Tracking granules at the Sun's surface and reconstructing velocity fields. II. Error analysis
R. Tkaczuk, M. Rieutord, N. Meunier, T. Roudier

TL;DR
This paper evaluates the impact of atmospheric noise on tracking solar granules to measure surface velocity fields, recommending filtering techniques and optimal sampling to improve accuracy.
Contribution
It demonstrates that k-omega filtering and granule lifetime thresholds significantly reduce errors in velocity measurements from ground-based solar observations.
Findings
k-omega filtering effectively reduces noise
Granule lifetime thresholds improve velocity accuracy
Sampling every 21 seconds is insufficient due to residual distortion
Abstract
The determination of horizontal velocity fields at the solar surface is crucial to understanding the dynamics and magnetism of the convection zone of the sun. These measurements can be done by tracking granules. Tracking granules from ground-based observations, however, suffers from the Earth's atmospheric turbulence, which induces image distortion. The focus of this paper is to evaluate the influence of this noise on the maps of velocity fields. We use the coherent structure tracking algorithm developed recently and apply it to two independent series of images that contain the same solar signal. We first show that a k-\omega filtering of the times series of images is highly recommended as a pre-processing to decrease the noise, while, in contrast, using destretching should be avoided. We also demonstrate that the lifetime of granules has a strong influence on the error bars of…
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