Finite-frequency Sensitivity Kernels in Spherical Geometry for Time–Distance Helioseismology
The inference of internal properties of the Sun from surface measurements of wave travel times is the goal of time–distance helioseismology. A critical step toward the accurate interpretation of shifts in travel time is the computation of sensitivity functions linking seismic measurements to internal structure. Here we calculate finite-frequency sensitivity kernels in spherical geometry for two-point measurements of travel time. We numerically build Green’s function by solving for it at each frequency and each degree of spherical harmonic and summing over all these pieces. These computations are performed in parallel (“embarrassingly”), thereby achieving significant speedup in wall-clock time. Kernels are calculated by invoking the first-order Born approximation connecting deviations in the wave field to perturbations in the operator. Validated flow kernels are shown to produce travel times within 0.47% of the true value for uniform flows up to 750 m s{sup −1}. We find that travel time can be obtained with errors of 1 ms or less for flows having magnitudes similar to meridional circulation. Alongside flows, we also compute and validate a sensitivity kernel for perturbations in sound speed. These accurate sensitivity kernels might improve the current inferences of subsurface flows significantly.