Listed are all scientific papers resulting from an ISSI activity written or co-authored by ISSI Team members, Working Group members, Workshop participants, visitors or staff members.
The subauroral region, located equatorward of the auroral oval, is a highly dynamic and complex interface between the magnetosphere, ionosphere, and thermosphere. While traditionally associated with stable optical structures such as stable auroral red arcs, recent observations have revealed a wide range of transient and extreme phenomena—such as subauroral ion drifts and strong thermal emission velocity enhancement—which highlight the region’s variability and intense coupling.
Optical aberrations and instrument resolution can affect the observed morphological properties of features in the solar atmosphere. However, little work has been done to study the effects of spatial resolution on the dynamical processes occurring in the Sun’s atmosphere.
The absolute calibration of period–luminosity (PL) relations of Cepheids in the Milky Way (MW) and its nearby galaxies has been a cornerstone in determining extragalactic distances and the current local expansion rate of the Universe. However, the universality of PL relations is still debated; in particular, the effect of metallicity on the Cepheid PL relation is not well understood.
Coagulation of dust particles in protoplanetary disks is the first step on the journey to the formation of planets. The surface free energy (SFE) of the dust particles determines the effectiveness of particles sticking to each other after collision, as well as the critical collision velocity above which fragmentation will occur. Studies of SFE have focused on the simplest silicate, silica, usually at standard temperature and pressure.
The recent discovery of strong tidal dissipation in Saturn’s interior has radically changed our view of the Saturnian system. While some questions are naturally answered by the new paradigm, others are emerging and require further measurement. This article presents the next key questions to be addressed by future space missions and analysis.
The importance of uncertainty estimates for Essential Climate Variable (ECV) data records is well recognized. Most ECV observing systems now estimate and report uncertainties as part of the measurement and retrieval procedure instead of leaving uncertainty characterization to a diagnostic “ex-post” validation/evaluation procedure. This paper focuses on the validation or evaluation of these prognostic “ex-ante” uncertainties provided with satellite ECV climate data records.
This article reviews the emerging field of exo-geoscience, focusing on the geological and geophysical processes thought to influence the evolution and (eu)habitability of rocky exoplanets. We examine the possible roles of planetary interiors, tectonic regimes, continental coverage, volatile cycling, magnetic fields, and atmospheric composition and evolution in shaping long-term climate stability and biospheric potential.
Blue large-amplitude pulsators (BLAPs) are a recently discovered group of hot pulsating stars whose evolutionary status remains uncertain. Their proposed progenitors are either ≃0.3M⊙ shell H-burning stars or ≃1.0M⊙ core He-burning stars, both relying on mass loss or a merger event in a (rarely observed) close interacting binary system.
Solar activity exhibits a range of quasi-periodic variations among different indices, reflecting the complex dynamics of the Sun. In this study, we investigate the temporal variation and hemispheric asymmetry of sunspot counts (SSC), sunspot areas (SSA), and X-ray solar flares during Solar Cycles 23 (SC23), SC24, and the ascending and maximum phase of SC 25 (1996–2024).
Accurate uncertainty information associated with essential climate variables (ECVs) is crucial for reliable climate modeling and understanding the spatiotemporal evolution of the Earth system. Recent developments in deep learning have remarkably advanced the estimation of ECVs with improved accuracy. However, the quantification of uncertainties associated with outputs of such deep learning models has yet to be widely adopted.
