LCT Active Region Survey: Preliminary Results We proposed to calculate LCT flows (Li et al. 2004, Welsch et al., 2004) in N > 30 ARs, some of which produced CMEs/flares. We want to: 1)Determine baseline flow values, and 2)See if shearing and/or converging flows are related to flares/CMEs. B. Welsch & Y. Li, Space Sciences Lab, UC-Berkeley

Accomplishments in first 6 months 1. YAFTA (Yet Another Feature Tracking Code) is publicly available –Wrote user’s manual (hard copies available here). –Put code & manual on-line in at: 2.Identified Candidate Events, See Table 1. Are you working on any of these events? Do you have any events that you want us to study? 3. Working with an undergraduate student.

Feature Tracking Algorithm Written in IDL, each feature’s data is stored in an IDL structure. Consists of: 1.Feature identification in an image. 2.Matching features between images. Useful for studying: 1.magnetic flux cancellation; 2.magnetic charge topology (MCT); 3.polarity inversion lines (PIL).

What are “features” in a magnetogram like that in Figure 1? My feature tracking algorithm groups contiguous, unipolar pixels into features. Optionally, a feature may contain: 1.All pixels of a |B z | > B thr, in which case they are isolated: B z = 0, or |B z |< B thr, obtains on their boundaries. (Fig. 2) 2.All pixels that are convex-up in |B z | & contiguous with a local maximum in |B z |. (Fig.3)

Fig. 1: B LOS in AR 8038, 10 May 1997

Fig. 2: Contiguous-Pixel Features

Fig. 3: Gradient-Based Features

Upon partitioning: Features below user set min. size are ignored. Flux-weighted quantities are calculated & stored: (velocities from LCT on magnetograms)

Next, Track Features YAFTA uses “reciprocal maximum flux overlap” (DeForest et al., 2005) to associate features across time steps. 96 min. MDI data are slowest cadence tried so far... YAFTA keeps track of fragmentation/ merging, appearance/ disappearance, etc. Can calculate rate of cancellation: “mutual apparent loss of magnetic flux in closely spaced features of opposite polarity.”

Figure 4. Cancelled Flux vs. Time

Flux Cancellation May: Peak rate of ~ 3 x Mx/hr Total of 4.4 x Mx cancelled Flux in a filament is ~ 2 x Mx –|B| ~ 100 G –A = H x W ~ (30 Mm)(6 Mm) ~ 2 x cm 2 …and a filament was observed to form and erupt from AR 8038 in this period.

PIL studies Find PIL by 2D topology: outline minority-polarity features. (Discard PILs that are too small?) Figure 5. All PILs (left), and PILs enclosing > 20 pix (right).

Q: How to quantify shear/ convergence along PILs? A: First, define a local coordinate system, x || & x _|_, and calculate points perpendicular to PIL x || x _|_ Figure 6.

Quantifying shear/convergence on PILs, cont’d: x || x _|_ Interpolate regularly-gridded LCT velocities onto points _|_ to PIL. Figure 7.

Finally, average shear & convergence over PIL: Differentiate to get shear, Also compute divergence, Average these over all cell boundaries identified as lying on PIL at each time step. See if shear/negative divergence correlate with flare and/or CMEs.

Three Events Selected so far: 1.AR 8038, May 1997: SHINE/ MURI event, simple global magnetic field 2.AR 8210, 30 April -03 May 1998: SHINE/ MURI event, complex global field 3.AR 8218, May 1998: global field similar to AR 8210, but no flares/CMEs! Why?! Suggestions for others are welcomed!

Conclusions Feature Tracking algorithm, with documentation, is freely available on-line. We have begun defining quantifiable measures of AR flows. –Please feel free to comment on our choices, and/or recommend others. We have begun AR/event selection. –We would like to coordinate event studies! –Please feel free to recommend events!