Articles | Volume 11, issue 4
The Cryosphere, 11, 1519–1535, 2017
The Cryosphere, 11, 1519–1535, 2017

Research article 03 Jul 2017

Research article | 03 Jul 2017

SEMIC: an efficient surface energy and mass balance model applied to the Greenland ice sheet

Mario Krapp1,2, Alexander Robinson3,1, and Andrey Ganopolski1 Mario Krapp et al.
  • 1Potsdam Institute for Climate Impact Research (PIK), P.O. Box 60 12 03, 14412 Potsdam, Germany
  • 2Department of Zoology, University of Cambridge, Cambridge CB2 3EJ, UK
  • 3Departamento de Astrofísica y Ciencias de la Atmósfera, Universidad Complutense de Madrid, 28040 Madrid, Spain

Abstract. 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.

Short summary
We present the snowpack model SEMIC. It calculates snow height, surface temperature, surface albedo, and the surface mass balance of snow- and ice-covered surfaces while using meteorological data as input. In this paper we describe how SEMIC works and how well it compares with snowpack data of a more sophisticated regional climate model applied to the Greenland ice sheet. Because of its simplicity and efficiency, SEMIC can be used as a coupling interface between atmospheric and ice sheet models.