Abstract

Context. Several upcoming and proposed space missions, such as Solar Orbiter, will be limited in telemetry and thus require data compression. Aims. We test the impact of data compression on local correlation tracking (LCT) of time-series of continuum intensity images. We evaluate the effect of several lossy compression methods (quantization, JPEG compression, and a reduced number of continuum images) on measurements of solar differential rotation with LCT. Methods. We apply the different compression methods to tracked and remapped continuum intensity maps obtained by the Helioseismic and Magnetic Imager (HMI) onboard the Solar Dynamics Observatory. We derive 2D vector velocities using the local correlation tracking code FLCT and determine the additional bias and noise introduced by compression to differential rotation. Results. We find that probing differential rotation with LCT is very robust to lossy data compression when using quantization. Our results are severely affected by systematic errors of the LCT method and the HMI instrument. The sensitivity of LCT to systematic errors is a concern for Solar Orbiter.

Highlights

  • Local correlation tracking of granulation (LCT; November & Simon 1988) is an important method for measuring flows in the photosphere, such as supergranulation or large-scale flows

  • We evaluate the effect of several lossy compression methods on measurements of solar differential rotation with local correlation tracking (LCT)

  • We only looked at differential rotation and supergranulation, which does not need to be representative for LCT in general

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Summary

Introduction

Local correlation tracking of granulation (LCT; November & Simon 1988) is an important method for measuring flows in the photosphere, such as supergranulation or large-scale flows It will play a significant role in upcoming and proposed space missions, such as Solar Orbiter (Marsch et al 2000; Marsden & Müller 2011; Löptien et al 2015). The time lag between the intensity images used by the LCT code is increased, reducing the number of images. These two approaches allow us to obtain first estimates of the performance of these compression methods

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