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Geophysical Fluid Dynamics: General

ORAL · T29 · ID: 22946

Presentations

  • Deep learning-enhanced ensemble-based data assimilation for high-dimensional nonlinear dynamical systems

    ORAL

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    Publication: 1.Towards physically consistent data-driven weather forecasting: Integrating data assimilation with equivariance-preserving spatial transformers in a case study with ERA5, A Chattopadhyay, M Mustafa, P Hassanzadeh, E Bach, K Kashinath<br>Geoscientific Model Development Discussions, 1-23<br>2. Deep learning-enhanced ensemble-based data assimilation for high-dimensional nonlinear dynamical systems, A Chattopadhyay, E Nabizadeh, E Bach, P Hassanzadeh (in prep)

    Presenters

    • Ashesh K Chattopadhyay

      Rice University, Rice Univ

    Authors

    • Ashesh K Chattopadhyay

      Rice University, Rice Univ

    • Ebrahim Nabizadeh

      Rice University

    • Eviatar Bach

      Laboratoire de Météorologie Dynamique

    • Pedram Hassanzadeh

      Rice University

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  • On the structures of the ice-covered flows in a bend

    ORAL

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    Publication: On the impacts of ice cover on shear velocity distribution in a bend (Koyuncu, Le) (Planned Paper)<br>The impacts of ice coverage on large-scale structures of turbulent flows in a river bend (Le, Koyuncu) (Planned Paper)

    Presenters

    • Berkay Koyuncu

      North Dakota State University

    Authors

    • Berkay Koyuncu

      North Dakota State University

    • Trung B Le

      North Dakota State University

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  • Data-driven modeling of non-local mixing phenomena in geophysical flows

    ORAL

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    Presenters

    • Jinlong Wu

      California Institute of Technology

    Authors

    • Jinlong Wu

      California Institute of Technology

    • Daniel Z Huang

      California Institute of Technology, Caltech

    • Zhaoyi Shen

      California Institute of Technology

    • Tapio Schneider

      California Institute of Technology

    • Andrew Stuart

      California Institute of Technology

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  • AMR-Wind: Adaptive mesh-refinement for atmospheric-boundary-layer wind energy simulations

    ORAL

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    Presenters

    • Michael J Brazell

      National Renewable Energy Laboratory, National Renewable Energy Laboratory (NREL)

    Authors

    • Michael J Brazell

      National Renewable Energy Laboratory, National Renewable Energy Laboratory (NREL)

    • Shreyas Ananthan

      Siemens Gamesa Renewable Energy Digital Ventures Lab, Siemens Gamesa Renewable Energy - Digital Ventures Lab

    • Ganesh Vijayakumar

      National Renewable Energy Laboratory

    • Lawrence Cheung

      Sandia National Laboratory, Sandia National Laboratories

    • Michael A Sprague

      National Renewable Energy Laboratory

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  • Simulating general flows in curvilinear domains with Dedalus

    ORAL

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    Presenters

    • Keaton Burns

      Massachusetts Institute of Technology MI

    Authors

    • Keaton Burns

      Massachusetts Institute of Technology MI

    • Geoffrey Vasil

      Univ of Sydney

    • Daniel Lecoanet

      Northwestern University, Northwestern

    • Jeff S Oishi

      Bates College

    • Benjamin P Brown

      University of Colorado, Boulder

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  • Turbulent structure of subcritical and supercritical gravity and turbidity currents

    ORAL

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    Publication: Salinas, J., Balachandar, Cantero, M., Control of turbulent transport in supercritical currents by three<br>families of hairpin vortices. Physical Review: Fluids. 2021, 6, 063801.

    Presenters

    • Jorge Salinas

      University of Florida

    Authors

    • Jorge Salinas

      University of Florida

    • S Balachandar

      University of Florida

    • Mariano I Cantero

      Instituto Balseiro, Instituto Balseiro, Universidad Nacional de Cuyo, Consejo Nacional de Investigaciones Cientificas y Tecnicas, Argentina

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  • Regime transition in subcritical and supercritical currents

    ORAL

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    Presenters

    • Jorge Salinas

      University of Florida

    Authors

    • Jorge Salinas

      University of Florida

    • S Balachandar

      University of Florida

    • Mariano I Cantero

      Instituto Balseiro, Instituto Balseiro, Universidad Nacional de Cuyo, Consejo Nacional de Investigaciones Cientificas y Tecnicas, Argentina

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  • Deep learning for surrogate modelling of 2D mantle convection

    ORAL

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    Publication: S. Agarwal, N. Tosi, P. Kessel, D. Breuer, and G. Montavon (2021). Deep learning for surrogate modelling of 2D mantle convection. Submitted to Physical Review Fluids.

    Presenters

    • Siddhant Agarwal

      German Aerospace Center (DLR), Berlin Institute of Technology

    Authors

    • Siddhant Agarwal

      German Aerospace Center (DLR), Berlin Institute of Technology

    • Nicola Tosi

      German Aerospace Center (DLR)

    • Pan Kessel

      Berlin Institute of Technology

    • Doris Breuer

      German Aerospace Center (DLR)

    • Grégoire Montavon

      Berlin Institute of Technology

    View abstract →