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Real-Time Solar Wind Prediction Based on SDO/AIA Coronal Hole Data

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Abstract

We present an empirical model based on the visible area covered by coronal holes close to the central meridian with the aim to predict the solar wind speed at 1 AU with a lead time of up to four days in advance with a time resolution of one hour. Linear prediction functions are used to relate coronal hole areas to solar wind speed. The function parameters are automatically adapted by using the information from the previous three Carrington Rotations. Thus the algorithm automatically reacts to the changes of the solar wind speed during different phases of the solar cycle. The adaptive algorithm was applied to and tested on SDO/AIA-193 Å observations and ACE measurements during the years 2011 – 2013, covering 41 Carrington Rotations. The solar wind needs on average 4.02±0.5 days to reach Earth. The algorithm produces good predictions for the 156 solar wind high-speed streams peak amplitudes with correlation coefficients of cc≈0.60. For 80 % of the peaks, the predicted arrival matches the ACE in situ measurements within a time window of 0.5 days. The same algorithm, using linear predictions, was also applied to predict the magnetic field strength in wind streams originating from coronal hole areas, but it did not give reliable predictions (cc≈0.15).

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Acknowledgements

We thank the referee for the careful evaluation of the paper and the helpful comments made to improve this paper. We acknowledge the NASA/SDO and the AIA teams. We acknowledge the ACE SWEPAM and MAG instrument teams and the ACE Science Center. The research leading to these results has received funding from the European Commission Seventh Framework Programme (FP7/2007-2013) under the grant agreement FP7 No. 263252 (COMESEP). T.R., A.M.V., and M.T. acknowledge the Austrian Science Fund (FWF): P24092-N16 and V195-N16. T.R. gratefully acknowledges support from NAWI Graz and the Forschungsstipendium by the University of Graz. B.V. acknowledges financial support by the Croatian Science Foundation under the project 6212 SOLSTEL.

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Authors and Affiliations

  1. Kanzelhöhe Observatory-IGAM, Institute of Physics, University of Graz, Universitätsplatz 5, 8010, Graz, Austria

    T. Rotter, A. M. Veronig & M. Temmer

  2. Faculty of Geodesy, Hvar Observatory, Zagreb, Croatia

    B. Vršnak

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  1. T. Rotter
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  2. A. M. Veronig
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Rotter, T., Veronig, A.M., Temmer, M. et al. Real-Time Solar Wind Prediction Based on SDO/AIA Coronal Hole Data. Sol Phys 290, 1355–1370 (2015). https://doi.org/10.1007/s11207-015-0680-5

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