The Greenland Ice Sheet has gained massive attention in recent years due to a sudden increase in mass loss at the onset of this century.
A significant part of this mass loss has been attributed to increased ice discharge at the margin through iceberg calving from marine-terminating outlet glaciers.
However, due to the lack of instrumental data beyond the past 20-30 years, it is difficult to evaluate if this was an outstanding event, or if it was part of a recurring phenomenon acting on inter-annual, inter-decadal, or centennial timescales.
It has been shown that climate warming is responsible for the recent mass loss, however, the exact processes involved in climate forcing of glacier melt is not well understood.
Altogether, this lack of knowledge is reflected in a great uncertainty in the model-based prognoses of the contribution from marine terminating glaciers to future sea level rise.
In this project the record of glacier variability and oceanographic changes is extended beyond the past 20–30 years by analysing marine sediment cores from the vicinity of marine Greenland glacier termini. These sediment cores have been retrieved during cruises conducted in 2009–2014 from fjords around Greenland.
By comparing such a large set of glacier and ocean reconstructions from different settings around Greenland we investigate the influence of oceanographic changes, such as inflow of warm water from the Atlantic Ocean and sea ice variability, on glacier stability – including the timescales involved in change - and gain understanding of the role of the glaciological and bathymetrical setting on outlet glacier changes.
The extended glaciological time series will serve as a tool for tuning an advanced numerical glacier model. Calibration of the model is carried out by running the model for the time period for which the extended glaciological time series has been constructed.
Here, the reconstructed ocean, air, and sea ice variability will be used as fixed input parameters and the model parameters can be adjusted.
Once the model demonstrates the ability to capture the observed glaciological variations (simulate the recorded changes), we will have increased confidence in the reliability of its prognostic assessments. This will enable a relatively more reliable prediction of future mass loss and changes in sea level.