October 15, 2010, 12:00 pm - 1:00 pm
October 15, 2010, 12:00 pm - 1:00 pm
The Origin of Coronal Structure
Spiro K. Antiochos (GSFC, Space Weather Laboratory)
One of the most important and most puzzling features of the solar coronal magnetic field is that it appears to have smooth structure with little evidence for non-potentiality except at special locations, photospheric polarity inversions lines, where the non-potentiality is observed as so-called filament channels. The free energy associated with the strong non-potentiality of filaments/prominences is the energy source for the most explosive solar activity, CMEs and flares. Given that photospheric motions continuously tangle the entire coronal field, the observed smoothness of the general corona is highly unexpected. Although reconnection can eliminate some of the injected structure, it cannot destroy helicity, which should build up to produce observable complexity. I propose that an inverse cascade process transports the injected helicity from the interior of coronal flux regions to their boundaries, polarity inversion lines, creating filament channels. I describe how the helicity is injected and transported and calculate the relevant rates. I argue that one process, helicity transport, can explain both the observed lack of and presence of structure in the Sun's magnetic field.
Connected to the Sun - But Can we Tell Where?
Peter Macneice (GSFC, Space Weather Laboratory)
Forecasting the arrival of Solar Energetic Particles(SEPs) is a priority in Space Weather. To forecast the arrival of prompt SEPs accelerated by flares requires an ability to model the magnetic fieldline connections between the Sun and Earth. The CCMC runs most of the models used by the Space Weather Forecasting agencies to model the corona and inner heliosphere and so is uniquely placed to examine the abilities of these models to identify the fieldline connections from the Earth to the Solar surface. In this talk we report on the accuracy of these models in reconstructing the sun-earth fieldline connectivity, and reflect on what will be needed in order to improve these models.