Validation of a Next Generation Data Assimilative Space Weather Model Driver

Accurate estimates of the global solar photospheric magnetic flux distribution are essential for making quality space weather forecasts. Maps of magnetic flux in the photosphere are the primary input to coronal. heliospheric. and other space weather models. The purpose of this dissertation is to validate the Air Force Data Assimilative Flux Transport (ADAPT) model. ADAPT is a new- class of photospheric flux transport model that uses real data with a data assimilation framework to keep the model steered towards the observed Sun. The primary product of ADAPT is an ensemble of 16 real-time global estimates of the radial component of the magnetic field in the photosphere. Helioseismic holography is a tool that has been used for nearly two decades to detect strong active regions on the far-side of the Sun (i, e. the side facing away from Earth). The purpose of this dissertation is to validate the performance of ADAPT when far-side helioseismic data is used as a source of data for updating the flux distribution on the far-side. This dissertation addresses the following three questions related to the further development of ADAPT: 1) Can helioseismology be used to detect the morphology of strong active regions. namely their bipolar tilt angle and area? 2) When used as a boundary condition in a magnetohydrodynamic solver. does ADAPT improve the predicted structure of the whitelight corona when helioseismic data are assimilated into the ADAPT framework? 3) By how much does the morphology of time whitelight corona vary between realizations within an ADAPT ensemble? The above three questions address critical areas of research designated by NASA, NOAA, the USAF, and other interested agencies by introducing new physics and phenomenology into space weather models.