Bed inversion#

To compute the initial ice thickness \(h_0\), OGGM follows a methodology largely inspired from [Farinotti_et_al_2009], but fully automated and relying on different methods for the mass balance and the calibration.


The principle is simple. Let’s assume for now that we know the flux of ice \(q\) flowing through a cross-section of our glacier. The flowline physics and geometrical assumptions can be used to solve for the ice thickness \(h\):

\[q = u S = \left(f_d h \tau^n + f_s \frac{\tau^n}{h}\right) S\]

With \(n=3\) and \(S = h w\) (in the case of a rectangular section) or \(S = 2 / 3 h w\) (parabolic section), the equation reduces to solving a polynomial of degree 5 with one unique solution in \(\mathbb{R}_+\). If we neglect sliding (the default in OGGM and in [Farinotti_et_al_2009]), the solution is even simpler.

Ice flux#

If we consider a point on the flowline and the catchment area \(\Omega\) upstream of this point we have:

\[q = \int_{\Omega} (\dot{m} - \rho \frac{\partial h}{\partial t}) \ dA = \int_{\Omega} \widetilde{m} \ dA\]

with \(\dot{m}\) the mass balance, and \(\widetilde{m} = \dot{m} - \rho \partial h / \partial t\) the “apparent mass balance” after [Farinotti_et_al_2009]. If the glacier is in steady state, the apparent mass balance is equivalent to the the actual (and observable) mass balance. Unfortunately, that is rarely the case, hence \(\partial h / \partial t\) is not known and there is no easy way to compute it. In order to continue, we have to make the assumption that our geometry is in equilibrium.

This however has a very useful consequence: indeed, for the calibration of our Mass balance models model it is required to find a date \(t^*\) at which the glacier would be in equilibrium with its average climate while conserving its modern geometry. Thus, we have \(\widetilde{m} = \dot{m}_{t^*}\), where \(\dot{m}_{t^*}\) is the 31-yr average mass balance centered at \(t^*\) (which is known since the mass balance model calibration).

The plot below shows the mass flux along the major flowline of Hintereisferner glacier at \(t^*\). By construction, the flux is maximal at the equilibrium line and zero at the glacier tongue.

In [1]: example_plot_massflux()


A number of climate and glacier related parameters are fixed prior to the inversion, leaving only one free parameter for the calibration of the bed inversion procedure: the inversion factor \(f_{inv}\). It is defined such as:

\[A = f_{inv} \, A_0\]

With \(A_0\) the standard creep parameter (\(2.4^{-24}\)). Currently, there is no “optimum” \(f_{inv}\) parameter in the model. There is a high uncertainty in the “true” \(A\) parameter as well as in all other processes affecting the ice thickness. Therefore, we cannot make any recommendation for the “best” parameter. Global sensitivity analyses show that the default value is a good compromise [Maussion_et_al_2019], but very likely leads to overestimated ice volume [Farinotti_et_al_2019].

New in version 1.4!

As of OGGM v1.4, the user can choose to calibrate \(A\) to match the consensus volume estimate from [Farinotti_et_al_2019] on any number of glaciers. We recommend to use a large number of glaciers (we match at the regional level) in order to allow some freedom to the model (it is not guaranteed that the consensus really is better for each glacier), but we assume that it is more accurate at large scales.

Distributed ice thickness#

To obtain a 2D map of the glacier ice thickness and bed, the flowline thicknesses need to be interpolated to the glacier mask. The current implementation of this step in OGGM is currently very simple, but provides nice looking maps:

In [2]: tasks.catchment_area(gdir)

In [3]: graphics.plot_distributed_thickness(gdir)



Farinotti, D., Huss, M., Bauder, A., Funk, M., & Truffer, M. (2009). A method to estimate the ice volume and ice-thickness distribution of alpine glaciers. Journal of Glaciology, 55 (191), 422–430.


Farinotti, D., Huss, M., Fürst, J. J., Landmann, J., Machguth, H., Maussion, F. and Pandit, A.: A consensus estimate for the ice thickness distribution of all glaciers on Earth, Nat. Geosci., 12(3), 168–173, doi:10.1038/s41561-019-0300-3, 2019.


Maussion, F., Butenko, A., Champollion, N., Dusch, M., Eis, J., Fourteau, K., Gregor, P., Jarosch, A. H., Landmann, J., Oesterle, F., Recinos, B., Rothenpieler, T., Vlug, A., Wild, C. T. and Marzeion, B.: The Open Global Glacier Model (OGGM) v1.1, Geosci. Model Dev., 12(3), 909–931, doi:10.5194/gmd-12-909-2019, 2019.