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Project details: GreenRise

Acronym: Green Rise
Title: Greenland glacial system and future sea-level rise - "Green Rise"
Duration: 01.01.2014 - 31.12.2017
Project manager: Prof. Dr. Hans Burchard
Funding: Leibniz-Gemeinschaft
Focus: Focus 2: Basin-scale ecosystem dynamics
Cooperation: Potsdam-Institut für Klimafolgenforschung (PIK)

Staff

Merten Siegfried

Description

The Greenland glacial system (GGS) consists of the ice sheet, the outlet glacier system, fjords into which most of the outlet glaciers terminate, the sub- and englacial hydrological system and the surface snow pack. Understanding the dynamics of the GGS, and being able to model these realistically, is an issue of great importance due to the potential of the Greenland Ice Sheet (GIS) to contribute significantly to future sea level rise. The GIS contains enough ice to raise global sea level by 7 m. Observational data suggest that during the past decade mass losses of the GIS significantly accelerated. The GIS contribution to sea level rise may become even more important in the future, yet sea level rise projections remain rather uncertain due to poor understanding of the ice sheet dynamics, in particular the role of fast processes associated with the ice streams, outlet glaciers, and their interaction with the ocean. Achieving progress in modelling of the entire GGS is thus crucial to improving future sea level rise projections. In the past decade considerable progress has been made in the development of models of individual elements of the GGS, such as regional climate models and 3-D ice sheet models. However, a comprehensive model of the entire GGS system does not yet exist. Coupling of state-of-the-art models for all relevant components of the GGS is eventually desirable, but currently computationally too expensive and therefore impractical. Here, we propose an alternative approach based on the use of intermediate complexity modelling components. Such an approach will allow us to design a computationally-efficient modelling tool suitable for performing a large ensemble of simulations of the GGS response to climate change, thus contributing significantly to the assessment of the risk of future sea-level rise.