Improvements to the Empirical Solar Wind Forecast (ESWF) model

• Published in: Solar physics 2023-03, Vol.298 (3), p.45, Article 45
• Main Authors: Milošić, D., Temmer, M., Heinemann, S. G., Podladchikova, T., Veronig, A., Vršnak, B.
• Format: Article
• Language: English
• Subjects: Algorithms; Astrophysics and Astroparticles; Atmospheric Sciences; Coronal holes; Correlation coefficient; Correlation coefficients; Interplanetary space; Lead time; Magnetic fields; Mathematical models; Physics; Physics and Astronomy; Propagation; Rarefaction; Solar corona; Solar physics; Solar wind; Solar wind effects; Space Exploration and Astronautics; Space Sciences (including Extraterrestrial Physics; Streams; Sun; Velocity; Wind effects; Wind speed
• ISSN: 0038-0938; 1573-093X
• DOI: 10.1007/s11207-022-02102-5

The empirical solar wind forecast (ESWF) model in its current version 2.0 runs as a space-safety service in the frame of ESA’s Heliospheric Weather Expert Service Centre. The ESWF model forecasts the solar-wind speed at Earth with a lead time of 4 days. The algorithm uses an empirical relation found between the area of solar coronal-holes (CHs), as observed in EUV within a 15 ∘  meridional slice, and the in-situ measured solar-wind speed at 1 AU. This relation however, forecasts Gaussian type speed profiles, as the CH rotates in and out of the meridional slice, causing some discrepancy in the timing between forecasted and observed solar-wind speed. With adaptations to the ESWF 2.0 algorithm we improve the precision and accuracy of the ESWF speed profiles. For that we implement compression and rarefaction effects occurring between solar-wind streams of different velocities in interplanetary space. By considering the propagation times for plasma parcels between the Sun and Earth and their interactions, we achieve the asymmetrical shape of the speed profile that is characteristic of high-speed streams (HSS). By further implementing CH segmentation, co-latitude information and dynamic thresholding, we find that the newly developed ESWF 3.2 performs significantly better than ESWF 2.0. For a sample of 294 different HSSs, we derive a relative increase in hits of the timing and peak velocity by 13.9 % . The Pearson correlation coefficient increases by 14.3 % from 0.35 to 0.40.