An Efficient, Time-Dependent High Speed Stream Model and Application to Solar Wind Forecasts

SPACE WEATHER-THE INTERNATIONAL JOURNAL OF RESEARCH AND APPLICATIONS(2023)

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摘要
Predicting space weather effects of the solar wind requires knowing the location and properties of any embedded high speed streams (HSSs) or stream interactions regions (SIRs) that form as the fast solar wind catches up to slow preceding wind. Additionally, this background solar wind affects the evolution of coronal mass ejections. We present the Mostly Empirical Operation Wind with a High Speed Stream (MEOW-HiSS) model, which runs nearly instantaneously. This model is derived from magnetohydrodynamic (MHD) simulations of an idealized HSS emanating from a circular coronal hole. We split the MHD HSS radial profiles into small regions well-described by simple functions (e.g., flat, linear, exponential, sinusoidal) that can be constrained using the MHD values. We then determine how the region boundaries and the constraining values change with CH area and the radial distance of the HSS front. MEOW-HiSS only requires this area and distance to reproduce the corresponding radial profile with an error of less than 10% for most parameters. MEOW-HiSS produces profiles at any subsequent times with almost no loss in accuracy. We compare MEOW-HiSS results to four HSS observed in situ at 1 au. We present a method for determining MEOW-HiSS inputs from extreme ultra-violet images and use these values to hindcast the observed cases. We find average accuracies of 2.8 cm(-3) in the number density (50% error over the full profile), 56.7 km/s in the radial velocity (10%), 2.2 nT in the absolute radial magnetic field (50%), 1.6 nT in the absolute longitudinal magnetic field (50%), and 7 x 10(4) K in the temperature (50%).
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solar wind forecasts
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