oggm.core.massbalance.ConstantMassBalance¶

class oggm.core.massbalance.ConstantMassBalance(gdir, mu_star=None, bias=None, y0=None, halfsize=15, filename='climate_historical', input_filesuffix='', **kwargs)[source]¶

Constant mass balance during a chosen period.

This is useful for equilibrium experiments. Note that is is the “correct” way to represent the average mass balance over a given period. See: https://oggm.org/2021/08/05/mean-forcing/

Attributes

y0int: the center year of the period
halfsizeint: the halfsize of the period
yearsndarray: the years of the period

__init__(gdir, mu_star=None, bias=None, y0=None, halfsize=15, filename='climate_historical', input_filesuffix='', **kwargs)[source]¶

Initialize

Parameters

gdirGlacierDirectory: the glacier directory
mu_starfloat, optional: set to the alternative value of mu* you want to use (the default is to use the calibrated value)
biasfloat, optional: set to the alternative value of the annual bias [mm we yr-1] you want to use (the default is to use the calibrated value)
y0int, optional, default: tstar: the year at the center of the period of interest. The default is to use tstar as center.
halfsizeint, optional: the half-size of the time window (window size = 2 * halfsize + 1)
filenamestr, optional: set to a different BASENAME if you want to use alternative climate data.
input_filesuffixstr: the file suffix of the input climate file

Methods

`__init__`(gdir[, mu_star, bias, y0, ...])	Initialize
`get_annual_climate`(heights[, year])	Average climate information at given heights.
`get_annual_mb`(heights[, year, add_climate])	Like self.get_monthly_mb(), but for annual MB.
`get_ela`([year])	Compute the equilibrium line altitude for a given year.
`get_monthly_climate`(heights[, year])	Average climate information at given heights.
`get_monthly_mb`(heights[, year, add_climate])	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.

Attributes

`bias`	Residual bias to apply to the original series.
`interp_m`
`interp_yr`
`prcp_fac`	Precipitation factor to apply to the original series.
`temp_bias`	Temperature bias to add to the original series.