Abstract
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.
Highlights
Modeling and predicting the Earth’s climate is a challenge for physical science, even more so in light of the already observable changes in Earth’s climate system (Fasullo and Balmaseda, 2014; Fasullo et al, 2016; IPCC, 2013, 2014)
In order to manage comparison to a visual classification of these images, and to learn how both score sets behave in terms of numerical values, the following two procedural steps are added in the postprocessing: (1) for the photographic sky type (PST), the sky type with the maximum contribution is taken as the image sky type; (2) an ice halo score (IHS) discriminator is used to assign a halo/no halo designator to an image
With this image analysis algorithm used on total sky imagers (TSIs) images to identify the PST and the appearance of 22◦ halos, the useful and logical step will be to relate these data to other instrument records: lidar for altitude, particle density, and particle phase, as well as photometric measurements to glean information on radiative flux
Summary
Modeling and predicting the Earth’s climate is a challenge for physical science, even more so in light of the already observable changes in Earth’s climate system (Fasullo and Balmaseda, 2014; Fasullo et al, 2016; IPCC, 2013, 2014). The fraction of smooth crystals necessary for halo display appearance is at a minimum 10 % for columns, and 40 % for plates, based on an analysis of scattering phase functions for single scattering events (van Diedenhoven, 2014) While this establishes a lower boundary, it is correct to say that the observability of a halo display allows one to conclude that smooth crystalline ice particles are present and single scattering events dominate. The consideration of the percentage of cirrus clouds that display optical halo features allows upon further study, inferences about the microphysical properties of the cloud This raises interest in examining existing long-term records of sky images.
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