Automated Swirl Detection Algorithm (ASDA) and Its Application to Simulation and Observational Data

Abstract

Swirling motions in the solar atmosphere have been widely observed in recent years and suggested to play a key role in channeling energy from the photosphere into the corona. Here, we present a newly-developed Automated Swirl Detection Algorithm (ASDA) and discuss its applications. ASDA is found to be very proficient at detecting swirls in a variety of synthetic data with various levels of noise, implying our subsequent scientific results are astute. Applying ASDA to photospheric observations with a spatial resolution of 39.2 km sampled by the Solar Optical Telescope (SOT) on-board Hinode, suggests a total number of 1.62 × 10 5 swirls in the photosphere, with an average radius and rotating speed of ∼ 290 km and < 1.0 km s −1 , respectively. Comparisons between swirls detected in Bifrost numerical MHD simulations and both ground-based and space-borne observations, suggest that: 1) the spatial resolution of data plays a vital role in the total number and radii of swirls detected; and 2) noise introduced by seeing effects could decrease the detection rate of swirls, but has no significant influences in determining their inferred properties. All results have shown that there is no significant difference in the analysed properties between counter-clockwise or clockwise rotating swirls. About 70% of swirls are located in intergranular lanes. Most of the swirls have lifetimes less than twice of the cadences, meaning future research should aim to use data with much higher cadences than 6 s. In the conclusions, we propose some promising future research applications where ASDA may provide useful insights.

Evidence of ubiquitous Alfvén pulses transporting energy from the photosphere to the upper chromosphere

“…2 and 3). This is consistent with the fact that more photospheric swirls were detected by the SOT observations than by the SST observations 14 . It is likely that the discrepancy in numbers of swirls detected based on the SOT and SST datasets was caused by the fact that SST data have lower cadence and spatial resolution than the SOT data, and also may suffer from residual seeing effects which were not corrected for during data processing.…”

“…The distribution of swirl lifetimes (Fig. 2d) is similar to that of the photospheric swirls 14 . The number of swirls drops nearly exponentially with increasing lifetime, with an average lifetime of ~21 s and maximum likelihood estimation 17 of the exponential rate parameter of ~0.05.…”

“…Based on the results obtained in this article, we propose future work that should be focused on to discover the complete energy channelling scenario by swirls in the solar atmosphere: given that both swirls and spicules 21,22 , are mostly located in inter-granular lanes 14,23 , our proposed conjecture is that swirls could also excite spicules through linear (e.g., linear Lorentz force) and/or non-linear (e.g., non-linear Alfvén pulses) processes to supply both momentum and energy into the chromosphere and corona.…”

“…We applied the automated swirl detection algorithm (ASDA) 14 to photospheric observations with a pixel size of ~39.2 km sampled by the Solar Optical Telescope (SOT) onboard the Hinode satellite 15 , and found on average 21.5 photospheric swirls in each frame with a FOV of ~800 Mm 2 (suggesting a swirl population of ~1.6 × 10 5 in the photosphere). These swirls had an average radius and rotating speed of ~290 and ~0.9 km s −1 , respectively.…”

Unveiling the magnetic nature of chromospheric vortices

“…Bonet et al 2010;Attie et al 2009;Vargas Domínguez et al 2011;Wedemeyer-Böhm et al 2012;Wedemeyer-Böhm & Rouppe van der Voort 2009;Tziotziou et al 2018). Quiet-Sun photospheric vortices have a typical size of 0.5−2 Mm and a mean lifetime up to 15 min (Bonet et al 2010;Wedemeyer et al 2013;Liu et al 2019a). There are estimated to be 3.1 × 10 −3 photospheric vortices Mm −2 min −1 (Bonet et al 2010;Vargas Domínguez et al 2011).…”