Examples and corresponding options

This section gives a very brief overview of some coupling options. Please see sections referenced below for more information.

One way coupling to a climate model

One-way coupling of PISM to a climate model can be achieved by reading a NetCDF file with time- and space-dependent climate data produced by a climate model.

There are two cases:

  • coupling to a climate model that includes surface (firn, snow) processes

  • coupling to a climate model providing near-surface air temperature and precipitation

Reading ice surface temperature and mass balance

This is the simplest case. It is often the preferred case, for example when the climate model in use has high quality surface mass and energy sub-models which are then preferred to the highly simplified (e.g. temperature index) surface models in PISM.


climatic_mass_balance, ice_surface_temp


-surface given -surface_given_file forcing.nc

See also

Reading top-surface boundary conditions from a file

Reading air temperature and precipitation

As mentioned above, if a climate model provides near-surface air temperature and precipitation, these data need to be converted into top-of-the-ice temperature and climatic mass balance.

One way to do that is by using a temperature index (PDD) model component included in PISM. This component has adjustable parameters; default values come from [148].


precipitation, air_temp


-atmosphere given -atmosphere_given_file forcing.nc -surface pdd

See also

Boundary conditions read from a file, Temperature-index scheme

If melt is negligible -surface pdd should be replaced with -surface simple (see section The “invisible” model).

Using climate anomalies

Prognostic modeling experiments frequently use time- and space-dependent air temperature and precipitation anomalies.


precipitation, air_temp, precipitation_anomaly, air_temp_anomaly


-atmosphere given,anomaly, -atmosphere_given_file forcing.nc, -atmosphere_anomaly_file anomalies.nc, -surface simple

See also

Boundary conditions read from a file, Using climate data anomalies, The “invisible” model

The simple surface model component re-interprets precipitation as climatic mass balance, which is useful in cases when there is no melt (Antarctic simulations is an example).

Simulations of the Greenland ice sheet typically use -surface pdd instead of -surface simple.


The SeaRISE-Greenland setup uses a parameterized near-surface air temperature [145] and a constant-in-time precipitation field read from an input (-i) file. A temperature-index (PDD) scheme is used to compute the climatic mass balance.


precipitation, lat, lon


-atmosphere searise_greenland -surface pdd

See also

SeaRISE-Greenland, Temperature-index scheme

The air temperature parameterization is a function of latitude (lat), longitude (lon) and surface elevation (dynamically updated by PISM).

SeaRISE-Greenland paleo-climate run

The air temperature parameterization in the previous section is appropriate for present day modeling. PISM includes some mechanisms allowing for corrections taking into account differences between present and past climates. In particular, one can use ice-core derived scalar air temperature offsets [8], precipitation adjustments [31], and sea level offsets from SPECMAP [9].


precipitation, delta_T, delta_SL, lat, lon


-atmosphere searise_greenland,delta_T -atmosphere_delta_T_file delta_T.nc -surface pdd -sea_level constant,delta_sl -ocean_delta_sl_file delta_SL.nc

See also

SeaRISE-Greenland, Scalar temperature offsets, Temperature-index scheme, Constant in time and space, Scalar sea level offsets

Note that the temperature offsets are applied to air temperatures at the atmosphere level. This ensures that \(\Delta T\) influences the PDD computation.

Antarctic paleo-climate runs


climatic_mass_balance, air_temp, delta_T, delta_SL


-surface given,delta_T -surface_delta_T_file delta_T.nc -sea_level constant,delta_sl -ocean_delta_sl_file delta_SL.nc

See also

Reading top-surface boundary conditions from a file, Scalar temperature offsets, Constant in time and space, Scalar sea level offsets

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