Sea ice as an evaluation target for HEM modelling and inversion

Abstract

We investigate helicopter electromagnetic (HEM) inversion schemes applied to synthetic and measured HEM sea ice profiling data. Direct HEM data-to-ice-thickness inversion is compared to three different formal, least squares layered earth inversion algorithms. By making several approximations, it is possible to directly invert a single channel measurement (i.e., the in-phase or quadrature component of a single frequency measurement) to obtain an estimate of sea ice thickness. Measurements from multiple input channels, however, can be used in a layered earth inversion to simultaneously recover several model parameters such as sea ice thickness, sea ice conductivity and sub-ice bathymetry. Synthetic data sets for a particular two-frequency HEM system showed that simple least squares inversion algorithms produce reliable estimates of sea ice thickness in cases where the ice is thicker than 3 m. These methods could also recover acceptable estimates of sea ice thickness when a thin, conductive, partially melted sea ice layer was present, and could determine shallow, sub-ice bathymetry in brackish water. As expected, 1D transformations and inversions of synthetic data for a three-dimensional pressure ridge keel structure contained artifacts, notably broadening of the apparent width of the keel. Prior to inverting a field data set acquired over rather thin (~ 0.5 m) Antarctic sea ice, we found it necessary to recalibrate the phase angle of the measurements using a phasor diagram-based method. Direct transformation of a single channel from the recalibrated data set produced more accurate estimates of sea-ice thickness than formal inversion of multi-channel data. We suggest that the least squares inversion methods are inferior in this situation because of the particular characteristics of the two-frequency HEM system used in this evaluation; the extreme differences in sensitivity of high and low frequency data components, the overall low sensitivity to sea ice conductivity (especially for thin ice), and the partially low signal-to noise ratios of the measurements. The data sets used in this study will be made available to the public to allow alternate inversion approaches to be applied and evaluated. It is suggested that inclusion of parameter bounds and other forms of regularization could help to improve the inversion results.