oggm.core.massbalance.UncertainMassBalance#
- class oggm.core.massbalance.UncertainMassBalance(basis_model, rdn_temp_bias_seed=None, rdn_temp_bias_sigma=0.1, rdn_prcp_fac_seed=None, rdn_prcp_fac_sigma=0.1, rdn_bias_seed=None, rdn_bias_sigma=100)[source]#
Adding uncertainty to a mass balance model.
There are three variables for which you can add uncertainty: - temperature (additive bias) - precipitation (multiplicative factor) - residual (a bias in units of MB)
- __init__(basis_model, rdn_temp_bias_seed=None, rdn_temp_bias_sigma=0.1, rdn_prcp_fac_seed=None, rdn_prcp_fac_sigma=0.1, rdn_bias_seed=None, rdn_bias_sigma=100)[source]#
Initialize.
- Parameters:
- basis_modelMassBalanceModel
the model to which you want to add the uncertainty to
- rdn_temp_bias_seedint
the seed of the random number generator
- rdn_temp_bias_sigmafloat
the standard deviation of the random temperature error
- rdn_prcp_fac_seedint
the seed of the random number generator
- rdn_prcp_fac_sigmafloat
the standard deviation of the random precipitation error (to be consistent this should be renamed prcp_fac as well)
- rdn_bias_seedint
the seed of the random number generator
- rdn_bias_sigmafloat
the standard deviation of the random MB error
Methods
__init__
(basis_model[, rdn_temp_bias_seed, ...])Initialize.
get_annual_mb
(heights[, year, fl_id])Like self.get_monthly_mb(), but for annual MB.
get_ela
([year])Compute the equilibrium line altitude for a given year.
get_monthly_mb
(heights[, year])Monthly mass balance at given altitude(s) for a moment in time.
get_specific_mb
([heights, widths, fls, year])Specific mb for this year and a specific glacier geometry.
is_year_valid
(year)Checks if a given date year be simulated by this model.
Attributes
prcp_fac
Precipitation factor to apply to the original series.
temp_bias
Temperature bias to add to the original series.