Interferometric synthetic aperture radar (InSAR) data suffer from an elevation bias due to signal penetration into the firn and ice surface, rendering the height information unusable for elevation and mass-change detection. This study estimates the penetration bias in X-band InSAR data to quantify its impact on elevation and mass-change detection and to demonstrate the applicability of TanDEM-X digital elevation models (DEMs) for cryosphere research. To achieve this, a multiple linear regression model is applied to a time series of four TanDEM-X DEMs acquired between 2010 and 2018 over the Sverdrup Glacier basin (SGB), Devon Ice Cap, Canada. The resulting penetration corrected TanDEM-X DEMs agreed to within ±14 cm of spatially and temporally coincident precise in situ kinematic dGPS data (±10 cm RMSE). Additionally, multi-year estimations of mass change for the SGB derived from differencing TanDEM-X DEMs over multi-year periods between 2010 and 2018, showed good agreement with mean deviation of 338 ± 166 mm w.e. with independent measurements of mass change derived from annual in situ surface mass balance over the same time periods. The results show that the penetration bias can vary significantly, leading to random under- and overestimations in the detection of elevation and mass changes.

Scenario–neutral methods are commonly used to rapidly compare system responses to changes in climate. Using glacier mass balance as a system response, we present a bottom-up, scenario–neutral method as an effective tool for preliminary and overview studies on glacier sensitivity and a complementary approach to traditional top–down methods. The method's main characteristic is its visual result: two–dimensional response surfaces depicting glacier mass balance. Their axes represent perturbations in temperature and precipitation relative to a baseline. The simplicity of our approach makes it applicable to all global glaciers. As a proof–of–concept, the Open Global Glacier Model (OGGM) is used to perform a scenario–neutral glacier sensitivity analysis for four glaciers. In addition, the integration with a top–down approach is demonstrated by overlaying temperature and precipitation from four Coupled Model Intercomparison Project Phase 6 (CMIP6) models, under four Shared Socioeconomic Pathways (SSP). Finally, the benefits of the method are discussed for decision–making and science communication. Assessing results shows that overall, this scenario–neutral method can provide useful information for the research of climate change impact on glacier mass, from aiding study design to science communication.

We developed automated ablation stakes to measure colocated in situ changes in relative glacier-surface elevation and climatological drivers of ablation. The designs, refined over 10 years of development and deployments, implement open-source hardware and common building materials. The ablation stakes record distance to the snow/ice surface, air temperature and relative humidity every 1–15 min. Using these high-frequency data, we demonstrate that melt factors calculated using standard melt-rate vs temperature regressions converge over averaging windows of approximately 12 h or greater. Furthermore, we evaluate an integral approach to estimating temperature-index melt factors for ablation. In a test case on Glaciar Perito Moreno, Argentina, this integral approach reveals an overall positive-degree-day melt factor of 7.5 mm w.e. $^\circ$C−1 d−1. We describe four deployments with iteratively improved designs and provide a list of materials required to construct an automated ablation stake.