Mutual Validation of Datasets for Analyzing Tilt Angles in Solar Active Regions
Lang Qin, Jie Jiang, Ruihui Wang

TL;DR
This study validates and refines solar active region tilt angle datasets, revealing more accurate average tilt angles, their correlation with AR properties, and supporting tilt quenching in solar cycle models.
Contribution
It introduces a mutual validation method for AR tilt datasets, reducing measurement errors and providing revised tilt angle statistics and their dependencies.
Findings
No significant difference between white-light and magnetogram tilt angles.
Revised average tilt angle around 7° with reduced scatter.
Strong correlation of tilt scatter with AR flux and sunspot area.
Abstract
The tilt angle of solar active regions (AR) is crucial for the Babcock-Leighton type dynamo models in the buildup of polar field. However, divergent results regarding properties of tilt angles were reported due to their wide scatter, caused by intrinsic solar mechanisms and measurement errors. Here, we mutually validate the magnetogram-based AR tilt angle dataset from Wang, Jiang, & Luo with the Debrecen Photoheliographic Data by identifying common data points where both datasets provide comparable tilt angles for the same AR/sunspot. The mutually validated datasets effectively reduce measurement errors, enabling a more accurate analysis of the intrinsic properties of tilt angles. Our mutually validated datasets reveal that the difference between white-light-based and magnetogram-based tilt angles has no significant difference. Also, the datasets show that an upward revision of average…
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Taxonomy
TopicsSolar Radiation and Photovoltaics
