Statistical Approach on Differential Emission Measure of Coronal Holes using the CATCH Catalog

Coronal holes are large-scale structures in the solar atmosphere that feature a reduced temperature and density in comparison to the surrounding quiet Sun and are usually associated with open magnetic fields. We perform a differential emission measure analysis on the 707 non-polar coronal holes in the Collection of Analysis Tools for Coronal Holes (CATCH) catalog to derive and statistically analyze their plasma properties (i.e. temperature, electron density, and emission measure). We use intensity filtergrams of the six coronal EUV filters from the Atmospheric Imaging Assembly onboard the Solar Dynamics Observatory, which cover a temperature range from $\approx10^{5.5}$ ≈ 10 5.5 to $10^{7.5}~\mbox{K}$ 10 7.5 K . Correcting the data for stray and scattered light, we find that all coronal holes have very similar plasma properties with an average temperature of $0.94 \pm0.18~\mbox{MK}$ 0.94 ± 0.18 MK , a mean electron density of $(2.4 \pm0.7) \times10^{8}~\mbox{cm}^{-3}$ ( 2.4 ± 0.7 ) × 10 8 cm − 3 , and a mean emission measure of $(2.8 \pm1.6) \times10^{26}~\mbox{cm}^{-5}$ ( 2.8 ± 1.6 ) × 10 26 cm − 5 . The temperature distribution within the coronal holes was found to be largely uniform, whereas the electron density shows a 30 to 40% linear decrease from the boundary towards the inside of the coronal hole. At distances greater than 20″ ($\approx15~\mbox{Mm}$ ≈ 15 Mm ) from the nearest coronal hole boundary, the density also becomes statistically uniform. The coronal hole temperature may show a weak solar-cycle dependency, but no statistically significant correlation of plasma properties with solar-cycle variations could be determined throughout the observed period between 2010 and 2019.

Differential Emission Measure Plasma Diagnostics of a Long-Lived Coronal Hole

We use Solar Dynamics Observatory (SDO)/Atmospheric Imaging Assembly (AIA) data to reconstruct the plasma properties from differential emission measure (DEM) analysis for a previously studied long-lived, low-latitude coronal hole (CH) over its lifetime of ten solar rotations. We initially obtain a non-isothermal DEM distribution with a dominant component centered around 0.9 MK and a secondary smaller component at 1.5 – 2.0 MK. We find that deconvolving the data with the instrument point spread function (PSF) to account for long-range scattered light reduces the secondary hot component. Using the 2012 Venus transit and a 2013 lunar eclipse to test the efficiency of this deconvolution, significant amounts of residual stray light are found for the occulted areas. Accounting for this stray light in the error budget of the different AIA filters further reduces the secondary hot emission, yielding CH DEM distributions that are close to isothermal with the main contribution centered around 0.9 MK. Based on these DEMs, we analyze the evolution of the emission measure (EM), density, and averaged temperature during the CH’s lifetime. We find that once the CH is clearly observed in EUV images, the bulk of the CH plasma reveals a quite constant state, i.e. temperature and density reveal no major changes, whereas the total CH area and the photospheric magnetic fine structure inside the CH show a distinct evolutionary pattern. These findings suggest that CH plasma properties are mostly “set” at the CH formation or/and that all CHs have similar plasma properties.

GRID-SITES: Gridded Solar Iterative Temperature Emission Solver for Fast DEM Inversion

The increasing size of solar datasets demands highly efficient and robust analysis methods. This paper presents an approach that can increase the computational efficiency of differential emission measure (DEM) inversions by an order of magnitude or higher, with the efficiency factor increasing with the size of the input dataset. The method, named the Gridded Solar Iterative Temperature Emission Solver (Grid-SITES) is based on grouping pixels according to the similarity of their intensities in multiple channels, and solving for one DEM per group. This is shown to be a valid approach, given a sufficiently high number of grid bins for each channel. The increase in uncertainty arising from the quantisation of the input data is small compared to the general measurement and calibration uncertainties. In this paper, we use the Solar Iterative Temperature Emission Solver (SITES) as the core method for the DEM inversion, although Grid-SITES provides a general framework which may be used with any DEM inversion method, or indeed any large multi-dimensional data inversion problem. The method is particularly efficient for processing larger images, offering a factor of 30 increase in speed for a 10 megapixel image. For a time series of observations, the gridded results can be passed sequentially to each new image, with new populated bins added as required. This process leads to increasing efficiency with each new image, with potential for a ${\approx\,}100$≈100 increase in efficiency dependent on the size of the images.

SITES: Solar Iterative Temperature Emission Solver for Differential Emission Measure Inversion of EUV Observations

Extreme ultraviolet (EUV) images of the optically-thin solar corona in multiple spectral channels give information on the emission as a function of temperature through differential emission measure (DEM) inversions. The aim of this paper is to describe, test, and apply a new DEM method named the Solar Iterative Temperature Emission Solver (SITES). The method creates an initial DEM estimate through a direct redistribution of observed intensities across temperatures according to the temperature response function of the measurement, and iteratively improves on this estimate through calculation of intensity residuals. It is simple in concept and implementation, is non-subjective in the sense that no prior constraints are placed on the solutions other than positivity and smoothness, and can process a thousand DEMs a second on a standard desktop computer. The resulting DEMs replicate model DEMs well in tests on Atmospheric Imaging Assembly/Solar Dynamics Observatory (AIA/SDO) synthetic data. The same tests show that SITES performs less well on very narrow DEM peaks, and should not be used for temperature diagnostics below ${\approx\,}0.5~\mbox{MK}$≈0.5MK in the case of AIA observations. The SITES accuracy of inversion compares well with two other established methods. A simple yet powerful new method to visualize DEM maps is introduced, based on a fractional emission measure (FEM). Applied to a set of AIA full-disk images, the SITES method and FEM visualization show very effectively the dominance of certain temperature regimes in different large-scale coronal structures. The method can easily be adapted for any multi-channel observations of optically-thin plasma and, given its simplicity and efficiency, will facilitate the processing of large existing and future datasets.

Broadening of the differential emission measure by multi-shelled and turbulent loops

Context. Broad differential emission measure (DEM) distributions in the corona are a sign of multi-thermal plasma along the line-of-sight. Traditionally, this is interpreted as evidence of multi-stranded loops. Recently, however, it has been shown that multi-stranded loops are unlikely to exist in the solar corona, because of their instability to transverse perturbations. Aims. We aim to test if loop models subject to the transverse wave-induced Kelvin-Helmholtz (TWIKH) instability result in broad DEMs, potentially explaining the observations. Methods. We took simulation snapshots and compute the numerical DEM. Moreover, we performed forward-modelling in the relevant AIA channels before reconstructing the DEM. Results. We find that turbulent loop models broaden their initial DEM, because of the turbulent mixing. The width of the DEM is determined by the initial temperature contrast with the exterior. Conclusions. We conclude that impulsively excited loop models have a rather narrow DEM, but that continuously driven models result in broad DEMs that are comparable to the observations.