Auxiliary Material
Three-dimensional seismic structure of a Mid-Atlantic Ridge
segment characterized by active detachment faulting (Trans-Atlantic
Geotraverse, 25°55'N-26°20'N)
Author names and affiliations
Minghui Zhao (mhzhao@scsio.ac.cn)
Key Laboratory of Marginal Sea Geology, South China Sea Institute of
Oceanology, Chinese Academy of Sciences, Guangzhou 510301, China
Phone: +86-20-89023192; Mob: 13560200916
Juan Pablo Canales (jpcanales@whoi.edu )
Woods Hole Oceanographic Institution, Woods Hole, Massachusetts 02543, USA
Phone: +1-508-289-2893;
Robert A Sohn (rsohn@whoi.edu )
Woods Hole Oceanographic Institution, Woods Hole, Massachusetts 02543, USA
Phone: +1-508-289-3616;
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S1. Random Initial Models
The 100 random 1D initial models were built by randomizing five parameters
defining a two-layer media: P-wave velocities at the top of the upper layer (seafloor), at
the interface between both layers, and at the bottom of the lower layer, and the
thicknesses of both layers. The five parameters were allowed to vary randomly within
certain predefined limits to avoid constructing unrealistic models (Auxiliary Figure S1).
The velocities at the seafloor, middle interface, and at the bottom of the model were
limited to 2–4 km/s, 5.3–7.3 km/s and 7.3–8.5 km/s, respectively. The thicknesses of both
layers were limited to be within 1–3 km and 7–9 km for the upper and lower layers,
respectively. For each Monte Carlo ensemble a 3D starting model was constructed by
draping the randomized 1D velocity model from the seafloor bathymetry.
S2. Model Uncertainty and Resolution Tests
We define statistical model uncertainty (Auxiliary Figure S2) as the standard
deviation of the 100 solutions. The central part of the preferred 3D model up to a depth of
4 km bsf (~8 km below sea level, bsl) is well constrained; velocities there have standard
deviation <0.2 km/s (Auxiliary Figure S2), smaller than the variance of the initial models
used in the Monte Carlo approach (Auxiliary Figure S1b). As expected, the edges of the
model have large uncertainties (>0.3 km/s) because of the lack of ray coverage in these
areas (Auxiliary Figure S2). Uncertainties in the well-constrained parts of the model are
generally <0.2 km/s, although the central part of the final model between 6 to 8 km bsl
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has somewhat larger uncertainties (0.2–0.3 km/s, Auxiliary Figure S2) due to a decreased
number of crossing rays.
We estimate model resolution by conducting checkerboard tests, which provide
information on the lateral and vertical resolution of a velocity model by examining the
ability to recover a synthetic velocity anomaly pattern superimposed on a background
velocity model [Zelt, 1998]. We built a perturbed velocity model by superimposing a 3D
sinusoidal velocity anomaly on a 1D model (Auxiliary Figure S1) with the magnitude of
10% background velocity. Synthetic travel times were generated by tracing rays through
the checkerboard model and then adding Gaussian random noise with a standard
deviation of 50 ms. The synthetic travel times were then used in an inversion using the
same parameters used in the true data inversion. We tested two checkerboard patterns
with sinusoidal functions with wavelengths of 20 and 10 km in the horizontal directions
(both with vertical wavelength of 4 km). Thus these checkerboard patterns allow us to
assess the inversion’s ability to resolve velocity anomalies of sizes 10102 km and
552 km, respectively (Auxiliary Figure S3).
The tests show that our inversion cannot constrain velocity variations at depths
greater than ~4 km bsf (8 km, bsl); thus we limit our interpretation of the velocity model
to structure above that level. Above a depth of 4 km bsf, features of 10 km in size are
well resolved along most of the central part of segment (Auxiliary Figure S3a, S3e, S3f),
but along the eastern and western sides of the model they can only be resolved in the
upper 2 km (<6 km bsl) and from -15≤Y≤5 km (Auxiliary Figure S3b, S3e, S3f). The
inversion can resolve features as small as 5 km in size at depths shallower than 2 km (<6
km bsl) along the central part of segment (-5≤X≤5 km and -25≤Y≤25 km, Auxiliary
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Figure S3c, S3d, S3g). At depths between 2–4 km bsf (6–8 km bsl), however, the
inversion can only resolve these smaller anomalies between -5≤X≤5 km and -15≤Y≤15
km, Auxiliary Figure S3c, S3d, S3h).
Auxiliary Figure S1. 100 randomized starting models. (a) 100 Monte Carlo ensembles
(blue lines) together with ensemble mean (red line). (b) Corresponding standard deviation
for the 100 starting models.
Auxiliary Figure S2. P-wave velocity uncertainties of the final model shown at crosssections through X=0 km and Y=0 km, and at depth slices at Z=0.5, 1.0, 2.0, and 4.0 km
bsf. Contours are drawn at 0.1 km/s interval.
Auxiliary Figure S3. Checker board tests. Results from two tests are shown: anomalies
with wavelengths of:(a, b, e, f) 20 km (lateral)×20 km (lateral)×4 km (vertical);(c, d, g, h)
with 10 km×10 km ×4 km. Recovered anomalies are shown for (a, c) X=0 km, (b, d) Y=0
km, (e, g) Z=5, and (f, h) Z=7 km. Horizontal sections for the case of smaller anomalies
in panels g and h show only the central part of the model with hypocenters from the
catalog of deMartin et al. [2007] (dots). Grid lines and yellow +/- symbols indicate the
sinusoidal synthetic velocity anomaly patterns, which are up to 10% in magnitude
relative to background velocity (mean of the 100 initial ensembles, Auxiliary Figure S1).
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