Gonzi, S. and Weinzierl, M. and Bocquet, F.‐X. and Bisi, M. M. and Odstrcil, D. and Jackson, B. V. and Yeates, A. R. and Jackson, D. R. and Henney, C. J. and Nikolos Arge, C. (2021) 'Impact of Inner Heliospheric Boundary Conditions on Solar Wind Predictions at Earth.', Space Weather, 19 (1). e2020SW002499.
Predictions of the physical parameters of the solar wind at Earth are at the core of operational space weather forecasts. Such predictions typically use line-of-sight observations of the photospheric magnetic field to drive a heliospheric model. The models Wang-Sheeley-Arge (WSA) and ENLIL for the transport in the heliosphere are commonly used for these respective tasks. Here we analyze the impact of replacing the potential field coronal boundary conditions from WSA with two alternative approaches. The first approach uses a more realistic nonpotential rather than potential approach, based on the Durham Magneto Frictional Code (DUMFRIC) model. In the second approach the ENLIL inner boundary conditions are based on Inter Planetary Scintillation observations (IPS). We compare predicted solar wind speed, plasma density, and magnetic field magnitude with observations from the WIND spacecraft for two 6-month intervals in 2014 and 2016. Results show that all models tested produce fairly similar output when compared to the observed time series. This is not only reflected in fairly low correlation coefficients (<0.3) but also large biases. For example, for solar wind speed some models have average biases of more than 150 km/s. On a positive note, the choice of coronal magnetic field model has a clear influence on the model results when compared to the other models in this study. Simulations driven by IPS data have a high success rate with regard to detection of the high speed solar wind. Our results also indicate that model forecasts do not degrade for longer forecast times.
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|Publisher Web site:||https://doi.org/10.1029/2020SW002499|
|Publisher statement:||©2020. The Authors. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.|
|Date accepted:||19 August 2020|
|Date deposited:||04 June 2021|
|Date of first online publication:||21 August 2020|
|Date first made open access:||04 June 2021|
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