108. Cool and hot emission in a recurring active region jet

February 28, 2020, from uksp_nug_ed

Author: Sargam M. Mulay (now University of Glasgow) Giulio Del Zanna, and Helen Mason at the University of Cambridge.

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Introduction

Solar jets are small scale energetic events that eject collimated plasma in the solar atmosphere. The appearance of jets in different magnetic environments (quiet sun, active region, and coronal holes) and their association with various explosive solar events (surges, nonthermal type-III radio burst, hard X-ray emission, and solar flares, etc.) make them most interesting candidates for space-weather studies.

Figure 1. Movie of the evolution of the AR jet in the IRIS SJI Si IV window and Si IV raster. The black vertical line shows the IRIS slit position.

Due to the dynamic nature of jets, they are difficult to observe simultaneously using imaging instruments and spectrographs. We were fortunate to find a simultaneous observation in the existing database. We carried out a comprehensive analysis of the cool (log T [K] < 5.7 (0.5 MK)) and hot (log T [K] > 6.0 (1.3 MK)) components of recurring active region jets (AR jets) using both spectroscopic observations from the Interface Region Imaging Spectrograph (IRIS; [3]) and imaging observations from the slit-jaw imager (IRIS/SJI), the Solar Dynamics Observatory Atmospheric Imaging Assembly (AIA; [8]) and the Hinode X-ray Telescope (XRT; [7]). A direct comparison of cool and hot plasma in AR jets has been carried out for the first time and the study provided important clues about their thermal structure.

Overview and kinematics

The homologous and recurrent AR jets were observed on July 10, 2015 (from 07:29 to 08:35 UT). They originated from the eastern boundary of active region NOAA 12381 and the footpoint of the jet was embedded in the penumbra of the trailing sunspot. A fine, multi-threaded structure of the jet “spire” was observed in multithermal AIA and SJI channels (see the movie in Fig. 1). Here, we measured the physical parameters for the AR jet-4 (observed during 08:19:07 – 08:30:27 UT) using Si IV 1402.77 Å and O IV 1401.16 Å lines.

Figure 2. Left panel: IRIS raster images of Si IV (raster’s start and end time - 08:18:46 and 08:35:11 UT) shows (a) intensity, (b) Doppler and (c) non-thermal velocities. Middle panel:(d)-(e) IRIS Slit-Jaw images (SJI) and (f) Fe XVIII emission derived from AIA 94 A channel. Right panel: (g)-(h) the XRT images and (i) temperature map of the jet. (The images are adapted from Mulay et al. 2017 and Chapter 7 of Mulay 2018)

The wavelength calibration was carried out using the photospheric O I 1355.6 Å line. Non-Gaussian Si IV line profiles (with a narrow core and broad wings) were seen at various pixels and the intensities were calculated by summing the total intensity under the line profile. An intensity raster map was created (see panel (a) of Fig. 2) and the Doppler velocities were obtained for the spire (green boxed region, -32±6 km/s, blue-shift) and footpoint region of the jet (yellow boxed region, 13±4 km/s, red-shift) (see panel (b) of Fig. 2). By considering that a single Gaussian is a good approximation for the core of the line, the Si IV line was fitted with single Gaussian and the nonthermal velocities (see panel (c) of Fig. 2) were measured at similar locations (spire – 69±6 and footpoint – 53±14 km/s).

Temperature structure of the jet

The temperature of the jet spire and footpoint regions (green and yellow boxed regions) was obtained by performing differential emission measure (DEM) analysis in the temperature interval 4.1<log T [K]<7.0. In order to combine the spectra from the IRIS (Si IV (log T [K] = 4.9) and O IV (log T [K] = 5.15) lines) and the images from the AIA (94, 131, 171, 193, 211, and 335 Å channels) in the DEM analysis, we substantially modified the xrt_dem_iterative2.pro routine [12]. This is the first time that such an analysis has been carried out, and the IRIS lines provided a better constraint on the lower temperatures (log T [K] < 5.4) for the DEMs.

The coalignment of AIA images with IRIS raster images was tricky for a number of reasons such as different exposure times, the sensitivity of the AIA channels to a broad range of temperatures, the temporal and spatial resolution of the IRIS slit, etc. The coalignment method given by [4] was followed and the time-averaged images for each AIA channel were obtained (see panels (a)-(d) of Fig. 3). The CHIANTI atomic database ([2], [6]), contribution functions of the Si IV and O IV lines, electron number densities from O IV lines (spire – 2.0×1010 and footpoint – 7.6×1010 cm-3) and the photospheric abundances by [1] were used in this analysis.

Figure 3. Top panel - (a)-(b) IRIS raster images and (c)-(d) time-averaged AIA images. Bottom panel - (e) DEM obtained using AIA images and IRIS spectra and (f) DEM obtained only using AIA images. (The images are adapted from Mulay et al. 2017 and Chapter 7 of Mulay 2018)

A best-fit DEM for the footpoint is shown in panel (e) of Fig. 3. By randomly varying the input intensities by 20%, the uncertainties on the DEM were obtained and they are plotted as 50% (blue), 80% (red), and 95% (yellow) of the solutions closest to best-fit DEM. The DEM curve shows strong cool emission in the footpoint along with hot emission which peaked at log T [K] = 6.5 with peak DEM of 7×1021 cm-5 K-1. The total EM (9.7×1031 cm-5) was obtained by integrating DEM over the temperature interval, 4.1 < log T [K] < 7.0. Further, we compared this AIA+IRIS DEM with the DEM that we obtained using only AIA EUV images (see panel (f) of Fig. 3). Because of the lower sensitivity of AIA EUV channels for log T [K] < 5.2, the DEMs were calculated for the temperature interval, 5.2 < log T [K] < 7.0. The DEM curve shows a similar peak temperature log T [K] = 6.5 as that obtained for AIA+IRIS DEM but a slightly higher peak DEM of 1.1×1022 cm-5 K-1 was obtained for the AIA DEM. The total EM (3.1×1028 cm-5) calculated for the AIA DEM in the temperature range 5.2 < log T [K] < 7.0 was found to be almost three orders of magnitude lower than that obtained for AIA+IRIS DEM. Both DEM curves fall sharply as there is no constraint on the higher temperatures (log T [K] > 6.6) of DEMs.

In order to get a reliable estimate of higher temperatures (log T [K] > 6.2), we estimated Fe XVIII 93.932 Å emission (see panels (f) of Fig. 2 and (d) of Fig. 3) from the AIA 94 Å channel using the empirical formula (I(Fe XVIII (93.93 Å)) = I(94 Å) – I(211 Å)/120 – I(171 Å)/450) given by [5]. The images show a clear indication of Fe XVIII emission at the footpoint and their comparison with simultaneous SJI images show the existence of cool plasma (log T [K] = 4.9-5.1) at the same location (see panels (d)-(f) of Fig. 2). The average temperature of log T [K] = 6.5 was obtained at the footpoint (shown at later phase of the jet-4 because of unavailability of XRT data during the jet-4) using filter-ratio (for details see Sect. 5.1 of [11]) of two XRT channels (see panels (g)-(i) of Fig. 2). The DEM weighted average temperature of log T [K] = 6.5 was obtained for the footpoint which showed a good agreement with the XRT temperature. These results indicate that Fe XVIII emission comes from the bulk plasma which was at T~3 MK but not from the plasma at temperature (log T [K] = 6.85 (7 MK)) that correspond to peak abundance for Fe XVIII.

Conclusions

We have carried out a multi-instrument, multi-thermal analysis on an active region jet. A better constraint on the lower temperatures for the DEMs was obtained by including the IRIS spectra along with AIA images in the DEM analysis. A difference of three orders of magnitude between the total EM values indicate the presence of low-temperature plasma (log T [K] < 5.4) at the footpoint, while the SJI images and Fe XVIII emission maps of the footpoint of the jet showed the hot emission is co-spatially and co-temporally associated with cool emission within the resolution/cadence of the observations.

References

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