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. Halo displays, in particular the 22∘ halo, havebeen captured in long time series of images obtained from total sky imagers(TSIs) at various Atmospheric Radiation Measurement (ARM) sites. Halodisplays form if smooth-faced hexagonal ice crystals are present in theoptical path. We describe an image analysis algorithm for long time seriesof TSI images which scores images with respect to the presence of22∘ halos. Each image is assigned an ice halo score (IHS) for22∘ halos, as well as a photographic sky type (PST), whichdifferentiates cirrostratus (PST-CS), partially cloudy (PST-PCL), cloudy(PST-CLD), or clear (PST-CLR) within a near-solar image analysis area. Thecolor-resolved radial brightness behavior of the near-solar region is usedto define the discriminant properties used to classify photographic sky typeand assign an ice halo score. The scoring is based on the tools ofmultivariate Gaussian analysis applied to a standardized sun-centered imageproduced 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 haloobservations and photographic sky type for the first 4 months of the year2018, for TSI images obtained at the Southern Great Plains (SGP) ARM site. Adetailed comparison of visual and algorithm scores for the month of March 2018 shows that the algorithm is about 90 % reliable in discriminating thefour photographic sky types and identifies 86 % of all visual haloscorrectly. Numerous instances of halo appearances were identified for theperiod January through April 2018, with persistence times between 5 and 220 min. Varying by month, we found that between 9 % and 22 % ofcirrostratus skies exhibited a full or partial 22∘ halo.

Analysis algorithm for sky type and ice halo recognition in all-sky images