This is a 3-year proposal focused on providing better images of short-wavelength heterogeneity in the Earth?fs deep mantle by analyzing large quantities of seismicly reflected waves. This research continues the PI?fs postdoctoral work that generated new high-resolution maps of discontinuity topography for the mantle transition zone. The proposal requests 3 years in order to rigorously and thoroughly evaluate a large data volume with abundant, but difficult to analyze low signal-to-noise data.
In this study, the PI proposes to improve upon his previous stacking-inversion method for the mantle transition zone [Lawrence and Shearer, 2008] by 1) improving the imaging technique with non-uniform and multiple grid inversion analyses, and 2) incorporating more data and data types to enhance data coverage. This study will also augment the technique to evaluate topography on a deeper set of interfaces associate with the D?? layer at the core mantle boundary.
Further analysis of reflected waves in the mantle will determine if a possible discontinuity at ~1100 km depth is robust, and independently confirmed with complementary data sets. If the interface is robust, geographical analysis will determine if the interface is a global or regional observation. Further analysis will also investigate the possibility of other, previously undiscovered horizontal, tilted, and/or semi-vertical discontinuities in the mantle. The verification of a new regional or global discontinuity would have major impacts on fields ranging from mineral physics and seismology to convection modeling and geochemistry.
We examined the interfaces at about 410 and 660 km depth within the Earth using seismic waves that reflect off these boundaries. Due to temperature and pressure conditions within the Earth, these boundaries are shallower or deeper at different locations. The project used SS precurors, waves that arrive before the SS wave because they reflect off the interface at greater depth. The exact delay time tells us exactly how deep the interface is at the location of reflection. We mapped out these reflections with higher resolution than was previously possible due to the massive increase in data available over the past decade. The new data fills in many gaps in reflection bounce points. This was a large undertaking. The new data was much larger than all prior data examined. We developed new automated techniques to keep good data and reject bad data. We also created new automated techniques to determine if a stack is stable or not. The new stacks have higher signal to noise, represent a smaller region of reflection, and are more stable than prior stacks. We were able to be more judicial with quality control than previous studies. The resultant tomographic images show a similar pattern to prior results, but with less short-wavelength variation. Some of the prior short-wavelength variation was likely due to noise or bias in the stacks. Nevertheless, the new tomographic images look highly similar to what was found before.
