A Three Dimensional Radially Anisotropic Model of Shear Velocity in the Whole Mantle

Mark Panning (now at Princeton) and Barbara Romanowicz


The 3D seismic velocity structure of the Earth's mantle represents a snapshot of its current thermal and chemical state. As tomographic models of the isotropic seismic velocity converge in their main features (Masters et al., 2000; Mégnin and Romanowicz, 2000; Ritsema and van Heijst, 2000; Gu et al., 2001), geodynamicists can use them to infer the density structure, and thus the buoyancy contrasts which drive mantle convection. This process, however, is complicated by the difficulty of separating thermal and chemical contrasts, and the lack of direct sensitivity of seismic velocities to the density contrasts which drive the convection.

In many regions of the mantle, analyzing the anisotropy of seismic velocities can give us another constraint on mantle dynamics. Random orientations of the anisotropic minerals which make up the mantle tend to cancel out on the macroscopic scale observable by seismic waves, unless crystals or materials with strongly contrasting elastic properties are aligned through deformation processes. While in the relatively cold regions of the lithosphere these anisotropic signatures can remain frozen in over geologic time-scales (Silver, 1996), observed anisotropy at greater depths likely requires dynamic support (Vinnik et al., 1992). Thus, the anisotropy observed at sub-lithospheric depths is most likely a function of the current mantle strain field, and these observations can help us map out mantle flow.

Model results

We have developed a 3D radially anisotropic S velocity model of the whole mantle (SAW642AN; Panning and Romanowicz, 2006), obtained using a large three component surface and body waveform dataset and an iterative inversion for structure and source parameters based on Nonlinear Asymptotic Coupling Theory (NACT) (Li and Romanowicz, 1995). The model is parameterized in level 4 spherical splines, which have a spacing of $\sim $800 km. The model shows a link between mantle flow and anisotropy in a variety of depth ranges.

In the uppermost mantle, we confirm previous observations of regions with $V_{SH}>V_{SV}$ starting at $\sim $80 km under oceanic regions and $\sim $200 km under stable continental lithosphere (Gung et al., 2003), suggesting horizontal flow beneath the lithosphere (figure 33.1). We also observe a $V_{SV}>V_{SH}$ signature at $\sim $150-300 km depth beneath major ridge systems with amplitude correlated with spreading rate for fast-spreading segments. In the transition zone (400-700 km depth), regions of subducted slab material are associated with $V_{SV}>V_{SH}$ (figure 33.2), while the ridge signal decreases. We also confirm the observation of radially symmetric $V_{SH}>V_{SV}$ in the lowermost 300 km (Panning and Romanowicz, 2004). The 3D deviations from this signature (figure 33.3) are associated with the large-scale low-velocity superplumes under the central Pacific and Africa, suggesting that $V_{SH}>V_{SV}$ is generated in the predominant horizontal flow of a mechanical boundary layer, with a change in signature related to transition to upwelling at the superplumes.

Figure 33.1: Comparison between SAW642AN $\xi $ (A-C) and the upper mantle $\xi $ calculated from SAW16AN (Gung et al., 2003) (D-F) at depths of 100 (top), 200 (middle), and 300 km (bottom).
\epsfig{file=panning06-2-1.eps, width=8cm}\end{center}\end{figure}

Figure 33.2: $\xi $ structure at depths 400-700 km (top two rows) and $V_S$ at depths of 400 and 600 km (third row). The bottom row shows the density anomalies for layers centered at depths of 362.5 km (left) and 652.5 km (right) for the model of Lithgow-Bertelloni and Richards (1998), normalized to the maximum density anomaly in each depth range.
\epsfig{file=panning06-2-2.eps, width=8cm}\end{center}\end{figure}

Figure 33.3: $V_S$ (A,B) and $\xi $ structure (C,D) at a depth of 2800 km centered under the central Pacific (A,C) and Africa (B,D)
\epsfig{file=panning06-2-3.eps, width=8cm}\end{center}\end{figure}


This research was supported by NSF grant EAR-0308750.


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