The small-scale structure of photospheric convection retrieved by a deconvolution technique applied to Hinode/SP data

TL;DR

This study applies a deconvolution technique to Hinode/SP solar data to better resolve photospheric convection, revealing stronger flows consistent with simulations and improving understanding of solar granulation dynamics.

Contribution

The paper introduces a deconvolution method that enhances the detection of convective flows in solar photosphere data, aligning observations with numerical simulations.

Findings

Enhanced upflows and downflows after deconvolution

Flow amplitudes reach ±3.0 km/s at ~50 km height

Velocity distributions match numerical simulation results

Abstract

Solar granules are bright patterns surrounded by dark channels called intergranular lanes in the solar photosphere and are a manifestation of overshooting convection. Observational studies generally find stronger upflows in granules and weaker downflows in intergranular lanes. This trend is, however, inconsistent with the results of numerical simulations in which downflows are stronger than upflows through the joint action of gravitational acceleration/deceleration and pressure gradients. One cause of this discrepancy is the image degradation caused by optical distortion and light diffraction and scattering that takes place in an imaging instrument. We apply a deconvolution technique to Hinode/SP data in an attempt to recover the original solar scene. Our results show a significant enhancement in both, the convective upflows and downflows, but particularly for the latter. After deconvolution, the up- and downflows reach maximum amplitudes of -3.0 km/s and +3.0 km/s at an average geometrical height of roughly 50 km, respectively. We found that the velocity distributions after deconvolution match those derived from numerical simulations. After deconvolution the net LOS velocity averaged over the whole FOV lies close to zero as expected in a rough sense from mass balance.