The solar corona, the outer atmosphere of the Sun, is heated to millions of degrees. This is several orders of magnitude hotter than the photosphere, the optical surface of the Sun, below, and a mystery that has baffled scientists for centuries. The answer to the question of how the solar corona is heated lies in the crucial magnetic connection through the atmosphere of the Sun. The magnetic field that threads the corona extends below the solar photosphere, where the convective motions drag the magnetic field footpoints, tangling and twisting them. The chromosphere is the atmospheric layer above the photosphere, below the corona, and the magnetic field provides an important connection between these layers. The exchange of mass and energy between the chromosphere and corona is an essential piece of this puzzle. The connection between the chromosphere and the corona is a challenging piece of the puzzle both observationally and computationally, as it is highly complex in space and time. We describe the history of the observations and theoretical understanding of the heating of the solar atmosphere, and end with future prospects of the coronal heating problem.

We explore the effects of changing heating parameters in closed coronal loops on the intensity of Atmospheric Imaging Assembly (AIA) observations. Using EBTEL (Enthalpy-Based Thermal Evolution of Loops) hydrodynamic simulations, we produce realizations of coronal loops with a series of heating events randomly drawn from a power law distribution. We repeat this procedure for multiple loop lengths, heating intensities, and characteristic heating frequencies to investigate how each of these parameters individually and in combination influences observable loop properties. We generate AIA intensities from the corona and transition region for each realization. The variations within and between models generated with these different parameters illustrate the sensitivity of narrowband imaging to the details of coronal heating. Using insights from this analysis, we generate images of observed coronal active regions using the GX Simulator SSW IDL package and interpret the causes of discrepancies between the models and observations.