We present the first quantitative comparison between the total magnetic reconnection flux in the low corona in the wake of coronal mass ejections (CMEs) and the magnetic flux in magnetic clouds (MCs) that reach 1 AU 2Y3 days after CME onset. The total reconnection flux is measured from flare ribbons, and the MC flux is computed using in situ observations at 1 AU, all ranging from 10 20 to 10 22 Mx. It is found that for the nine studied events in which the association between flares, CMEs, and MCs is identified, the MC flux is correlated with the total reconnection flux È r . Further, the poloidal (azimuthal) MC flux È p is comparable with the reconnection flux È r , and the toroidal (axial) MC flux È t is a fraction of È r . Events associated with filament eruption do not exhibit a different È t, p -È r relation from events not accompanied by erupting filaments. The relations revealed between these independently measured physical quantities suggest that for the studied samples, the magnetic flux and twist of interplanetary magnetic flux ropes, reflected by MCs, are highly relevant to low-corona magnetic reconnection during the eruption. We discuss the implications of this result for the formation mechanism of twisted magnetic flux ropes, namely, whether the helical structure of the magnetic flux rope is largely pre-existing or formed in situ by low-corona magnetic reconnection. We also measure magnetic flux encompassed in coronal dimming regions (È d ) and discuss its relation to the reconnection flux inferred from flare ribbons and MC flux.

We report here on the present state-of-the-art in algorithms used for resolving the 180 • ambiguity in solar vector magnetic field measurements. With present observations and techniques, 268 T.R. METCALF ET AL. some assumption must be made about the solar magnetic field in order to resolve this ambiguity. Our focus is the application of numerous existing algorithms to test data for which the correct answer is known. In this context, we compare the algorithms quantitatively and seek to understand where each succeeds, where it fails, and why. We have considered five basic approaches: comparing the observed field to a reference field or direction, minimizing the vertical gradient of the magnetic pressure, minimizing the vertical current density, minimizing some approximation to the total current density, and minimizing some approximation to the field's divergence. Of the automated methods requiring no human intervention, those which minimize the square of the vertical current density in conjunction with an approximation for the vanishing divergence of the magnetic field show the most promise.

On the basis of observations of solar granulation obtained with the New Solar Telescope (NST) of Big Bear Solar Observatory, we explored proper motion of bright points (BPs) in a quiet sun area, a coronal hole, and an active region plage. We automatically detected and traced bright points (BPs) and derived their mean-squared displacements as a function of time (starting from the appearance of each BP) for all available time intervals. In all three magnetic environments, we found the presence of a super-diffusion regime, which is the most pronounced inside the time interval of 10-300 seconds. Super-diffusion, measured via the spectral index, γ, which is the slope of the mean-squared displacement spectrum, increases from the plage area (γ = 1.48) to the quiet sun area (γ = 1.53) to the coronal hole (γ = 1.67). We also found that the coefficient of turbulent diffusion changes in direct proportion to both temporal and spatial scales. For the minimum spatial scale (22 km) and minimum time scale (10 sec), it is 22 and 19 km 2 s −1 for the coronal hole and the quiet sun area, respectively, whereas for the plage area it is about 12 km 2 s −1 for the minimum time scale of 15 seconds. We applied our BP tracking code to 3D MHD model data of solar convection (Stein et al. 2007) and found the super-diffusion with γ = 1.45. An expression for the turbulent diffusion coefficient as a function of scales and γ is obtained.

Spicules are rapidly evolving fine-scale jets of magnetized plasma in the solar chromosphere. It remains unclear how these prevalent jets originate from the solar surface and what role they play in heating the solar atmosphere. Using the Goode Solar Telescope at the Big Bear Solar Observatory, we observed spicules emerging within minutes of the appearance of opposite-polarity magnetic flux around dominant-polarity magnetic field concentrations. Data from the Solar Dynamics Observatory showed subsequent heating of the adjacent corona. The dynamic interaction of magnetic fields (likely due to magnetic reconnection) in the partially ionized lower solar atmosphere appears to generate these spicules and heat the upper solar atmosphere.

In this study we use the ordinal logistic regression method to establish a prediction model, which estimates the probability for each solar active region to produce X-, M-, or Cclass flares during the next 1-day time period. The three predictive parameters are (1) the total unsigned magnetic flux T flux , which is a measure of an active region's size, (2) the length of the strong-gradient neutral line L gnl , which describes the global nonpotentiality of an active region, and (3) the total magnetic dissipation E diss , which is another proxy of an active region's nonpotentiality. These parameters are all derived from SOHO MDI magnetograms. The ordinal response variable is the different level of solar flare magnitude. By analyzing 174 active regions, L gnl is proven to be the most powerful predictor, if only one predictor is chosen. Compared with the current prediction methods used by the Solar Monitor at the Solar Data Analysis Center (SDAC) and NOAA's Space Weather Prediction Center (SWPC), the ordinal logistic model using L gnl , T flux , and E diss as predictors demonstrated its automatic functionality, simplicity, and fairly high prediction accuracy. To our knowledge, this is the first time the ordinal logistic regression model has been used in solar physics to predict solar flares.