Estimate of the regularly gridded 3D vector flow field from a set of tomographic maps

TL;DR

The paper presents a method to reconstruct a regularly gridded 3D vector flow field from tomographic maps obtained via time-distance inversions, addressing the smoothing effect of averaging kernels.

Contribution

It introduces and validates an algorithm to derive true flow fields on a uniform grid from smoothed tomographic data, including noise handling.

Findings

Effective reconstruction of flow fields demonstrated with synthetic data

Method accounts for noise and smoothing effects

Provides a tool for better flow field analysis in plasma studies

Abstract

Time--distance inversions usually provide tomographic maps of the interesting plasma properties (we will focus on flows) at various depths. These maps however do not correspond directly to the flow field, but rather to the true flow field smoothed by the averaging kernels. We introduce a method to derive a regularly gridded estimate of the true velocity field from the set of tomographic maps. We aim mainly to reconstruct the flow on a uniform grid in the vertical domain. We derive the algorithm, implement it and validate using synthetic data. The use of the synthetic data allows us to investigate the influence of random noise and to develop the methodology to deal with it properly.