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EnKF-C provides a compact generic framework for off-line data assimilation (DA) into large-scale layered geophysical models with the ensemble Kalman filter (EnKF).
Following are its other main features:
coded in C for GNU/Linux platform;
model-agnostic;
can conduct DA in EnKF, ensemble optimal interpolation (EnOI), or hybrid EnKF/EnOI modes;
permits multiple model grids;
can handle rectangular, curvilinear, or unstructured horizontal grids, z, sigma or hybrid vertical grids.
EnKF-C is coded for simplicity, scalability and robustness. To handle as large systems as possible it uses shared memory capabilities of MPI-3. Here is a snapshot of ensemble spread of sea surface temperature from the 96-member EnKF ocean forecasting system with MOM5 based OFAM3 model (51 x 1500 x 3600 grid), assimilating about 14M super-observations at each 3-day cycle.
For more information see README and user guide. (An older version of the user guide is also available from arXiv.) Have a feel for how the code works by running the included example.
Checkout EnKF-C by running git clone https://github.com/sakov/enkf-c.
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EnKF code for DA with large-scale layered geophysical models.