Browsing NTNU Open by Journals "Quarterly Journal of the Royal Meteorological Society"

Now showing items 1-3 of 3

    • Comparison of ensemble-based data assimilation methods for sparse oceanographic data 

      Beiser, Florian; Holm, Håvard Heitlo; Eidsvik, Jo (Peer reviewed; Journal article, 2023-12-10)
      Probabilistic forecasts in oceanographic applications, such as drift trajectory forecasts for search-and-rescue operations, face challenges due to high-dimensional complex models and sparse spatial observations. We discuss ...

    • Estimating stratospheric polar vortex strength using ambient ocean-generated infrasound and stochastics-based machine learning 

      Vorobeva, Ekaterina; Eggen, Mari Dahl; Midtfjord, Alise Danielle; Benth, Fred Espen; Hupe, Patrick; Brissaud, Quentin; Orsolini, Yvan Joseph Georges Emile G.; Näsholm, Sven Peter (Journal article; Peer reviewed, 2024)
      There are sparse opportunities for direct measurement of upper stratospheric winds, yet improving their representation in subseasonal-to-seasonal prediction models can have significant benefits. There is solid evidence ...

    • A revised implicit equal-weights particle filter 

      Skauvold, Jacob; Eidsvik, Jo; van Leeuwen, Peter Jan; Amezcua, Javier (Peer reviewed; Journal article, 2019)
      Particle filters are fully nonlinear data assimilation methods and as such are highly relevant. While the standard particle filter degenerates for high‐dimensional systems, recent developments have opened the way for new ...