Automatic data analysis for Sky Brightness Monitor

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 precipitable water vapor content for candidate sites. Our processes also provide a possible way for full-disk solar telescopes to track the Sun without an extra guiding system.