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Abstract We report on a flare-driven coronal rain event observed along postflare loops during the decay phase of an X1.6-class solar flare. Although high-resolution studies of flare-driven coronal rain have been conducted, imaging spectroscopic studies are rare due to observational difficulties. Our observation taken with the Fast Imaging Solar Spectrograph, installed at the 1.6 m Goode Solar Telescope of the Big Bear Solar Observatory, provided unprecedented high-resolution spectroscopic imaging data of coronal rain in the Hαand Caii854.2 nm lines. We identify two locations along postflare loops with rain displaying distinctly different thermal properties, different Doppler velocities, and different patterns of acceleration and deceleration. We also observed intense brightening at one footpoint of coronal rain, where the spectroscopic analysis reveals an energy conversion process resulting in significant localized chromospheric heating. We thoroughly investigate the footpoint brightening Doppler velocities and compare their spectral line profiles to typical flare-ribbon line profiles. We estimate the spatial scale of the fine structure of the coronal rain and the footpoint brightening. Our results provide important insights into the dynamic and thermal properties of flare-driven coronal rain and the related chromospheric response, which will help validate the flare-driven modeling of coronal rain. 

Context.The elemental abundance in the solar corona differs from that in the photosphere, with low first ionization potential (FIP) elements showing enhanced abundances, a phenomenon known as the FIP effect. This effect is considered to be driven by ponderomotive forces associated with magnetohydrodynamic (MHD) waves, particularly incompressible transverse waves. Aims.We aim to investigate the relationship between coronal abundance fractionation and transverse MHD waves in the chromosphere. We focus on analyzing the spatial correlation between the FIP fractionation and these waves, while exploring wave properties to validate the ponderomotive-force-driven fractionation model. Methods.We analyzed the Hαdata from the Fast Imaging Solar Spectrograph of the Goode Solar Telescope to detect chromospheric transverse MHD waves, and Si X(low FIP) and S X(high FIP) spectra from the EUV Imaging Spectrometer on board Hinode to determine the relative abundance in an active region. By extrapolating linear-force-free magnetic fields with Solar Dynamics Observatory/Helioseismic and Magnetic Imager magnetograms, we examine the connection between chromospheric waves and coronal composition. Around 400 wave packets were identified, and their properties, including the period, velocity amplitude, propagation speed, and propagation direction, were studied. Results.These chromospheric transverse MHD waves, mostly incompressible or weakly compressible, are found near loop footpoints, particularly in the sunspot penumbra and superpenumbral fibrils. The highly fractionated coronal region is associated with areas where these waves were detected within closed magnetic fields. Our examination of the statistics of wave properties revealed that downward-propagating low-frequency waves are particularly prominent, comprising about 43% of the detected waves. Conclusions.The correlation between abundance fractionation and transverse MHD waves, along with wave properties, supports the hypothesis that FIP fractionation occurs due to the ponderomotive force from transverse MHD waves in the chromosphere. Additionally, the observed characteristics of these chromospheric waves provide valuable observational constraints for understanding the FIP fractionation process. 

Abstract We report the detection of transverse magnetohydrodynamic waves, also known as Alfvénic waves, in the chromospheric fibrils of a solar-quiet region. Unlike previous studies that measured transversal displacements of fibrils in imaging data, we investigate the line-of-sight (LOS) velocity oscillations of the fibrils in spectral data. The observations were carried out with the Fast Imaging Solar Spectrograph of the 1.6 m Goode Solar Telescope at the Big Bear Solar Observatory. By applying spectral inversion to the Hαand Caii8542 Å line profiles, we determine various physical parameters, including the LOS velocity in the chromosphere of the quiet Sun. In the Hαdata, we select two adjacent points along the fibrils and analyze the LOS velocities at those points. For the time series of the velocities that show high cross-correlation between the two points and do not exhibit any correlation with intensity, we interpret them as propagating Alfvénic wave packets. We identify a total of 385 Alfvénic wave packets in the quiet-Sun fibrils. The mean values of the period, velocity amplitude, and propagation speed are 7.5 minutes, 1.33 km s⁻¹, and 123 km s⁻¹, respectively. We find that the detected waves are classified into three groups based on their periods, namely, 3, 5, and 10 minute bands. Each group of waves exhibits distinct wave properties, indicating a possible connection to their generation mechanism. Based on our results, we expect that the identification of Alfvénic waves in various regions will provide clues to their origin and the underlying physical processes in the solar atmosphere. 

Abstract A multilayer spectral inversion (MLSI) model has recently been proposed for inferring the physical parameters of plasmas in the solar chromosphere from strong absorption lines taken by the Fast Imaging Solar Spectrograph (FISS). We apply a deep neural network (DNN) technique in order to produce the MLSI outputs with reduced computational costs. We train the model using two absorption lines, H α and Ca ii 8542 Å, taken by FISS, and 13 physical parameters obtained from the application of MLSI to 49 raster scans (∼2,000,000 spectra). We use a fully connected network with skip connections and multi-branch architecture to avoid the problem of vanishing gradients and to improve the model’s performance. Our test shows that the DNN successfully reproduces the physical parameters for each line with high accuracy and a computing time of about 0.3–0.4 ms per line, which is about 250 times faster than the direct application of MLSI. We also confirm that the DNN reliably reproduces the temporal variations of the physical parameters generated by the MLSI inversion. By taking advantage of the high performance of the DNN, we plan to provide physical parameter maps for all the FISS observations, in order to understand the chromospheric plasma conditions in various solar features.