Digital elevation models (DEMs) from the spaceborne interferometric radar mission TanDEM-X hold a large potential for glacier change assessments. However, a bias is potentially introduced through the penetration of the X-band signal into snow and firn. To improve our understanding of radar penetration on glaciers, we compare DEMs derived from the almost synchronous acquisition of TanDEM-X and Pléiades optical stereo-images of Grosser Aletschgletscher in March 2021. We found that the elevation bias – averaged per elevation bin – can reach up to 4–8 m in the accumulation area, depending on post co-registration corrections. Concurrent in situ measurements (ground-penetrating radar, snow cores, snow pits) reveal that the signal is not obstructed by the last summer horizon but reaches into perennial firn. Because of volume scattering, the TanDEM-X surface is determined by the scattering phase centre and does not coincide with a specific firn layer. We show that the bias corresponds to more than half of the decadal ice loss rate. To minimize the radar penetration bias, we recommend to select DEMs from the same time of the year and over long observation periods. A correction of the radar penetration bias is recommended, especially when combining optical and TanDEM-X DEMs.
Bulk aerodynamic methods have been shown to perform poorly in computing turbulent heat fluxes at glacier surfaces during shallow katabatic winds. Katabatic surface layers have different wind shear and flux profiles to the surface layers for which the bulk methods were developed, potentially invalidating their use in these conditions. In addition, eddy covariance-derived turbulent heat fluxes are unlikely to be representative of surface conditions when eddy covariance data are collected close to the wind speed maximum (WSM). Here we utilize two months of eddy covariance and meteorological data measured at three different heights (1 m, 2 m, and 3 m) at Kaskawulsh Glacier in the Yukon, Canada, to re-examine the performance of bulk methods relative to eddy covariance-derived fluxes under different near-surface flow regimes. We propose a new set of processing methods for one-level eddy covariance data to ensure the validity of calculated fluxes during highly variable flows and low-level wind speed maxima, which leads to improved agreement between eddy covariance-derived and modelled fluxes across all flow regimes, with the best agreement (correlation >0.9) 1 m above the surface. Contrary to previous studies, these results show that adequately processed eddy covariance data collected at or above the WSM can provide valid estimates of surface heat fluxes.
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