The Principal Investigator (PI) will investigate the accuracy of plasma velocities derived from solar photospheric and chromospheric magnetograms, using model data that more realistically simulates photospheric and chromospheric magnetic evolution. He will conduct these tests in collaboration with model developers and users of several velocity estimation methods. This study is motivated by the fact that magnetogram sequences are extensively used by the community to estimate velocities and the fluxes of magnetic energy and helicity into the solar corona, thereby driving dynamic models of the coronal magnetic field. However, synthetic magnetograms derived from magnetohydrodynamic (MHD) simulations of magnetoconvection in the solar interior have demonstrated that such magnetogram sequencing methods of estimating velocities are error prone.
The PI will address several scientifically interesting questions, such as whether velocities are more accurately reconstructed from photospheric or chromospheric magnetograms, and whether current methods reconstruct the energy and helicity fluxes accurately. His coordinated analyses of magnetogram observations will determine how well the differing velocity estimation methods agree and how variations in instrumental spatial resolution affect these estimated velocities.
The PI plans to hold annual workshops to promote research partnerships. He will post his synthetic and observed data sets on journal-hosted web sites to ensure widespread and long-term dissemination of his findings, and to permit standardized benchmarking of velocity estimation methods within the community. His research team will supervise students and introduce them to statistical methods of data analysis. This work will lead to enhanced predictive space weather capabilities, and thereby impact society through better forecasts for solar disturbances that propagate to Earth and affect our technological infrastructure.
Society is adversely affected by solar flares and coronal mass ejections (CMEs), but their impacts can be mitigated by successful prediction. These phenomena are driven by the release of energy stored in the magnetic field of the low corona, but the magnetic field vector in the corona cannot be measured, so processes at work in the buildup of coronal magnetic energy remain poorly understood, hampering prediction. In contrast, the vector magnetic field at the photosphere, below the corona, can be measured, and estimates of photospheric velocities can be used to quantify the flux of magnetic energy across the photosphere into the corona. Tests of techniques for estimating photospheric flows, however, show that these methods are imperfect. We sought to investigate methods of validating and improving techniques for estimating photospheric flows. We report four key findings. (1) Velocity estimates from two independent methods applied to photospheric magnetic field observations were significantly correlated, indicating reproducibility of the velocity estimates. (2) Properties of photospheric flow patterns were found to be associated with flare activity for both methods, independent of both the method used to estimate velocities and other, previously established predictors of flare activity. This motivates further studies of flare prediction based upon photospheric flows. (3) Output from realistic simulations of photospheric evolution, performed with the MURaM radiative-MHD code, revealed that realistic photospheric dynamics at the shortest spatial and temporal scales are inconsistent with the underlying assumption of current velocity estimation methods, which assume that velocities are related to magnetic evolution via the ideal induction equation. In particular, the highest-speed flows are the shortest lived, and appear not to affect magnetic fields as strongly as longer-lived, larger-scale flows. Photospheric evolution therefore appears "sub-inductive," i.e., magnetic fields do not evolve as rapidly as predicted based upon the instantaneous magnetic and velocity fields. Consequently, understanding the quantitative relationships between flow fields and magnetic evolution at the photosphere will require additional investigation. (4) Autocorrelation of flow maps can be used to quantify flow lifetimes, and thereby to determine optimal parameters for estimating photospheric flows. Longer-lived flows are slower and operate on larger spatial scales than shorter-lived flows. Additional effort will be required to identify the spatial and temporal scales of flows that are most relevant for the transport of magnetic energy into the solar corona. It is plausible that different flow scales are responsible for infrequent, transient phenomena, such as flares/CMEs, versus more steady phenomena, such as coronal heating.
