1. Other SOLIS Data: Intensity, Line Depth, and Equivalent Width from the VSM Harrison P. Jones (National Solar Observatory) Level 1 ProcessedLevel 1 Processed Continuum Intensity Equivalent Width Line Depth Line-of-Sight Magnetogram Fe I 630.215 nmCa II 854.2 nm SOLIS Vector Spectromagnetograph 11 June 2004 Motivation Line-of-sight and vector magnetograms from the SOLIS Vector Spectromagnetograph (VSM) provide important information for studies of solar and heliospheric structure and activity. Additional information is available. Intensity, Line Depth and Equivalent Width (I, D, W) are computed from each VSM spectral scan line for line-of-sight magnetograms but are not currently carried beyond Level 1 processing (flat-fielding and accumulation of quantities computed for scan lines into images). (I,D,W) provide ancillary thermodynamic information which Continues the data archive from NASA/NSO Spectromagnetograph (SPM). Enables feature classification. Informs photospheric and chromospheric models. As is evident from accompanying images, Level 1 I, D, and W observations carry severe artifacts which are not removed by spectral flat-fielding. These are preferentially oriented along image columns (spatial scan direction) and probably result from slight differences in illumination and subsequent fringe patterns between flat-field and data scans. Similar artifacts were present in SPM data. This paper presents algorithms for producing useful (I, D, W) images from Level 1 data and estimates effort for application to the entire VSM data set. Method Least-squares fits to I, W, and D are computed for each image column and the ratio of the data to the fits comprise the final result. Least squares fits account for large-scale trends such as center-to-limb variation. Computing ratios removes column streaks. Regions of large contrast (e.g. sunspots) are iteratively rejected from the data which determine the least-squares fits. Basis functions Fourth order (cubic) splines with breakpoints spaced more closely near the limbs for quantities such as I with rapid variation near limb. The examples shown use a (low) intensity threshold to define the limb but have not otherwise been trimmed to avoid rapid variations near the limb. Fourth order Legendre polynomials for quantities (e.g. 854.2 nm W, D) with more gradual center-to-limb variation and more pronounced contrast at medium spatial scales. Results Application of the algorithms to photospheric and chromospheric VSM magnetograms from 11 June 2004 are shown at right. In all cases the least-squares ratioing of the data removes vertical streaks and reveals spatial structure not apparent in the Level 1 data without obviously introducing artifacts. Currently, considerable time is required for preliminary processing which includes locating the Level 1 data, extracting the images, removing artifacts not shown here such as the inter-camera gap and “crosshairs”, and replacing a few individual columns of clearly corrupted data with averages of neighboring columns. Scripts already exist or can easily be constructed to speed this process. The algorithm itself requires a few seconds per image for Legendre fitting and about a minute per image for cubic-spline fitting on a MacBook Pro or modestly high-end Linux workstation. To Do Test algorithm on more days—more issues may be discovered. Process entire data set Will take about 6 months of full-time effort. Resources for this task have not been identified.