Abstract

Abstract. Over a decade ago the semidiurnal lunar M2 ocean tide was identified in CHAMP satellite magnetometer data. Since then and especially since the launch of the satellite mission Swarm, electromagnetic tidal observations from satellites are increasingly used to infer electric properties of the upper mantle. In most of these inversions, ocean tidal models are used to generate oceanic tidal electromagnetic signals via electromagnetic induction. The modeled signals are subsequently compared to the satellite observations. During the inversion, since the tidal models are considered error free, discrepancies between forward models and observations are projected only onto the induction part of the modeling, e.g., Earth's conductivity distribution. Our study analyzes uncertainties in oceanic tidal models from an electromagnetic point of view. Velocities from hydrodynamic and assimilative tidal models are converted into tidal electromagnetic signals and compared. Respective uncertainties are estimated. The studies main goal is to provide errors for electromagnetic inversion studies. At satellite height, the differences between the hydrodynamic tidal models are found to reach up to 2 nT, i.e., over 100 % of the local M2 signal. Assimilative tidal models show smaller differences of up to 0.1 nT, which in some locations still corresponds to over 30 % of the M2 signal.

Highlights

  • The study of electromagnetic (EM) oceanic tidal signals (EMOTS) has a long history

  • EMOTS from the M2 are detectable in CHAMP satellite magnetometer observations (Tyler et al, 2003; Sabaka et al, 2015)

  • The study is restricted to tidal magnetic amplitudes of the semidiurnal lunar tide, M2

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Summary

Introduction

The study of electromagnetic (EM) oceanic tidal signals (EMOTS) has a long history (see references in Larsen, 1968; Sanford, 1971). EMOTS from the M2 are detectable in CHAMP satellite magnetometer observations (Tyler et al, 2003; Sabaka et al, 2015). Kuvshinov et al (2006) studied the sensitivity of EMOTS to lithosphere resistance. The strategy is to use discrepancies between observed and modeled EMOTS (Schnepf et al, 2014) to infer lithosphere and upper mantle resistance (Schnepf et al, 2015). Magnetometer satellites allow us to conduct these studies with global coverage. Grayver et al (2016, 2017) use EMOTS from satellite observations to constrain lithosphere, mantle conductivity, and water content profiles. Saynisch et al (2016, 2017) propose to use EMOTS to detect changes in oceanic conductance due to salinity and temperature changes Magnetometer satellites allow us to conduct these studies with global coverage. Grayver et al (2016, 2017) use EMOTS from satellite observations to constrain lithosphere, mantle conductivity, and water content profiles. Saynisch et al (2016, 2017) propose to use EMOTS to detect changes in oceanic conductance due to salinity and temperature changes

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