Poster abstract details

Plasma motions in the Sun cover a wide range of scales in time and space, from granulation to rotation. One of the main goals of helioseismology is to map internal motions in order to learn about convection, the global internal dynamics and the mechanism of the solar dynamo. We focus on inferrence of supergranular-scale flows on time scales of a day and more in upper 5 Mm of the convection zone. We demonstrate the performance and validation of linear OLA-type inversions for flows in time-distance helioseismology by considering solar-like artificial data. We show that the method is able to recover the given flow field within the predicted accuracy. Furthermore, we show that the leakage of the signal from horizontal components of the flow field into the vertical one causes serious difficulties when inverting for the vertical velocity component. To solve this issue, we have developed and tested the procedure of minimising this cross-talk effect. We demonstrate that reliable inversions of $v_z$ down to 4 Mm below the surface are possible with travel-time maps averaged over at least 24 hours.