismicity
was recorded. This magma pooled underneath residual mush from the previous eruption in 1989/90. Heat
and fluids percolating through this resulted in remobilization of the residual material.
The entire GPS network subsided and moved inward toward the volcano from the
summer of 2008 to summer of 2009 indicating that most of the material erupted was left over from the previous
Cartoon illustrating the evolution of the Redoubt Volcano plumbing system as suggested by geodetic,
seismic, and petrologic data. We tie deep seismicity (Power et al., 2013),
petrology (Coombs et al., 2013), and our observations together by proposing a two reservoir system
in the mid- to shallow crust. Material from 25 to 38 km migrated to about 13 km depth
beginning as early as May 2008; reheating and remobilizing residing material in a prolate
spheroid from 7 to 11.5 km. This resulted in migration to 2-4.5 km depth
(Coombs et al., 2013); supported by shallow seismic tremor beginning in January/February 2009
(Buurman et al., 2013). This material extruded from 23 March 2009 on. The mix of fresh and reheated
material from the deeper stages of the system replaced extruded material and made the shallow removal
undetectable by geodesy (Grapenthin et al., JVGR, 2013b
Over the 5 years of recording many small eruptions at Bezymianny we found only very small co-eruptive activity.
The interesting observation here is, however, that the entire network subsides at rates up to 15 mm/yr. Neither
subduction zone tectonics nor adjustment to volcanic loads seem to explain these observations. We infer that a
a deep deflating sill beneath Klyuchevskoy at ~33 km depth can induce a signal very similar to what we
record. However, to confirm this model, a much broader GPS network must be deployed.
Sill model (white rectangle, double line indicates down dip end) inferred from seismicity
below 22.5 km (black circles). Velocity predictions relative to ES1 for this model,
assuming a closing rate 0.22 m/yr for the sill, are shown as white (horizontal) and black (vertical) vectors.
(A) Continuous site BZ08 in summer of 2010. In the background: Kluchevskoy
with a small ash plume to the left, Kamen in the middle, and Bezymianny to the
right and degassing. (B) Campaign site BEZR with spike mount setup and Trimble
NetRS receiver in 2010. (C) Continuous site BZ06 with solar setup installed in 2010.
Bezymianny's dome steams in the background, which is the normal state.
(Grapenthin et al., JVGR, 2013a
Other studies, I was involved in focused, for example, on resolving a broad, dough-nut shaped, inflation pattern with central subsidence
in InSAR data at Hekla volcano, Iceland. While we explained the inflation with a deep magma chamber and the central subsidence with adjustment to lava loading,
other work suggests that a vertical cigar shaped model could induce the same pattern. Exciting stuff!
Crustal Loading Studies (top)
I have a great interest in how surface load dynamics
affect the state of the crust and reveal details of
the rheology of underlying materials, as well as how we can use
crustal dynamics to reconstruct past loading histories.
Conceptual model of an Earth-load-response-system.
The load (input, solid black rectangle) is applied to the pointed black line which represents the initial state of
the Earth's surface. The Earth (filter) responds to the mass force (little black arrows) through surface displacement,
changing its state to the one denoted by the solid black line (output). The load, however, may vary over time which is
denoted by a load history. At first it might raise to a maximum level which results in maximum displacement and then it could drop to a
minimum represented by the dashed gray lines that limit or extend the load box. Depending on the load history, the displacement
might alternate between the upper and the lower dashed, gray surface lines, linked to minimum and maximum load, respectively.
In addition to these elastic properties, another important property is that of time
dependent stress relaxation or material creep which is the adjustment to a new stress state by ductile material flow, which in the
depicted system is a filter property
(Grapenthin, Computers & Geosciences, 2014
As a visiting student in Iceland I worked on seasonal variations
in continuous GPS time series. We linked this signal to changes
in snow load on Iceland's major ice caps
(Grapenthin et al., 2006).
To facilitate this work, I wrote software that simulates the crustal response to
surface load changes. This code eventually turned into my
diploma thesis in computer science
(German M.Sc. equivalent) and has since been called CrusDe,
and developed quite a bit further (Grapenthin, 2013).
CrusDe's key capability is the implementation of an abstract relationship between Earth model and surface
load, which enables an easy (plug-in based) exchange of problem specific model realizations.
Some of my work uses CrusDe, for example, to address the bias surface loads (lava flows, glaciers)
can introduce in magma source inversions at volcanoes (Grapenthin et al.
2013). I am currently
working on including a spherical Earth geometry and, of course, applying it
to exciting loading problems.
A map of Iceland and its largest ice caps (V:
Vatnajökull, L: Langjökull, M: Myrdalsjökull, and H:
Hofsjökull). The red dots represent the CGPS stations in
Iceland's ISGPS network as in 2005 and used in this study.
The colors represent calculated absolute peak-to-peak
seasonal displacement due to maximum winter load
using E = 40 GPa. (a) Vertical displacement with a
peak of 37 mm under the center of Vatnajökull. (b) Vector
lengths of horizontal displacements with a maximum of
6 mm east and north of Vatnajökull (displacement towards
load during loading, opposite direction during unloading).
Comparison of predicted and observed results of
temporal modeling using a harmonic load at four CGPS stations:
HOFN, SAUD, SKRO, and SOHO, in east, north and up component
over the years 1999-2006. The detrended CGPS time series are
shown by green dots. The red line is the best fit to the time
series. The blue line is the modeled displacement using
E = 40 GPa. Time series, best fit, and modeled displacement are relative to station REYK.
(Grapenthin et al., GRL, 2006
| Last modified: December 16 2014 05:15.