Day 4

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Paper title Spatio-temporal patterns in Antarctic firn thickness variations from satellite altimetry and modelling
  1. Maria Theresia Kappelsberger Technische Universität Dresden Speaker
  2. Martin Horwath Technische Universität Dresden
  3. Matthias Oskar Willen Technische Universität Dresden
  4. Ludwig Schröder Bundesamt für Kartographie und Geodäsie
Form of presentation Poster
  • A9. Polar Science and Cryosphere
    • A9.04 Mass Balance of the Cryosphere
Abstract text Our understanding of the Antarctic Ice Sheet’s response to climate change is limited. Quantifying the processes that drive changes in ice mass or ice sheet elevation is needed to improve it. So far, signals related to surface mass balance (SMB) and firn compaction are poorly constrained, especially on a sub basin scale. We analyze these signals by distinguishing between fluctuations at decadal to monthly time scales (‘weather effects’) and long-term trends due to past and ongoing climate change (‘climate effects’). We use surface elevation changes (SEC) from multi-mission satellite altimetry and firn thickness variations from SMB and firn modelling results over the time period 1993 to 2016. Dominant temporal patterns are identified by the model output. They capture the occurrence of events affecting firn thickness and characterize the weather effects. We fit these patterns to the temporal variations of altimetric SEC by estimating the related amplitudes and spatial patterns. First results indicate stronger amplitudes of the weather effects observed by altimetry than by the model results with an increase of this difference in amplitudes towards the ice sheet margins. By means of our approach, it is possible to characterize in a statistical sense and to quantify in a deterministic sense the weather-induced fluctuations in firn thickness at a local scale and explore unexplained signals in the altimetric SEC that may imply SMB-related climate effects apart from effects induced by changing ice flow dynamics. A better understanding of the ice sheet processes can then contribute to improvements in SMB and firn modelling.