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 technical details, including dependencies, compilation steps, and runtime troubleshooting, please refer to enkf/README.
Detailed documentation is available in the 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 examples.
Checkout EnKF-C by running git clone https://github.com.
Sakov, P., 2014: EnKF-C user guide. Technical Report, Bureau of Meteorology. Available online from the EnKF-C arXiv Paper Repository.