EGU23-2096, updated on 22 Feb 2023
https://doi.org/10.5194/egusphere-egu23-2096
EGU General Assembly 2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

The Evolution of the Snow Facies on the Greenland Ice Sheet Observed by the Last Decade of TanDEM-X Interferometric SAR Data

Alexandre Becker Campos1,2, Paola Rizzoli2, Carolina Gonzalez2, José-Luis Bueso-Bello1,2, and Matthias Braun1
Alexandre Becker Campos et al.
  • 1Institut für Geographie, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
  • 2German Aerospace Center (DLR), Weßling, Germany

Climate change and the resulting accelerating melt on the Greenland and Antarctic ice sheets are causing dramatic and irreversible changes at a global scale, significantly contributing to sea-level rise. In this scenario, monitoring the evolution of diagenetic snow facies can provide valuable insights to better comprehend climate-related variables and trends. Previous studies of the Greenland ice sheet led to the definition of four main snow facies, depending on the amount of snow melt and on the properties of the snow pack itself: the inner dry snow zone, where melt does not occur; the percolation zone, where a limited amount of melt per year occurs, leading to the generation of larger snow grains and the formation of small ice structures; the wet snow zone, where a substantial part of the snow melt drains off during summer and is characterized by the presence of multiple ice layers; and the outer ablation zone, where the previous year accumulation completely melts during summer, resulting in a surface of bare ice and surface moraine. By exploiting X-band TanDEM-X interferometric synthetic aperture radar (InSAR) acquisitions, previous works explored the idea of classifying different snow facies of the Greenland ice sheet utilizing an unsupervised machine learning clustering approach. The analysis was performed using data acquired in winter 2010/2011 only, under the assumption of stable climatic conditions and similar acquisition geometries. In this paper, we further investigate the evolution of the snow facies of Greenland throughout the last decade of TanDEM-X observations, proposing unsupervised machine learning strategies for snow facies characterization by using InSAR features such as backscatter, volume decorrelation, the incidence angle and height of ambiguity. We use TanDEM-X data acquired during the winter of 2010/2011, 2015/2016, 2016/2017, 2020/2021, and 2021/2022, where full or partial coverage of the Greenland ice sheet is available. The challenges and caveats of such approaches for different image acquisition geometries will be presented. Finally, the potential of TanDEM-X for investigating large-scale interannual changes in the dry snow zone over Greenland will be investigated as well.  

How to cite: Becker Campos, A., Rizzoli, P., Gonzalez, C., Bueso-Bello, J.-L., and Braun, M.: The Evolution of the Snow Facies on the Greenland Ice Sheet Observed by the Last Decade of TanDEM-X Interferometric SAR Data, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-2096, https://doi.org/10.5194/egusphere-egu23-2096, 2023.