Explore the vast range of titles available.

We have measured the perpendicular correlation length L⊥ of Alfvénic waves in the corona using data from the Daniel K. Inouye Solar Telescope (DKIST) Cryogenic Near Infrared Spectropolarimeter (Cryo-NIRSP) instrument. These data have high spatial resolution and were collected using a raster, enabling us to unambiguously identify the parallel and perpendicular directions with respect to the wave propagation. We find that the measured median L⊥ ≈ 3.5 Mm, which is about half the value found by previous measurements. We ascribe the smaller value measured here to the improved spatial resolution of DKIST. There is a gradual decrease of L⊥ as a function of frequency. We also computed the spatial correlation length of the observed static density structures and found that their typical correlation lengths of ≈8.4 Mm were significantly larger than those of the waves.

We present revised point-spread functions (PSFs) for the Atmospheric Imaging Assembly (AIA) on board the Solar Dynamics Observatory. These PSFs provide a robust estimate of the light diffracted by the meshes holding the entrance and focal plane filters and the light that is diffusely scattered over the detector by the microroughness of the mirrors. We first calibrate the diffracted light using flare images. Our modeling of the diffracted light provides reliable determinations of the mesh parameters and finds that about 24%–33% of the collected light is diffracted, depending on the AIA channel. Then, we fit the diffuse scattered light using partially lunar-occulted images. We find that the diffuse scattered light can be modeled as a superposition of two power-law functions that scatter light over the entire detector. The amount of diffuse scattered light ranges from 10% to 35%, depending on the AIA channel. In total, AIA diffracts and diffusely scatters about 37%–55% of the collected light over the detector. When correcting for this, bright image regions increase in intensity by about 30%, dark image regions decrease by up to 90%, and the associated differential emission measure analysis of solar features is affected accordingly. Finally, we compare the image reconstructions using our new PSFs to those from the AIA team and B. Poduval et al. We find that our PSFs outperform the others, better correcting for the flare diffraction pattern and far more accurately predicting long-distance scattered light in lunar occultations.

Coronal holes (CHs) are known to be sources of high-speed solar wind streams (HSSs), yet the physical mechanisms linking CH position and characteristics to solar wind (SW) behaviour remain unclear. Our results reveal that the latitude of CHs, especially smaller ones, combined with the heliographic latitude of the solar disk’s central point (B0 angle), plays a critical role in driving discrepancies in SW velocity across the heliosphere. To investigate this, we use archival data from STEREO-B, STEREO-A, and Earth to simulate an L5-L1 configuration, where L5 is a vantage point approximately behind Earth in its orbit (as proposed for the Vigil mission), and L1 is between Earth and the Sun where SW measurements are typically taken. We use these insights to develop a predictive algorithm for HSSs, beginning with an analysis of the separation angle and distances between L5 and L1. We then introduce a predictive indicator and empirical criteria based on CH properties and the B0 angle to adjust for changes in SW velocity at L1. Our results show that the L5 viewpoint demonstrates the capability to significantly improve the accuracy and lead times of HSS predictions, enhancing our understanding of the CH-HSS relationship and potentially improving space weather forecasting.

Coronal holes are usually defined as dark structures seen in the extreme ultraviolet and X-ray spectrum which are generally associated with open magnetic fields. Deriving reliably the coronal hole boundary is of high interest, as its area, underlying magnetic field, and other properties give important hints as regards high speed solar wind acceleration processes and compression regions arriving at Earth. In this study we present a new threshold-based extraction method, which incorporates the intensity gradient along the coronal hole boundary, which is implemented as a user-friendly SSW-IDL GUI. The Collection of Analysis Tools for Coronal Holes (CATCH) enables the user to download data, perform guided coronal hole extraction and analyze the underlying photospheric magnetic field. We use CATCH to analyze non-polar coronal holes during the SDO-era, based on 193 Å filtergrams taken by the Atmospheric Imaging Assembly (AIA) and magnetograms taken by the Heliospheric and Magnetic Imager (HMI), both on board the Solar Dynamics Observatory (SDO). Between 2010 and 2019 we investigate 707 coronal holes that are located close to the central meridian. We find coronal holes distributed across latitudes of about ± 60 ∘ , for which we derive sizes between 1.6 × 10 9 and 1.8 × 10 11  km 2 . The absolute value of the mean signed magnetic field strength tends towards an average of 2.9 ± 1.9  G. As far as the abundance and size of coronal holes is concerned, we find no distinct trend towards the northern or southern hemisphere. We find that variations in local and global conditions may significantly change the threshold needed for reliable coronal hole extraction and thus, we can highlight the importance of individually assessing and extracting coronal holes.

Forecasting the arrival of coronal mass ejections (CMEs) is vital for protecting satellites, power systems, and human spaceflight. We present the Heliospheric Observer for Predicting CME Arrival via Nonlinear Drag Assimilation (HELIOPANDA), a framework that integrates the drag-based model (DBM) with spacecraft observations using iterative parameter estimation and Kalman filter assimilation. We introduce a method for estimating the solar wind speed w and drag parameter γ, two key but usually unknown quantities controlling CME propagation, through direct solutions of the DBM equations. We tested the method on 4480 synthetic CME profiles spanning CME speeds of 200–3500 km s−1, solar wind speeds of 250–800 km s−1, and drag parameters of 0.1–1.0 × 10−7 km−1. The results demonstrate that the framework provides accurate reconstructions of the DBM input parameters, providing a solid basis for in situ and remote-sensing applications. By testing a single virtual spacecraft positioned at nine distances along the Sun–Earth line, HELIOPANDA achieved arrival-time errors as low as 0.6 hr for a 600 km s−1 CME and 1 hr for a 2500 km s−1 CME when the spacecraft was located 30 million km from the Sun. We developed a Kalman filter framework to assimilate noisy heliospheric data into the DBM, enabling recursive updates of CME kinematics and robust estimates of w and γ, and yielding Earth and Mars arrival-time predictions within 1–2 hr using 160 simulated hourly measurements. By combining DBM, parameter recovery, and data assimilation, HELIOPANDA provides a pathway to real-time, multipoint CME forecasts, suited to observations from Solar Orbiter, Parker Solar Probe, PUNCH, and planned L4/L5 missions.

We investigate the properties and relationship between Doppler velocity fluctuations and intensity fluctuations in the off-limb quiet Sun corona. These are expected to reflect the properties of Alfvénic and compressive waves, respectively. The data come from the Coronal Multichannel Polarimeter (COMP). These data were studied using spectral methods to estimate the power spectra, amplitudes, perpendicular correlation lengths, phases, trajectories, dispersion relations, and propagation speeds of both types of fluctuations. We find that most velocity fluctuations are due to Alfvénic waves but that intensity fluctuations come from a variety of sources, likely including fast and slow mode waves, as well as aperiodic variations. The relation between the velocity and intensity fluctuations differs depending on the underlying coronal structure. On short closed loops, the velocity and intensity fluctuations have similar power spectra and speeds. In contrast, on longer nearly radial trajectories, the velocity and intensity fluctuations have different power spectra, with the velocity fluctuations propagating at much faster speeds than the intensity fluctuations. Considering the temperature sensitivity of COMP, these longer structures are more likely to be closed fields lines of the quiet Sun rather than cooler open field lines. That is, we find the character of the interactions of Alfvénic waves and density fluctuations depends on the length of the magnetic loop on which they are traveling.

In a thorough study, we investigate the origin of a remarkable plasma and magnetic field configuration observed in situ on June 22, 2011, near L1, which appears to be a magnetic ejecta (ME) and a shock signature engulfed by a solar wind high-speed stream (HSS). We identify the signatures as an Earth-directed coronal mass ejection (CME), associated with a C7.7 flare on June 21, 2011, and its interaction with a HSS, which emanates from a coronal hole (CH) close to the launch site of the CME. The results indicate that the major interaction between the CME and the HSS starts at a height of 1.3 R ⊙ up to 3 R ⊙ . Over that distance range, the CME undergoes a strong north-eastward deflection of at least 30 ∘ due to the open magnetic field configuration of the CH. We perform a comprehensive analysis for the CME–HSS event using multi-viewpoint data (from the Solar TErrestrial RElations Observatories , the Solar and Heliospheric Observatory and the Solar Dynamics Observatory ), and combined modeling efforts (nonlinear force-free field modeling, Graduated Cylindrical Shell CME modeling, and the Forecasting a CME’s Altered Trajectory – ForeCAT model). We aim at better understanding its early evolution and interaction process as well as its interplanetary propagation and related in situ signatures, and finally the resulting impact on the Earth’s magnetosphere.

A plethora of coronal models, from empirical to more complex magnetohydrodynamic (MHD) ones, are being used for reconstructing the coronal magnetic field topology and estimating the open magnetic flux. However, no individual solution fully agrees with coronal hole observations and in situ measurements of open flux at 1 au, as there is a strong deficit between the model and observations contributing to the known problem of the missing open flux. In this paper, we investigate the possible origin of the discrepancy between modeled and observed magnetic field topology by assessing the effect on the simulation output by the choice of the input boundary conditions and the simulation setup, including the choice of numerical schemes and the parameter initialization. In the frame of this work, we considered four potential field source surface-based models and one fully MHD model, different types of global magnetic field maps, and model initiation parameters. After assessing the model outputs using a variety of metrics, we conclude that they are highly comparable regardless of the differences set at initiation. When comparing all models to coronal hole boundaries extracted by extreme-ultraviolet filtergrams, we find that they do not compare well. This mismatch between observed and modeled regions of the open field is a candidate contributing to the open flux problem.

A coronal hole formed as a result of a quiet-Sun filament eruption close to the solar disk center on 2014 June 25. We studied this formation using images from the Atmospheric Imaging Assembly (AIA), magnetograms from the Helioseismic and Magnetic Imager, and a differential emission measure analysis derived from the AIA images. The coronal hole developed in three stages: (1) formation, (2) migration, and (3) stabilization. In the formation phase, the emission measure (EM) and temperature started to decrease 6 hr before the filament erupted. Then, the filament erupted and a large coronal dimming formed over the following 3 hr. Subsequently, in a phase lasting 15.5 hr, the coronal dimming migrated by ≈150″ from its formation site to a location where potential field source surface extrapolations indicate the presence of open magnetic field lines, marking the transition into a coronal hole. During this migration, the coronal hole drifted across quasi-stationary magnetic elements in the photosphere, implying the occurrence of magnetic interchange reconnection at the boundaries of the coronal hole. In the stabilization phase, the magnetic properties and area of the coronal hole became constant. The EM of the coronal hole decreased, which we interpret as a reduction in plasma density due to the onset of plasma outflow into interplanetary space. As the coronal hole rotated toward the solar limb, it merged with a nearby preexisting coronal hole. At the next solar rotation, the coronal hole was still apparent, indicating a lifetime of >1 solar rotation.

Coronal holes are recognized as the primary sources of heliospheric open magnetic flux (OMF). However, a noticeable gap exists between in situ measured OMF and that derived from remote-sensing observations of the Sun. In this study, we investigate the OMF evolution and its connection to solar structures throughout 2014, with special emphasis on the period from September to October, where a sudden and significant OMF increase was reported. By deriving the OMF evolution at 1 au, modeling it at the source surface, and analyzing solar photospheric data, we provide a comprehensive analysis of the observed phenomenon. First, we establish a strong correlation between the OMF increase and the solar magnetic field derived from a potential-field source-surface model (cc Pearson = 0.94). Moreover, we find a good correlation between the OMF and the open flux derived from solar coronal holes (cc Pearson = 0.88), although the coronal holes only contain 14%–32% of the Sun’s total open flux. However, we note that while the OMF evolution correlates with coronal hole open flux, there is no correlation with the coronal hole area evolution (cc Pearson = 0.0). The temporal increase in OMF correlates with the vanishing remnant magnetic field at the southern pole, caused by poleward flux circulations from the decay of numerous active regions months earlier. Additionally, our analysis suggests a potential link between the OMF enhancement and the concurrent emergence of the largest active region in solar cycle 24. In conclusion, our study provides insights into the strong increase in OMF observed during 2014 September–October.