oggm.tasks.run_random_climate

oggm.tasks.run_random_climate(gdir, nyears=1000, y0=None, halfsize=15, bias=None, seed=None, temperature_bias=None, store_monthly_step=False, climate_filename='climate_monthly', climate_input_filesuffix='', output_filesuffix='', init_model_fls=None, zero_initial_glacier=False, unique_samples=False, **kwargs)[source]

Runs the random mass-balance model for a given number of years.

This will initialize a oggm.core.massbalance.MultipleFlowlineMassBalance, and run a oggm.core.flowline.robust_model_run().

Parameters:
gdir : oggm.GlacierDirectory

the glacier directory to process

nyears : int

length of the simulation

y0 : int, optional

central year of the random climate period. The default is to be centred on t*.

halfsize : int, optional

the half-size of the time window (window size = 2 * halfsize + 1)

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

seed : int

seed for the random generator. If you ignore this, the runs will be different each time. Setting it to a fixed seed accross glaciers can be usefull if you want to have the same climate years for all of them

temperature_bias : float

add a bias to the temperature timeseries

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_monthly’ (default) or ‘gcm_data’

climate_input_filesuffix: str

filesuffix for the input climate file

output_filesuffix : str

this add a suffix to the output file (useful to avoid overwriting previous experiments)

init_model_fls : []

list of flowlines to use to initialise the model (the default is the present_time_glacier file from the glacier directory)

zero_initial_glacier : bool

if true, the ice thickness is set to zero before the simulation

unique_samples: bool

if true, chosen random mass-balance years will only be available once per random climate period-length if false, every model year will be chosen from the random climate period with the same probability

kwargs : dict

kwargs to pass to the FluxBasedModel instance

Notes

Files writen to the glacier directory: