Ensemble Forecasts of Solar Wind Connectivity to 1 Rs using ADAPT-WSA

TL;DR

This paper introduces an ensemble forecasting method for solar wind connectivity to 1 Rs using ADAPT-WSA models, providing probabilistic source region predictions crucial for space weather analysis.

Contribution

The paper presents a novel ensemble forecast approach combining ADAPT-WSA models to generate probabilistic solar wind source region predictions.

Findings

Produces a 2D probability distribution of source regions.

Reflects complex source configurations with minimal assumptions.

Computationally efficient ensemble forecasting method.

Abstract

The solar wind which arrives at any location in the solar system is, in principle, relatable to the outflow of solar plasma from a single source location. This source location, itself usually being part of a larger coronal hole, is traceable to 1 Rs along the Sun's magnetic field, in which the entire path from 1 Rs to a location in the heliosphere is referred to as the solar wind connectivity. While not directly measurable, the connectivity between the near-Earth solar wind is of particular importance to space weather. The solar wind solar source region can be obtained by leveraging near-sun magnetic field models and a model of the interplanetary solar wind. In this article we present a method for making an ensemble forecast of the connectivity presented as a probability distribution obtained from a weighted collection of individual forecasts from the combined Air Force Data Assimilative Photospheric Flux Transport - Wang Sheeley Arge (ADAPT-WSA) model. The ADAPT model derives the photospheric magnetic field from synchronic magnetogram data, using flux transport physics and ongoing data assimilation processes. The WSA model uses a coupled set of potential field type models to derive the coronal magnetic field, and an empirical relationship to derive the terminal solar wind speed observed at Earth. Our method produces an arbitrary 2D probability distribution capable of reflecting complex source configurations with minimal assumptions about the distribution structure, prepared in a computationally efficient manner.