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<p>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 inner boundary condition in solar wind models. However, our understanding of the photospheric magnetic field topology is inherently constrained by the limitation of systematically observing the Sun from only one vantage point, Earth. To address this challenge, we introduce global magnetic field maps that assimilate far-side active regions derived from helioseismology into solar wind modeling. Through a comparative analysis between the combined surface flux transport and helioseismic Far-side Active Region Model (FARM) and the base Surface Flux Transport Model without far-side active regions (SFTM), we assess the feasibility and efficacy of incorporating helioseismic far-side information in space weather forecasting. We are employing the Wang-Sheeley-Arge solar wind (WSA) model for statistical evaluation and leveraging the EUropean Heliospheric FOrecasting Information Asset (EUHFORIA), a three-dimensional heliospheric MHD model, to analyze a case study. Using the WSA model, we show that including far-side magnetic data improves solar wind forecasts for 2013 – 2014 by up to <InlineEquation ID="IEq1"> <EquationSource Format="MATHML"><math> <mn>50</mn> <mi mathvariant="normal">%</mi> </math></EquationSource> <EquationSource Format="TEX">$50\%$</EquationSource> </InlineEquation> in correlation and <InlineEquation ID="IEq2"> <EquationSource Format="MATHML"><math> <mn>3</mn> <mi mathvariant="normal">%</mi> </math></EquationSource> <EquationSource Format="TEX">$3\%$</EquationSource> </InlineEquation> in root mean square error and mean absolute error, especially near the Earth and Solar TErrestrial RElations Observatory – Ahead (STEREO-A). Additionally, our 3D modeling shows significant localized differences in heliospheric structure that can be attributed to the presence or absence of active regions in the magnetic maps used as input boundaries. This highlights the importance of including far-side information to more accurately model and predict space weather effects caused by solar wind, solar transients, and geomagnetic disturbances.</p>

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

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年11月10日

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  • Stephan G. Heinemann,
  • Dan Yang,
  • Shaela I. Jones,
  • Jens Pomoell,
  • Eleanna Asvestari,
  • Carl J. Henney,
  • Charles N. Arge,
  • Laurent Gizon

摘要

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 inner boundary condition in solar wind models. However, our understanding of the photospheric magnetic field topology is inherently constrained by the limitation of systematically observing the Sun from only one vantage point, Earth. To address this challenge, we introduce global magnetic field maps that assimilate far-side active regions derived from helioseismology into solar wind modeling. Through a comparative analysis between the combined surface flux transport and helioseismic Far-side Active Region Model (FARM) and the base Surface Flux Transport Model without far-side active regions (SFTM), we assess the feasibility and efficacy of incorporating helioseismic far-side information in space weather forecasting. We are employing the Wang-Sheeley-Arge solar wind (WSA) model for statistical evaluation and leveraging the EUropean Heliospheric FOrecasting Information Asset (EUHFORIA), a three-dimensional heliospheric MHD model, to analyze a case study. Using the WSA model, we show that including far-side magnetic data improves solar wind forecasts for 2013 – 2014 by up to 50 % $50\%$ in correlation and 3 % $3\%$ in root mean square error and mean absolute error, especially near the Earth and Solar TErrestrial RElations Observatory – Ahead (STEREO-A). Additionally, our 3D modeling shows significant localized differences in heliospheric structure that can be attributed to the presence or absence of active regions in the magnetic maps used as input boundaries. This highlights the importance of including far-side information to more accurately model and predict space weather effects caused by solar wind, solar transients, and geomagnetic disturbances.