Automated swirl detection algorithm (ASDA) and its application to simulation and observational data

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 pixel size of 39.2 km sampled by the Solar Optical Telescope on board Hinode suggests a total number of 1.62 × 105 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 analyzed properties between counterclockwise or clockwise rotating swirls. About 70% of swirls are located in intergranular lanes. Most of the swirls have lifetimes of less than twice 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 insight.