The interplay of ice-firn model and station calibration in RNO-G

In-ice radio neutrino detectors, such as the newly constructed and operational Radio Neutrino Observatory in Greenland (RNO-G), rely on ice models to understand the in-ice signal propagation. Most often the ice is approximated in first order by a single exponential profile because it allows for computationally fast signal propagation. However, such models do not encompass the whole complexity of the ice, which may lead to systematic uncertainties. This is especially true for the upper part of the ice (the firn) where most of the RNO-G antennas are situated. Therefore, we developed a new refractive index model of the ice at Summit Station which can be used in both simulation and analysis. This contribution shows how both density data and signals from various known radio sources, such as the on board radio pulser and weather balloons, can lead to a more accurate description of the ice. This revised ice model results in a better understanding of signal arrival times, thus resulting in an improved station calibration in RNO-G. In the future we expect to bridge the gap even further by performing dedicated and more rigorous ice measurement in the field.