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Revolutionising ocean climate monitoring through space-based magnetometry and Artificial Intelligence

CORDIS · observation · Publication date unknown

Revolutionising ocean climate monitoring through space-based magnetometry and Artificial Intelligence The tidal flow of ionized particles in seawater across Earth’s geomagnetic field induces electromagnetic (EM) signals within the ocean and solid Earth. These periodic signals are sensitive to oceanic properties such as salinity, temperature, and ultimately heat content, offering unique opportunities for climate monitoring. Despite 25 years of satellite-based tidal EM observations, their potential to estimate oceanic heat content (OHC) variations from space remains largely unexplored. PHOENIX proposes a pioneering framework to recover OHC from tidal EM fields by employing Physics-Informed Neural Networks (PINNs). This approach mitigates the inherent non-uniqueness of Earth sciences problems and the sparsity and uncertainties of available datasets by embedding physical constraints directly into the neural network architecture. A new 3-D EM solver will enforce these

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recordType

award

status

SIGNED

region

EU

value

202125.12

unit

EUR