Updated studies of radio propagation through polar firn using paraPropPython: Contribution to ICRC 2023

Ultra high energy neutrinos can be detected by measurement of radio emission, produced either from Askaryan emission, or via reflection of an in-ice radar transmission off the neutrino’s ionization trail. Accurate reconstruction of the properties depend on accurately modeling radio propagation through the firn layer, the transition between fresh snow and glacial ice, where the refractive index is inhomogeneous over depth and range. The paraPropPython code uses the parabolic equation (PE) simulation method for improved modeling of RF transmission in polar firn. PE methods permit simulation of arbitrary RF waveforms through data-defined depth and range dependent refractive index profiles on a scale of several kilometres, accounting for features such as surface roughness, crevasses and refrozen-ice layers, and can also model back-scatter off of in-ice anomalies. This work aims to examine the effects of ice inhomogeneities on signal properties using the parabolic wave equation (PE) method of simulation radio propagation, using the upper firn layer of the Greenland ice sheet at the Summit station as an example. We also present improvements and updates to paraPropPython, and show an inversion method to reconstruct refractive index profiles from ice-penetrating radar data.