1) High resolution mass balance, melt water production, dynamics modelingUiO, (Schuler), UNIS (Benn), NPI, NVE, (USw, IMAU, UI)
Glacier mass balance data (WP1) will be used to calibrate surface mass balance models. Initially, these will be driven by data from weather stations. Downscaling algorithms will be used to adjust data from General Circulation Models (GCM) to the regional scale. Forced by these climate datasets, the mass balance modeling will be extended into the past (reanalysis) and future (climate scenarios). Surface mass balance modeling yields meltwater production rates which, together with computed driving stresses will be used to outline regions where enhanced glacier flow is expected. This information will be used in modeling ice dynamics using SICOPOLOS, a well documented and tested 3-dimensional, thermo-mechanically coupled ice sheet model. The coupled modeling approach ensures that the mass balance-hydrology-dynamics feedback mechanism (Fig. 1) is included in the analysis of glacier response to climate change. In addition, this approach allows the model to be calibrated on different levels using data obtained in WP1, thereby enhancing reliability of the model results. In addition, three key glaciological processes will be modeled in detail within the project: meltwater storage, temperature evolution, and calving dynamics.
2) Meltwater storage - superimposed ice
UNIS(Böggild), UiO, NPI (UI, UB)
A wide spectrum of models has been developed to estimate melt water storage (MWS) on glaciers. However, many suffer from over-simplifications and lack proper physical treatment of driving processes. Improved parameterization and verification of internal accumulation is needed in mass balance models. We will focus on the spatial variability and total volume of MWS by a combination of model analysis and targeted field work; analyse the processes from high resolution and small scale test fields on Kongsvegen / Kronebreen and Austfonna, assess relevant glaciological parameters and their gradients on glaciers from existing data and new field data by snow radar, shallow cores, snow pits, temperature, density etc., analyse parameters controlling meltwater storage and SI formation from detailed model analysis.
3) Temperature modeling
UMB (Rolstad), UiO, (UI,UB)
Changes in glacier dynamics may be related to changes in the temperature regime. Thermo-dynamical numerical modeling will be conducted to determine the thermal regime of Austfonna and initialize the thermomechanically-coupled ice dynamics model. Input data will come from existing borehole data, field work and remote sensing. The temperature conditions on the bed will be verified from GPR data.
4) Calving dynamics
UNIS (Benn), UMB (Rolstad)
Numerical modeling of the dynamic response of Kronebreen and Austfonna to climate change will include physically-based representations of calving losses, by incorporating the calving model tested and developed in WP 4.