NEDAS.models.qg.fortran package

class NEDAS.models.qg.fortran.QGFortranModel(**kwargs)[source]

Bases: Model

Class for configuring and running the qg model

kmax: int
nz: int
restart_dt: float
psi_init_type: str
model_code_dir: str
model_env: str
spinup_hours: int
filename(**kwargs)[source]
read_grid(**kwargs)[source]

Read the grid information from the model output.

Parameters:

**kwargs – Keyword arguments for reading the grid.

read_mask(**kwargs)[source]
read_var(**kwargs)[source]

Read a variable from the model output.

Parameters:

**kwargs – Keyword arguments for reading the variable.

Returns:

The read variable.

Return type:

np.ndarray

write_var(var, **kwargs)[source]

Write a variable to the model output.

Parameters:

  • var (np.ndarray) – The variable to write.

  • **kwargs – Keyword arguments for writing the variable.

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.

generate_truth(*args, **kwargs) → None[source]

Generate truth (nature run) model states. Use for running synthetic observation experiments.

generate_init_ensemble(*args, **kwargs) → None[source]

Generate initial perturbed model states for ensemble forecasts.

Parameters:

  • nens (int) – ensemble size

  • **kwargs

Subpackages

Submodules