Abstract
Abstract. The Antarctic Peninsula (AP) is one of the widely studied polar regions because of its sensitivity to climate change and potential contribution of its glaciers to global sea level rise. Precise digital elevation models (DEMs) at a high spatial resolution are much demanded for investigating the complex glacier system of the AP at fine scales. However, the two most recent circum-Antarctic DEMs, the 12 m TanDEM-X DEM (TDM DEM) from bistatic interferometric synthetic aperture radar (InSAR) data acquired between 2013 and 2014 and the Reference Elevation Model of Antarctica mosaic (REMA mosaic) at an 8 m spatial resolution derived from optical data acquired between 2011 and 2017 have specific individual limitations in this area. The TDM DEM has the advantage of good data consistency and few data voids (approx. 0.85 %), but there exist residual systematic elevation errors such as phase-unwrapping errors in the non-edited DEM version. The REMA mosaic has high absolute vertical accuracy, but on the AP it suffers from extended areas with data voids (approx. 8 %). To generate a consistent, gapless and high-resolution topography product of the AP, we fill the data voids in the TDM DEM with newly processed TDM raw DEM data acquired in austral winters of 2013 and 2014 and detect and correct the residual systematic elevation errors (i.e., elevation biases) in the TDM DEM with the support of the accurately calibrated REMA mosaic. Instead of a pixelwise replacement with REMA mosaic elevations, these provide reference values to correct the TDM elevation biases over entire regions detected through a path propagation algorithm. The procedure is applied iteratively to gradually correct the errors in the TDM DEM from a large to small scale. The proposed method maintains the characteristics of an InSAR-generated DEM and is minimally influenced by temporal or penetration differences between the TDM DEM and REMA mosaic. The performance of the correction is evaluated with laser altimetry data from Operation IceBridge and ICESat-2 missions. The overall root mean square error (RMSE) of the corrected TDM DEM has been reduced from more than 30 m to about 10 m which together with the improved absolute elevation accuracy indicates comparable values to the REMA mosaic. The generated high-resolution DEM depicts the up-to-date topography of the AP in detail and can be widely used for interferometric applications as well as for glaciological studies on individual glaciers or at regional scales.
Highlights
Antarctic Peninsula (AP) glaciers have the potential to raise the global sea level by 69±5 mm (Huss and Farinotti, 2014)
When comparing the original TDM Digital elevation models (DEMs) and the corresponding Reference Elevation Model of Antarctica (REMA) mosaic (Fig. 6a and b, respectively), elevation surface offsets with boundaries caused by phase unwrapping and DEM calibration errors are visible in the TanDEM-X DEM (TDM DEM) as well as in the elevation difference map (Fig. 6c)
For the REMA mosaic, the root mean square error (RMSE) is less than 2 m and the mean average error (MAE) is no more than 3 m for both LVIS 2015 and ATL06 datasets in both corrected and uncorrected regions, indicating that the REMA mosaic is high precision and qualified as ground reference for TDM DEM elevation error correction
Summary
Antarctic Peninsula (AP) glaciers (north of 70◦ S) have the potential to raise the global sea level by 69±5 mm (Huss and Farinotti, 2014). In recent decades they have undergone extensive changes as a consequence of regional climate warming and oceanographic change (Cook et al, 2005, 2014, 2016; Seehaus et al, 2018; Rott et al, 2018; Rignot et al, 2019; Dryak and Enderlin, 2020). As a complex mountainous coastal glacier system, the mass balance of the individual glaciers is affected by climate and oceanographic forcings and by the subglacial and surrounding topography (Cook et al, 2012). DEMs support the mass budget method (Rignot et al, 2011b; Shepherd et al, 2018; Sutterley et al, 2014) and calculating ice velocity (Rignot et al, 2011a; Mouginot et al, 2012) and provide constraints for geodynamic and ice flow modeling (Cornford et al, 2015; Ritz et al, 2015)
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