We present SEMIC, a Surface Energy and
Mass balance model of Intermediate Complexity for
snow- and ice-covered surfaces such as the Greenland ice sheet. SEMIC is fast
enough for glacial cycle applications, making it a suitable replacement for
simpler methods such as the positive degree day (PDD) method often used in ice
sheet modelling. Our model explicitly calculates the main processes involved
in the surface energy and mass balance, while maintaining a simple interface
and requiring minimal data input to drive it. In this novel approach, we parameterise
diurnal temperature variations in order to more realistically capture the
daily thaw–freeze cycles that characterise the ice sheet mass balance. We
show how to derive optimal model parameters for SEMIC specifically to
reproduce surface characteristics and day-to-day variations similar to the
regional climate model MAR (Modèle Atmosphérique Régional, version 2)
and its incorporated multilayer snowpack model SISVAT (Soil Ice Snow
Vegetation Atmosphere Transfer). A validation test shows that SEMIC simulates
future changes in surface temperature and surface mass balance in good
agreement with the more sophisticated multilayer snowpack model SISVAT
included in MAR. With this paper, we present a physically based surface model
to the ice sheet modelling community that is general enough to be used with
in situ observations, climate model, or reanalysis data, and that is at the
same time computationally fast enough for long-term integrations, such as
glacial cycles or future climate change scenarios