Section outline

  • A new way to observe and monitor the ocean

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    SUBMERSE (SUBMarine cablEs for ReSearch and Exploration) is an innovative EU-funded project that aims to turn existing submarine telecommunication cables into an international fiber optic sensing network, providing near real-time data flows to monitor the Earth and its systems.

    During the SUBMERSE Community Event in April 2026, this training session focused on the visualisation and preliminary processing of DAS data for oceanographic applications. The trainers demonstrated how to handle high-volume DAS records by using a downsampled dataset from the GeoLab fibre in Madeira. Participants were provided a prepared workflow in Colab to familiarise themselves with how signals change along different segments of a submarine cable, moving from land and the narrow shelf into deep water.

    In the following video, HCMR Research Associate Athanasia Papapostolou introduces the key role of Distributed Acoustic Sensing (DAS) and State of Polarisation (SOP) technologies in physical oceanography. Fiber optic sensing offers a cost-effective approach to monitor and measure massive global phenomena and climate change, where traditional sensors are too expensive to deploy. Undersea cables are uniquely positioned to provide the high-resolution boundary conditions needed for coastal forecasting models. That's why existing submarine telecom infrastructures can become a new way to observe and monitor the ocean.

  • Tutorial: Oceanographic applications

    • Notebook: DAS for Oceanographic applications URL

      Open this Colab notebook to replicate the exercises presented in the video tutorial.

      This notebook explores Distributed Acoustic Sensing (DAS) data from the GeoLab fibre on Madeira Island. It demonstrates how to read, visualise, and analyse DAS files. Key steps include:

      • Data loading and preparation: Downloading a pre-processed DAS HDF5 file (downsampled to 2Hz) and loading it into a NumPy array.
      • Time-series analysis: Plotting single channel time-series to observe raw data.
      • Frequency domain analysis: Generating spectrograms and magnitude spectra for individual channels.
      • Spatial and temporal visualisation: Plotting time-space diagrams (plotTimeSpace and plotSpaceTime) to visualize data across channels and time.
      • Frequency-Wavenumber (F-K) analysis: Calculating and plotting F-K spectra to identify wave propagation characteristics, including the overlay of theoretical ocean surface gravity wave (OSGW) dispersion curves.
      • Noise identification: Calculating and plotting the standard deviation per channel to identify potentially noisy channels.

      The notebook also provides context on wave types in the ocean and their typical frequency ranges, and explores channel segmentation based on bathymetric profiles.

  • Trainer panel