Detecting and Characterising Small-Scale Brightenings in Solar Imaging Data
نویسندگان
چکیده
Abstract Observations of small-scale brightenings in the low solar atmosphere can provide valuable constraints on possible heating and heat transport mechanisms. We present a method for detection analysis brightenings, demonstrate its application to time-series imagery Interface Region Imaging Spectrograph (IRIS) extreme ultraviolet (EUV). The is based spatio-temporal band-pass filtering, adaptive thresholding centroid tracking, records an event’s spatial position, duration, total brightness maximum brightness. Spatial area, brightness, position are also recorded as functions time throughout lifetime. Detected fragment, or merge, over – thus number distinct regions constituting brightening event time, $N_{\mathit{frag}}$ N frag , which simple measure coherence complexity. A test made synthetic datacube composed static background IRIS data, Poisson noise $\approx 10^{4}$ ≈ 10 4 randomly-distributed, moving, Gaussian brightenings. Maximum duration follow power-law distributions, results show range successfully extract information. shows that reliable brightest most accurately detected events, with error 6%. Event speed generally underestimated by around 15% have uncertainty 20–30%. 30%, has 30%. Applying this real quiet-sun data spanning 19 minutes $54.40''\times 55.23''$ 54.40 ″ × 55.23 field view (FOV) yields 2997 detections, 1340 these detections either remain un-fragmented fragment two at least once during their lifetime ( $N_{\mathit{frag}}\le 2$ ≤ 2 ), equating density $3.96\times 10^{-4}$ 3.96 − arcsec −2 s −1 . will be used future large-scale statistical several (QS) sets from IRIS, other EUV imagers, types including H $\alpha $ α visible photospheric imagery.
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ژورنال
عنوان ژورنال: Solar Physics
سال: 2021
ISSN: ['1573-093X', '0038-0938']
DOI: https://doi.org/10.1007/s11207-021-01885-3