Investigating the bias of TanDEM-X digital elevation models of glaciers on the Tibetan Plateau: impacting factors and potential effects on geodetic mass-balance measurements

Abstract

The TanDEM-X DEM is a valuable data source for estimating glacier mass balance. However, the accuracy of TanDEM-X elevation over glaciers can be affected by microwave penetration and phase decorrelation. To investigate the bias of TanDEM-X DEMs of glaciers on the Tibetan Plateau, these DEMs were subtracted from SPOT-6 DEMs obtained around the same time at two study sites. The average bias over the studied glacier areas in West Kunlun (175.0 km2) was 2.106 ± 0.012 m in April 2014, and it was 1.523 ± 0.011 m in Geladandong (228.8 km2) in October 2013. By combining backscatter coefficients and interferometric coherence maps, we found surface decorrelation and baseline decorrelation can cause obvious bias in addition to microwave penetration. If the optical/laser data and winter TanDEM-X data were used as new and historic elevation sources for mass-balance measurements over an arbitrary observation period of 10 years, the glacier mass loss rates in West Kunlun and Geladandong would be potentially underestimated by 0.218 ± 0.016 and 0.158 ± 0.011 m w.e. a−1, respectively. The impact is therefore significant, and users should carefully treat the bias of TanDEM-X DEMs when retrieving a geodetic glacier mass balance.

Brief communication: Increased glacier mass loss in the Russian High Arctic (2010–2017)

“…Thus, the differences in backscatter intensity could be caused by either accumulation of fresh snow at the glacier surface or days with snowmelt during September 2016. It is likely that the depth of signal penetration in the winter seasons 2010/11 and 2016/17 was relatively large, i.e., several meters, as found by previous studies (Millan et al, 2015;Zhao and Floricioiu, 2017;Abdullahi et al, 2018;Li et al, 2021), but similar due to comparable dry and frozen surface conditions. For TanDEM-X DEMs of the Antarctic Peninsula it was observed that the measured coldseason heights rather referred to the refrozen firn of the previous summer than to the actual glacier surface (Rott et al, 2014).…”

“…In general, SAR penetration is close to zero for melting snow surfaces and bare glacier ice and increases in dry snow. Xband penetration depths of several meters have been observed in different regions (e.g., Millan et al, 2015;Zhao and Floricioiu, 2017;Abdullahi et al, 2018;Li et al, 2021). Previously, penetration depths have been estimated by a number of studies (e.g., Abdullahi et al, 2018Abdullahi et al, , 2019Li et al, 2021) using backscatter intensity.…”

“…Xband penetration depths of several meters have been observed in different regions (e.g., Millan et al, 2015;Zhao and Floricioiu, 2017;Abdullahi et al, 2018;Li et al, 2021). Previously, penetration depths have been estimated by a number of studies (e.g., Abdullahi et al, 2018Abdullahi et al, , 2019Li et al, 2021) using backscatter intensity. SAR backscatter intensity depends on physical properties of the glacier ice, such as grain size and density, roughness and water content (Wessel et al, 2016), and changes between melting and frozen conditions.…”

Measuring glacier mass changes from space—a review

“…They are only able to provide a region-wide mass balance estimate when aggregated over sufficiently large regions so that glaciers (in particular the different elevations bands) are well sampled. The denser sampling by CryoSat-2 swath altimetry and ICESat-2 allows resolving regions of 100 by 100 km and infer the seasonal elevation changes (Jakob et al 2021, Wang et al 2021. For ICESat, the spatial sampling was sparser and temporally more irregular so that mass loss estimates were mostly restricted to a single value (for the period 2003-2008) over large regions (Kääb et al 2015).…”

Estimating the Changes in Glaciers and Glacial Lakes in the Xixabangma Massif, Central Himalayas, between 1974 and 2018 from Multisource Remote Sensing Data

“…where l is the length of the glacier/lake boundary and r is the image resolution. The uncertainty of the average glacier elevation (δ average ) was calculated on the basis of the uncertainty of the elevation difference over stable regions and the spatial autocorrection of the elevation difference [7,43]. The computation formula is…”