Small-Scale and Transient EUV Kernels in Solar Flare Ribbons

Abstract

Flare ribbons form when energy released by coronal magnetic reconnection is deposited in the low solar atmosphere, so by studying the dynamics of flare ribbons, one obtains an indirect measurement of reconnection. Our aim is to quantify the spatial and temporal scales of substructures in the Extreme Ultraviolet (EUV) flare ribbons, known as kernels, as a probe of the spatial extent and duration of energy injection during the impulsive phase of solar flares. Unprecedented observations of an M2.5 GOES-class flare from the March 2024 major flare campaign of Solar Orbiter were used. These data were obtained at high-cadence in short-exposure mode with the Extreme Ultraviolet Imager's high-resolution telescope, HRI_EUV. Individual kernels were automatically identified using a classical computer vision algorithm. Size distributions of ribbon kernels were derived, and an average light curve of individual kernels was extracted. The EUV flare kernels were small ($\lesssim 60~\text{pixels} \approx 1~\text{Mm}^2$) and a significant fraction were unresolved at a plate scale of 135 km/pix. Furthermore, we derived surprisingly short EUV kernel heating times of less than a few seconds. The average profile exhibits a sharp rise of $1.7\pm0.3$ s from half-maximum, requiring an additional $2.3^{+0.7}_{-0.4}$ s to return to its reference value. Our findings indicate that approximately half of the kernels were unresolved in this flare, despite the enhanced angular resolution offered by Solar Orbiter's proximity to the Sun at 0.38 AU here. Furthermore, we show that energy was only injected in a localised region ($\lesssim 1~\text{Mm}^2$) of flare ribbons for less than a few seconds. These results necessitate an in-depth investigation into the implications of such small-scale and transient injections on the energy flux deposited in solar flares, and the resulting response of the solar atmosphere.

Figures (10)

• Figure 1: Figure showing the flaring active region observed by FSI and HRI$_{\mathrm{EUV}}~$ during the Solar Orbiter flare campaign on 2024-03-23 in log scale. The image on the right highlights the field of view of HRI$_{\mathrm{EUV}}~$ and the green box denotes the region of interest within the FOV of HRI that is studied in this work. The HRI$_{\mathrm{EUV}}~$ frame shows a normal exposure observation of the flare at the non-thermal peak time (23:41:14 UT). During the M2.5 GOES-class flare, the two bright flare ribbons were saturated in the normal exposure frames.
• Figure 2: Figure showing a normal exposure frame taken at 2024-03-23 23:40:10 UT ($\text{t}=0$) followed by six short-exposures and finally a normal exposure when the cycle repeated. The first and last frames highlight the saturation levels reached in the active region during the main flare energy release. The short-exposures highlight the small-scale of EUV kernels within the otherwise fully saturated flare ribbons. All colourmaps are linearly scaled, with the short-exposure frames normalised to the maximum intensity at $\text{t} = 14~\text{s}$ and the normal exposures scaled to the saturation value.
• Figure 3: Overview time profiles of the M2.5 GOES-class flare SOL2024-03-23T23:41. Panel a) shows the STIX light curves for the entire flare and panel b) shows a closer look at the high energy X-ray profiles (22-45 keV) compared to the 174 Å spatially integrated (over the ROI shown in Figure \ref{['fig:overview_ribbons']}), short-exposure time profile. The short-exposure EUV data was taken at $2~\text{s}$ cadence with $4~\text{s}$ gaps every 6 frames. The correspondence between hard X-ray and EUV emission is notable.
• Figure 4: Examples of kernels identified using the watershed method in two frames at 23:40:20 UT and 23:40:50 UT. The first row shows the raw data measured by HRI$_{\mathrm{EUV}}$. The second row shows the data after the $10\%~\text{I}_{\text{max}}$ threshold has been applied. Rows three and four show the labels that were output by the watershed segmentation method when a minimum marker separation of 4 and 3 pixels was used, respectively.
• Figure 5: Kernel size histograms showing the number of bright pixels identified in a kernel using the watershed method with two different thresholds applied to both the original and the "running difference" data. These distributions demonstrate that a significant fraction of kernels were unresolved and that the brightest kernels had sizes that were on the order of the instrument's PSF. The characterisation of faint kernels depends strongly on the threshold applied and their sizes are thus somewhat ambiguous. The vertical shaded area masks kernels whose size estimates are unreliable due to artificial shrinkage caused by data thresholding.