oggm.tasks.run_from_climate_data¶
-
oggm.tasks.run_from_climate_data(gdir, ys=None, ye=None, min_ys=None, max_ys=None, store_monthly_step=False, climate_filename='climate_historical', climate_input_filesuffix='', output_filesuffix='', init_model_filesuffix=None, init_model_yr=None, init_model_fls=None, zero_initial_glacier=False, bias=None, **kwargs)[source]¶ Runs a glacier with climate input from e.g. CRU or a GCM.
This will initialize a
oggm.core.massbalance.MultipleFlowlineMassBalance, and run aoggm.core.flowline.flowline_model_run().Parameters: - gdir :
oggm.GlacierDirectory the glacier directory to process
- ys : int
start year of the model run (default: from the glacier geometry date if init_model_filesuffix is None, else init_model_yr)
- ye : int
end year of the model run (default: last year of the provided climate file)
- min_ys : int
if you want to impose a minimum start year, regardless if the glacier inventory date is earlier (e.g. if climate data does not reach).
- max_ys : int
if you want to impose a maximum start year, regardless if the glacier inventory date is later (e.g. if climate data does not reach).
- store_monthly_step : bool
whether to store the diagnostic data at a monthly time step or not (default is yearly)
- climate_filename : str
name of the climate file, e.g. ‘climate_historical’ (default) or ‘gcm_data’
- climate_input_filesuffix: str
filesuffix for the input climate file
- output_filesuffix : str
for the output file
- init_model_filesuffix : str
if you want to start from a previous model run state. Can be combined with init_model_yr
- init_model_yr : int
the year of the initial run you want to start from. The default is to take the last year of the simulation.
- init_model_fls : []
list of flowlines to use to initialise the model (the default is the present_time_glacier file from the glacier directory). Ignored if init_model_filesuffix is set
- zero_initial_glacier : bool
if true, the ice thickness is set to zero before the simulation
- bias : float
bias of the mb model. Default is to use the calibrated one, which is often a better idea. For t* experiments it can be useful to set it to zero
- kwargs : dict
kwargs to pass to the FluxBasedModel instance
Notes
Files writen to the glacier directory:
- gdir :