[S18-1] Inner core structure and dynamics

[S18-1-06] Studies of inner core anisotropy from noise interferometry

^○Xiaodong Song¹, Tao Wang², Han Xia^1,2 (1.University of Illinois, Champaign, USA, 2.Nanjing University, Nanjing, China)

Studies of the inner core have relied on body waves (mainly PKP) and core-sensitive normal modes generated by strong earthquakes. Despite the complex pattern of the inner core anisotropy, it's shown to be predominantly cylindrically symmetric with the symmetry (fast) axis parallel to the Earth's spin axis from earthquake data. However, we recently found that the fast axis in the inner part of the inner core (IIC) is close to the equator from inner-core waves (PKIKP2 and PKIIKP2 phases) extracted from autocorrelations of earthquake coda (Wang et al., 2015). To confirm the equatorial IIC anisotropy, we examined stations at low latitudes (within ±35º), which reduces the influence of the polar anisotropy and possible contamination from the large Fresnel zones. Using a number of improved procedures of both autocorrelation and cross-correlation, we extracted high-quality empirical Green's functions at 52 globally distributed arrays. We observed large variations (up to nearly 11 s) between the PKIKP2 and PKIIKP2 phases and the pattern matches very well previous IIC model, providing further support for the equatorial anisotropy model of the IIC. Separately, earthquake-generated PKP differential travel times have been instrumental in mapping the inner core anisotropy. We found that triplicated PKP phases can be extracted from the stacks of station–station correlations (Xia et al., 2016). Both ambient noise and earthquake coda contribute to the PKP phases. However, the contributions vary with frequency and with body-wave phases. At shorter periods (5–20 s), three branches of PKP (df, bc and ab) can be extracted from ambient noise and the ab phase from earthquake coda. At longer periods (15–50 s), earthquake coda are effective in generating the df branch, but not the ab branch. The usefullness of the new type of data remains to be explored, but it's likely to complement the limited distribution of earthquake data with certain critical samplings.