Published in

Springer Verlag, Solar Physics, 3(289), p. 769-792

DOI: 10.1007/s11207-013-0353-1

Links

Tools

Export citation

Search in Google Scholar

A Multi-Observatory Inter-Comparison of Line-of-Sight Synoptic Solar Magnetograms

This paper is available in a repository.
This paper is available in a repository.

Full text: Download

Green circle
Preprint: archiving allowed
Green circle
Postprint: archiving allowed
Red circle
Published version: archiving forbidden
Data provided by SHERPA/RoMEO

Abstract

The observed photospheric magnetic field is a crucial parameter for understanding a range of fundamental solar and heliospheric phenomena. Synoptic maps, in particular, which are derived from the observed line-of-sight photospheric magnetic field and built up over a period of 27 days, are the main driver for global numerical models of the solar corona and inner heliosphere. Yet, in spite of 60 years of measurements, quantitative estimates remain elusive. In this study, we compare maps from seven solar observatories (Stanford/WSO, NSO/KPVT, NSO/SOLIS, NSO/GONG, SOHO/MDI, UCLA/MWO, and SDO /HMI) to identify consistencies and differences among them. We find that while there is a general qualitative consensus, there are also some significant differences. We compute conversion factors that relate measurements made by one observatory to another using both synoptic map pixel-by-pixel and histogram-equating techniques, and we also estimate the correlation between datasets. For example, Wilcox Solar Observatory (WSO) synoptic maps must be multiplied by a factor of 3 – 4 to match Mount Wilson Observatory (MWO) estimates. Additionally, we find no evidence that the MWO saturation correction factor should be applied to WSO data, as has been done in previous studies. Finally, we explore the relationship between these datasets over more than a solar cycle, demonstrating that, with a few notable exceptions, the conversion factors remain relatively constant. While our study was able to quantitatively describe the relationship between the datasets, it did not uncover any obvious “ground truth.” We offer several suggestions for how this may be addressed in the future.