NEDAS.models.lorenz96 package
Submodules
NEDAS.models.lorenz96.core module
NEDAS.models.lorenz96.generate_init_ensemble module
NEDAS.models.lorenz96.generate_truth module
NEDAS.models.lorenz96.model module
Module contents
- class NEDAS.models.lorenz96.Lorenz96Model(**kwargs)[source]
-
- io_mode: Literal['online', 'offline'] = 'online'
- nx: int
- F: float
- dt: float
- restart_dt: float
- memory: dict = {}
- read_grid(**kwargs)[source]
Read the grid information from the model output.
- Parameters:
**kwargs – Keyword arguments for reading the grid.
- z_coords(**kwargs)[source]
Get the vertical coordinates of the model.
- Parameters:
**kwargs – Keyword arguments for getting the vertical coordinates.
- Returns:
The vertical coordinates.
- Return type:
np.ndarray
- preprocess(*args, **kwargs)[source]
Preprocess the model data.
- Parameters:
**kwargs – Keyword arguments for preprocessing.
- postprocess(*args, **kwargs)[source]
Postprocess the model data.
- Parameters:
**kwargs – Keyword arguments for postprocessing.
- run(*args, **kwargs)[source]
Run the model forward in time.
- Parameters:
*args – Arguments
**kwargs – Keyword arguments
- Keyword Arguments:
time (datetime) – current time when forecast starts
restart_dir (str) – directory where restart files are located
forecast_period (int) – forecast period in hours
If self.ens_run_strategy == ‘batch’, the method will run all ensemble members in one go, expect additional kwargs[‘nens’] to be the ensemble size. If self.ens_run_strategy == ‘scheduler’, the method runs a single member indexed by kwargs[‘member’], and kwargs[‘worker_id’] is the pid assigned by the scheduler to run this method.