Funding period: 2015 – 2017 (resp.)
This project devotes itself to the question, what is the change in height by the densification of firn.
The test area is the Vestfonna Ice Cap (VIC) on the island Nordaustlandet in the north east of Svalbard. The VIC is ~2400 km² in size and has a dome like shape with well defined outlet glaciers. Further test sites with a magnificent in situ measurement archive are welcome.
The propulsion are inaccuracies introduced during the conversion between measured volume change into glacier mass changes. Until now, we calculated glacier mass balances with a constant conversion factor of 850 kg m-3 or the density of ice (917 kg m-3) for entire glacier basins, altitude dependent density variations and firn layer thickness were unnoticed this way. Or we used constant densities for the ablation (900 kg m-3) and accumulation (600 kg m-3) areas, whereby not homogeneous density variations with varying climate conditions were not considered. A decline of the accuracy in the amount of mass change is the consequence. This inaccuracy is a systematic component of uncertainty in geodetically determined mass balances, and thus need to be addressed for accuracy improvement.
The aim is to develop a firn elevation change model (FecMo) Surface Energy Balance (SEB) parameters (e.g. radiation, temperature, wind speed, precipitation, cloud cover fraction). At the moment the model is based on the COupled Snowpack and Ice surface energy and MAss balance glacier model (COSIMA) developed by Huintjes et al. (2015) (link to the open access Git repository). Latter model consists of a SEB model and an integrated subsurface model. Beside the surface energy component, the model has a discrete layer based subsurface structure.
To remove access restrictions by proprietary software, COSIMA-FecMo is developed in the programming language Python. Simple configuration and site specific initialization options will be implemented, additionally it will be possible to replace entire Py-modules (e.g. precipitation, albedo, densification) if more accurate modules are available. The python model will be offered to the scientific community.
FecMo will be forced by climate reanalysis data (e.g. Modèle Atmosphérique Régional (MAR), ERA-interim data from the ECMWF). The forcing will be validated by a AWS network on and around the ice cap. One part of AWS data was recorded during the International Polar Year Project Kinnvika (IPY Kinnvika) between 2007 and 2010, another part is free of charge from the MET Norway (eKlima) and the UNIS. FecMo will be calibrated by in situ measurements from the IPY Kinnvika on mass balance components (ablation, snow package character, firn properties).
The project combines remote sensing data (TanDEM-X, ICESat, CryoSat-2, Sentinel-1A, Aster) and methods (DInSAR, geodetic approach), climate data reanalysis and downscaling (MAR/ERA-Interim) and the extensive analysis of the IPY Kinnvika archive (GPR, snow pit, stake and AWS measurements, GPS and DGPS profiles).
At the end of our study, we will be able to derive layer based firn densities and to estimate firn densification on glaciers and ice caps to retrieve the amount of elevation change that is attributed to compaction.
Project members: Björn Saß
Huintjes E, Sauter T, Schröter B, et al (2015) Evaluation of a Coupled Snow and Energy Balance Model for Zhadang Glacier, Tibetan Plateau, Using Glaciological Measurements and Time-Lapse Photography. Arct Antarct Alp Res 47:573–590. doi: 10.1657/AAAR0014-073
This work is funded by the German Environmental Foundation Scholarship Program (Deutsche Bundesstiftung Umwelt, DBU).