oggm.core.massbalance.LinearMassBalance

class oggm.core.massbalance.LinearMassBalance(ela_h, grad=3.0, max_mb=None)[source]

Constant mass-balance as a linear function of altitude.

__init__(ela_h, grad=3.0, max_mb=None)[source]

Initialize.

Parameters
ela_h: float

Equilibrium line altitude (units: [m])

grad: float

Mass-balance gradient (unit: [mm w.e. yr-1 m-1])

max_mb: float

Cap the mass balance to a certain value (unit: [mm w.e. yr-1])

Attributes
temp_biasfloat, default 0

A “temperature bias” doesn’t makes much sense in the linear MB context, but we implemented a simple empirical rule: + 1K -> ELA + 150 m

Methods

__init__(ela_h[, grad, max_mb])

Initialize.

get_annual_mb(heights, **kwargs)

Like self.get_monthly_mb(), but for annual MB.

get_ela([year])

Compute the equilibrium line altitude for this year

get_monthly_mb(heights, **kwargs)

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

prcp_bias

temp_bias

Temperature bias to add to the original series.