most citedQuantifying Uncertainties in Solar Wind Forecasting Due to Incomplete Solar Magnetic Field Information

4 citations · 4 across the 3 of their papers we have counts for

collaborators

7 papers

astro-ph.SR2025

Neural Enhancement of the Traditional Wang-Sheeley-Arge Solar Wind Relation

Prateek Mayank, Enrico Camporeale, Arpit K. Shrivastav +2

The Wang-Sheeley-Arge (WSA) model has been the cornerstone of operational solar wind forecasting for nearly two decades, owing to its simplicity and physics-based formalism. Howeve…

astro-ph.SR2025

Evaluating Solar Wind Forecast Using Magnetic Maps That Include Helioseismic Far-Side Information

Stephan G. Heinemann, Dan Yang, Shaela I. Jones +5

To model the structure and dynamics of the heliosphere well enough for high-quality forecasting, it is essential to accurately estimate the global solar magnetic field used as inne…

astro-ph.SR2025

What Causes Errors in Wang-Sheeley-Arge Solar Wind Modeling at L1 ?

Satabdwa Majumdar, Martin Reiss, Karin Muglach +1

Previous ambient solar wind (SW) validation studies have reported on discrepancies between modeled and observed SW conditions at L1. They indicated that a major source of discrepan…

astro-ph.SR2025

Ensemble Modeling of the Solar Wind Flow with Boundary Conditions Governed by Synchronic Photospheric Magnetograms. I. Multi-point Validation in the Inner Heliosphere

Dinesha V. Hegde, Tae K. Kim, Nikolai V. Pogorelov +2

The solar wind (SW) is a vital component of space weather, providing a background for solar transients such as coronal mass ejections, stream interaction regions, and energetic par…

astro-ph.SR20254 cited

Quantifying Uncertainties in Solar Wind Forecasting Due to Incomplete Solar Magnetic Field Information

Stephan G. Heinemann, Jens Pomoell, Ronald M. Caplan +5

Solar wind forecasting plays a crucial role in space weather prediction, yet significant uncertainties persist due to incomplete magnetic field observations of the Sun. Isolating t…

astro-ph.SR2025

Quantitative Image-Based Validation Framework for Assessing Global Coronal Magnetic Field Models

Christopher E. Rura, Vadim M. Uritsky, Shaela I. Jones +3

Coronagraph observations provide key information about the orientation of the Sun's magnetic field. Previous studies used various algorithms to segment quasi-radial features in cor…