Data Sources

Below we detail the sources of the data we use to construct the boundary conditions of the HUXt forecasts.

Ambient Solar Wind Structure

The Wang-Sheeley-Arge (WSA) model

The WSA model is widely used in both research and operational space weather forecasting to estimate the ambient solar wind structure in the low heliosphere [1]. WSA is an empirical model that relates the structure of the coronal magnetic field to the solar wind flow speed. It takes as an input a synoptic map of the photospheric magnetic field structure, such as those produced by the National Solar Observatory's Global Oscillation Network Group (GONG).

CorTom

Professor Huw Morgan and his colleagues at the University of Aberystwyth developed a coronal rotational tomography method (CorTom) to estimate the density and flow speed of the solar wind in the upper corona and low heliosphere [2]. CorTom is applied to the STEREO SECCHI Coronagraph data to estimate the solar wind flow speed at 8 solar radii, and these speeds are used as an inner boundary condition to HUXt, after they have been mapped to 21.5 solar radii.

BRaVDA

The Burger Radial Variational Data Assimilation (BRaVDA) scheme is a variational data assimilation scheme that estimates the structure of the solar wind flow in the low heliosphere [3]. BRaVDA assimilates in-situ solar wind speed observations with model estimates of the solar wind speed structure, such as those provided by the WSA model. Following Turner et al. (2025) [4], we use BRaVDA output generated from assimilating the real-time solar wind speed observations from the L1 Lagrange point with output from the WSA model.

Cone CME parameters

NASA M2M Cone Files

The NASA Moon-to-Mars (M2M) Space Weather Analysis Office has forecasters that produce cone CME fits to coronagraph observations to enable real-time space weather forecasting. These are made publicly available by NASA's Coordinated Community Modelling Center (CCMC) via the Database of Notifications, Knowledge, and Information (DONKI) catalogue.

ACME

Professor Huw Morgan and his colleagues at the University of Aberystwyth developed an Automatic CME (ACME) characterisation methodology [5]. ACME is applied to the STEREO SECCHI Coronagraph data to automatically identify and characterise the spatial structure and flow of CMEs in the low heliosphere. From this, estimates of the cone CME paramters are derived which are then used with HUXt.