Scientific Reports Sci Rep 2045-2322 12 2019 9 1 Estimating global ocean heat content from tidal magnetic satellite observations Christopher Irrgang http://orcid.org/0000-0001-8274-1678 Jan Saynisch http://orcid.org/0000-0001-9619-0336 Maik Thomas Abstract

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.

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