Stochastic Transport in Upper Ocean Dynamics III
Springer International Publishing (Verlag)
978-3-031-70659-2 (ISBN)
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This open-access proceedings volume brings selected, peer-reviewed contributions presented at the Fourth Stochastic Transport in Upper Ocean Dynamics (STUOD) 2023 Workshop, held at IFREMER in Plouzané, France, September 25-28, 2023. The STUOD project is supported by an ERC Synergy Grant, and led by Imperial College London, the National Institute for Research in Computer Science and Automatic Control (INRIA), and the French Research Institute for Exploitation of the Sea (IFREMER). The project aims to deliver new capabilities for assessing variability and uncertainty in upper ocean dynamics. It will provide decision makers a means of quantifying the effects of local patterns of sea level rise, heat uptake, carbon storage, and change of oxygen content and pH in the ocean. Its multimodal monitoring will enhance the scientific understanding of marine debris transport, tracking of oil spills, and accumulation of plastic in the sea.
All topics of these proceedings are essential to the scientific foundations of oceanography which has a vital role in climate science. Studies convened in this volume focus on a range of fundamental areas, including:
- Observations at a high resolution of upper ocean properties such as temperature, salinity, topography, wind, waves and velocity;
- Large-scale numerical simulations;
- Data-based stochastic equations for upper ocean dynamics that quantify simulation error;
- Stochastic data assimilation to reduce uncertainty.
These fundamental subjects in modern science and technology are urgently required in order to meet the challenges of climate change faced today by human society. This proceedings volume represents a lasting legacy of crucial scientific expertise to help meet this ongoing challenge, for the benefit of academics and professionals in pure and applied mathematics, computational science, data analysis, data assimilation, and oceanography.
Bertrand Chapron is a Director of Research at Ifremer - French Research Institute for Exploitation of the Sea, France. His research activities lie in applied mathematics, physical oceanography, electromagnetic wave theory and its applications to ocean remote sensing, and data processing.
Dan Crisan is a Professor at the Department of Mathematics of Imperial College London, UK, and Director of the EPSRC Centre for Doctoral Training in the Mathematics of Planet Earth. His current research interests lie in stochastic analysis, fluid dynamics, nonlinear filtering and probabilistic numerical methods.
Darryl Holm is a Professor of Mathematics at Imperial College London, UK, and a Fellow of Los Alamos National Laboratory, USA. His works have applied geometric mechanics in many topics, including geophysical fluid dynamics (GFD) for ocean circulation, stochastic fluid dynamics, turbulence, nonlinear waves, and stochastic optimal control for shape analysis.
Étienne Mémin is a Director of Research at Inria - National Institute for Research in Digital Science and Technology, France. His research focuses on stochastic modeling of fluid flows and data assimilation, an activity that crosses disciplines such as geophysics, fluid mechanics, and applied mathematics.
Jane-Lisa Coughlan is a Programme Project Manager at Imperial College London, UK.
Generative Modelling of Stochastic Rotating Shallow Water Noise.- Collisions of Burgers Bores with Nonlinear Waves.- Average dissipation for stochastic transport equations with Lévy noise.- General Solution Theory for the Stochastic Navier-Stokes Equations.- Geometric theory of perturbation dynamics around non-equilibrium fluid flows.- On forward-backward SDE approaches to conditional estimation.- Data Assimilation for the Stochastic Camassa-Holm Equation Using Particle Filtering: A Numerical Investigation.- Some properties of a non-hydrostatic stochastic oceanic primitive equations model.- Derivation of stochastic models for coastal waves.- The Effects of Unresolved Scales on Analogue Forecasting Ensembles.- Particle-based algorithm for stochastic optimal control.- Maximum likelihood estimation of subgrid flows from tracer image sequences.- Transport noise defined from wavelet transform for model-based stochastic ocean models.- Stochastic fluids with transport noise: Approximating diffusion from data using SVD and ensemble forecast back-propagation.
| Erscheinungsdatum | 20.11.2024 |
|---|---|
| Reihe/Serie | Mathematics of Planet Earth |
| Zusatzinfo | XIV, 345 p. 72 illus., 67 illus. in color. |
| Verlagsort | Cham |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Themenwelt | Mathematik / Informatik ► Mathematik ► Angewandte Mathematik |
| Schlagworte | conference proceedings • Data Analysis • Data Assimilation • Deep learning • Dynamical Systems • Mathematics of Planet Earth • math open access proceedings • ocean modelling • Ocean Observations • open access • stochastic partial differential equations • STUOD |
| ISBN-10 | 3-031-70659-5 / 3031706595 |
| ISBN-13 | 978-3-031-70659-2 / 9783031706592 |
| Zustand | Neuware |
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