REMORA

REMORA: Regional Modeling of Oceans Refined Adaptively (built on AMReX) - Published in JOSS (2025)

https://github.com/seahorce-scidac/remora

Keywords

Repository

A GPU-enabled version of ROMS

README.rst

REMORA
------
.. image:: https://joss.theoj.org/papers/10.21105/joss.07958/status.svg
   :target: https://doi.org/10.21105/joss.07958

REMORA (Regional Model of the Ocean Refined Adaptively) is a new GPU-enabled code designed to replicate the functionality of the ROMS code but with the ability to exploit GPU architectures.

Like ROMS, REMORA solves the incompressible time-dependent Navier-Stokes equation with the Boussinesq and hydrostatic approximations. These equations are solved on a curvilinear grid with a stretched, terrain-following vertical coordinate. We use a split-explicit time-stepping shceme, where several fast barotropic (2D) steps take place within each baroclinic (3D) update. There are a number of user-specified options, including advection schemes, boundary conditions, mixing parametrizations, and surface flux parametrizations.

`REMORA` is built upon the `AMReX `_ software framework
for massively parallel block-structured applications. The AMReX software framework provides performance portability across multiple architectures.

Getting Started
~~~~~~~~~~~~~~~

See `Getting Started `_ for instructions as to how to clone the REMORA
and AMReX codes, and for how to build and run a REMORA example.  Minimum requirements for system software are also given there.

Documentation
~~~~~~~~~~~~~~~~~

Documentation of the REMORA theory and implementation is available `here `_ .

In addition, there is doxygen documentation of the REMORA Code available `here `_

Development model
~~~~~~~~~~~~~~~~~

See CONTRIBUTING.md for how to contribute to REMORA development.

License
~~~~~~~~~

REMORA Copyright (c) 2023, The Regents of the University of California,
through Lawrence Berkeley National Laboratory, Triad National Security, LLC
through Los Alamos National Laboratory, UChicago Argonne LLC through
Argonne National Laboratory, Battelle Memorial Institute through Pacific
Northwest National Laboratory (subject to receipt of any required approvals
from the U.S. Dept. of Energy) and TechTrans International, Inc. All rights reserved.

If you have questions about your rights to use or distribute this software,
please contact Berkeley Lab's Intellectual Property Office at
IPO@lbl.gov.

NOTICE.  This Software was developed under funding from the U.S. Department
of Energy and the U.S. Government consequently retains certain rights.  As
such, the U.S. Government has been granted for itself and others acting on
its behalf a paid-up, nonexclusive, irrevocable, worldwide license in the
Software to reproduce, distribute copies to the public, prepare derivative
works, and perform publicly and display publicly, and to permit others to do so.

The license for REMORA can be found in the LICENSE.md file.

Citation
~~~~~~~~~

To cite REMORA, please use the following reference:

.. image:: https://joss.theoj.org/papers/10.21105/joss.07958/status.svg
   :target: https://doi.org/10.21105/joss.07958

::

  @article{REMORA_JOSS,
      doi = {10.21105/joss.07958},
      url = {https://doi.org/10.21105/joss.07958},
      year = {2025},
      publisher = {The Open Journal},
      volume = {10},
      number = {110},
      pages = {7958},
      author = {Hannah Klion and Robert Hetland and Jean Sexton and Ann Almgren and Iulian Grindeanu and Kyle Hinson and Vijay Mahadevan},
      title = {REMORA: Regional Modeling of Oceans Refined Adaptively (built on AMReX)},
      journal = {Journal of Open Source Software}
  }

Owner

JOSS Publication

REMORA: Regional Modeling of Oceans Refined Adaptively (built on AMReX)

Published

June 11, 2025

DOI

10.21105/joss.07958

Volume 10, Issue 110, Page 7958

Authors

Hannah Klion
Lawrence Berkeley National Laboratory

Robert Hetland
Pacific Northwest National Laboratory

Jean Sexton
Lawrence Berkeley National Laboratory

Ann Almgren
Lawrence Berkeley National Laboratory

Iulian Grindeanu
Argonne National Laboratory

Kyle Hinson
Pacific Northwest National Laboratory

Vijay Mahadevan
Argonne National Laboratory

Editor

Jack Atkinson

Tags

ocean modeling mesoscale

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