Characteristics of the 1979–2020 Antarctic firn layer simulated with IMAU-FDM v1.2A

• Published in: The Cryosphere
• Main Authors: Veldhuijsen, Sanne B. M., van de Berg, Willem Jan, Brils, Max, Kuipers Munneke, Peter, van den Broeke, Michiel R.
• Format: Article in Journal/Newspaper
• Language: English
• Published: Copernicus Publications 2023
• Subjects: article; Verlagsveröffentlichung; Antarctic; Antarctic Peninsula; Dronning Maud Land; Ellsworth Land; The Antarctic; Wilkes Land; Antarc*; ice core; Ice Sheet; The Cryosphere
• Online Access: https://doi.org/10.5194/tc-17-1675-2023; https://noa.gwlb.de/receive/cop_mods_00065959; https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00064464/tc-17-1675-2023.pdf; https://tc.copernicus.org/articles/17/1675/2023/tc-17-1675-2023.pdf

Firn simulations are essential for understanding Antarctic ice sheet mass change, as they enable us to convert satellite altimetry observed volume changes to mass changes and column thickness to ice thickness and to quantify the meltwater buffering capacity of firn. Here, we present and evaluate a simulation of the contemporary Antarctic firn layer using the updated semi-empirical IMAU Firn Densification Model (IMAU-FDM) for the period 1979–2020. We have improved previous fresh-snow density and firn compaction parameterizations and used updated atmospheric forcing. In addition, the model has been calibrated and evaluated using 112 firn core density observations across the ice sheet. We found that 62 % of the seasonal and 67 % of the decadal surface height variability are due to variations in firn air content rather than firn mass. Comparison of simulated surface elevation change with a previously published multi-mission altimetry product for the period 2003–2015 shows that performance of the updated model has improved, notably in Dronning Maud Land and Wilkes Land. However, a substantial trend difference (>10 cm yr−1) remains in the Antarctic Peninsula and Ellsworth Land, mainly caused by uncertainties in the spin-up forcing. By estimating previous climatic conditions from ice core data, these trend differences can be reduced by 38 %.