Tomographic inversion of S-SKS times for shear velocity heterogeneity in D″: Degree 12 and hybrid models

Differential travel times between 5 (or diffracted S) and SKS were measured to study the global distribution of shear wave velocity heterogeneity in the lowermost 250 km of the mantle (the D″ region). Commencing with -3000 S-SKS times with variable qualities, we minimize uneven path coverage by thinning redundantly sampled regions (e.g., the Fiji-Tonga to North America corridor) and collect additional data for sparsely sampled areas, especially in the Southern Hemisphere. About 1500 paths were retained, distributed to reconcile both high-density and homogeneous sampling. We compare (1) spherical harmonic and (2) equal-area block parameterizations of D″ shear velocity heterogeneity for identical minimum resolving lengths and mean model errors. We show that the two parameterizations result in indistinguishable patterns of heterogeneity and power distribution for resolution down to a block size of 4.5° × 4.5° and maximum spherical harmonic degree of 40. We demonstrate synthetically that a high-degree (L) inversion followed by a lower-degree (L_s) spherical harmonic synthesis effectively circumvents model contamination from expansion truncation effects. Tomographic inversion of this data set yields a global distribution of D″ heterogeneity robust up to degree 12. In our preferred model (L=40, L_s=12, rms ∼1%), surface hotspots and estimated lower mantle plume roots are located in or at edges of low-velocity regions (δV_s<-2%), for both the Atlantic-Indian low-velocity corridor as well as the low velocities beneath the central Pacific. Although the above parameterizations entail no intrinsic difference in resolvability, higher resolution is regionally achieved by removing the derived degree 12 model from the data then inverting the corrected residuals using 4.5°×4.5° blocks. This hybrid method prevents power loss at intermediate to long wavelengths from otherwise severe damping and recovers smaller-scale structure where constraints are better than the global average, such as beneath the Pacific and Eurasia. A synthetic recovery test yields resolvability maps that reflect both the path geometry and the quality of data, which help to identify robust features in both the degree 12 and the hybrid D″ models.