AGS-PRF: Improving Space Weather and Space Climate Predictions by Investigating and Modeling Surface Flux Transport on the Sun

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The goal of this two-year postgraduate fellowship research project is to improve the forecasting capabilities of space climate and space weather models. Solar storms, which are one component of space weather, have the potential to do significant damage to satellites, power grids, and humans in space. Prediction of these eruptions from the solar surface is in its infancy and this project vastly improve the basis of the predictive models. The goals are to improve understanding of the flows on the Sun's surface, the interaction of these flows with the magnetic field, and how the flows combine with the magnetic field to impact the Sun's eleven year cycle and its dynamo. One very important task project is to produce the most accurate full-Sun maps of the magnetic field on the surface (the photosphere) to date. This is very timely as this model and its resulting products will be immediately useful to forecasters such as those at NOAA/SWPC (National Oceanographic and Atmospheric Administrations Space Weather Prediction Center). The Principle Investigator of this project is an early career scientist from an underrepresented minority who will work with undergraduate (REU) students to carry out the work.This project is based on the Advective Flux Transport (AFT) model, developed by the PI and her collaborators at the National Center for Atmospheric Research (NCAR). This is a surface flux transport model that advects the magnetic flux on the sun using observational data for of near-surface flows. It can also assimilate magnetogram data for increased realism. Some of the stated goals of this project are to promote AFT as a cross discipline bridge, and to improve the space weather and climate forecasting capabilities of the model. This will be done, in part, by providing synchronic maps as magnetic source data, interfacing with dynamo models to connect with internal dynamics, investigating active region source properties, incorporating complex far-side active region emergence and investigate ever more sophisticated data assimilation techniques. Accomplishing these goals will help provide the knowledge needed to reproduce a range of cycle amplitudes and variations, potentially including the recovery from a Maunder-type Grand minimum and improve our understanding of the role of surface dynamics in modulating the solar activity cycle which will extend the predictive capability of flux transport models.