Atmospheric Measurement Techniques
Atmospheric Measurement Techniques
AMT
Articles | Volume 19, issue 16
Articles | Volume 19, issue 16
https://doi.org/10.5194/amt-19-5457-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-19-5457-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 19, issue 16
Research article
 | 
25 Aug 2026
Research article |  | 25 Aug 2026

A novel segmentation algorithm for the ARM user facility all-sky imagers using machine learning applications

Israel Silber, Donna M. Flynn, Jennifer M. Comstock, Erol L. Cromwell, and Brian D. Ermold

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Short summary
We describe ASISKYCOVER, a new machine learning algorithm for pixel segmentation of all-sky imager (ASI-16) data used by the Atmospheric Radiation Measurement (ARM) User Facility. ASISKYCOVER provides cloud cover and thickness estimates, detects artifacts, and reports uncertainties. Using one year of data from the ARM Southern Great Plains site and comparisons with other ARM datasets, we demonstrate its use and robustness, which will improve cloud cover analyses and data evaluation efforts.
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