Articles | Volume 7, issue 2
https://doi.org/10.5194/esd-7-397-2016
https://doi.org/10.5194/esd-7-397-2016
Research article
 | 
26 Apr 2016
Research article |  | 26 Apr 2016

An ice sheet model of reduced complexity for paleoclimate studies

Basil Neff, Andreas Born, and Thomas F. Stocker

Abstract. IceBern2D is a vertically integrated ice sheet model to investigate the ice distribution on long timescales under different climatic conditions. It is forced by simulated fields of surface temperature and precipitation of the Last Glacial Maximum and present-day climate from a comprehensive climate model. This constant forcing is adjusted to changes in ice elevation. Due to its reduced complexity and computational efficiency, the model is well suited for extensive sensitivity studies and ensemble simulations on extensive temporal and spatial scales. It shows good quantitative agreement with standardized benchmarks on an artificial domain (EISMINT). Present-day and Last Glacial Maximum ice distributions in the Northern Hemisphere are also simulated with good agreement. Glacial ice volume in Eurasia is underestimated due to the lack of ice shelves in our model.

The efficiency of the model is utilized by running an ensemble of 400 simulations with perturbed model parameters and two different estimates of the climate at the Last Glacial Maximum. The sensitivity to the imposed climate boundary conditions and the positive degree-day factor β, i.e., the surface mass balance, outweighs the influence of parameters that disturb the flow of ice. This justifies the use of simplified dynamics as a means to achieve computational efficiency for simulations that cover several glacial cycles. Hysteresis simulations over 5 million years illustrate the stability of the simulated ice sheets to variations in surface air temperature.

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