TARPs: Tracked Active Region Patches from
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TARPs: Tracked Active Region Patches from
TARPs: Tracked Active Region Patches from SOHO/MDI SH23A 2087 Michael Turmon (JPL/Caltech); J. Todd Hoeksema, Monica Bobra (Stanford University) Synoptic 2001 M-TARPs (lines mark month boundaries) Summary Methodology: Finding Active Regions • We are developing a new data product for the MDI Resident Archive containing tracked magnetic features on the scale of solar active regions, abbreviated MDITARPs (MDI Tracked Active Region Patches). This data product, derived from lineof-sight (LOS) magnetograms and continuum intensitygrams, is a companion to the already-released HARP (HMI Active Region Patch) data product from HMI. Together, the two data products cover May 1996 to the present, and should eventually span two solar cycles. • We first compute a full-disk activity mask given input magnetogram and intensity images (Turmon et al. 2002) taking spherical geometry into account (Turmon et al. 2010). Large spatially-coherent regions are identified within the LOS magnetograms and intensitygrams and tracked from image to image, accounting for merges as regions grow. After the region disappears, the numbered track (“TARP”) is placed into a data series by finding the smallest box of constant latitude/longitude extent that encompasses all appearances of the region. Mask: 2011/02/14 12:00 • Following Liu et al. 2012, MDI mask activity model is obtained from HMI model by scaling by 1.4. • Sample HMI mask (right) shows typical mask appearance. The MDI-TARP data series provides all geometric and heliographic information needed to track active patches in MDI and other solar data sets. For each numbered TARP, the data series defines at each time step a rectangular CCD cutout, and it provides a mask within the cut-out indicating the active pixels within a regular, smoothly-evolving blob. • Group pixel-scale activity from masks into NOAA AR-scale regions We used a matched filter approach with an elongated Gaussian kernel of FWHM ~50x25Mm (~40x20 MDI pixels) at disk center. MDI Mask Summary keywords such as areas and integrated fluxes are included for each appearance of the region. The data product described here is in draft form, with release as a data series on Stanford University’s JSOC expected in June 2014. • • After M-TARPs are indexed by a number called HARPNUM, analogous to NOAA AR number, and time step (T_REC). • For a single M-TARP, the data series is a list of rectangular patches and metadata containing the observed lifespan of the TARP. A 1-day pad is appended on both ends of the TARP. This padding period is seen in the empty, dotted boxes in the tracked frames (e.g., in the next poster panel). • Each rectangular patch in the list is a cutout from the image plane. A patch can be overlaid on a full-disk image (e.g., the LOS magnetograms) by a simple coordinate shift. Patch WCS are included for other projections. where P is a permutation matrix giving the B-to-A mapping. Fast, exact solution by linear programming. • The footprint covered by the patch is determined by the the smallest lat/lon bounding box that encompasses all appearances of that TARP. See below. • Chaining this association across many frames yields complete tracks. • • Tracks can be finalized only after they are unseen for a long-enough time. The animating idea behind the sizing of the lat/lon bounding box is that the observer is hovering over the AR, staying at a constant latitude and moving at a constant angular rate in longitude. • Shown below are four patches of the 200 total making up M-TARP 7570. The colored masks below are stored as bitmaps in a suitable integer encoding. • Compute the overlap area between extrapolated track (using standard latitude-dependent motion relationship) and new region. • Overlap of patch a in A and patch b in B is D(a,b). • Solve linear assignment problem to match A up to B: A B Merging Tracks and Complex ARs Kernel at Limb Kernel at Disk Center • Tracks are first identified using past and current data. Thus, growing regions may merge in later appearances. • Coping with the consequences of merges adds considerable complexity to the implementation. This complexity is hidden in the final data product. Convolved with Template Identified Groups • Care is taken so that regions near the detection threshold are not cut into separate temporal pieces as they exceed and then sink below the threshold. 2002.04.09 01:36 2002.04.11 17:36 2002.04.17 01:36 à Time 2002.04.18 09:36 2002 Sep. 02, 11:11 TAI Tracked Frames • Before Chain regions together to make a track: singlelink most likely tracker using overlap area • The MDI TARP is often not a contiguous region. For shrinking regions, the M-TARP lat/lon bounding box can be much larger than the currently active area. It can even contain other TARPs. Use the bitmap to determine what is part of the TARP. This work was sponsored by NASA’s Heliophysics HDEE Program Element. • The MDI TARP Data Product • Mask: zoom Active Region Grouping • • Bayesian approach trades off pixel-by-pixel agreement of the mask value to the data against spatial coherence of labels (a prior). Mask Model and Example The MDI-TARP data series is intended for: • Subsetting individual active regions • Computation of space weather indices for individual active regions • Facilitating long-term or synoptic statistical studies of active regions Methodology: Active Region Tracking MDI TARP vs. HMI HARP Correspondence MDI TARP vs. HMI HARP Region Boundaries We checked for correspondence between MDI TARPs and HMI HARPs using the ~140 ARs in the May–October 2010 overlap period. By checking location and shape, we determined matching regions (in green) and misses (in gray). We find 130 matches and 11 misses of each type (TARP present but no HARP, and vice versa). The quick-looks here are sampled 1/day from the 96m (15/day) full series. M-TARPs are colored blobs. NOAA ARs are yellow crosses. The M-TARP/NOAA correspondence is found and coded in keywords. • For the 2010 overlap, we overlaid the nine largest MDI TARPs over the HMI HARPs, projecting the MDI TARPs into the HMI coordinates by image WCS. • Some HMI HARPs enclose more activity within one HARP (blue blobs below correspond to differently-numbered MDI TARPs). Color Key HMI HARP 92 + MDI TARP 14113 at 2010.07.25 19:12:00 TAI MDI TARP Pixels = 8601, MDI Active Pixels = 1320 HMI HARP 226 + MDI TARP 14242 at 2010.10.26 19:12:00 TAI MDI TARP Pixels = 7192, MDI Active Pixels = 1193 50 100 Outside the HARP & M-TARP 150 Centroid of MDI-TARPs and HMI HARPs Synoptic: May 2010 – October 2010 40 Example TARP merges: green (7570), pink (7561). Expired: violet (7507), red (7538), etc. New: tan (7586), etc. In the M-TARP, outside HARP 50 200 250 100 300 100 200 300 400 500 600 700 800 900 1000 In the HARP, outside M-TARP 1100 150 HMI HARP 211 + MDI TARP 14226 at 2010.10.15 00:00:00 TAI MDI TARP Pixels = 9358, MDI Active Pixels = 776 HARP & M-TARP coincide 200 30 50 100 250 Active in M-TARP, not in HARP 150 300 200 20 Active in HARP, not in M-TARP Latitude (deg.) 250 350 300 350 10 450 MDI TARP 0 100 200 • HARP (HMI) MDI−HMI Match OK −10 Active in HARP & M-TARP 400 400 No MDI or HMI match 300 400 500 600 700 800 900 1000 100 1100 200 300 400 500 600 More typically, as below, the HARP and the M-TARP coincide well. HMI HARP 115 + MDI TARP 14136 at 2010.08.09 20:48:00 TAI MDI TARP Pixels = 10125, MDI Active Pixels = 810 HMI HARP 86 + MDI TARP 14105 at 2010.07.14 22:24:00 TAI MDI TARP Pixels = 15672, MDI Active Pixels = 1646 HMI HARP 104 + MDI TARP 14127 at 2010.08.02 04:48:00 TAI MDI TARP Pixels = 8138, MDI Active Pixels = 813 50 50 −20 50 100 100 100 150 150 200 150 200 −30 250 200 250 300 250 350 300 −40 300 2097 2098 2099 2100 2101 2102 450 350 400 2096 400 350 2103 500 450 400 500 450 100 Carrington Rotation Number 100 Some extra HARPs are found due to enhanced spatial/temporal resolution of HMI. With current settings, some extra M-TARPs are found due to grouping (next panel). These results are consistent with the good MDI/HMI agreement found by Liu et al. (2012), especially for relatively high fields. 200 300 400 500 600 700 800 200 300 400 500 600 700 800 900 500 100 HMI HARP 185 + MDI TARP 14198 at 2010.09.23 20:48:00 TAI MDI TARP Pixels = 8542, MDI Active Pixels = 762 200 300 400 500 600 HMI HARP 187 + MDI TARP 14205 at 2010.09.29 08:00:00 TAI MDI TARP Pixels = 8866, MDI Active Pixels = 1329 700 HMI HARP 175 + MDI TARP 14187 at 2010.09.17 14:24:00 TAI MDI TARP Pixels = 12522, MDI Active Pixels = 1412 50 50 100 50 100 150 100 150 150 200 200 200 250 250 250 300 300 350 300 350 400 350 100 200 300 400 500 600 700 800 100 200 300 400 500 150 Histogram of Track Lengths MDI TARP Data Characteristics • Tracks cover April 1996 – October 2010 (all usable MDI) • 15 years, 72100 masks, 6170 M-TARPs. • Median M-TARP length = 4.1 days = 61 frames 459 are ≥ 12 days (180 frames) • The ease of computing per-AR quantities should enable new studies that would have been prohibitive. Status and Plans 100 The draft data product here will be improved before an expected June 2014 release: Excess of short−duration ARs partly due to image artifacts from energetic particles 1 day = 15 synoptic images • Better suppression of extraneous patches due to energetic particles. • Improved correspondence of MDI TARPs to HMI HARPs. • We hope to identify sunspots within the activity mask. 50 0 0 1 2 3 4 5 6 7 8 9 10 11 Track Length (days) Excluding 1-day Padding 12 13 14 15 16 References M. Turmon, J. T. Hoeksema, X. Sun, M. Bobra, “HARPs – Tracked active region patch data product from SDO/HMI,” 2012 AGU fall meeting, abstract #SH13A-2246. M. Turmon, H. Jones, J. Pap, O. Malanushenko, “Statistical feature recognition for multidimensional solar imagery”, Solar Physics, 262(2), 2010. Y. Liu, J. T. Hoeksema, P. H. Scherrer, et al., “Comparison of line-of-sight magnetograms taken by SDO/HMI and SOHO/MDI,” Solar Physics, 279(1), 2012. H. Jones, G. Chapman, K. Harvey, J. Pap, D. Preminger, M. Turmon, S. Walton, “A comparison of feature classification...”, Solar Physics, 248(2), 2007. M. Turmon, J. Pap, S. Mukhtar, “Statistical pattern recognition for labeling solar active regions: Application to SoHO/MDI,” Astrophys. Jour., 568(1), 2002, 396-407. 600 700 800 900 1000 100 200 300 400 500 600 700 turmon@jpl.nasa.gov todd@sun.stanford.edu mbobra@sun.stanford.edu National Aeronautics and Space Administration Jet Propulsion Laboratory California Institute of Technology Pasadena, California Copyright 2012. All rights reserved. 800 900
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