The main objective of the NASA-NSF SWQU “A New-generation Software to Improve the Accuracy of Space Weather Predictions” effort is to develop a data-driven time-dependent model of the solar corona and heliosphere. This model will provide coronal and solar wind predictions and be made available to the public. One key component of this model is the use of a data-assimilation flux transport model to generate an ensemble of synchronic radial magnetic field maps to use as boundary conditions for the coronal field model. While flux transport models have long been established in the community, they are not open source or available for public use. We therefore are developing a new Open-source Flux Transport (OFT) software suite. The computational core of the OFT is the High-Performance Flux Transport code (HipFT). HipFT implements advection, diffusion, and data assimilation for the solar surface on a logically rectangular non-uniform spherical grid. It is written in Fortran and parallelized for use with multi-core CPUs and GPUs using a combination of OpenACC/MP directives and Fortran’s standard parallel ‘do concurrent’. To alleviate the strict time-step stability criteria for the diffusion equation, we use a Legendre polynomial extended stability Runge-Kutta super time-stepping algorithm (RKL2). The code is designed to be modular, incorporating various differential rotation, meridianal flow, super granular convective flow, and data assimilation models. Multiple realizations of the evolving flux will be computed in parallel using MPI in order to produce an ensemble of model outputs for uncertainty quantification. Here, we describe the initial implementation of the HipFT code and demonstrate its validation and performance. We use an analytic solution of surface diffusion and rigid rotational longitudinal velocity to validate the advection and diffusion implementations. We also compare realistic flux transport test problems against the established AFT flux transport code.

The National Research Council published a report on Enhancing the Effectiveness of Team Science in 2015. This report identified 7 fundamental challenges that large research teams, such as the NASA DRIVE Science Centers (DSC), might face including: high diversity of membership, deep knowledge integration, large size, goal misalignment, permeable boundaries, geographic dispersion, and high task interdependence. In Phase I, the COFFIES DSC formed a Center Effectiveness Team (CET) to identify and help overcome these and other unique challenges, including those introduced by the COVID-19 pandemic. CET members have focused on finding and exploring novel ways to align and direct the Science Teams with the goal of enabling breakthrough science. We will present the CET initiatives and implementations, and review the lessons learned for future large-scale science collaborations.

We present a new, multicomponent magnetic proxy for solar activity derived from full disk magnetograms that can be used in the specification and forecasting of the Sun’s radiative output. To compute this proxy we project Carrington maps, such as the synchronic Carrington maps computed with the Advective Flux Transport (AFT) surface flux transport model, to heliographic cartesian coordinates and determine the total unsigned flux as a function of absolute magnetic flux density. Performing this calculation for each day produces an array of time series, one for each flux density interval. Since many of these time series are strongly correlated, we use principal component analysis to reduce them to a smaller number of uncorrelated time series. We show that the first few principal components accurately reproduce widely used proxies for solar activity, such the the 10.7\,cm radio flux and the Mg core-to-wing ratio. This suggests that these magnetic time series can be used as a proxy for irradiance variability for emission formed over a wide range of temperatures.