Cast shadows reveal changes in glacier surface elevation

Accurate measurements of glacier surface topography and their changes play an essential role in various glaciological studies related to glacier dynamics and mass balance. The focus of this study is on mapping glacier digital elevation model (DEM) and elevation changes in the western Qilian Mountains, northern Tibetan Plateau, by synergistically using the TanDEM-X (TDX) bistatic Interferometric Synthetic Aperture Radar (InSAR) data in 2013 and Shuttle Radar Topography Mission (SRTM) DEM in 2000. The first high-resolution and high-precision glacier DEM is derived in this region by a TDX InSAR procedure with a nonlocal (NL) filter. Validated against the Ice, Cloud, and land Elevation Satellite (ICESat) height references, the absolute height error of the TanDEM-X DEM derived with the NL filter and the Goldstein filter with the parameters investigated is, respectively, 1.493 ± 0.747 and 1.857 ± 1.709 m. Further, four combinations of differential phase method (DiffPha) and DEM differencing method (DiffDem) with Goldstein filter and NL filter are applied to estimate glacier elevation changes between 2000 and 2013. The synergistic use of the DiffPha method and the NL filter is superior to other three combinations in terms of uncertainty and noise reduction. Generally, a clear surface thinning can be found in most glacier tongue regions, the maximum value of elevation lowering up to approximately −40 m, whereas a slight thickening is detected in accumulation areas, which are in agreement with the height difference results between GPS measurements and SRTM DEM over Laohugou Glacier No.12. This study demonstrates the potential of the TanDEM-X bistatic InSAR in mapping surface topography and elevation changes of valley glaciers in the Tibetan Plateau.

The Antarctic Peninsula (AP), encompassing the ice sheet and its peripheral glaciers, is a highly dynamic component of the cryosphere, disproportionately contributing to sea level rise. However, a large spread remains between the mass changes estimated using gravimetry, altimetry and the input/output method. Among these techniques, the satellite (radar or laser) altimetry method has a resolution of, at best, 1 km, which is too coarse to resolve the complex pattern of changes in the Peninsula. Therefore, we use digital elevation models (DEMs; 30x30 m) to map elevation changes for the entire Peninsula, combining 476 DEMs derived from SPOT5-HRS satellite images (2006-2008) and 2525 strips of the Reference Elevation Model of Antarctica (2020-2022) to provide a comprehensive 14-year record. We bias-corrected each DEM using near-synchronous ICESat/-2 laser altimetry measurements.Our observations cover 70% of the AP ice sheet and 60% of its peripheral glaciers, including for regions of the Peninsula poorly studied to date and decipher a spatially complex pattern of elevation changes. After correction with different models of firn air content and solid-earth response, we find that between 2007 and 2021, the AP ice sheet lost -27 ± 9 Gt/yr while its peripheral glaciers lost -14 ± 2 Gt/yr. For the AP ice sheet, our new estimate is 4 to 5 times more negative than the one obtained in IMBIE using purely altimetry data (-6 ± 6 Gt/yr from 2006 to 2018) and in better agreement with gravimetry and the input/output method. Our study highlights the importance of resolving fine scale elevation changes of glaciers and ice sheets.

Glacier surging is a dynamic instability that affects the flow of some glaciers, modifying the glacier area, surface velocity, and surface elevation. It is also among the major causes of ice dams and glacier lake floods. Previous studies have shown that in the West Kunlun Mountains| (WKM) where a cluster of surge‐type glaciers had been found, the glaciers were relatively stable in recent years. Nevertheless, the surge cycle and its impact on glacier changes on a regional scale are poorly understood. In this study, we updated the surge‐type glacier inventory of the WKM using the detailed changes in glacier length, surface velocity, and surface elevation during the 1972–2020 period using 78 Landsat optical images, 86 Sentinel‐1 synthetic aperture radar (SAR) images, and three digital elevation models of the WKM. The updated results show that among the 423 glaciers in the WKM, 10 are confirmed as surge‐type glaciers, three are likely surge‐type glaciers, and five are possible surge‐type glaciers. Furthermore, these 18 glaciers account for 63% of the total glacier area. During the period analyzed, there were marked changes in the lengths, areas and surface elevations of all surge‐type glaciers, while those of the non‐surge‐type glaciers were relatively stable. These results appear to indicate that the observed regional trends of glaciers in the WKM recently may be related to the existence of surge‐type glaciers. Furthermore, the surge‐type glacier underwent advance after accelerating for 3–4 years, which could be used to forecast when glacier termini may advance and avoid the possible catastrophic damages.

Ice loss rates at the Northern Patagonian Icefield derived using a decade of satellite remote sensing

Glaciers in the central Andes of Chile are fundamental freshwater sources for ecosystems and communities. Overall, glaciers in this region have shown continuous recession and down-wasting, but long-term glacier mass balance studies providing precise estimates of these changes are scarce. Here, we present the first long-term (1955–2013/2015), region-specific glacier elevation and mass change estimates for the Maipo River Basin, from which the densely populated metropolitan region of Chile obtains most of its freshwater supply. We calculated glacier elevation and mass changes using historical topographic maps, Shuttle Radar Topography Mission (SRTM), TerraSAR-X add-on for Digital Elevation Measurements (TanDEM-X), and airborne Light Detection and Ranging (LiDAR) digital elevation models. The results indicated a mean regional glacier mass balance of −0.12 ± 0.06 m w.e.a−1, with a total mass loss of 2.43 ± 0.26 Gt for the Maipo River Basin between 1955–2013. The most negative glacier mass balance was the Olivares sub-basin, with a mean value of −0.29 ± 0.07 m w.e.a−1. We observed spatially heterogeneous glacier elevation and mass changes between 1955 and 2000, and more negative values between 2000 and 2013, with an acceleration in ice thinning rates starting in 2010, which coincides with the severe drought. Our results provide key information to improve glaciological and hydrological projections in a region where water resources are under pressure.

Ice elevation and areal changes of glaciers from the Northern Patagonia Icefield, Chile

Recent elevation changes of Svalbard glaciers derived from ICESat laser altimetry

The monitoring of glaciers in Switzerland has a long tradition, yet glacier changes during the 20th century are only known through sparse observations. Here, we estimate a halving of Swiss glacier volumes between 1931 and 2016 by mapping historical glacier elevation changes at high resolution. Our analysis relies on a terrestrial image archive known as TerrA, which covers about 86 % of the Swiss glacierised area with 21,703 images acquired during the period 1916–1947 (1931 on average). We developed a semi-automated workflow to generate digital elevation models (DEMs) from these images, resulting in a 45 % total glacier coverage. Using the geodetic method, we estimate a Swiss-wide glacier mass balance of –0.52 ± 0.09 m w.e. a−1 between 1931 and 2016. This equates to a 51.5 ± 6.1 % loss in glacier volume. We find that low elevation, high debris cover, and gently sloping glacier termini are conductive to particularly high mass losses. In addition to these glacier-specific, quasi- centennial elevation changes, we present a new inventory of glacier outlines with known timestamps and complete attributes from around 1931. The fragmented spatial coverage and temporal heterogeneity of the TerrA archive are the largest sources of uncertainty in our glacier-specific estimates, reaching up to 0.50 m w.e. a−1. We suggest that the high-resolution mapping of historic surface elevations could unlock great potentials also for research fields other than glaciology.

Greenlandic glaciers distinct from the ice sheet make up 12% of the global glacierized area and store about 10% of the global glacier ice volume (Farinotti et al., 2019). However, knowledge about recent climate change-induced volume changes of these 19,000 individual glaciers is limited. The small number of available glaciological and geodetic mass-balance observations have a limited spatial coverage, and the representativeness of these measurements for the region is largely unknown, factors which make a regional assessment of mass balance challenging. Here we use two recently released digital elevation models (DEMs) to assess glacier-wide elevation changes of 1,526 glaciers covering 3,785 km2 in west-central Greenland: The historical AeroDEM representing the surface in 1985 and a TanDEM-X composite representing 2010–2014. The results show that on average glacier surfaces lowered by about 14.0 ± 4.6 m from 1985 until 2012 or 0.5 ± 0.2 m yr−1, which is equivalent to a sample mass loss of ~45.1 ± 14.9 Gt in total or 1.7 ± 0.6 Gt yr−1. Challenges arise from the nature of the DEMs, such as large areas of data voids, fuzzy acquisition dates, and potential radar penetration. We compared several different interpolation methods to assess the best method to fill data voids and constrain unknown survey dates and the associated uncertainties with each method. The potential radar penetration is considered negligible for this assessment in view of the overall glacier changes, the length of the observation period, and the overall uncertainties. A comparison with earlier studies indicates that for glacier change assessments based on ICESat, data selection and averaging methodology strongly influences the results from these spatially limited measurements. This study promotes improved assessments of the contribution of glaciers to sea-level rise and encourages to extend geodetic glacier mass balances to all glaciers on Greenland.

This chapter contains sections titled: Introduction Sea ice chemistry Biological activity: the modification of the chemical composition of sea ice by sympagic organisms Stable carbon isotopes in sea ice Arctic river inputs into sea ice Data collection and in situ measurements: some challenges Future perspectives Acknowledgements References

Quantifying glacier elevation and mass changes is essential for understanding glacier dynamics as well as the interaction between volcanic activity and ice cover. This study investigates glacier elevation and mass changes within the Klyuchevskaya Volcanic Group (KVG) on the Kamchatka Peninsula using TanDEM-X and SRTM C-band SAR data combined with a differential SAR interferometric approach. Elevation and mass changes are assessed for the period 2000–2020, demonstrating the suitability of TanDEM-X digital elevation models for geodetic glacier analysis in volcanically active environments. Cumulative mass loss 2000-2020 amounts to −0.782 ± 0.058 Gt. For the total glacierized area of 204.15 km², an average elevation change rate of −0.347 ± 0.011 m a⁻¹ is derived, corresponding to a specific mass balance of −295 ± 23 kg m⁻² a⁻¹ for the period 2012-2020, with locally much higher losses. Marked temporal variability is observed, with strongly increased mass loss after 2015/16 (-0.528±0.014 m a-1) coinciding with intensified volcanic activity. Enhanced supraglacial debris cover following frequent and larger eruptions significantly influences glacier mass budgets, as supported by Landsat 8 Normalized Difference Snow Index analyses. Despite the absence of field-based debris thickness measurements, spatial patterns across individual glaciers highlight the critical role of volcanic debris in modulating glacier response.

Measuring surface deformation is crucial for a better understanding of spatial-temporal evolution and the mechanism of mining-induced deformation, thus effectively assessing the mining-related geohazards, such as landslides or damage to surface infrastructures. This study proposes a method of retrieving surface deformation by combining multi-temporal digital surface models (DSMs) with image homonymous features using China’s ZY-3 satellite stereo imagery. DSM is generated from three-line-array images of ZY-3 satellite using a rational function model (RFM) as the imaging geometric model. Then, elevation changes in deformation are extracted using the difference of DSMs acquired at different times, while planar displacements of deformation are calculated using image homonymous features extracted from multi-temporal digital orthographic maps (DOMs). Scale invariant feature transform (SIFT) points and line band descriptor (LBD) lines are selected as two kinds of salient features for image homonymous features generation. Cross profiles are also extracted for deformation in typical regions. Four sets of stereo imagery acquired in 2012 to 2022 are used for deformation extraction and analysis in the Fushun coalfield of China, where surface deformation is quite distinct and coupled with rising and descending elevation together. The results show that 21.60% of the surface in the study area was deformed from 2012 to 2017, while a decline from 2017 to 2022 meant that 17.19% of the surface was deformed with a 95% confidence interval. Moreover, the ratio of descending area was reduced to 6.44% between 2017 and 2022, which is lower than the ratios in other years. The slip deformation area in the west open pit mine is about 1.22 km2 and the displacement on the south slope is large, reaching an average of 26.89 m and sliding from south to north to the bottom of the pit between 2012 and 2017, but elevations are increased by an average of about 16.35 m, involving an area of about 0.86 km2 between 2017 and 2022 due to the restoration of the open pit. The results demonstrate that more quantitative features and specific surface deformation can be retrieved in mining areas by combining image features with DSMs derived from ZY-3 satellite stereo imagery.

Glaciers play an important role in the climate system. The elevation change of a glacier is an important parameter in studies of glacier dynamics. Only a few ground-based measurements of high mountain glaciers are available due to their remoteness, high elevation, and complex topography. The acquisition from the German TanDEM-X (TerraSAR-X add-on for Digital Elevation Measurement) SAR imaging configuration provides a reliable data sources for studying the elevation change of glaciers. In this study, the bistatic TanDEM-X data that cover the Geladandong Mountain on the Tibetan Plateau were processed with SAR interferometry technique and the elevation changes of the mountain’s glaciers during 2000–2014 were obtained. The results indicated that although distinct positive and negative elevation changes were found for different glacier tongues, the mean elevation change was about -0.14±0.26 m a-1. Geoscience Laser Altimeter System (GLAS) data were obtained for comparison and verification. The investigation using GLAS data demonstrated the efficacy of the proposed method in determining glacier elevation change. Thus, the presented approach is appropriate for monitoring glacier elevation change and it constitutes a valuable tool for studies of glacier dynamics.

The study evaluates the global glacier inventories available for the study area viz., RGI, GAMDAM and ICIMOD, with the newly generated Kashmir University Glacier Inventory (KUGI) for three Himalaya basins; Jhelum, Suru and Chenab in the north-western Himalaya, comprising of 2096 glaciers spread over an area of 3300 km2. The KUGI was prepared from the Landsat data supplemented by Digital Elevation Model, Google Earth images and limited field surveys. The KUGI comprises of 154 glaciers in the Jhelum, 328 in the Suru and 1614 in the Chenab basin, corresponding to the glacier area of 85.9 ± 11.4 km2, 487 ± 16.2 km2 and 2727 ± 90.2 km2 respectively. The investigation revealed that most of the glaciers in the study area are < 1 km2 in size, however, the glaciers in 1–5 km2 size class cover most (55.8 %) of the glacier area. Majority of the glaciers, both in terms of number and area, are at 4500–5500 m asl except in the Jhelum where the glaciers are mostly situated between 4000–5000 m asl altitude. The glaciers in the three basins mainly harbor slopes ranging from 10–30°. It was also observed that the southern aspects host more number of large-sized glaciers than the northern aspects. Comparative analyses of the inventories revealed that the GAMDAM (RAB = 0.75) and RGI (RAB = 0.73) inventories are consistent with the KUGI. However, discrepancies were observed in the debris-covered and shadowed glaciers particularly in the ICIMOD inventory. The glacier elevation changes were also estimated for glaciers in the three basins using the Tandem-X and SRTM-C DEMs from 2000 to 2012. The investigation revealed a strong control of glacial morphology, topography, and debris cover on glacier thinning. Glacier elevation change of −1.33 ± 0.8 m a−1 was observed in the Jhelum basin but a similar glacier elevation changes of −1.08 ± 0.7 m a−1 and −1.09 ± 0.8 m a−1 was observed in the Suru and Chenab basins respectively. Evaluation of the glacier inventories and assessment of glacier elevation change in the data-scarce Himalaya, reported in this article, would constitute a reliable database for research particularly in hydrology, glaciology, and climate change. The dataset is freely available at http://doi.org/10.5281/zenodo.4461799 (Romshoo et al., 2021).

The accuracy of topographic correction of Landsat data based on a Digital Surface Model (DSM) depends on the quality, scale and spatial resolution of the DSM data used and the co-registration between the DSM and the satellite image. A physics-based bidirectional reflectance distribution function (BRDF) and atmospheric correction model in conjunction with a 1-second DSM was used to conduct the analysis in this paper. The results show that for the examples used from Australia, the 1-second DSM, can provide an effective product for this task. However, it was found that some remaining artefacts in the DSM data, originally due to radar shadow, can still cause significant local errors in the correction. Where they occur, false shadows and over-corrected surface reflectance factors can be observed. More generally, accurate co-registration between satellite images and DSM data was found to be critical for effective correction. Mis-registration by one or two pixels could lead to large errors of retrieved surface reflectance factors in gully and ridge areas. Using low-resolution DSM data in conjunction with high-resolution satellite images will also fail to correct significant terrain components where they occur at the finer scales of the satellite images. DSM resolution appropriate to the resolution of satellite image and the roughness of the terrain is needed for effective results, and the rougher the terrain, the more critical will be the accurate registration.