Automatic data analysis for Sky Brightness Monitor
M. Y. Zhao, Y. Liu, A. Elmhamdi, A. S. Kordi, H.A. Al-trabulsy, X. F., Zhang, T. F. Song, S. Q. Liu, Y. D. Shen, Z. J. Tian, Y. H. Miao

TL;DR
This paper introduces an automated data processing method for Sky Brightness Monitors that enhances sky condition assessment and supports solar observations by accurately analyzing large datasets.
Contribution
The paper presents a novel automatic processing technique for SBM data, enabling efficient separation of solar and sky regions and recognition of supporting arms in large datasets.
Findings
Effective separation of Sun and sky regions in SBM data
Significant analysis of scattered-light levels
Potential for guiding full-disk solar telescopes
Abstract
The Sky Brightness Monitor (SBM) is an important instrument to measure the brightness level for the sky condition, which is a critical parameter for judging a site for solar coronal observations. In this paper we present an automatic method for the processing of SBM data in large quantity, which can separate the regions of the Sun and the nearby sky as well as recognize the regions of the supporting arms in the field of view. These processes are implemented on the data acquired by more than one SBM instruments during our site survey project in western China. An analysis applying the result from our processes has been done for the assessment of the scattered-light levels by the instrument. Those results are considerably significant for further investigations and studies, notably to derive a series of the other important atmospheric parameters such as extinctions, aerosol content and…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
