# 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
gdiroggm.GlacierDirectory

the glacier directory to process

nyearsint

length of the simulation

y0int, optional

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

halfsizeint, optional

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

biasfloat

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

seedint

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_biasfloat

add a bias to the temperature timeseries

store_monthly_stepbool

whether to store the diagnostic data at a monthly time step or not (default is yearly)

climate_filenamestr

name of the climate file, e.g. ‘climate_monthly’ (default) or ‘gcm_data’

climate_input_filesuffix: str

filesuffix for the input climate file

output_filesuffixstr

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_glacierbool

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

kwargsdict

kwargs to pass to the FluxBasedModel instance

Notes

Files writen to the glacier directory: