Modeling the corona and solar wind using ADAPT maps that include far-side observations

Abstract

As the primary input to nearly all coronal and solar wind models, global estimates of the solar photospheric magnetic field distribution are critical for reliable modeling of the corona and heliosphere. Over the last several years the Air Force Research Laboratory (AFRL), in collaboration with Los Alamos National Laboratory (LANL) and the National Solar Observatory (NSO), has developed a model that produces more realistic estimates of the instantaneous global photospheric magnetic field distribution than those provided by traditional photospheric field synoptic maps. The Air Force Data Assimilative Photospheric flux Transport (ADAPT) model is a photospheric flux transport model, originally developed at NSO, that makes use of data assimilation methodologies developed at LANL. The flux transport model evolves the observed solar magnetic flux using relatively well understood transport processes when measurements are not available and then updates the modeled flux with new observations using data assimilation methods that rigorously take into account model and observational uncertainties. ADAPT originally only made use of Earth-side magnetograms, but the code has now been modified to assimilate helioseismic far-side active region data such as those available from the Global Oscillation Network Group. As a preliminary test, a helioseismically detected active region that first emerged on the far-side of the Sun in early July 2010 is incorporated into maps produced by ADAPT and then used in the Wang-Sheeley-Arge (WSA) model to simulate the corona and solar wind. The WSA model results, with and without far-side data included in the ADAPT global maps, are compared here with coronal EUV and in situ solar wind observations available from STEREO. We find that the observed and modeled values are in better agreement when including the far-side detection.