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Showing 1–3 of 3 results
Advanced filters: Author: Yevgeny Aksenov Clear advanced filters

  • Deep learning and numerical simulations of CryoSat-2 radar altimeter data are used to generate a pan-Arctic sea-ice thickness dataset for the Arctic melt period.

    • Jack C. Landy
    • Geoffrey J. Dawson
    • Yevgeny Aksenov
    Research
    Nature
    Volume: 609, P: 517-522

  • Accurate seasonal forecasts of sea ice are highly valuable, particularly in the context of sea ice loss due to global warming. A new machine learning tool for sea ice forecasting offers a substantial increase in accuracy over current physics-based dynamical model predictions.

    • Tom R. Andersson
    • J. Scott Hosking
    • Emily Shuckburgh
    ResearchOpen Access
    Nature Communications
    Volume: 12, P: 1-12

  • The Transpolar Drift, which governs the transport of freshwater, nutrients, carbon and contaminants across the Arctic Ocean, varies interannually, and is affected by fine-scale flow structures and processes, according to high-resolution simulations and satellite data.

    • Chris Wilson
    • Yevgeny Aksenov
    • Andrew C. Coward
    ResearchOpen Access
    Communications Earth & Environment
    Volume: 2, P: 1-10