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

摘要

The porosity of sea ice is a fundamental physical parameterudthat governs the mechanical strength of sea ice and the mobilityudof gases and nutrients for biological processes and biogeochemicaludcycles in the sea ice layer. However, little is known about theudspatial distribution of the sea ice porosity and its variability betweenuddifferent sea ice types; an efficient and nondestructiveudmethod to measure this property is currently missing. Sea iceudporosity is linked to the bulk electrical conductivity of seaudice, a parameter routinely used to discriminate between seaudice and seawater by electromagnetic (EM) induction sensors.udHere, we have evaluated the prospect of porosity retrieval ofudsea ice by means of bulk conductivity estimates using 1D multifrequencyudEM inversion schemes. We have focused on two inversionudalgorithms, a smoothness-constrained inversion and audMarquardt-Levenberg inversion, which we modified for theudnonlinear signal bias caused by a passive bucking coil operatedudin such a highly conductive environment. Using synthetic modelingudstudies, 1D inversion algorithms and multiple frequencies,udwe found that we can resolve the sea ice conductivity withinud+-0.01 S∕m. Using standard assumptions for the conductivity-udporosity relation of sea ice, we were able to estimateudporosity with an uncertainty of +-1.2%, which enables efficientudand nondestructive surveys of the internal state of the sea iceudcover.