GT-scopy: A Data Processing and Enhancing Package (Level 1.0–1.5) for Ground Solar Telescopes—Based on the 1.6 m Goode Solar Telescope

Abstract The increasing demand for high-resolution solar observations has driven the development of advanced data processing and enhancement techniques for ground-based solar telescopes. This study focuses on developing a python-based package (GT-scopy) for data processing and enhancing for giant solar telescopes, with application to the 1.6 m Goode Solar Telescope (GST) at Big Bear Solar Observatory. The objective is to develop a modern data processing software for refining existing data acquisition, processing, and enhancement methodologies to achieve atmospheric effect removal and accurate alignment at the sub-pixel level, particularly within the processing levels 1.0–1.5. In this research, we implemented an integrated and comprehensive data processing procedure that includes image de-rotation, zone-of-interest selection, coarse alignment, correction for atmospheric distortions, and fine alignment at the sub-pixel level with an advanced algorithm. The results demonstrate a significant improvement in image quality, with enhanced visibility of fine solar structures both in sunspots and quiet-Sun regions. The enhanced data processing package developed in this study significantly improves the utility of data obtained from the GST, paving the way for more precise solar research and contributing to a better understanding of solar dynamics. This package can be adapted for other ground-based solar telescopes, such as the Daniel K. Inouye Solar Telescope (DKIST), the European Solar Telescope (EST), and the 8 m Chinese Giant Solar Telescope, potentially benefiting the broader solar physics community.