Improved 1D inversions for sea ice thickness and conductivity from electromagnetic induction data: Inclusion of nonlinearities caused by passive bucking

The porosity of sea ice is a fundamental physical parameter that governs the mechanical strength of sea ice and the mobility of gases and nutrients for biological processes and biogeochemical cycles in the sea ice layer. However, little is known about the spatial distribution of the sea ice porosity and its variability between different sea ice types; an efficient and nondestructive method to measure this property is currently missing. Sea ice porosity is linked to the bulk electrical conductivity of sea ice, a parameter routinely used to discriminate between sea ice and seawater by electromagnetic (EM) induction sensors. Here, we have evaluated the prospect of porosity retrieval of sea ice by means of bulk conductivity estimates using 1D multifrequency EM inversion schemes. We have focused on two inversion algorithms, a smoothness-constrained inversion and a Marquardt-Levenberg inversion, which we modified for the nonlinear signal bias caused by a passive bucking coil operated in such a highly conductive environment. Using synthetic modeling studies, 1D inversion algorithms and multiple frequencies, we found that we can resolve the sea ice conductivity within +-0.01 S∕m. Using standard assumptions for the conductivity- porosity relation of sea ice, we were able to estimate porosity with an uncertainty of +-1.2%, which enables efficient and nondestructive surveys of the internal state of the sea ice cover