SYNCHRONIC CORONAL HOLE MAPPING USING MULTI-INSTRUMENT EUV IMAGES: DATA PREPARATION AND DETECTION METHOD

We describe a method for the automatic mapping of coronal holes (CHs) using simultaneous multi-instrument EUV imaging data. Synchronized EUV images from STEREO/EUVI A and B 195 angstrom and SDO/AIA 193 angstrom are preprocessed, including point-spread function deconvolution and the application of data-derived intensity corrections which account for center-to-limb variations (limb brightening) and inter-instrument intensity normalization. We systematically derive a robust limb-brightening correction that takes advantage of unbiased long-term averages of data and respects the physical nature of the problem. The new preprocessing greatly assists in CH detection, allowing for the use of a simplified variable-connectivity, two-threshold region-growing image segmentation algorithm to obtain consistent detection results. We generate synchronic EUV and CH maps, and show a preliminary analysis of CH evolution. Several data and code products are made available to the community (www.predsci.com/chd): for the period of this study (2010 June 10 to 2014 August 18), we provide synchronic EUV and CH map data at 6 hr cadence, data-derived limb-brightening corrections for STEREO/EUVI A and B 195 angstrom and SDO/AIA 193 angstrom and inter-instrument correction factors to equate their intensities. We also provide the CH image segmentation code module (ezseg) implemented in both FORTRAN-OpenMP and GPU-accelerated C-CUDA. A complete implementation of our CH detection pipeline in the form of a ready-to-use MATLAB driver script euv2chm utilizing ezseg is also made available.