Speaker
Description
A key uncertainty in mass balance studies of glaciers and ice sheets is still today the density for the volume-to-mass conversion. This is not only reported on a global scale [1] but also for recent local studies [2], where even the presence of in situ measurements can only partly capture the density uncertainty [3]. The volume-to-mass conversion factor can span a wide range from 0 to 2000 kg m−3 but many studies use fixed density values such as 850 ± 60 kg m−3 [4]. Therefore, there is a clear need for improved spatial and temporal information about ice sheet subsurface properties.
Polarimetric and multi-baseline interferometric SAR techniques are promising tools to investigate the subsurface properties of glaciers and ice sheets, due to the signal penetration of up to several tens of meters into dry snow, firn, and ice. (Pol-)InSAR models were shown to provide information about refrozen melt layers [5] and signal extinction [6]. With TomoSAR, the imaging of subsurface features in glaciers [7], and ice sheets [8][9] was demonstrated and the effect of subsurface layers, different ice types, firn bodies, and crevasses was recognized. Such subsurface structure information can provide at most an indirect information about density and a related parameter retrieval method is missing. Further, a general challenge is the ambiguity between the depth of scatterers and the density, because the density determines the permittivity which is required to account for the slower signal propagation speed in the subsurface.
One way of addressing this is the integration of polarimetric measurements. PolSAR models provide a link between the co-polarization HH-VV phase difference (CPD) and the dielectric anisotropy of the firn volume [10]. This modeling approach establishes a relationship of the measured CPD to firn density, firn anisotropy and the vertical backscattering distribution. The integration of vertical backscatter profiles from Pol-InSAR or TomoSAR into the PolSAR CPD model theoretically allows the inversion of firn density from polarimetric and interferometric SAR data. This is investigated with experimental airborne F-SAR data over Greenland. First experiments [11], albeit promising, did not answer yet to which degree a practical inversion is possible. Open questions are the sensitivity and requirements in terms of incidence angles and baselines. The results of this study should give an indication if such an approach might be feasible with future spaceborne SAR systems.
In this context, we will investigate first ideas for potential subsurface information retrieval with BIOMASS that go beyond pure tomographic imaging, since there is a unique chance for suitable baselines over Antarctica during the commissioning phase [12]. Large areas of Antarctica might have a too homogeneous subsurface structure that will be difficult to grasp with the tomographic capabilities of BIOMASS. However, selected cases exist, with e.g. a strong firn-ice contrast, where the potential to derive subsurface structure information with BIOMASS will be assessed. A further evaluation will concern the nominal tomographic phase of BIOMASS, which lacks suitable baselines at high latitudes. Still, some particular subsurface features in the Patagonian ice fields could be a target of interest.
[1] D.G. Vaughan et al., “Observations: Cryosphere,” in Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, [Stocker, T.F. et al. (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, USA, 2013.
[2] K. Shahateet, T. Seehaus, F. Navarro, C. Sommer, and M. Braun, “Geodetic Mass Balance of the South Shetland Islands Ice Caps, Antarctica, from Differencing TanDEM-X DEMs,” Remote Sensing, vol. 13, no. 17, p. 3408, Aug. 2021, doi: 10.3390/rs13173408.
[3] F. J. Navarro, U. Y. Jonsell, M. I. Corcuera, and A. Martín-Español, “Decelerated mass loss of Hurd and Johnsons Glaciers, Livingston Island, Antarctic Peninsula,” J. Glaciol., vol. 59, no. 213, pp. 115–128, 2013, doi: 10.3189/2013JoG12J144.
[4] M. Huss, “Density assumptions for converting geodetic glacier volume change to mass change,” The Cryosphere, vol. 7, no. 3, pp. 877–887, May 2013, doi: 10.5194/tc-7-877-2013.
[5] G. Fischer, K. P. Papathanassiou and I. Hajnsek, "Modeling Multifrequency Pol-InSAR Data from the Percolation Zone of the Greenland Ice Sheet," IEEE Transactions on Geoscience and Remote Sensing, vol. 57, no. 4, pp. 1963-1976, 2019.
[6] E. W. Hoen and H. Zebker, “Penetration depths inferred from interferometric volume decorrelation observed over the Greenland ice sheet,” IEEE Transactions on Geoscience and Remote Sensing, vol. 38, no. 6, pp. 2571–2583, 2000.
[7] S. Tebaldini, T. Nagler, H. Rott, and A. Heilig, “Imaging the Internal Structure of an Alpine Glacier via L-Band Airborne SAR Tomography,” IEEE Transactions on Geoscience and Remote Sensing, vol. 54, no. 12, pp. 7197–7209, 2016.
[8] F. Banda, J. Dall, and S. Tebaldini, “Single and Multipolarimetric P-Band SAR Tomography of Subsurface Ice Structure,” IEEE Transactions on Geoscience and Remote Sensing, vol. 54, no. 5, pp. 2832–2845, 2016.
[9] M. Pardini, G. Parrella, G. Fischer, and K. Papathanassiou, “A Multi-Frequency SAR Tomographic Characterization of Sub-Surface Ice Volumes,” in Proceedings of EUSAR, Hamburg, Germany, 2016.
[10] G. Parrella, I. Hajnsek, and K. P. Papathanassiou, “Retrieval of Firn Thickness by Means of Polarisation Phase Differences in L-Band SAR Data,” Remote Sensing, vol. 13, no. 21, p. 4448, Nov. 2021, doi: 10.3390/rs13214448.
[11] G. Fischer, K. Papathanassiou, I. Hajnsek, and G. Parrella, “Combining PolSAR, Pol-InSAR and TomoSAR for Snow and Ice Subsurface Characterization,” in Proceedings of the ESA POLinSAR Workshop, Online, Apr. 2021.
[12] T. Taillade et al., “Monitoring Cryosphere Sub-Surfaces with BIOMASS mission,” in preparation, ESA BioGeoSAR Workshop, Rome, Nov. 2023.
