Abstract. Halo displays, in particular the 22∘ halo, have
been captured in long time series of images obtained from total sky imagers
(TSIs) at various Atmospheric Radiation Measurement (ARM) sites. Halo
displays form if smooth-faced hexagonal ice crystals are present in the
optical path. We describe an image analysis algorithm for long time series
of TSI images which scores images with respect to the presence of
22∘ halos. Each image is assigned an ice halo score (IHS) for
22∘ halos, as well as a photographic sky type (PST), which
differentiates cirrostratus (PST-CS), partially cloudy (PST-PCL), cloudy
(PST-CLD), or clear (PST-CLR) within a near-solar image analysis area. The
color-resolved radial brightness behavior of the near-solar region is used
to define the discriminant properties used to classify photographic sky type
and assign an ice halo score. The scoring is based on the tools of
multivariate Gaussian analysis applied to a standardized sun-centered image
produced from the raw TSI image, following a series of calibrations,
rotation, and coordinate transformation. The algorithm is trained based on a training set for each class of images. We present test results on halo
observations and photographic sky type for the first 4 months of the year
2018, for TSI images obtained at the Southern Great Plains (SGP) ARM site. A
detailed comparison of visual and algorithm scores for the month of March 2018 shows that the algorithm is about 90 % reliable in discriminating the
four photographic sky types and identifies 86 % of all visual halos
correctly. Numerous instances of halo appearances were identified for the
period January through April 2018, with persistence times between 5 and 220 min. Varying by month, we found that between 9 % and 22 % of
cirrostratus skies exhibited a full or partial 22∘ halo.
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