GP33A-06 / Fall AGU Meeting, San Francisco, December 2004 Magnetic signals generated by the ocean circulation and their variability. Manoj, C. (1,2) Kuvshinov, A. (3,4), Maus, S. (5,1) and Lühr, H. (1). 1) GeoForchungsZentrum - Potsdam, Germany 2) National Geophysical Research Institute - Hyderabad, India 3) Danish Space Research Institute - Copenhagen, 4) Geoelectromagnetic Research Institute - Troitsk, Russia 5) NOAA's National Geophysical Data Centre - Boulder, USA

GP33A-06 / Fall AGU Meeting, San Francisco, December 2004 Electrically charged ions make ocean a conducting fluid. As the ocean-water flow through the ambient geomagnetic field, it generates secondary electric and magnetic fields (motional induction). Magnetic fields generated by ocean can be divided into “poloidal” and “toroidal” parts. The toroidal fields have higher strength (1-100 nT) than the poloidal fields (1-10 nT). However, only the poloidal fields are observable outside the ocean. The large spatial decay scales of the poloidal fields allow it to reach distant land and satellite based sensors. Introduction

GP33A-06 / Fall AGU Meeting, San Francisco, December 2004 Recently Tyler et al (2003), for the first time identified ocean-magnetic signals in the satellite magnetic data. This results confirm the non-trivial contribution of the ocean-magnetic signals to the geomagnetic fields. Fig: Observed and predicted magnetic signal of the M2 ocean tide. (Tyler et al, Science, 2003). Figures A and C are observations and B and D are predictions. Background

GP33A-06 / Fall AGU Meeting, San Francisco, December Numerical prediction of the magnetic fields. >> 3D EM code >> Sensitivity analysis >> Ocean models 2. Magnetic fields generated by ocean circulation. >> Predicted fields at sea and satellite altitude >> Effect of ocean eddies 3. Temporal variations. >> Range of variability >> Monsoon & El Niño variations 4. Conclusions Road map

GP33A-06 / Fall AGU Meeting, San Francisco, December 2004 We used a 3D global EM induction code to predict ocean-magnetic fields. (Kuvshinov et al., 2002; 2004) Uses a volume integral equations approach to simulate EM fields over a 3D conductivity model of the Earth, excited by inducing currents. where, σ - Mean sea water conductivity 3.2 S/m U - Depth integrated velocity m 2 /s B - Geomagnetic field derived from IGRF 2000 in nT For ocean-magnetic signals, this current J is calculated as, Numerical predictions

GP33A-06 / Fall AGU Meeting, San Francisco, December 2004 Sensitivity of the ocean-magnetic signals Log(∑|Br|) in nT The sensitivity is influenced largely by the vertical component of the main geomagnetic field. This means ocean near geomagnetic equator produces least signals where as areas closer to geomagnetic poles produces maximum signals In addition, the distribution of sensitivity is also influenced by the lateral conductivity contrast.

GP33A-06 / Fall AGU Meeting, San Francisco, December 2004 We used two state-of-the-art ocean models for the velocity data. 1) The horizontal velocity data from ECCO ( adjoint model run ( ) were used to estimate ocean-magnetic signals and their temporal variations on a 1 0 x 1 0 resolution. We use this model to predict the seasonal and interannual variations in ocean-magnetic signals. 2) To simulate the magnetic signatures of ocean eddies, the x resolution velocity data from OCCAM model ( Ocean circulation models used log√(U 2 +V 2 )

GP33A-06 / Fall AGU Meeting, San Francisco, December 2004 Predicted ocean magnetic signals ECCO OCCAM 0 km 430 km nT

GP33A-06 / Fall AGU Meeting, San Francisco, December 2004 Magnetic signals from ocean eddies At sea levelAt satellite altitude The simulation with OCCAM velocity data brought out the magnetic effects of ocean eddies. However, effects of individual eddies do not show up in predicted the fields at satellite altitude.

GP33A-06 / Fall AGU Meeting, San Francisco, December 2004 Deviation from mean for predictions from nT

GP33A-06 / Fall AGU Meeting, San Francisco, December 2004 Range of variability nT

GP33A-06 / Fall AGU Meeting, San Francisco, December 2004 Seasonal variations. nT Difference between the predictions for Summer and Winter, BrBr The difference map is dominated by a series of anomalies in Indian and western Pacific oceans. The variability in northern Indian ocean is probably related to Monsoon.

GP33A-06 / Fall AGU Meeting, San Francisco, December 2004 The difference map (El Niño ( ) and La Niña (1999) ) has lower magnitude than seasonal variation. Probable reasons: 1) Weak vertical component of the geomagnetic field. 2) El Niño affects only the surface currents. El Niño variations La Niña El Niño Difference

GP33A-06 / Fall AGU Meeting, San Francisco, December 2004 Uses in Magnetic field models We have applied corrections for tidal ocean signals that completely removed the tidal magnetic noise from observed data In a similar way, the predicted magnetic signals from ocean circulation will be used to improve the crustal magnetic field models. (Maus et al, 2004)

GP33A-06 / Fall AGU Meeting, San Francisco, December 2004 Conclusions Magnetic signals generated from ocean circulation is within the range of the observational capability of satellites Temporal variations in ocean – magnetic signals have lesser amplitudes. Ocean eddies also contributes significantly to geomagnetic fields, but signatures from individual eddies are not shown up at satellite altitude. High sensitivity of magnetic signals to ocean flow over ACC and western boundary currents improves their chances of detection.

GP33A-06 / Fall AGU Meeting, San Francisco, December 2004 Acknowledgements ECCO and OCCAM modeling groups for making their data available ESA for the financial support