Estimating global ocean heat content from tidal magnetic signals with machine learning
Oceanic processes related to climate change can be tracked by magnetic signals that are generated by ocean tides. As such, the periodic magnetic signals of the M2 tide contain trends that are related to the continuously warming ocean. In turn, long-term observations of the tidally induced magnetic field can be used as an additional measure of the heat budget and the overall warming of the ocean. We utilize artificial neural networks as non-linear inversion schemes to investigate this topic. With the help of a neural network, which was trained with ocean temperature data and corresponding simulated tidal M2 magnetic fields over the time period 1990-2015, we could, for the first time, derive global ocean heat content values from recent Swarm satellite observations.
Reference
Saynisch-Wagner, J., Baerenzung, J., Irrgang, C., Hornschild, A., Thomas, M. (2021): Tide induced magnetic signals and their errors derived from CHAMP and Swarm satellite magnetometer observations. - Earth Planets and Space, 73, 234.
Irrgang, C., Saynisch, J., Thomas, M. (2019): Estimating global ocean heat content from tidal magnetic satellite observations. - Scientific Reports, 9, 7893. https://doi.org/10.1038/s41598-019-44397-8
Saynisch, J., Irrgang, C., Thomas, M. (2018): Estimating ocean tide model uncertainties for electromagnetic inversion studies. - Annales Geophysicae, 36, 1009-1014. https://doi.org/10.5194/angeo-36-1009-2018
Saynisch, J., Petereit, J., Irrgang, C., Thomas, M. (2017): Impact of oceanic warming on electromagnetic oceanic tidal signals - a CMIP5 climate model based sensitivity study. - Geophysical Research Letters, 44, 10, 4994-5000. https://doi.org/10.1002/2017GL073683
Saynisch, J., Petereit, J., Irrgang, C., Kuvshinov, A., Thomas, M. (2016): Impact of climate variability on the tidal oceanic magnetic signal - a model based sensitivity study. - Journal of Geophysical Research, 121, 8, 5931-5941. https://doi.org/10.1002/2016JC012027
Irrgang, C., Saynisch, J., Thomas, M. (2016): Impact of variable seawater conductivity on motional induction simulated with an ocean general circulation model. - Ocean Science, 12, 1, 129-136. https://doi.org/10.5194/os-12-129-2016
Irrgang, C., Saynisch, J., Thomas, M. (2016): Ensemble simulations of the magnetic field induced by global ocean circulation: Estimating the uncertainty. - Journal of Geophysical Research, 121, 3, 1866-1880. https://doi.org/10.1002/2016JC011633