A Uniform Series of Low-Latitude Coronal Holes in 1973–2018

Abstract

Coronal holes (CHs) are regions in the solar corona characterized by plasma density lower than in the surrounding quiet Sun. Therefore they appear dark in images of the solar atmosphere made, e.g., in extreme ultraviolet (EUV). Identifying CHs on solar images is difficult since CH boundaries are not sharp, but typically obscured by magnetic structures of surrounding active regions. Moreover, the areas, shapes, and intensities of CHs appear differently in different wavelengths. Coronal holes have been identified both visually by experienced observers and, more recently, by automated detection methods using different techniques. In this article, we apply a recent, robust CH identification algorithm to a new set of homogenized EUV synoptic maps based on four EUV lines measured by the Solar and Heliospheric Observatory/Extreme ultraviolet Imaging Telescope (SOHO/EIT) in 1996–2018 and the Solar Dynamics Observatory/Atmospheric Imaging Assembly (SDO/AIA) in 2010–2018 and create corresponding CH synoptic maps. We also use CHs of the hand-drawn McIntosh archive (McA) from 1973–2009 to extend the CH database to earlier times. We discuss the success of the four EUV lines to find CHs at high or low latitudes, and confirm that the combined EIT 195 Å/AIA 193 Å series applies best for both polar and low-latitude CH detection. While the polar CH detection suffers from the vantage-point limitation, the low-latitude CH areas extracted from this line correlate with the McA CH data very well. Using the simultaneous measurements between EIT and McA and EIT and AIA, we scale the different data series to the same level and form the longest uniform series of low-latitude CHs in 1973–2018. We find that, while the solar cycle maxima of low-latitude CHs in the descending phase of Solar Cycles 21–23 attain roughly similar values, the corresponding maximum during Solar Cycle 24 is reduced by a factor of two. This suggests that magnetic flux emergence is crucial for the formation of low-latitude CHs.

Magnetic Storms During the Space Age: Occurrence and Relation to Varying Solar Activity

“…This year is known to be the record year of geomagnetic activity in space age (Mursula et al., 2015, 2017) and one of the record years of HSS occurrence (see Figure 2). In this year, the HSSs mainly originated from low‐latitude coronal holes (Gibson et al., 2009; Hamada et al., 2021; Mursula et al., 2017). Accordingly, the occurrence of HSS/CIR storms at this time was less strongly controlled by solar polar coronal holes than in the other cycles.…”

“…This year also marks the all‐time maximum of all HSS/CIR storms during the 65‐year time interval, as seen in the second panel of Figures 5 and 6. This year was the third most frequent year in high‐speed streams (see Figure 2) that mostly emanated from persistent, isolated low‐latitude coronal holes (Gibson et al., 2009; Hamada et al., 2021; Mursula et al., 2017).…”

“…In addition, there is also a related long‐term change in the solar magnetic field structure, which affects coronal holes and, thereby, the occurrence of HSS/CIRs and magnetic storms produced by them. In fact, while in the earlier, active cycles there were only small and short‐lived coronal holes at low latitudes (Fujiki et al., 2016), the declining phase of cycle 23 was characterized by rather large, persistent low‐latitude coronal holes (Gibson et al., 2009; Hamada et al., 2021), which led to a space age record activity of HSSs and geomagnetic activity in 2003 (Mursula et al., 2015). Another long‐term change is the recent weakening of solar polar fields (Smith & Balogh, 2008; Wang et al., 2009; Zhou & Smith, 2009) as the result of reduced emergence of new flux on the solar surface.…”

Instrument-To-Instrument translation: Instrumental advances drive restoration of solar observation series via deep learning

“…(1) The single channel discriminator for the magnetograms assures that the generated magnetograms correspond to the domain of real magnetograms, independent of their content. (2) The content of the image is bound by the multi channel discriminator, that verifies that the generated magnetograms are consistent with EUV filtergrams of the SDO domain. (3) From the identity transformation B-B, we truncate the magnetogram from the SDO input data and enforce the reconstruction of the same magnetogram (see Sect.…”

“…The automated homogenization of data sets provides an integral component for long-term studies (e.g., solar cycle studies, historic sunspots, studies of rare events) and for studies that combine data from multiple instruments. Especially when dealing with large amounts of data, the automatic adjustment can be faster and more consistent than treating the data sets of the individual instruments separately [1,2]. Data driven methods rely on the diversity and amount of data, and the inclusion of additional data sets can significantly increase the performance [3].…”