Summer 2022, in less than a week, two glaciers collapsed. First in Italy on July 3 (Marmolada) then in Kyrgyzstan on July 9 (Juuku pass). The collapse of the Marmolada glacier caused eleven fatalities. In both cases, we immediately requested the tasking of Pléiades satellites to estimate the collapse volumes by photogrammetry. In both cases, the images were acquired three days after the event, and less than one day later we had the first estimates. We found that the Marmolada glacier lost 65,000 ± 10,000 m3. The Jukuu pass glacier lost a volume almost twenty times greater (1,145,000 m3), which remains however much lower than the volumes involved during the collapse of the Aru glaciers on the Tibetan plateau in 2016 (68 and 83 million m3) or the Kolka Glacier in 2002 (130 million m3). From the Marmolada elevation model and orthoimages we could also estimate that the rupture was approximately 80 m wide and 25 m deep.  In the case of the Juuku glacier, the tongue of the glacier collapsed entirely over a width of almost 300 m and the maximum elevation drop reached 50 m.

How to cite: Gascoin, S. and Berthier, E.: Remote sensing analysis of Marmolada (Italy) and Juuku pass (Kyrgyzstan) glacier collapses, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14011, https://doi.org/10.5194/egusphere-egu23-14011, 2023.

The geodetic method has become a popular tool to measure glacier elevation changes over large glacierized regions with high accuracy for multiannual/decadal time periods. In contrast, the glaciological method provides annually to seasonally resolved information on glacier mass balance, but only for a small sample of the world’s glaciers (less than 1%). Various methods have been proposed to bridge the gap regarding the spatio-temporal coverage of glacier change observations and provide annually resolved glacier mass balances using the geodetic sample as calibration. Thanks to a new globally near-complete (96% of the world’s glaciers) dataset of geodetic mass balance between 2000 and 2020, a global-scale assessment of annual mass changes at glacier-specific level has now become feasible. Inspired by previous methodological frameworks, we developed a new approach to combine the glacier outlines from the globally complete Randolph Glacier Inventory with the mass balance and elevation change observations from the Fluctuation of Glaciers database of the World Glacier Monitoring Service (WGMS). Our results provide a global assessment of annual glacier mass change and related uncertainties for every individual glacier since 1976. The glacier-specific time series can then be integrated into an annually-resolved gridded global glacier change product at any user-requested spatial resolution, useful for comparison with, for example, gravity-based products, calibration or validation of glacier mass balance models operating at a global scale and to improve assessments of glacier contribution to regional hydrology and global sea-level rise. These developments additionally open a new door of opportunity to keep on pushing the frontiers of glacier change observations towards future assessments of global glacier mass changes at increased temporal resolutions.

How to cite: Dussaillant, I., Hugonnet, R., Huss, M., Berthier, E., and Zemp, M.: An annual mass balance estimate for each of the world’s glaciers based on observations., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16174, https://doi.org/10.5194/egusphere-egu23-16174, 2023.

Glaciers are crucial sources of freshwater in particular for the arid lowlands surrounding High Mountain Asia. In order to better constrain glacio-hydrological models, annual, or even better, seasonal information about glacier mass changes is highly beneficial. In this study, we test the suitability of very high-resolution Pleiades DEMs to measure glacier-wide mass balance at annual and seasonal scales in two regions of High Mountain Asia (Muztagh Ata in Eastern Pamir and parts of Western Nyainqêntanglha, South-central Tibetan Plateau), where recent estimates have shown contrasting glacier behaviour. We find that the average annual mass balance in Muztagh Ata between 2020 and 2022 was -0.11 ±0.21 m w.e. a-1, suggesting the continuation of a recent phase of slight mass loss following a prolonged period of balanced mass budgets previously observed. The mean annual mass balance in Western Nyainqêntanglha for the same period was highly negative (-0.60 ±0.15 m w.e. a-1 on average), suggesting increased mass loss rates. The 2022 winter (+0.21 ±0.24 m w.e.) and summer (-0.31 ±0.15 m w.e.) mass budgets in Muztag Ata and Western Nyainqêntanglha (-0.04 ±0.27 m w.e. [winter]; -0.66 ±0.07 m w.e. [summer]) suggest winter and summer accumulation-type regimes, respectively. We support our findings by implementing a Sentinel-1–based Glacier Index to identify the firn and wet snow areas on glaciers and characterize accumulation type and demonstrate the potential of very high-resolution Pleiades data to monitor mass balance at short time scales and to improve our understanding of glacier accumulation regimes across High Mountain Asia.

How to cite: Bolch, T., Falaschi, D., Bhattacharya, A., Huang, L., and King, O.: Annual to seasonal glacier mass balance in High Mountain Asia derived from Pléiades stereo images: examples from the Pamir and the Tibetan Plateau, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12612, https://doi.org/10.5194/egusphere-egu23-12612, 2023.

With temperatures in the Arctic rising rapidly at a rate of 3-4 times the global mean, monitoring the state of the Greenland ice sheet has never been more relevant.

In-situ observations from the Arctic, in particular from the Greenland ice sheet, are scarce due to the cost and difficulty of maintaining instrumentation in the harsh and remote environment. Yet, the fate of the ice sheet concerns 100s of millions of people living in coastal zones worldwide. To gain understanding of the ice sheet processes leading to sea level rise and increase our ability to capture those in climate models, there is an urgent need to collect in-situ observations from the ice sheet surface. Similarly, ground-truthing observations are necessary for validation and calibration of satellite-derived estimates of ice sheet change.

The Geological Survey of Denmark and Greenland (GEUS), along with partner institutions Asiaq and DTU Space, currently operates a combined network of 40 automatic weather stations (AWS) on ice in Greenland, mainly through the Programme for Monitoring of the Greenland Ice Sheet (PROMICE) and the Greenland Climate Network (GC-Net).

GEUS has implemented a new pipeline providing near-real-time hourly weather observations from the PROMICE and GC-Net stations to its users and the World Meteorological Organization (WMO) for use in numerical weather prediction. The satellite-transmitted AWS data is processed and submitted to the WMO via the Danish Meteorological Institute with a latency of 7 minutes after observations are recorded.

Here, we present the recent advances in our AWS instrumentation, data processing and database solution to invite discussion on how we can best meet the community needs for in-situ observations from the ice sheet.

How to cite: Ahlstrøm, A. P., Fausto, R. S., Box, J. E., Karlsson, N. B., How, P. R., Wright, P. J., Vandecrux, B., Rutishauser, A., Mankoff, K. D., Colgan, W. T., Citterio, M., Messerli, A., Solgaard, A. M., Larsen, S. H., Korsgaard, N. J., Kjeldsen, K. K., Nielsen, R. B., Houtz, D., and Andersen, S. B. and the GEUS GlacioLab Team: Recent advances in monitoring surface mass balance of the Greenland ice sheet, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13870, https://doi.org/10.5194/egusphere-egu23-13870, 2023.

Quantifying glacier elevation and volume changes is critical to understanding the response of glaciers to climate change and related impacts, such as regional runoff and global sea-level rise. Spaceborne remote sensing techniques enable the quantification of spatially distributed glacier elevation changes at regional and global scales using multi-temporal digital elevation models (DEMs). A growing number of spaceborne studies exist to assess glacier elevation changes but they show widespread differences often beyond the error bars. Here, we present the results of a community-based inter-comparison experiment using spaceborne optical (ASTER) and radar (TanDEM-X) sensors to assess elevation changes for selected individual glaciers and regional glacier samples. Using a predefined set of DEMs, participating groups provided their own estimates using various processing strategies.  

For the selected individual glaciers, the results were validated using airborne data. The validation shows that the median of the spaceborne ensemble is biased by a few decimetres per year with a standard deviation of about half a meter per year. An interesting finding is that no sensor and no processing strategy perform significantly better for all experiment sites. At the regional scale, we find that the co-registration of DEMs is the most relevant processing step for an accurate assessment of elevation change. Other corrections such as gap filling, filtering, and radar penetration have less impact in general but can be essential for individual cases. Temporal corrections (i.e. seasonal and annual) can have a great impact; however, they are not yet well resolved by the remote sensing community.

Our study confirms that the currently available spaceborne geodetic assessments result in relatively widespread glacier elevation changes. Therefore, we recommend an ensemble approach of observations from multiple observational sources. Furthermore, there is a need to establish best practices for related uncertainty estimates.

How to cite: Piermattei, L., Brun, F., Sommer, C., Braun, M. H., and Zemp, M.: Observing glacier elevation changes from spaceborne optical and radar sensors, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9215, https://doi.org/10.5194/egusphere-egu23-9215, 2023.

Glaciers are one of the most important indicators of climate change. Monitoring their evolution is, therefore, crucial for safeguarding the Earth’s ecosystem. In this study, exploiting photogrammetric optical satellite processing techniques, we used image pairs from Ikonos-2 and Plèiades-HR satellites to generate Digital Surface Models (DSMs) of Forni Glacier (Ortles–Cevedale group, Italy) and compute its morphological variations between 2009 and 2016. In addition, we used DSMs generated from Unmanned Aerial Vehicle (UAV) acquisitions collected during summer campaigns from 2014 to 2021 for comparison with very high-resolution DSMs on the terminal portion of the glacier including its tongue, which is also the area more affected by morphological changes. To evaluate the glacier height loss, DSMs co-registration was applied to remove DSM biases due to inconsistencies in the georeferencing of the different satellite image pairs. For this purpose, we used the 2016 UAV DSM as a reference, and we co-registered all the optical DSMs to the 2016 UAV DSM using the Nuth and Kaab algorithm. The DSM height differences after co-registration highlighted a final accuracy of one meter. Since optical satellite data have the advantage of providing information on very large areas, we analysed glacier change not only on small areas of Forni Glacier tongue but also on larger regions including parts of the entire glacial apparatus to depict the evolution of the glacier at different altitudes. Results from optical DSMs were consistent with the average annual variation of the glacier suggested by UAV DSMs analysis, confirming an average 5.00 m/y loss on the Forni tongue during 2014-2016.  Furthermore, based on both UAV and optical data, melting trends have highlighted how climate change is causing an acceleration in the melting process, with values averaging 3.3 m/y in the period 2009-2013, 3.8 m/y in 2009-2016 and 4.7 m/y in 2009-2021. With reference to the optical data only, we observed that the intensity of melting varied at different altitudes, with 10 m of maximum variation above 3000 m, and 30 m between 2600-3000 m during 2009-2016. Our results suggested that despite the limitations related to weather conditions (e.g. cloud coverage) and time revisit, high-resolution optical satellite imagery can certainly be used to estimate relevant morphological variations of glaciers in the order of meter/years, offering the opportunity of monitoring large-scale areas.

How to cite: Ranaldi, L., Belloni, V., Fugazza, D., and Crespi, M.: Glacier change monitoring using optical satellite imagery: the case of Forni Glacier, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13794, https://doi.org/10.5194/egusphere-egu23-13794, 2023.

Glaciers are an important contributor to the freshwater supply in the Central Asian region. Their response to climate change has profound consequences for the land-use applications, and is thus essential to understand. The collapse of the Soviet Union has interrupted the vast majority of the conducted glacier mass balance observations, which began to re-establish in 2010. The existing data gap, limited spatial resolution of glaciological measurements, and the high heterogeneity of the region limits the use of in-situ data. Mass balance models rely on observation-based calibration and validation data, such as transient snowlines (TSLs), a transition between snow and ice-covered surfaces on a glacier at a given point in time. At the end of the ablation season TSL approximates the equilibrium line. From TSL we can calculate the snow-covered area fraction (SCAF), the area on the glacier surface that is snow covered in relation to the total glacier area. The TSL and SCAF can be mapped from satellite imagery due to the distinctive spectral and structural signature of snow over time. Our approach presented in this contribution is based on the MODIS time-series, harnessing the advantage of long and close-to-daily observations records for the period before high-resolution satellites became available. To resolve the issue of MODIS coarse spatial resolution, we retrieved SCAF from multispectral Sentinel-2 and cloud-independent Sentinel-1 SAR imagery using established workflow. The automatic classification and calculation of SCAF is performed using the cloud computing service of the Google Earth Engine, which makes the entire approach easily applicable on a large number of remote glaciers worldwide. We validated the results independently with Landsat data over selected glaciers in Central Asia. From the  SCAF time-series we analysed changes in various parameters indicative for the atmospheric conditions and its changes  (amongst others the length of ablation period, the minimum SCAF, and the seasonal SCAF changes ) as well as their 20-year trends. Our results provide a unique time series of temporally and spatially high-resolved SCAF estimates giving observation-based information on the heterogeneity of the region’s climatic setting as well as its changes on subseasonal scale. 

How to cite: Kim, D., Callegari, M., Ullmann, T., and Barandun, M.: Sub-seasonal snowline dynamics of glaciers in Central Asia from multi-sensor satellite observations, 2000-2021, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-225, https://doi.org/10.5194/egusphere-egu23-225, 2023.

Glacier displacement can in principle be measured at the large-scale by cross-correlation of satellite images. At weekly to monthly scales, the expected displacement is often of the same order as the noise for the commonly used satellite images, complicating the retrieval of accurate glacier velocity. Assessments of velocity changes on short time scales and over complex areas such as mountain ranges are therefore still lacking, but are essential to better understand how glacier dynamics are driven by internal and external factors. In this study, we take advantage of the wide availability and redundancy of satellite imagery over the Western Pamir to retrieve glacier velocity changes over 10 days for 7 years for a wide range of glacier geometry and dynamics. Our results reveal strong seasonal trends. In spring/summer, we observe velocity increases of up to 300% compared to a slow winter period. These accelerations clearly migrate upglacier throughout the melt-season, which we link to changes in subglacial hydrology efficiency. In autumn, we observe glacier accelerations that have rarely been observed before. These episodes are primarily confined to the upper ablation zone with a clear downglacier migration. We suggest that they result from glacier instabilities caused by sudden subglacial pressurization in response to (1) supraglacial pond drainage and/or (2) gradual closure of the hydrological system. Our 10-day resolved measurements allow us to characterize the short-term response of glacier to changing meteorological and climatic conditions.

How to cite: Nanni, U., Scherler, D., Ayoub, F., Millan, R., Herman, F., and Avouac, J.-P.: Climatic control on seasonal variations of moutain glacier surface velocity, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13863, https://doi.org/10.5194/egusphere-egu23-13863, 2023.

Digital elevation models (DEMs) from the spaceborne interferometric radar mission TanDEM-X hold a large potential for glacier elevation change assessments and monitoring. However, a bias is potentially introduced through the penetration of the X-band signal into snow and firn that can be substantial. The magnitude of this bias has been analysed in some glaciarized regions of the world; still, the knowledge about X-band penetration of TanDEM-X in the European Alps is limited.

In this study, we investigated the unique situation of almost synchronous acquisition of TanDEM-X and Pléiades DEMs over the Grosser Aletschgletscher, complemented with in-situ observations (ground penetrating radar, snow cores, snow pits), all within a four-day period in late winter 2021. The comparison of the TanDEM-X and Pléiades DEM revealed an elevation bias due to radar penetration of up to 8 m above 3400 m. Further, the concurrent in-situ measurements reveal that the signal is not obstructed by the last summer horizon but reaches into perennial firn.

Our study improves our understanding about the magnitude of X-band penetration of TanDEM-X in the Alps and the underlying process with a relevance for glaciology, snow science, remote sensing and the wider geoscience community.

How to cite: Bannwart, J., Piermattei, L., Dussaillant, I., Krieger, L., Floricioiu, D., Berthier, E., Roeoesli, C., Machguth, H., and Zemp, M.: Elevation bias due to penetration of spaceborne radar signal on Grosser Aletschgletscher, Switzerland, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15661, https://doi.org/10.5194/egusphere-egu23-15661, 2023.

Surface melting of alpine glaciers is spatially and temporally heterogeneous and is strongly influenced by climatic and non-climatic variables. Especially supra-glacial debris causes significant uncertainty on the ice melting rate with its physical property and thickness. A thick debris layer decrease ice melting rate, whereas a thin layer increase it with its low albedo. Therefore, a scientific method for spatial quantification of debris influences on the melting rate should be established to assess future projection of glacier shrinkage corresponding to the climate change.

Estimating  thermal resistance (TR), which quantifies how hard the ground heat flux (G) travels to ice-debris interface, with remote-sensing data has been attempted in several studies. However, uncertainties caused by the linear temperature gradient have not been resolved, as well as non-negligible underestimation of TR values. Therefore, this study aims to assess TR calculations on multi-spatial and multi-temporal conditions in detail, and discusses the current state of TR estimation and the potential for further improvement.

A study site is defined in Satopanth glacier [30.77°N; 79.40°E], a debris-covered glacier located in Garhwal region, India. Sampling domains of 12 circles with 100-m radius are put with 1-km intervals through the flow line of supra-glacial debris. In addition, four circles of the same size were placed outside the glacier in the lower reaches.

To calculate TR, first, broadband albedo and surface temperature (Ts) are calculated from all available Landsat-8 data in an orbit path [Path 145; Row 39] acquired from 2013 to the present (N= 81). These have a revisit cycle of 16 days. Cloud-covered pixels and frozen pixels (Ts < 0°C) are removed. Second, downward shortwave/longwave radiations and sensible/latent heat flux are collected from a 1-hour resolution product of ERA5. Combining these inputs, considering surface energy budget, G is calculated as a residue of energy flux, and then TR is calculated as Ts (°C) divided by G.

Our result shows a positive correlation that higher Ts leads higher values of G and TR. This trend have no significant difference between debris-covered surface and off-glacier terrains. It suggests that, in most sample areas with relatively thick debris, G does not reach the ice-debris interface. High-gradient inclinations of G versus Ts increase is identified in a lower part of Ts range (0-5°C). It may be caused by heat absorption because of ice mass under relatively thin debris layer, but such inclination is not reflected in TR’s gradient. In the lower Ts surfaces (0-5°C), slightly lower R is estimated for thinner-debris domains. For the thinner debris layer TR might reflects debris thickness. These features in other multiple glaciers will be shown and compared in the presentation.

Our result suggested that maximum debris thickness of G transfer (DTmax) may be defined. Smaller than the DTmax, G transfer may be estimated, whereas larger than the DTmax, G might be zero. In such domain, spatial distributions of ice cliff and supra-glacial pond are more dominant for melting projection. Further assessments might derive a perspective of multiple models for TR estimation according to debris thickness.

How to cite: Nagai, H., Nuimura, T., Takigawa, M., Patel, L., Laha, S., Pratap, B., Konya, K., Sharma, P., Fujita, K., Sato, Y., and Sakai, A.: Toward improvement of satellite-derived thermal resistance for supra-glacial debris, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4768, https://doi.org/10.5194/egusphere-egu23-4768, 2023.

Glaciers in the tropical Andes of Peru and Bolivia are important but rapidly declining water resources. Precise knowledge of their extent is thus mandatory for calculation of their volume, area changes and mass balance. Due to wrongly mapped seasonal snow, the glacier outlines currently available from the widely used RGIv6 are often too large, resulting in errors for change assessment and volume estimation. Apart from snow cover, also frequent cloud cover and shadows cast by the steep terrain make glacier mapping in this region challenging.

For this study, we have mapped all glaciers in Peru and Bolivia using cloud-free Landsat TM scenes from 1998 and Sentinel-2 scenes from 2020. In both years seasonal snow off glaciers was largely absent. Glacier extents were mapped with a standard band ratio (red/SWIR) and a scene specific threshold value. Wrongly classified lakes and missing debris cover were manually corrected, the latter also by using the very high-resolution satellite images available in the ESRI Basemap. The Copernicus DEM GLO-30 was used to derive new drainage divides and topographic information for each glacier.

In total, we mapped 3586 glaciers larger than 0.01 km² covering an area of 1747 km² in 1998. This is 419 km² or 20% less than the 2166 km² in RGIv6. As glacier outlines in RGIv6 are from 2000 to 2009 and most area change studies found continuous and strong area decrease over this period, a ‘back-calculation’ of all glacier areas to the year 1998 with an annual shrinkage rate of 1% gives a mean area overestimation of 27% for 1998. This value varies regionally and is smaller in the Cordillera Blanca and much larger (>50%) in other regions. The related modelled glacier volumes for these regions are thus also overestimated. From 1998 to 2020 glaciers have lost 23% of their area (-1% per year).

How to cite: Paul, F. and Rastner, P.: Glacier extents in Peru and Bolivia are overestimated in RGIv6 by 27%, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12724, https://doi.org/10.5194/egusphere-egu23-12724, 2023.