Research field 2: Reducing uncertainties

Reducing uncertainties

Glacier extent is an ECV and various international attempts exist to harmonize a global glacier inventory data set with outlines if possible from multiple data sources (GLIMS, IASC Randolph Glacier Inventory, RGI). However, to date no real operational large-scale repeat mapping capabilities exist. Glacier outlines are required at different time intervals e.g. with matching observational intervals for specific mass balance computations out of remote sensing measurements (e.g. for comparison with in-situ observations or on regional scale) or to validate ice dynamic modelling.

The radar signal can penetrate into snow, firn, and ice bodies depending on liquid water content and internal structure of the porous medium as well as radar imaging parameters. Consequently, the interferometric phase center of the backscattered radar signal is located at a certain depth below the actual topographic surface, leading to a bias between the glacier surface and the estimated one from SAR interferometry (Rott et al 2021, Rizzoli et al 2017). Radar penetration is still a large source of uncertainty in estimates of glacier volume and mass change from bi-static SAR mission data like bi-static TanDEM-X or the upcoming HRWS MirrorSAR (Braun et al. 2019, Huber et al. 2020).

Glacier mass balance variations are an essential indicator for regional and global climate fluctuations. Today, glacier volume changes can be detected with satellite based systems to a reasonable degree of accuracy, while density estimates of the affected volume are still based on models and a priori assumptions. Even though, methods for volume to mass conversion are established, there exists a considerable knowledge gap with respect to validation and temporal stability of the assumptions. Especially the transient evolution of the firn pack will strongly influence the density assumptions of the glaciers with time.