New Homogeneous Dataset of Solar EUV Synoptic Maps from SOHO/EIT and SDO/AIA

Abstract

Synoptic maps of solar EUV intensities have been constructed for many decades in order to display the distribution of the different EUV emissions across the solar surface, with each map representing one Carrington rotation (i.e. one rotation of the Sun). This article presents a new solar EUV synoptic map dataset based on full-disk images from the Solar and Heliospheric Observatory/Extreme Ultraviolet Imaging Telescope (SOHO/EIT) and Solar Dynamics Observatory/Atmospheric Imaging Assembly (SDO/AIA). In order to remove the significant and complicated drift of EIT and AIA EUV intensities due to sensor degradation, we construct the synoptic maps in standardized intensity scale. We describe a method of homogenizing the SOHO/EIT maps with SDO/AIA maps by transforming the EIT intensity histograms to AIA levels. The new maps cover the years from 1996 to 2018 with 307 SOHO/EIT and 116 SDO/AIA synoptic maps, respectively. These maps provide a systematic and homogeneous view of the entire solar surface in four EUV wavelengths, and are well suited, e.g., for studying long-term coronal hole evolution.

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

“…The two other wavelengths, 171 Å and 304 Å, also depict surprisingly different LLCH results for EIT and AIA, despite being the same wavelengths. Apparently, the contrast of different solar features even in the same wavelength is different in the two instruments, most likely due to instrumental reasons, e.g., differences in image contrast which are not compensated by the overall intensity histogram transformations employed by Hamada, Asikainen, and Mursula (2019). The AIA 193 Å line and EIT 195 Å give the closest agreement even for LLCH, when the four corresponding EIT/AIA wavelengths are compared.…”

“…Synoptic Maps Hamada, Asikainen, and Mursula (2019) recently constructed a new homogeneous database of synoptic EUV maps from SOHO/EIT and SDO/AIA full-disk images (http://satdat.oulu. fi/solar_data/).…”

“…by solar cycle (SC) variation, or by the degradation of EIT and AIA sensors. The homogenized maps produced in this way are well suited for studying CHs (Hamada, Asikainen, and Mursula, 2019). The SOHO/EIT and SDO/AIA based synoptic EUV maps span from 1996 to 2018 and from 2010 to 2018, respectively (see Table 2).…”

“…A recently developed algorithm by Hamada et al (2018), which we also use in this article, attempts to overcome these problems by detecting CHs in four different wavelengths and using magnetogram data to ensure that the detected dark CH candidates have a sufficiently unipolar magnetic field to differentiate them from dark filament channels which do not have a preferred net magnetic polarity. Hamada, Asikainen, and Mursula (2019) have recently constructed a new, homogenized set of EUV synoptic maps from the Solar and Heliospheric Observatory/Extreme ultraviolet Imaging Telescope (SOHO/EIT) and the Solar Dynamics Observatory/Atmospheric Imaging Assembly (SDO/AIA) measurements extending from 1996 and 2010 to 2018, respectively. These synoptic maps have been constructed using the same spatial resolution, which reduces the differences between the maps that have different resolutions.…”

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

“…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].…”