The Sun exhibits a myriad of ejections and eruptions that are key for the mass and energy balance of the solar atmosphere and provide a significant input to the solar wind and coronal heating. Among them, surges are of fundamental importance given their frequent association with many of the other explosive and/or ejective phenomena like Ellerman Bombs, ultraviolet (UV) bursts, and coronal jets. Even though they have been observed for decades now, the understanding of these bursty ejections of cool and dense plasma has progressed slowly due to the complexity of the physics of the chromosphere, where partial ionization and departures from local-thermodynamic equilibrium (LTE) take place. As a consequence, there are still many open questions concerning their physical nature and driving mechanisms, as well as their relationship to other dynamic phenomena at various scales, that can only be tackled at present. To solve the puzzle, two main challenges must be confronted: one is the adequate treatment of the physics of the chromospheric plasma; the other is the need to directly compare numerical simulations and observations through forward modeling and inversion.
Our 11-member team has two main interconnected goals: (1) to develop radiative MHD models of surges, and (2) to get a complete characterization of the spectral profiles of surges in the main chromospheric lines, such as Halpha and Mg II h&k, in which they are observed. To that end, we intend to use the state-of-the-art Bifrost code, including a number of relevant physical mechanisms missing in previous surge simulations. This will allow us to explore for the first time the role of the nonequilibrium ionization of hydrogen in surges, which is also essential for the subsequent calculation of synthetic profiles of the canonical Halpha line to compare with chromospheric observations. We also plan to take advantage of the available high-resolution observations from the Swedish 1-m Solar Telescope (SST) and the Interface Region Imaging Spectrograph (IRIS) to obtain representative profiles of surges in different wavelengths through unsupervised machine learning techniques, thus reducing the number of profiles to interpret and to invert. The achievement of these goals will open a new avenue to directly compare numerical experiments with observations, thus providing a joint perspective about surges that is currently missing in solar physics, and moving towards the solution of the long-standing puzzle of the solar atmosphere.