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Automated Identification of Coronal Holes from Synoptic EUV Maps

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Abstract

Coronal holes (CHs) are regions of open magnetic field lines in the solar corona and the source of the fast solar wind. Understanding the evolution of coronal holes is critical for solar magnetism as well as for accurate space weather forecasts. We study the extreme ultraviolet (EUV) synoptic maps at three wavelengths (195 Å/193 Å, 171 Å and 304 Å) measured by the Solar and Heliospheric Observatory/Extreme Ultraviolet Imaging Telescope (SOHO/EIT) and the Solar Dynamics Observatory/Atmospheric Imaging Assembly (SDO/AIA) instruments. The two datasets are first homogenized by scaling the SDO/AIA data to the SOHO/EIT level by means of histogram equalization. We then develop a novel automated method to identify CHs from these homogenized maps by determining the intensity threshold of CH regions separately for each synoptic map. This is done by identifying the best location and size of an image segment, which optimally contains portions of coronal holes and the surrounding quiet Sun allowing us to detect the momentary intensity threshold. Our method is thus able to adjust itself to the changing scale size of coronal holes and to temporally varying intensities. To make full use of the information in the three wavelengths we construct a composite CH distribution, which is more robust than distributions based on one wavelength. Using the composite CH dataset we discuss the temporal evolution of CHs during the Solar Cycles 23 and 24.

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Notes

  1. After completing the analysis discussed in this article, it came to our knowledge that the Space Weather Lab synoptic maps, whose pixel values appeared to represent logarithmic pixel intensity in the numerical range from 0 to 255, correspond to 8-bit color table pixel values of the map used to plot the images (Karna, 2017, private communication). The erroneous synoptic maps have been in the public server for several years, and they have been used in a few publications, but have recently (November 2017) been corrected. Fortunately, the map used was monochromatic so that the color table values are proportional to the real pixel intensity. Thus, this is not a problem for the novel CH detection method presented in this article, which relies on contrasts between pixel values. However, a more significant problem might occur that can be related to the fact that the color table values clip the real pixel values below (above) the lower (upper) threshold. This clipping of pixel values is clearly seen in the SDO/AIA histograms of Figure 1.

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Acknowledgements

We acknowledge the financial support by the Academy of Finland to the ReSoLVE Centre of Excellence (projects 272157, 307411) as well as to project 257403. The EUV/magnetogram synoptic map data were obtained from the Stanford Solar Observatories Group ( http://sun.stanford.edu/synop/EIT/index.html ) and the Space Weather Lab at George Mason University (http://space_weather.gmu.edu/projects/ synop). The monthly sunspot areas were obtained from the Royal Observatory of Greenwich – USAF/NOAA Sunspot Data center ( https://solarscience.msfc.nasa.gov/greenwch.shtml ).

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  1. ReSoLVE Centre of Excellence, Space Climate Research Unit, University of Oulu, Oulu, Finland

    Amr Hamada, Timo Asikainen, Ilpo Virtanen & Kalevi Mursula

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  1. Amr Hamada
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Correspondence to Amr Hamada, Timo Asikainen, Ilpo Virtanen or Kalevi Mursula.

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Hamada, A., Asikainen, T., Virtanen, I. et al. Automated Identification of Coronal Holes from Synoptic EUV Maps. Sol Phys 293, 71 (2018). https://doi.org/10.1007/s11207-018-1289-2

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