ALBERT

Description: In this study, we propose a statistical method to validate sea-level reconstructions using geological records known as sea-level indicators (SLIs). SLIs are often the only available data to retrace late-glacial relative sea level (RSL). Determining the RSL from SLI height is not straight forward, the elevation at which an SLI was found usually does not represent the past RSL. In contrast, it has to be related to past RSL by investigating sample’s type, habitat and deposition conditions. For instance, water distribution at which a specific specimen is found today can be related to the indicator's depositional height range. Furthermore, the precision of dating varies between geological samples, and, in case of radiocarbon dating, the age has to be calibrated using a non-linear calibration curve. To avoid an a-priori assumption like normal-distributed uncertainties, we define likelihood functions which take into account the indicative meaning’s available error information and calibration statistics represented by joint probabilities. For this conceptional study, we restrict ourselves to one type of indicators, shallow-water shells, which are usually considered as low-grade samples giving only a lower limit of former sea level, as the depth range in which they live spreads over several tens of meters, and does not follow a normal distribution. The presented method is aimed to serve as a strategy for glacial isostatic adjustment reconstructions, in this case for the German Paleo-Climate Modelling Initiative PalMod (https://www.palmod.de/en) and by extending it to other SLI types.

Description: Ocean tides generate electromagnetic (EM) signals that are emitted into space and can be recorded with low-Earth-orbiting satellites. Observations of oceanic EM signals contain aggregated information about global transports of water, heat, and salinity. We utilize an artificial neural network (ANN) as a non-linear inversion scheme and demonstrate how to infer ocean heat content (OHC) estimates from magnetic signals of the lunar semi-diurnal (M2) tide. The ANN is trained using monthly OHC estimates based on oceanographic in-situ data from 1990–2015 and the corresponding computed tidal magnetic fields at satellite altitude. We show that the ANN can closely recover inter-annual and decadal OHC variations from simulated tidal magnetic signals. Using the trained ANN, we present the first OHC estimates from recently extracted tidal magnetic satellite observations. Such space-borne OHC estimates can complement the already existing in-situ measurements of upper ocean temperature and can also allow insights into abyssal OHC, where in-situ data are still very scarce.

Description: Oceanic magnetic signals are sensitive to ocean velocity, salinity, and heat content. The detection of respective signals with global satellite magnetometers would pose a very valuable source of information. While tidal magnetic fields are already detected, electromagnetic signals of the ocean circulation still remain unobserved from space. We propose to use satellite altimetry to construct proxy magnetic signals of the ocean circulation. These proxy time series could subsequently be fitted to satellite magnetometer data. The fitted data could be removed from the observations or the fitting constants could be analyzed for physical properties of the ocean, e.g., the heat budget. To test and evaluate this approach, synthetic true and proxy magnetic signals are derived from a global circulation model of the ocean. Both data sets are compared in dependence of location and time scale. We study and report when and where the proxy data describe the true signal sufficiently well. Correlations above 0.6 and explained variances of above 80% can be reported for large parts of the Antarctic ocean, thus explaining the major part of the global, sub‐seasonal magnetic signal.

Description: The interactions of flowing electrically conductive seawater with Earth’s magnetic field generate electric currents within the oceans, as well as secondary electric currents induced in the resistive solid Earth. The ocean-induced magnetic field (OIMF) is an observable signature of these currents. Ignoring tidally forced ocean flows, the global ocean circulation system is driven by wind forcing on the ocean surface and by the temperature- and salinity-dependent buoyancy force. Ocean circulation’s magnetic signals contribute to the total magnetic field observed at the Earth’s surface or by low-orbit satellite missions. In this paper, we concentrate on accurate numerical modelling of the OIMF employing various approaches. Using a series of numerical test cases in different scenarios of increasing complexity, we evaluate the applicability of the unimodal thin-sheet approximation, the importance of galvanic coupling between the oceans and the underlying mantle (i.e. the bimodal solution), the effects of vertical stratification of ocean flow as well as the effects of vertical stratification of both oceanic and underlying electrical conductivity, and the influence of electromagnetic self-induction. We find that the inclusion of galvanic ocean-mantle coupling has the largest effect on the predicted OIMF. Self-induction is important only on the largest spatial scales, influencing the lowest spherical harmonic coefficients of the OIMF spectrum. We find this conclusion important in light of the recent Swarm satellite mission which has the potential to observe the large-scale OIMF and its seasonal variations. The implementation of fully three-dimensional ocean flow and conductivity heterogeneity due to bathymetry, which substantially increases the computational demands of the calculations, can play some role for regional studies, or when a more accurate OIMF prediction is needed within the oceans, e.g. for comparison with seafloor observations. However, the large-scale signals at the sea surface or at satellite altitude are less affected.

Description: ESA's satellite magnetometer mission Swarm is supposed to lower the limit of observability for oceanic processes. While periodic magnetic signals from ocean tides are already detectable in satellite magnetometer observations, changes in the general ocean circulation are yet too small or irregular for a successful separation. An approach is presented that utilizes the good detectability of tidal magnetic signals to detect changes in the oceanic electric conductivity distribution. Ocean circulation, tides and the resultant magnetic fields are calculated with a global general ocean circulation model coupled to a 3D electromagnetic induction model. For the decay of the meridional overturning circulation, as an example, the impact of climate variability on tidal oceanic magnetic signals is demonstrated. Total overturning decay results in anomalies of up to 0.7 nT in the radial magnetic M2 signal at sea level. The anomalies are spatially heterogeneous and reach in extended areas 30% or more of the unperturbed tidal magnetic signal. The anomalies should be detectable in long time series from magnetometers on land or at the ocean bottom. The anomalies at satellite height (430 km) reach 0.1 nT and pose a challenge for the precision of the Swarm mission. Climate variability induced deviations in the tide system (e.g., tidal velocities and phases) are negligible. Changes in tidal magnetic fields are dominated by changes in sea water salinity and temperature. Therefore, it is concluded that observations of tidal magnetic signals could be used as a tool to detect respective state changes in the ocean. This article is protected by copyright. All rights reserved.

Description: As the world ocean moves through the ambient geomagnetic core field, electric currents are generated in the entire ocean basin. These oceanic electric currents induce weak magnetic signals that are principally observable outside of the ocean and allow inferences about large-scale oceanic transports of water, heat, and salinity. The ocean-induced magnetic field is an integral quantity and, to first order, it is proportional to depth-integrated and conductivity-weighted ocean currents. However, the specific contribution of oceanic transports at different depths to the motional induction process remains unclear and is examined in this study. We show that large-scale motional induction due to the general ocean circulation is dominantly generated by ocean currents in the upper 2000 m of the ocean basin. In particular, our findings allow relating regional patterns of the oceanic magnetic field to corresponding oceanic transports at different depths. Ocean currents below 3000 m, in contrast, only contribute a small fraction to the ocean-induced magnetic signal strength with values up to 0.2 nT at sea surface and less than 0.1 nT at the Swarm satellite altitude. Thereby, potential satellite observations of ocean-circulation-induced magnetic signals are found to be likely insensitive to deep ocean currents. Furthermore, it is shown that annual temporal variations of the ocean-induced magnetic field in the region of the Antarctic Circumpolar Current contain information about sub-surface ocean currents below 1000 m with intra-annual periods. Specifically, ocean currents with sub-monthly periods dominate the annual temporal variability of the ocean-induced magnetic field.

Description: The variability of oceanic contributions to Earth’s magnetic field ranges from sub-daily scales to thousands of years. To study the sensitivity and the range of oceanic magnetic signals, an induction model is coupled to an ocean general circulation model. In the presented study, the sensitivity of the induction process to spatial and temporal variations in sea-water conductivity is investigated. In current calculations of ocean induced magnetic fields, a realistic distribution of sea-water conductivity is often neglected. We shown that assuming an ocean-wide constant conductivity is insufficient to accurately capture the spatial and, more important, the temporal variability of the magnetic signal. Using a realistic global sea-water conductivity distribution changes the temporal variability of the magnetic field up to 45%. Vertical gradients in sea-water conductivity prove to be a key factor for the variability of the oceanic induced magnetic field.

Description: In contrast to ocean circulation signals, ocean tides are already well detectable by electromagnetic measurements. Oceanic electric conductivities from the Coupled Model Intercomparison Project Phase 5 (CMIP5) climate simulations are combined with tidal currents of M2 and O1 to estimate electromagnetic tidal signals and their sensitivity to global warming. Ninety-four years of global warming lead to differences of ±0.3 nT in tidal magnetic amplitudes and ±0.1 mV/km in the tidal electric amplitudes at sea level. Locally, the climate induced changes can be much higher, e.g., +1 nT in the North Atlantic. In general, all studied electromagnetic tidal amplitudes show large scale climate induced anomalies that are strongest in the northern hemisphere and amount to 30% of their actual values. Consequently, changes in oceanic electromagnetic tidal amplitudes should be detectable in electromagnetic records. Electric and magnetic signals, as well as tides of different frequencies contain complementary regional information.

Description: 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 2nT, i.e., over 100% of the local M2 signal. Assimilative tidal models show smaller differences of up to 0.1nT, which in some locations still corresponds to over 30% of the M2 signal.

Description: The general circulation of the world ocean generates characteristic magnetic signals by interacting with the ambient geomagnetic field. These ocean-induced magnetic signals can principally be measured by satellites and could serve as indirect observations of the ocean. Since the so-called motionally induced magnetic field is to first order proportional to conductivity-weighted and depth-integrated ocean velocities, global oceanic magnetic field observations could provide new constraints on oceanic transports of water, heat, and salinity. However, many aspects of electromagnetic induction in the ocean are either not well understood or unknown. This ranges from the basic characterization of motional induction in the ocean to possible applications and benefits for ocean modelling. This cumulative thesis encompasses the characterization of electromagnetic induction in the ocean, both in terms of physical properties and model uncertainties. One new application of electromagnetic induction in the ocean is investigated, namely the possibility to constrain an ocean general circulation model with satellite observations of the ocean-induced magnetic field. An electromagnetic induction model is implemented into an ocean general circulation model. This model combination allows the investigation of specific influences of seawater properties on motional induction. In previous studies, the electric conductivity of seawater was often treated in a simplified way by assuming it to be uniformly distributed in the ocean and temporally constant. In the first application of the combined numerical models, it is shown that this assumption is insufficient for capturing the temporal variability of motional induction accurately. Considering a realistic three-dimensional seawater conductivity distribution based on ocean temperature and salinity increases the temporal variability of ocean-induced magnetic signals by up to 45 %. These changes are found to predominantly originate from large vertical gradients of seawater conductivity in the upper ocean. The modelling of the general ocean circulation and of motional induction is affected by various uncertainties and errors, which are introduced by forcing input data and by the numerical models themselves. For potential applications of motional induction, e.g., a reliable comparison of model results with observational data, or data assimilation experiments, a realistic estimation of model uncertainties is essential. Ensemble simulations based on different error scenarios are performed to estimate the aggregated uncertainty of the modelled ocean-induced magnetic field. It is shown that the uncertainty of the modelled ocean-induced magnetic field reaches up to 30 % of the signal strength and is subject to large spatial and seasonal variations. The wind stress forcing of the ocean model is a major source of uncertainty. However, specific spatially and temporally robust regions are identified in the ocean-induced magnetic field that retain a small uncertainty in all error scenarios. Based on the previous findings, data assimilation experiments with artificial satellite observations of the ocean-induced magnetic field are designed and conducted for the first time. In a model-based twin study, artificial satellite observations of the oceanic magnetic field are generated and sequentially assimilated into an ocean general circulation model with a localized ensemble Kalman filter. The impact of the data assimilation on the induced magnetic field, ocean velocities, temperature, and salinity is measured. Compared to a reference simulation without data assimilation, the ocean-induced magnetic field is improved by up to 17 % globally and up to 54 % locally. Improvements of the underlying depth-integrated ocean velocities show values up to 7 % globally, and up to 50 % locally. These improvements result from a consistently better recovery of ocean velocities from the sea surface down to the bottom of the ocean. However, the Kalman filter fails to improve ocean temperature and salinity globally. Kalman filter adjustments of the wind stress forcing of the ocean model are found to be essential for a successful data assimilation.