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MPAS Data Assimilation
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MPAS-JEDI offers a versatile data-assimilation system for MPAS and is the focus of development within NSF NCAR/MMM. MPAS-JEDI provides interfaces for MPAS to the Joint Effort for Data assimilation Integration (JEDI), whose development is led by the Joint Center for Satellite Data Assimilation (`JCSDA <https://www.jcsda.org/>`_). MPAS-JEDI benefits from collaboration with the JCSDA core team and leverages contributions to JEDI from other partners, including NOAA, NASA, UK Met Office, and US Navy. MPAS-JEDI's capabilities include the use of regional, global, quasi-uniform, and variable-resolution MPAS meshes, the direct assimilation of remotely sensed observations, such as satellite radiances, and both variational and ensemble DA techniques.

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Resources
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*   `Download the latest tagged version of MPAS-JEDI code <https://github.com/JCSDA/mpas-bundle/tree/3.0.2>`_
*   `MPAS-JEDI Tutorial Practice Guide <https://www2.mmm.ucar.edu/projects/mpas-jedi/tutorial/202410HOWARD/>`_ based on latest tagged code
*   MPAS-JEDI papers:

    *   Implementation and initial 3DEnVar results, `Liu et al. 2022 <https://gmd.copernicus.org/articles/15/7859/2022/gmd-15-7859-2022.html>`_
    *   Ensemble of data assimilations (EDA), `Guerrette et al. 2023 <https://gmd.copernicus.org/articles/16/7123/2023/>`_
    *   Static background-error covariances and 3DVar results, `Jung et al. 2024 <https://gmd.copernicus.org/articles/17/3879/2024/>`_

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An implementation of a serial ensemble Kalman filter for MPAS, through the Data Assimilation Research Testbed (DART), is also available. MPAS/DART was developed in collaboration with the Data Assimilation Research Section within NSF NCAR's Computational and Information Systems Lab. For further information, see `Ha et al. 2017 <https://doi.org/10.1175/MWR-D-17-0145.1>`_ or the `DART pages <https://dart.ucar.edu/research/mpas/>`_.

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