Articles | Volume 14, issue 9
https://doi.org/10.5194/essd-14-4287-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-14-4287-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
22 Sep 2022
Data description paper |
| 22 Sep 2022
| 22 Sep 2022
Calving fronts and where to find them: a benchmark dataset and methodology for automatic glacier calving front extraction from synthetic aperture radar imagery
Pattern Recognition Lab, Computer Science Department, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
Thorsten Seehaus
Institute of Geography, Department of Geography and Geosciences, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
Matthias Braun
Institute of Geography, Department of Geography and Geosciences, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
Andreas Maier
Pattern Recognition Lab, Computer Science Department, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
Vincent Christlein
Pattern Recognition Lab, Computer Science Department, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
Related authors
Oskar Herrmann, Nora Gourmelon, Thorsten Seehaus, Andreas Maier, Johannes J. Fürst, Matthias H. Braun, and Vincent Christlein
The Cryosphere, 17, 4957–4977, https://doi.org/10.5194/tc-17-4957-2023, https://doi.org/10.5194/tc-17-4957-2023, 2023
Short summary
Short summary
Delineating calving fronts of marine-terminating glaciers in satellite images is a labour-intensive task. We propose a method based on deep learning that automates this task. We choose a deep learning framework that adapts to any given dataset without needing deep learning expertise. The method is evaluated on a benchmark dataset for calving-front detection and glacier zone segmentation. The framework can beat the benchmark baseline without major modifications.
Katrina Lutz, Lily Bever, Christian Sommer, Thorsten Seehaus, Angelika Humbert, Mirko Scheinert, and Matthias Braun
The Cryosphere, 18, 5431–5449, https://doi.org/10.5194/tc-18-5431-2024, https://doi.org/10.5194/tc-18-5431-2024, 2024
Short summary
Short summary
The estimation of the amount of water found within supraglacial lakes is important for understanding how much water is lost from glaciers each year. Here, we develop two new methods for estimating supraglacial lake volume that can be easily applied on a large scale. Furthermore, we compare these methods to two previously developed methods in order to determine when it is best to use each method. Finally, three of these methods are applied to peak melt dates over an area in Northeast Greenland.
Katrina Lutz, Ilaria Tabone, Angelika Humbert, and Matthias Braun
EGUsphere, https://doi.org/10.5194/egusphere-2024-3056, https://doi.org/10.5194/egusphere-2024-3056, 2024
Short summary
Short summary
Supraglacial lakes develop from meltwater collecting on the surface of glaciers. These lakes can drain rapidly, discharging meltwater to the glacier bed. In this study, we assess the spatial and temporal distribution of rapid drainages in Northeast Greenland using optical satellite images. After comparing rapid drainage occurrence with several environmental and geophysical parameters, little indication of the influencing conditions for a rapid drainage was found.
Kaian Shahateet, Johannes J. Fürst, Francisco Navarro, Thorsten Seehaus, Daniel Farinotti, and Matthias Braun
EGUsphere, https://doi.org/10.5194/egusphere-2024-1571, https://doi.org/10.5194/egusphere-2024-1571, 2024
Short summary
Short summary
In the present work, we provide a new ice-thickness reconstruction of the Antarctic Peninsula Ice Sheet north of 70º S by using inversion modeling. This model consists of two steps; the first takes basic assumptions of the rheology of the glacier, and the second uses mass conservation to improve the reconstruction where the previously made assumptions are expected to fail. Validation with independent data showed that our reconstruction improved compared to other reconstruction available.
Livia Piermattei, Michael Zemp, Christian Sommer, Fanny Brun, Matthias H. Braun, Liss M. Andreassen, Joaquín M. C. Belart, Etienne Berthier, Atanu Bhattacharya, Laura Boehm Vock, Tobias Bolch, Amaury Dehecq, Inés Dussaillant, Daniel Falaschi, Caitlyn Florentine, Dana Floricioiu, Christian Ginzler, Gregoire Guillet, Romain Hugonnet, Matthias Huss, Andreas Kääb, Owen King, Christoph Klug, Friedrich Knuth, Lukas Krieger, Jeff La Frenierre, Robert McNabb, Christopher McNeil, Rainer Prinz, Louis Sass, Thorsten Seehaus, David Shean, Désirée Treichler, Anja Wendt, and Ruitang Yang
The Cryosphere, 18, 3195–3230, https://doi.org/10.5194/tc-18-3195-2024, https://doi.org/10.5194/tc-18-3195-2024, 2024
Short summary
Short summary
Satellites have made it possible to observe glacier elevation changes from all around the world. In the present study, we compared the results produced from two different types of satellite data between different research groups and against validation measurements from aeroplanes. We found a large spread between individual results but showed that the group ensemble can be used to reliably estimate glacier elevation changes and related errors from satellite data.
Angelika Humbert, Veit Helm, Ole Zeising, Niklas Neckel, Matthias H. Braun, Shfaqat Abbas Khan, Martin Rückamp, Holger Steeb, Julia Sohn, Matthias Bohnen, and Ralf Müller
EGUsphere, https://doi.org/10.5194/egusphere-2024-1151, https://doi.org/10.5194/egusphere-2024-1151, 2024
Short summary
Short summary
We study the evolution of a massive lake on the Greenland Ice Sheet using satellite and airborne data and some modelling. The lake is emptying rapidly. The water flows to the base of the glacier through cracks and gullies that remain visible over years. Some of them become reactive. We find features inside the glacier that stem from the drainage events with even 1 km width. These features are persistent over the years, although they are changing in shape.
Torsten Kanzow, Angelika Humbert, Thomas Mölg, Mirko Scheinert, Matthias Braun, Hans Burchard, Francesca Doglioni, Philipp Hochreuther, Martin Horwath, Oliver Huhn, Jürgen Kusche, Erik Loebel, Katrina Lutz, Ben Marzeion, Rebecca McPherson, Mahdi Mohammadi-Aragh, Marco Möller, Carolyne Pickler, Markus Reinert, Monika Rhein, Martin Rückamp, Janin Schaffer, Muhammad Shafeeque, Sophie Stolzenberger, Ralph Timmermann, Jenny Turton, Claudia Wekerle, and Ole Zeising
EGUsphere, https://doi.org/10.5194/egusphere-2024-757, https://doi.org/10.5194/egusphere-2024-757, 2024
Short summary
Short summary
The Greenland Ice Sheet represents the second-largest contributor to global sea-level rise. We quantify atmosphere, ice and ocean-based processes related to the mass balance of glaciers in Northeast Greenland, focusing on Greenland’s largest floating ice tongue, the 79N Glacier. We find that together, the different in situ and remote sensing observations and model simulations to reveal a consistent picture of a coupled atmosphere-ice sheet-ocean system, that has entered a phase of major change.
Anna Wendleder, Jasmin Bramboeck, Jamie Izzard, Thilo Erbertseder, Pablo d'Angelo, Andreas Schmitt, Duncan J. Quincey, Christoph Mayer, and Matthias H. Braun
The Cryosphere, 18, 1085–1103, https://doi.org/10.5194/tc-18-1085-2024, https://doi.org/10.5194/tc-18-1085-2024, 2024
Short summary
Short summary
This study analyses the basal sliding and the hydrological drainage of Baltoro Glacier, Pakistan. The surface velocity was characterized by a spring speed-up, summer peak, and autumn speed-up. Snow melt has the largest impact on the spring speed-up, summer velocity peak, and the transition from inefficient to efficient drainage. Drainage from supraglacial lakes contributed to the fall speed-up. Increased summer temperatures will intensify the magnitude of meltwater and thus surface velocities.
Oskar Herrmann, Nora Gourmelon, Thorsten Seehaus, Andreas Maier, Johannes J. Fürst, Matthias H. Braun, and Vincent Christlein
The Cryosphere, 17, 4957–4977, https://doi.org/10.5194/tc-17-4957-2023, https://doi.org/10.5194/tc-17-4957-2023, 2023
Short summary
Short summary
Delineating calving fronts of marine-terminating glaciers in satellite images is a labour-intensive task. We propose a method based on deep learning that automates this task. We choose a deep learning framework that adapts to any given dataset without needing deep learning expertise. The method is evaluated on a benchmark dataset for calving-front detection and glacier zone segmentation. The framework can beat the benchmark baseline without major modifications.
Thorsten Seehaus, Christian Sommer, Thomas Dethinne, and Philipp Malz
The Cryosphere, 17, 4629–4644, https://doi.org/10.5194/tc-17-4629-2023, https://doi.org/10.5194/tc-17-4629-2023, 2023
Short summary
Short summary
Existing mass budget estimates for the northern Antarctic Peninsula (>70° S) are affected by considerable limitations. We carried out the first region-wide analysis of geodetic mass balances throughout this region (coverage of 96.4 %) for the period 2013–2017 based on repeat pass bi-static TanDEM-X acquisitions. A total mass budget of −24.1±2.8 Gt/a is revealed. Imbalanced high ice discharge, particularly at former ice shelf tributaries, is the main driver of overall ice loss.
Alexandra M. Zuhr, Erik Loebel, Marek Muchow, Donovan Dennis, Luisa von Albedyll, Frigga Kruse, Heidemarie Kassens, Johanna Grabow, Dieter Piepenburg, Sören Brandt, Rainer Lehmann, Marlene Jessen, Friederike Krüger, Monika Kallfelz, Andreas Preußer, Matthias Braun, Thorsten Seehaus, Frank Lisker, Daniela Röhnert, and Mirko Scheinert
Polarforschung, 91, 73–80, https://doi.org/10.5194/polf-91-73-2023, https://doi.org/10.5194/polf-91-73-2023, 2023
Short summary
Short summary
Polar research is an interdisciplinary and multi-faceted field of research. Its diversity ranges from history to geology and geophysics to social sciences and education. This article provides insights into the different areas of German polar research. This was made possible by a seminar series, POLARSTUNDE, established in the summer of 2020 and organized by the German Society of Polar Research and the German National Committee of the Association of Polar Early Career Scientists (APECS Germany).
Franziska Temme, David Farías-Barahona, Thorsten Seehaus, Ricardo Jaña, Jorge Arigony-Neto, Inti Gonzalez, Anselm Arndt, Tobias Sauter, Christoph Schneider, and Johannes J. Fürst
The Cryosphere, 17, 2343–2365, https://doi.org/10.5194/tc-17-2343-2023, https://doi.org/10.5194/tc-17-2343-2023, 2023
Short summary
Short summary
Calibration of surface mass balance (SMB) models on regional scales is challenging. We investigate different calibration strategies with the goal of achieving realistic simulations of the SMB in the Monte Sarmiento Massif, Tierra del Fuego. Our results show that the use of regional observations from satellite data can improve the model performance. Furthermore, we compare four melt models of different complexity to understand the benefit of increasing the processes considered in the model.
Christian Sommer, Johannes J. Fürst, Matthias Huss, and Matthias H. Braun
The Cryosphere, 17, 2285–2303, https://doi.org/10.5194/tc-17-2285-2023, https://doi.org/10.5194/tc-17-2285-2023, 2023
Short summary
Short summary
Knowledge on the volume of glaciers is important to project future runoff. Here, we present a novel approach to reconstruct the regional ice thickness distribution from easily available remote-sensing data. We show that past ice thickness, derived from spaceborne glacier area and elevation datasets, can constrain the estimated ice thickness. Based on the unique glaciological database of the European Alps, the approach will be most beneficial in regions without direct thickness measurements.
Christian Sommer, Thorsten Seehaus, Andrey Glazovsky, and Matthias H. Braun
The Cryosphere, 16, 35–42, https://doi.org/10.5194/tc-16-35-2022, https://doi.org/10.5194/tc-16-35-2022, 2022
Short summary
Short summary
Arctic glaciers have been subject to extensive warming due to global climate change, yet their contribution to sea level rise has been relatively small in the past. In this study we provide mass changes of most glaciers of the Russian High Arctic (Franz Josef Land, Severnaya Zemlya, Novaya Zemlya). We use TanDEM-X satellite measurements to derive glacier surface elevation changes. Our results show an increase in glacier mass loss and a sea level rise contribution of 0.06 mm/a (2010–2017).
Peter Friedl, Thorsten Seehaus, and Matthias Braun
Earth Syst. Sci. Data, 13, 4653–4675, https://doi.org/10.5194/essd-13-4653-2021, https://doi.org/10.5194/essd-13-4653-2021, 2021
Short summary
Short summary
Consistent and continuous data on glacier surface velocity are important inputs to time series analyses, numerical ice dynamic modeling and glacier mass flux computations. We present a new data set of glacier surface velocities derived from Sentinel-1 radar satellite data that covers 12 major glaciated regions outside the polar ice sheets. The data comprise continuously updated scene-pair velocity fields, as well as monthly and annually averaged velocity mosaics at 200 m spatial resolution.
Mirko Scheinert, Christoph Mayer, Martin Horwath, Matthias Braun, Anja Wendt, and Daniel Steinhage
Polarforschung, 89, 57–64, https://doi.org/10.5194/polf-89-57-2021, https://doi.org/10.5194/polf-89-57-2021, 2021
Short summary
Short summary
Ice sheets, glaciers and further ice-covered areas with their changes as well as interactions with the solid Earth and the ocean are subject of intensive research, especially against the backdrop of global climate change. The resulting questions are of concern to scientists from various disciplines such as geodesy, glaciology, physical geography and geophysics. Thus, the working group "Polar Geodesy and Glaciology", founded in 2013, offers a forum for discussion and stimulating exchange.
Catrin Stadelmann, Johannes Jakob Fürst, Thomas Mölg, and Matthias Braun
The Cryosphere, 14, 3399–3406, https://doi.org/10.5194/tc-14-3399-2020, https://doi.org/10.5194/tc-14-3399-2020, 2020
Short summary
Short summary
The glaciers on Kilimanjaro are unique indicators for climatic changes in the tropical midtroposphere of Africa. A history of severe glacier area loss raises concerns about an imminent future disappearance. Yet the remaining ice volume is not well known. Here, we reconstruct ice thickness maps for the two largest remaining ice bodies to assess the current glacier state. We believe that our approach could provide a means for a glacier-specific calibration of reconstructions on different scales.
Thorsten Seehaus, Philipp Malz, Christian Sommer, Stefan Lippl, Alejo Cochachin, and Matthias Braun
The Cryosphere, 13, 2537–2556, https://doi.org/10.5194/tc-13-2537-2019, https://doi.org/10.5194/tc-13-2537-2019, 2019
Short summary
Short summary
The glaciers in Peru are strongly affected by climate change and have shown significant ice loss in the last century. We present the first multi-temporal, countrywide quantification of glacier area and ice mass changes. A glacier area loss of −548.5 ± 65.7 km2 (−29 %) and ice mass loss of −7.62 ± 1.05 Gt is obtained for the period 2000–2016. The ice loss rate increased towards the end of the observation period. The glacier changes revealed can be attributed to regional climatic changes and ENSO.
Peter Friedl, Thorsten C. Seehaus, Anja Wendt, Matthias H. Braun, and Kathrin Höppner
The Cryosphere, 12, 1347–1365, https://doi.org/10.5194/tc-12-1347-2018, https://doi.org/10.5194/tc-12-1347-2018, 2018
Short summary
Short summary
Fleming Glacier is the biggest tributary glacier of the former Wordie Ice Shelf. Radar satellite data and airborne ice elevation measurements show that the glacier accelerated by ~27 % between 2008–2011 and that ice thinning increased by ~70 %. This was likely a response to a two-phase ungrounding of the glacier tongue between 2008 and 2011, which was mainly triggered by increased basal melt during two strong upwelling events of warm circumpolar deep water.
Thorsten Seehaus, Alison J. Cook, Aline B. Silva, and Matthias Braun
The Cryosphere, 12, 577–594, https://doi.org/10.5194/tc-12-577-2018, https://doi.org/10.5194/tc-12-577-2018, 2018
Short summary
Short summary
The ice sheet of northern Antarctic Peninsula has been significantly affected by climate change within the last century. A temporally and spatially detailed study on the evolution of glacier retreat and flow speeds of 74 basins is provided. Since 1985 a total frontal retreat of 238 km2 and since 1992 regional mean changes in ice flow by up to 58 % are observed. The trends in ice dynamics are correlated with geometric parameters of the glacier catchments and regional climatic settings.
Johannes Jakob Fürst, Fabien Gillet-Chaulet, Toby J. Benham, Julian A. Dowdeswell, Mariusz Grabiec, Francisco Navarro, Rickard Pettersson, Geir Moholdt, Christopher Nuth, Björn Sass, Kjetil Aas, Xavier Fettweis, Charlotte Lang, Thorsten Seehaus, and Matthias Braun
The Cryosphere, 11, 2003–2032, https://doi.org/10.5194/tc-11-2003-2017, https://doi.org/10.5194/tc-11-2003-2017, 2017
Short summary
Short summary
For the large majority of glaciers and ice caps, there is no information on the thickness of the ice cover. Any attempt to predict glacier demise under climatic warming and to estimate the future contribution to sea-level rise is limited as long as the glacier thickness is not well constrained. Here, we present a two-step mass-conservation approach for mapping ice thickness. Measurements are naturally reproduced. The reliability is readily assessible from a complementary map of error estimates.
Melanie Rankl, Johannes Jakob Fürst, Angelika Humbert, and Matthias Holger Braun
The Cryosphere, 11, 1199–1211, https://doi.org/10.5194/tc-11-1199-2017, https://doi.org/10.5194/tc-11-1199-2017, 2017
B. Osmanoglu, F. J. Navarro, R. Hock, M. Braun, and M. I. Corcuera
The Cryosphere, 8, 1807–1823, https://doi.org/10.5194/tc-8-1807-2014, https://doi.org/10.5194/tc-8-1807-2014, 2014
M. Rankl, C. Kienholz, and M. Braun
The Cryosphere, 8, 977–989, https://doi.org/10.5194/tc-8-977-2014, https://doi.org/10.5194/tc-8-977-2014, 2014
Related subject area
Domain: ESSD – Ice | Subject: Glaciology
Ice thickness and bed topography of Jostedalsbreen ice cap, Norway
PRODEM: an annual series of summer DEMs (2019 through 2022) of the marginal areas of the Greenland Ice Sheet
Climate and ablation observations from automatic ablation and weather stations at A. P. Olsen Ice Cap transect, northeast Greenland, for May 2008 through May 2022
Glaciological and meteorological monitoring at Long Term Ecological Research (LTER) sites Mullwitzkees and Venedigerkees, Austria, 2006–2022
A newly digitized ice-penetrating radar data set acquired over the Greenland ice sheet in 1971–1979
Multitemporal characterization of a proglacial system: a multidisciplinary approach
Spatial and temporal stable water isotope data from the upper snowpack at the EastGRIP camp site, NE Greenland, sampled in summer 2018
High temporal resolution records of the velocity of Hansbreen, a tidewater glacier in Svalbard
A high-resolution calving front data product for marine-terminating glaciers in Svalbard
Calving front positions for 19 key glaciers of the Antarctic Peninsula: a sub-seasonal record from 2013 to 2023 based on a deep learning application to Landsat multispectral imagery
Spatial and temporal variability of environmental proxies from the top 120 m of two ice cores in Dronning Maud Land (East Antarctica)
Inventory of glaciers and perennial snowfields of the conterminous USA
A comprehensive and version-controlled database of glacial lake outburst floods in High Mountain Asia
Unlocking archival maps of the Hornsund fjord area for monitoring glaciers of the Sørkapp Land peninsula, Svalbard
Antarctic Ice Sheet paleo-constraint database
Ice-core data used for the construction of the Greenland Ice-Core Chronology 2005 and 2021 (GICC05 and GICC21)
Antarctic Bedmap data: Findable, Accessible, Interoperable, and Reusable (FAIR) sharing of 60 years of ice bed, surface, and thickness data
A new inventory of High Mountain Asia surging glaciers derived from multiple elevation datasets since the 1970s
Ice core chemistry database: an Antarctic compilation of sodium and sulfate records spanning the past 2000 years
Mass balance of the Greenland and Antarctic ice sheets from 1992 to 2020
Interdecadal glacier inventories in the Karakoram since the 1990s
Landsat- and Sentinel-derived glacial lake dataset in the China–Pakistan Economic Corridor from 1990 to 2020
Processing methodology for the ITS_LIVE Sentinel-1 ice velocity products
Multitemporal glacier inventory revealing four decades of glacier changes in the Ladakh region
A new global dataset of mountain glacier centerlines and lengths
2000 years of annual ice core data from Law Dome, East Antarctica
A 41-year (1979–2019) passive-microwave-derived lake ice phenology data record of the Northern Hemisphere
Rescue and homogenization of 140 years of glacier mass balance data in Switzerland
Mette K. Gillespie, Liss M. Andreassen, Matthias Huss, Simon de Villiers, Kamilla H. Sjursen, Jostein Aasen, Jostein Bakke, Jan M. Cederstrøm, Hallgeir Elvehøy, Bjarne Kjøllmoen, Even Loe, Marte Meland, Kjetil Melvold, Sigurd D. Nerhus, Torgeir O. Røthe, Eivind W. N. Støren, Kåre Øst, and Jacob C. Yde
Earth Syst. Sci. Data, 16, 5799–5825, https://doi.org/10.5194/essd-16-5799-2024, https://doi.org/10.5194/essd-16-5799-2024, 2024
Short summary
Short summary
We present an extensive ice thickness dataset from Jostedalsbreen ice cap that will serve as a baseline for future studies of regional climate-induced change. Results show that Jostedalsbreen currently (~2020) has a maximum ice thickness of ~630 m, a mean ice thickness of 154 ± 22 m and an ice volume of 70.6 ±10.2 km3. Ice of less than 50 m thickness covers two narrow regions of Jostedalsbreen, and the ice cap is likely to separate into three parts in a warming climate.
Mai Winstrup, Heidi Ranndal, Signe Hillerup Larsen, Sebastian B. Simonsen, Kenneth D. Mankoff, Robert S. Fausto, and Louise Sandberg Sørensen
Earth Syst. Sci. Data, 16, 5405–5428, https://doi.org/10.5194/essd-16-5405-2024, https://doi.org/10.5194/essd-16-5405-2024, 2024
Short summary
Short summary
Surface topography across the marginal zone of the Greenland Ice Sheet is constantly evolving. Here we present an annual series (2019–2022) of summer digital elevation models (PRODEMs) for the Greenland Ice Sheet margin, covering all outlet glaciers from the ice sheet. The PRODEMs are based on fusion of CryoSat-2 radar altimetry and ICESat-2 laser altimetry. With their high spatial and temporal resolution, the PRODEMs will enable detailed studies of the changes in marginal ice sheet elevations.
Signe Hillerup Larsen, Daniel Binder, Anja Rutishauser, Bernhard Hynek, Robert Schjøtt Fausto, and Michele Citterio
Earth Syst. Sci. Data, 16, 4103–4118, https://doi.org/10.5194/essd-16-4103-2024, https://doi.org/10.5194/essd-16-4103-2024, 2024
Short summary
Short summary
The Greenland Ecosystem Monitoring programme has been running since 1995. In 2008, the Glaciological monitoring sub-program GlacioBasis was initiated at the Zackenberg site in northeast Greenland, with a transect of three weather stations on the A. P. Olsen Ice Cap. In 2022, the weather stations were replaced with a more standardized set up. Here, we provide the reprocessed and quality-checked data from 2008 to 2022, i.e., the first 15 years of continued monitoring.
Lea Hartl, Bernd Seiser, Martin Stocker-Waldhuber, Anna Baldo, Marcela Violeta Lauria, and Andrea Fischer
Earth Syst. Sci. Data, 16, 4077–4101, https://doi.org/10.5194/essd-16-4077-2024, https://doi.org/10.5194/essd-16-4077-2024, 2024
Short summary
Short summary
Glaciers in the Alps are receding at unprecedented rates. To understand how this affects the hydrology and ecosystems of the affected regions, it is important to measure glacier mass balance and ensure that records of field surveys are kept in standardized formats and well-documented. We describe glaciological measurements of ice ablation and snow accumulation gathered at Mullwitzkees and Venedigerkees, two glaciers in the Austrian Alps, since 2007 and 2012, respectively.
Nanna B. Karlsson, Dustin M. Schroeder, Louise Sandberg Sørensen, Winnie Chu, Jørgen Dall, Natalia H. Andersen, Reese Dobson, Emma J. Mackie, Simon J. Köhn, Jillian E. Steinmetz, Angelo S. Tarzona, Thomas O. Teisberg, and Niels Skou
Earth Syst. Sci. Data, 16, 3333–3344, https://doi.org/10.5194/essd-16-3333-2024, https://doi.org/10.5194/essd-16-3333-2024, 2024
Short summary
Short summary
In the 1970s, more than 177 000 km of observations were acquired from airborne radar over the Greenland ice sheet. The radar data contain information on not only the thickness of the ice, but also the properties of the ice itself. This information was recorded on film rolls and subsequently stored. In this study, we document the digitization of these film rolls that shed new and unprecedented detailed light on the Greenland ice sheet 50 years ago.
Elisabetta Corte, Andrea Ajmar, Carlo Camporeale, Alberto Cina, Velio Coviello, Fabio Giulio Tonolo, Alberto Godio, Myrta Maria Macelloni, Stefania Tamea, and Andrea Vergnano
Earth Syst. Sci. Data, 16, 3283–3306, https://doi.org/10.5194/essd-16-3283-2024, https://doi.org/10.5194/essd-16-3283-2024, 2024
Short summary
Short summary
The study presents a set of multitemporal geospatial surveys and the continuous monitoring of water flows in a large proglacial area (4 km2) of the northwestern Alps. Activities were developed using a multidisciplinary approach and merge geomatic, hydraulic, and geophysical methods. The goal is to allow researchers to characterize, monitor, and model a number of physical processes and interconnected phenomena, with a broader perspective and deeper understanding than a single-discipline approach.
Alexandra M. Zuhr, Sonja Wahl, Hans Christian Steen-Larsen, Maria Hörhold, Hanno Meyer, Vasileios Gkinis, and Thomas Laepple
Earth Syst. Sci. Data, 16, 1861–1874, https://doi.org/10.5194/essd-16-1861-2024, https://doi.org/10.5194/essd-16-1861-2024, 2024
Short summary
Short summary
We present stable water isotope data from the accumulation zone of the Greenland ice sheet. A spatial sampling scheme covering 39 m and three depth layers was carried out between 14 May and 3 August 2018. The data suggest spatial and temporal variability related to meteorological conditions, such as wind-driven snow redistribution and vapour–snow exchange processes. The data can be used to study the formation of the stable water isotopes signal, which is seen as a climate proxy.
Małgorzata Błaszczyk, Bartłomiej Luks, Michał Pętlicki, Dariusz Puczko, Dariusz Ignatiuk, Michał Laska, Jacek Jania, and Piotr Głowacki
Earth Syst. Sci. Data, 16, 1847–1860, https://doi.org/10.5194/essd-16-1847-2024, https://doi.org/10.5194/essd-16-1847-2024, 2024
Short summary
Short summary
Understanding the glacier response to accelerated climate warming in the Arctic requires data obtained in the field. Here, we present a dataset of velocity measurements of Hansbreen, a tidewater glacier in Svalbard. The glacier's velocity was measured with GPS at 16 stakes mounted on the glacier's surface. The measurements were conducted from about 1 week to about 1 month. The dataset offers unique material for validating numerical models of glacier dynamics and satellite-derived products.
Tian Li, Konrad Heidler, Lichao Mou, Ádám Ignéczi, Xiao Xiang Zhu, and Jonathan L. Bamber
Earth Syst. Sci. Data, 16, 919–939, https://doi.org/10.5194/essd-16-919-2024, https://doi.org/10.5194/essd-16-919-2024, 2024
Short summary
Short summary
Our study uses deep learning to produce a new high-resolution calving front dataset for 149 marine-terminating glaciers in Svalbard from 1985 to 2023, containing 124 919 terminus traces. This dataset offers insights into understanding calving mechanisms and can help improve glacier frontal ablation estimates as a component of the integrated mass balance assessment.
Erik Loebel, Celia A. Baumhoer, Andreas Dietz, Mirko Scheinert, and Martin Horwath
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-535, https://doi.org/10.5194/essd-2023-535, 2024
Revised manuscript accepted for ESSD
Short summary
Short summary
Glacier calving front positions are important for understanding glacier dynamics and constrain ice modelling. We apply a deep learning framework on multispectral Landsat imagery to create a calving front record for 19 key outlet glaciers of the Antarctic Peninsula. The resulting data product includes 2064 calving front locations from 2013 to 2023 and achieves sub-seasonal temporal resolution.
Sarah Wauthy, Jean-Louis Tison, Mana Inoue, Saïda El Amri, Sainan Sun, François Fripiat, Philippe Claeys, and Frank Pattyn
Earth Syst. Sci. Data, 16, 35–58, https://doi.org/10.5194/essd-16-35-2024, https://doi.org/10.5194/essd-16-35-2024, 2024
Short summary
Short summary
The datasets presented are the density, water isotopes, ions, and conductivity measurements, as well as age models and surface mass balance (SMB) from the top 120 m of two ice cores drilled on adjacent ice rises in Dronning Maud Land, dating from the late 18th century. They offer many development possibilities for the interpretation of paleo-profiles and for addressing the mechanisms behind the spatial and temporal variability of SMB and proxies observed at the regional scale in East Antarctica.
Andrew G. Fountain, Bryce Glenn, and Christopher Mcneil
Earth Syst. Sci. Data, 15, 4077–4104, https://doi.org/10.5194/essd-15-4077-2023, https://doi.org/10.5194/essd-15-4077-2023, 2023
Short summary
Short summary
Glaciers are rapidly shrinking globally. To identify past change and provide a baseline for future change, we inventoried the extent of glaciers and perennial snowfields across the western USA excluding Alaska. Using mostly aerial imagery, we digitized the outlines of all glaciers and perennial snowfields equal to or larger than 0.01 km2 using a geographical information system. We identified 1331 (366.52 km2) glaciers and 1176 (31.00 km2) snowfields.
Finu Shrestha, Jakob F. Steiner, Reeju Shrestha, Yathartha Dhungel, Sharad P. Joshi, Sam Inglis, Arshad Ashraf, Sher Wali, Khwaja M. Walizada, and Taigang Zhang
Earth Syst. Sci. Data, 15, 3941–3961, https://doi.org/10.5194/essd-15-3941-2023, https://doi.org/10.5194/essd-15-3941-2023, 2023
Short summary
Short summary
A new inventory of glacial lake outburst floods (GLOFs) in High Mountain Asia found 697 events, causing 906 deaths, 3 times more than previously reported. This study provides insights into the contributing factors behind GLOFs on a regional scale and highlights the need for interdisciplinary approaches, including scientific communities and local knowledge, to understand GLOF risks in Asia. This study allows integration with other datasets, enabling future local and regional risk assessments.
Justyna Dudek and Michał Pętlicki
Earth Syst. Sci. Data, 15, 3869–3889, https://doi.org/10.5194/essd-15-3869-2023, https://doi.org/10.5194/essd-15-3869-2023, 2023
Short summary
Short summary
In our research, we evaluate the potential of archival maps of Hornsund fjord area, southern Spitsbergen, published by the Polish Academy of Sciences for studying glacier changes. Our analysis concerning glaciers in the north-western part of the Sørkapp Land peninsula revealed that, in the period 1961–2010, a maximum lowering of their surface was about 100 m for the largest land-terminating glaciers and over 120 m for glaciers terminating in the ocean (above the line marking their 1984 extents).
Benoit S. Lecavalier, Lev Tarasov, Greg Balco, Perry Spector, Claus-Dieter Hillenbrand, Christo Buizert, Catherine Ritz, Marion Leduc-Leballeur, Robert Mulvaney, Pippa L. Whitehouse, Michael J. Bentley, and Jonathan Bamber
Earth Syst. Sci. Data, 15, 3573–3596, https://doi.org/10.5194/essd-15-3573-2023, https://doi.org/10.5194/essd-15-3573-2023, 2023
Short summary
Short summary
The Antarctic Ice Sheet Evolution constraint database version 2 (AntICE2) consists of a large variety of observations that constrain the evolution of the Antarctic Ice Sheet over the last glacial cycle. This includes observations of past ice sheet extent, past ice thickness, past relative sea level, borehole temperature profiles, and present-day bedrock displacement rates. The database is intended to improve our understanding of past Antarctic changes and for ice sheet model calibrations.
Sune Olander Rasmussen, Dorthe Dahl-Jensen, Hubertus Fischer, Katrin Fuhrer, Steffen Bo Hansen, Margareta Hansson, Christine S. Hvidberg, Ulf Jonsell, Sepp Kipfstuhl, Urs Ruth, Jakob Schwander, Marie-Louise Siggaard-Andersen, Giulia Sinnl, Jørgen Peder Steffensen, Anders M. Svensson, and Bo M. Vinther
Earth Syst. Sci. Data, 15, 3351–3364, https://doi.org/10.5194/essd-15-3351-2023, https://doi.org/10.5194/essd-15-3351-2023, 2023
Short summary
Short summary
Timescales are essential for interpreting palaeoclimate data. The data series presented here were used for annual-layer identification when constructing the timescales named the Greenland Ice-Core Chronology 2005 (GICC05) and the revised version GICC21. Hopefully, these high-resolution data sets will be useful also for other purposes.
Alice C. Frémand, Peter Fretwell, Julien A. Bodart, Hamish D. Pritchard, Alan Aitken, Jonathan L. Bamber, Robin Bell, Cesidio Bianchi, Robert G. Bingham, Donald D. Blankenship, Gino Casassa, Ginny Catania, Knut Christianson, Howard Conway, Hugh F. J. Corr, Xiangbin Cui, Detlef Damaske, Volkmar Damm, Reinhard Drews, Graeme Eagles, Olaf Eisen, Hannes Eisermann, Fausto Ferraccioli, Elena Field, René Forsberg, Steven Franke, Shuji Fujita, Yonggyu Gim, Vikram Goel, Siva Prasad Gogineni, Jamin Greenbaum, Benjamin Hills, Richard C. A. Hindmarsh, Andrew O. Hoffman, Per Holmlund, Nicholas Holschuh, John W. Holt, Annika N. Horlings, Angelika Humbert, Robert W. Jacobel, Daniela Jansen, Adrian Jenkins, Wilfried Jokat, Tom Jordan, Edward King, Jack Kohler, William Krabill, Mette Kusk Gillespie, Kirsty Langley, Joohan Lee, German Leitchenkov, Carlton Leuschen, Bruce Luyendyk, Joseph MacGregor, Emma MacKie, Kenichi Matsuoka, Mathieu Morlighem, Jérémie Mouginot, Frank O. Nitsche, Yoshifumi Nogi, Ole A. Nost, John Paden, Frank Pattyn, Sergey V. Popov, Eric Rignot, David M. Rippin, Andrés Rivera, Jason Roberts, Neil Ross, Anotonia Ruppel, Dustin M. Schroeder, Martin J. Siegert, Andrew M. Smith, Daniel Steinhage, Michael Studinger, Bo Sun, Ignazio Tabacco, Kirsty Tinto, Stefano Urbini, David Vaughan, Brian C. Welch, Douglas S. Wilson, Duncan A. Young, and Achille Zirizzotti
Earth Syst. Sci. Data, 15, 2695–2710, https://doi.org/10.5194/essd-15-2695-2023, https://doi.org/10.5194/essd-15-2695-2023, 2023
Short summary
Short summary
This paper presents the release of over 60 years of ice thickness, bed elevation, and surface elevation data acquired over Antarctica by the international community. These data are a crucial component of the Antarctic Bedmap initiative which aims to produce a new map and datasets of Antarctic ice thickness and bed topography for the international glaciology and geophysical community.
Lei Guo, Jia Li, Amaury Dehecq, Zhiwei Li, Xin Li, and Jianjun Zhu
Earth Syst. Sci. Data, 15, 2841–2861, https://doi.org/10.5194/essd-15-2841-2023, https://doi.org/10.5194/essd-15-2841-2023, 2023
Short summary
Short summary
We established a new inventory of surging glaciers across High Mountain Asia based on glacier elevation changes and morphological changes during 1970s–2020. A total of 890 surging and 336 probably or possibly surging glaciers were identified. Compared to the most recent inventory, this one incorporates 253 previously unidentified surging glaciers. Our results demonstrate a more widespread surge behavior in HMA and find that surging glaciers are prone to have steeper slopes than non-surging ones.
Elizabeth R. Thomas, Diana O. Vladimirova, Dieter R. Tetzner, B. Daniel Emanuelsson, Nathan Chellman, Daniel A. Dixon, Hugues Goosse, Mackenzie M. Grieman, Amy C. F. King, Michael Sigl, Danielle G. Udy, Tessa R. Vance, Dominic A. Winski, V. Holly L. Winton, Nancy A. N. Bertler, Akira Hori, Chavarukonam M. Laluraj, Joseph R. McConnell, Yuko Motizuki, Kazuya Takahashi, Hideaki Motoyama, Yoichi Nakai, Franciéle Schwanck, Jefferson Cardia Simões, Filipe Gaudie Ley Lindau, Mirko Severi, Rita Traversi, Sarah Wauthy, Cunde Xiao, Jiao Yang, Ellen Mosely-Thompson, Tamara V. Khodzher, Ludmila P. Golobokova, and Alexey A. Ekaykin
Earth Syst. Sci. Data, 15, 2517–2532, https://doi.org/10.5194/essd-15-2517-2023, https://doi.org/10.5194/essd-15-2517-2023, 2023
Short summary
Short summary
The concentration of sodium and sulfate measured in Antarctic ice cores is related to changes in both sea ice and winds. Here we have compiled a database of sodium and sulfate records from 105 ice core sites in Antarctica. The records span all, or part, of the past 2000 years. The records will improve our understanding of how winds and sea ice have changed in the past and how they have influenced the climate of Antarctica over the past 2000 years.
Inès N. Otosaka, Andrew Shepherd, Erik R. Ivins, Nicole-Jeanne Schlegel, Charles Amory, Michiel R. van den Broeke, Martin Horwath, Ian Joughin, Michalea D. King, Gerhard Krinner, Sophie Nowicki, Anthony J. Payne, Eric Rignot, Ted Scambos, Karen M. Simon, Benjamin E. Smith, Louise S. Sørensen, Isabella Velicogna, Pippa L. Whitehouse, Geruo A, Cécile Agosta, Andreas P. Ahlstrøm, Alejandro Blazquez, William Colgan, Marcus E. Engdahl, Xavier Fettweis, Rene Forsberg, Hubert Gallée, Alex Gardner, Lin Gilbert, Noel Gourmelen, Andreas Groh, Brian C. Gunter, Christopher Harig, Veit Helm, Shfaqat Abbas Khan, Christoph Kittel, Hannes Konrad, Peter L. Langen, Benoit S. Lecavalier, Chia-Chun Liang, Bryant D. Loomis, Malcolm McMillan, Daniele Melini, Sebastian H. Mernild, Ruth Mottram, Jeremie Mouginot, Johan Nilsson, Brice Noël, Mark E. Pattle, William R. Peltier, Nadege Pie, Mònica Roca, Ingo Sasgen, Himanshu V. Save, Ki-Weon Seo, Bernd Scheuchl, Ernst J. O. Schrama, Ludwig Schröder, Sebastian B. Simonsen, Thomas Slater, Giorgio Spada, Tyler C. Sutterley, Bramha Dutt Vishwakarma, Jan Melchior van Wessem, David Wiese, Wouter van der Wal, and Bert Wouters
Earth Syst. Sci. Data, 15, 1597–1616, https://doi.org/10.5194/essd-15-1597-2023, https://doi.org/10.5194/essd-15-1597-2023, 2023
Short summary
Short summary
By measuring changes in the volume, gravitational attraction, and ice flow of Greenland and Antarctica from space, we can monitor their mass gain and loss over time. Here, we present a new record of the Earth’s polar ice sheet mass balance produced by aggregating 50 satellite-based estimates of ice sheet mass change. This new assessment shows that the ice sheets have lost (7.5 x 1012) t of ice between 1992 and 2020, contributing 21 mm to sea level rise.
Fuming Xie, Shiyin Liu, Yongpeng Gao, Yu Zhu, Tobias Bolch, Andreas Kääb, Shimei Duan, Wenfei Miao, Jianfang Kang, Yaonan Zhang, Xiran Pan, Caixia Qin, Kunpeng Wu, Miaomiao Qi, Xianhe Zhang, Ying Yi, Fengze Han, Xiaojun Yao, Qiao Liu, Xin Wang, Zongli Jiang, Donghui Shangguan, Yong Zhang, Richard Grünwald, Muhammad Adnan, Jyoti Karki, and Muhammad Saifullah
Earth Syst. Sci. Data, 15, 847–867, https://doi.org/10.5194/essd-15-847-2023, https://doi.org/10.5194/essd-15-847-2023, 2023
Short summary
Short summary
In this study, first we generated inventories which allowed us to systematically detect glacier change patterns in the Karakoram range. We found that, by the 2020s, there were approximately 10 500 glaciers in the Karakoram mountains covering an area of 22 510.73 km2, of which ~ 10.2 % is covered by debris. During the past 30 years (from 1990 to 2020), the total glacier cover area in Karakoram remained relatively stable, with a slight increase in area of 23.5 km2.
Muchu Lesi, Yong Nie, Dan Hirsh Shugar, Jida Wang, Qian Deng, Huayong Chen, and Jianrong Fan
Earth Syst. Sci. Data, 14, 5489–5512, https://doi.org/10.5194/essd-14-5489-2022, https://doi.org/10.5194/essd-14-5489-2022, 2022
Short summary
Short summary
The China–Pakistan Economic Corridor plays a vital role in foreign trade and faces threats from water shortage and water-related hazards. An up-to-date glacial lake dataset with critical parameters is basic for water resource and flood risk research, which is absent from the corridor. This study created a glacial lake dataset in 2020 from Landsat and Sentinel images from 1990–2000, using a threshold-based mapping method. Our dataset has the potential to be widely applied.
Yang Lei, Alex S. Gardner, and Piyush Agram
Earth Syst. Sci. Data, 14, 5111–5137, https://doi.org/10.5194/essd-14-5111-2022, https://doi.org/10.5194/essd-14-5111-2022, 2022
Short summary
Short summary
This work describes NASA MEaSUREs ITS_LIVE project's Version 2 Sentinel-1 image-pair ice velocity product and processing methodology. We show the refined offset tracking algorithm, autoRIFT, calibration for Sentinel-1 geolocation biases and correction of the ionosphere streaking problems. Validation was performed over three typical test sites covering the globe by comparing with other similar global and regional products.
Mohd Soheb, Alagappan Ramanathan, Anshuman Bhardwaj, Millie Coleman, Brice R. Rea, Matteo Spagnolo, Shaktiman Singh, and Lydia Sam
Earth Syst. Sci. Data, 14, 4171–4185, https://doi.org/10.5194/essd-14-4171-2022, https://doi.org/10.5194/essd-14-4171-2022, 2022
Short summary
Short summary
This study provides a multi-temporal inventory of glaciers in the Ladakh region. The study records data on 2257 glaciers (>0.5 km2) covering an area of ~7923 ± 106 km2 which is equivalent to ~89 % of the total glacierised area of the Ladakh region. It will benefit both the scientific community and the administration of the Union Territory of Ladakh, in developing efficient mitigation and adaptation strategies by improving the projections of change on timescales relevant to policymakers.
Dahong Zhang, Gang Zhou, Wen Li, Shiqiang Zhang, Xiaojun Yao, and Shimei Wei
Earth Syst. Sci. Data, 14, 3889–3913, https://doi.org/10.5194/essd-14-3889-2022, https://doi.org/10.5194/essd-14-3889-2022, 2022
Short summary
Short summary
The length of a glacier is a key determinant of its geometry; glacier centerlines are crucial inputs for many glaciological applications. Based on the European allocation theory, we present a new global dataset that includes the centerlines and lengths of 198 137 mountain glaciers. The accuracy of the glacier centerlines was 89.68 %. The constructed dataset comprises 17 sub-datasets which contain the centerlines and lengths of glacier tributaries.
Lenneke M. Jong, Christopher T. Plummer, Jason L. Roberts, Andrew D. Moy, Mark A. J. Curran, Tessa R. Vance, Joel B. Pedro, Chelsea A. Long, Meredith Nation, Paul A. Mayewski, and Tas D. van Ommen
Earth Syst. Sci. Data, 14, 3313–3328, https://doi.org/10.5194/essd-14-3313-2022, https://doi.org/10.5194/essd-14-3313-2022, 2022
Short summary
Short summary
Ice core records from Law Dome in East Antarctica, collected over the the last 3 decades, provide high-resolution data for studies of the climate of Antarctica, Australia and the Southern and Indo-Pacific oceans. Here, we present a set of annually dated records from Law Dome covering the last 2000 years. This dataset provides an update and extensions both forward and back in time of previously published subsets of the data, bringing them together into a coherent set with improved dating.
Yu Cai, Claude R. Duguay, and Chang-Qing Ke
Earth Syst. Sci. Data, 14, 3329–3347, https://doi.org/10.5194/essd-14-3329-2022, https://doi.org/10.5194/essd-14-3329-2022, 2022
Short summary
Short summary
Seasonal ice cover is one of the important attributes of lakes in middle- and high-latitude regions. This study used passive microwave brightness temperature measurements to extract the ice phenology for 56 lakes across the Northern Hemisphere from 1979 to 2019. A threshold algorithm was applied according to the differences in brightness temperature between lake ice and open water. The dataset will provide valuable information about the changing ice cover of lakes over the last 4 decades.
Lea Geibel, Matthias Huss, Claudia Kurzböck, Elias Hodel, Andreas Bauder, and Daniel Farinotti
Earth Syst. Sci. Data, 14, 3293–3312, https://doi.org/10.5194/essd-14-3293-2022, https://doi.org/10.5194/essd-14-3293-2022, 2022
Short summary
Short summary
Glacier monitoring in Switzerland started in the 19th century, providing exceptional data series documenting snow accumulation and ice melt. Raw point observations of surface mass balance have, however, never been systematically compiled so far, including complete metadata. Here, we present an extensive dataset with more than 60 000 point observations of surface mass balance covering 60 Swiss glaciers and almost 140 years, promoting a better understanding of the drivers of recent glacier change.
Cited articles
Akiba, T., Sano, S., Yanase, T., Ohta, T., and Koyama, M.: Optuna: A
Next-generation Hyperparameter Optimization Framework, in: Proceedings of the
25th ACM SIGKDD International Conference on Knowledge Discovery and Data
Mining, Anchorage, AS, USA, 4–8 August 2019, 2623–2631,
https://doi.org/10.1145/3292500.3330701, 2019. a
Amundson, J. M., Fahnestock, M., Truffer, M., Brown, J., Lüthi, M. P., and
Motyka, R. J.: Ice mélange dynamics and implications for terminus stability,
Jakobshavn Isbræ, Greenland, J. Geophys. Res., 115, F01005,
https://doi.org/10.1029/2009JF001405, 2010. a
Åström, J. A., Vallot, D., Schäfer, M., Welty, E. Z., O'Neel, S.,
Bartholomaus, T. C., Liu, Y., Riikilä, T. I., Zwinger, T., Timonen, J.,
and Moore, J. C.: Termini of calving glaciers as self-organized critical
systems, Nat. Geosci., 7, 874–878, https://doi.org/10.1038/ngeo2290, 2014. a
Baumhoer, C., Dietz, A., Dech, S., and Kuenzer, C.: Remote Sensing of Antarctic
Glacier and Ice-Shelf Front Dynamics – A Review, Remote Sens., 10,
1445, https://doi.org/10.3390/rs10091445, 2018. a, b
Baumhoer, C. A., Dietz, A. J., Kneisel, C., Paeth, H., and Kuenzer, C.: Environmental drivers of circum-Antarctic glacier and ice shelf front retreat over the last two decades, The Cryosphere, 15, 2357–2381, https://doi.org/10.5194/tc-15-2357-2021, 2021. a, b
Bengio, Y.: Practical
Recommendations for Gradient-Based Training of Deep Architectures, in: Neural Networks: Tricks of the Trade, 2 edn.,
Springer, Berlin, Heidelberg, 437–478,
https://doi.org/10.1007/978-3-642-35289-8_26, 2012. a
Bishop, C. M.: Neural networks for pattern recognition, 1
edn., edited by: Jordan, M., Kleinberg, J., and Schölkopf, B., Clarendon Press, ISBN-10 0-387-31073-8,
ISBN-13 978-0387-31073-2,
1995. a
Burgess, E. W., Forster, R. R., and Larsen, C. F.: Flow velocities of Alaskan
glaciers, Nat. Commun., 4, 2146, https://doi.org/10.1038/ncomms3146, 2013. a
Chen, L.-C., Papandreou, G., Kokkinos, I., Murphy, K., and Yuille, A. L.:
DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous
Convolution, and Fully Connected CRFs, IEEE T. Pattern. Anal., 40, 834–848,
https://doi.org/10.1109/TPAMI.2017.2699184, 2018a. a
Cheng, D., Hayes, W., and Larour, E.: CALFIN: Calving front dataset for
East/West Greenland, 1972–2019, Dryad [data set], https://doi.org/10.7280/D1FH5D,
2020. a, b, c, d
Cheng, D., Hayes, W., Larour, E., Mohajerani, Y., Wood, M., Velicogna, I., and Rignot, E.: Calving Front Machine (CALFIN): glacial termini dataset and automated deep learning extraction method for Greenland, 1972–2019, The Cryosphere, 15, 1663–1675, https://doi.org/10.5194/tc-15-1663-2021, 2021. a, b, c, d, e, f, g, h, i, j
Chollet, F.: Xception: Deep Learning With Depthwise Separable Convolutions, in:
Proceedings of the IEEE Conference on Computer Vision and Pattern
Recognition, Honolulu, HI, USA, 21–26 July 2017, 1251–1258,
https://doi.org/10.1109/CVPR.2017.195, 2017. a
Cook, A. J. and Vaughan, D. G.: Overview of areal changes of the ice shelves on the Antarctic Peninsula over the past 50 years, The Cryosphere, 4, 77–98, https://doi.org/10.5194/tc-4-77-2010, 2010. a
Cook, A. J., Murray, T., Luckman, A., Vaughan, D. G., and Barrand, N. E.: A new 100-m Digital Elevation Model of the Antarctic Peninsula derived from ASTER Global DEM: methods and accuracy assessment, Earth Syst. Sci. Data, 4, 129–142, https://doi.org/10.5194/essd-4-129-2012, 2012. a
Cooper, A.: Historical observations of Prince Gustav Ice Shelf, Polar
Rec., 33, 285–294, https://doi.org/10.1017/S0032247400025389, 1997. a
Davari, A., Islam, S., Seehaus, T., Hartmann, A., Braun, M., Maier, A., and
Christlein, V.: On Mathews Correlation Coefficient and Improved Distance Map
Loss for Automatic Glacier Calving Front Segmentation in SAR Imagery, IEEE T.
Geosci. Remote., 60, 5213212, https://doi.org/10.1109/TGRS.2021.3115883, 2021. a, b, c, d, e, f, g, h
Davari, A., Baller, C., Seehaus, T., Braun, M., Maier, A., and Christlein, V.:
Pixel-wise Distance Regression for Glacier Calving Front Detection and
Segmentation, IEEE T. Geosci. Remote., 60, 5224610,
https://doi.org/10.1109/TGRS.2022.3158591, 2022. a, b, c, d
Dryak, M. C. and Enderlin, E. M.: Analysis of Antarctic Peninsula glacier
frontal ablation rates with respect to iceberg melt-inferred variability in
ocean conditions, J. Glaciol., 66, 457–470, https://doi.org/10.1017/jog.2020.21, 2020. a
ESA Greenland Ice Sheet CCI project team: ESA Greenland Ice Sheet Climate
Change Initiative (Greenland_Ice_Sheet_cci): Greenland Calving Front
Locations, v3.0, Centre for Environmental Data Analysis [data set],
https://catalogue.ceda.ac.uk/uuid/8889dfe3de45406e815bce13ae8a0c92 (last access: 20 September 2022),
2019. a, b
Fausto, R. S., Andersen, J., Hansen, K., Box, J. E., Andersen, S. B.,
Ahlstrøm, A. P., van As, D., Citterio, M., Colgan, W., Karlsson, N. B.,
Kjeldsen, K. K., Korsgaard, N. J., Larsen, S. H., Mankoff, K. D., Pedersen,
A. Ø., Shields, C. L., Solgaard, A., and Vandecrux, B.: Programme for
monitoring of the Greenland ice sheet (PROMICE): Calving front line,
1999–2018, Arctic Data Center [data set],
https://doi.org/10.22008/promice/data/calving_front_lines, 2019. a, b, c
Fawcett, T.: An introduction to ROC analysis, Pattern Recogn. Lett., 27,
861–874, https://doi.org/10.1016/j.patrec.2005.10.010, 2006. a, b
Frederikse, T., Landerer, F., Caron, L., Adhikari, S., Parkes, D., Humphrey,
V. W., Dangendorf, S., Hogarth, P., Zanna, L., Cheng, L., and Wu, Y.-H.: The
causes of sea-level rise since 1900, Nature, 584, 393–397,
https://doi.org/10.1038/s41586-020-2591-3, 2020. a
Gao, B.-C., Han, W., Tsay, S. C., and Larsen, N. F.: Cloud Detection over the
Arctic Region Using Airborne Imaging Spectrometer Data during the Daytime, J.
App. Meteorol. Clim., 37, 1421–1429,
https://doi.org/10.1175/1520-0450(1998)037<1421:CDOTAR>2.0.CO;2,
1998. a
Gerrish, L., Fretwell, P., and Cooper, P.: High resolution vector polylines of
the Antarctic coastline (7.4), UK Polar Data Centre, Natural Environment
Research Council, UK Research & Innovation [data set],
https://doi.org/10.5285/e46be5bc-ef8e-4fd5-967b-92863fbe2835, 2021. a, b
Gourmelon, N., Seehaus, T., Braun, M. H., Maier, A., and Christlein, V.:
Calving Fronts and Where to Find Them, Zenodo [code],
https://doi.org/10.5281/zenodo.6469519, 2022a. a
Gourmelon, N., Seehaus, T., Braun, M. H., Maier, A., and Christlein, V.: CaFFe
(CAlving Fronts and where to Find thEm: a benchmark dataset and methodology
for automatic glacier calving front extraction from sar imagery), PANGAEA
[data set], https://doi.org/10.1594/PANGAEA.940950, 2022b. a, b, c
Gourmelon, N., Seehaus, T., Braun, M. H., Maier, A., and Christlein, Vincent: Calving Fronts and Where to Find Them, GitHub [code], https://github.com/Nora-Go/Calving_Fronts_and_Where_to_Find_Them, last access: 20 September 2022c. a
Hartmann, A., Davari, A., Seehaus, T., Braun, M., Maier, A., and Christlein,
V.: Bayesian U-Net for Segmenting Glaciers in SAR Imagery, in: 2021 IEEE
International Geoscience and Remote Sensing Symposium IGARSS, Brussels,
Belgium, 11–16 July 2021, 3479–3482,
https://doi.org/10.1109/IGARSS47720.2021.9554292, 2021. a, b, c, d
Holzmann, M., Davari, A., Seehaus, T., Braun, M., Maier, A., and Christlein,
V.: Glacier Calving Front Segmentation Using Attention U-Net, in: 2021 IEEE
International Symposium on Geoscience and Remote Sensing (IGARSS), Brussels,
Belgium, 11–16 July 2021, 3483–3486,
https://doi.org/10.1109/IGARSS47720.2021.9555067, 2021. a, b, c, d
Hugonnet, R., McNabb, R., Berthier, E., Menounos, B., Nuth, C., Girod, L.,
Farinotti, D., Huss, M., Dussaillant, I., Brun, F., and Kääb, A.:
Accelerated global glacier mass loss in the early twenty-first century,
Nature, 592, 726–731, https://doi.org/10.1038/s41586-021-03436-z, 2021. a
Isensee, F., Jaeger, P. F., Kohl, S. A. A., Petersen, J., and Maier-Hein,
K. H.: nnU-Net: a self-configuring method for deep learning-based biomedical
image segmentation, Nat. Methods, 18, 203–211,
https://doi.org/10.1038/s41592-020-01008-z, 2021. a
Jaccard, P.: The Distribution of the Flora in the Alpine Zone, New Phytol., 11,
37–50, https://doi.org/10.1111/j.1469-8137.1912.tb05611.x, 1912. a
Joughin, I., Das, S. B., King, M. A., Smith, B. E., Howat, I. M., and Moon, T.:
Seasonal Speedup Along the Western Flank of the Greenland Ice
Sheet, Science, 320, 781–783, https://doi.org/10.1126/science.1153288, 2008. a, b
Joughin, I., Smith, B. E., Howat, I. M., Floricioiu, D., Alley, R. B., Truffer,
M., and Fahnestock, M.: Seasonal to decadal scale variations in the surface
velocity of Jakobshavn Isbrae, Greenland: Observation and model-based
analysis, J Geophys. Res.-Earth., 117, F02030, https://doi.org/10.1029/2011JF002110, 2012. a, b
Khan, S. A., Aschwanden, A., Bjørk, A. A., Wahr, J., Kjeldsen, K. K., and
Kjær, K. H.: Greenland ice sheet mass balance: a review, Rep. Prog.
Phys., 78, 046801, https://doi.org/10.1088/0034-4885/78/4/046801, 2015. a, b
King, M. and Howat, I.: Data from: Dynamic ice loss from the Greenland Ice
Sheet driven by sustained glacier retreat, Dryad [data set],
https://doi.org/10.5061/dryad.qrfj6q5cb, 2020. a, b, c
Kingma, D. P. and Ba, J.: Adam: A Method for Stochastic Optimization, arXiv [preprint], https://doi.org/10.48550/arXiv.1412.6980, 22 December 2014. a
Koch, E. W. and Rosolowsky, E. W.: Filament identification through mathematical
morphology, Mon. Not. R. Astron. Soc., 452, 3435–3450,
https://doi.org/10.1093/mnras/stv1521, 2015. a
Krimmel, R. M.: Photogrammetric Data Set, 1957–2000, and Bathymetric
Measurements for Columbia Glacier, Alaska, Tech. Rep., U.S.
Geological Survey, https://doi.org/10.3133/wri20014089, 2001. a
Lewis, D. D.: Representation Quality in Text Classification: An Introduction
and Experiment, in: Proceedings of the Workshop on Speech and Natural
Language, Hidden Valley, Pennsylvania, USA, 24–27 June 1990, 288–295,
https://doi.org/10.3115/116580.116681, 1990. a
Ling, C. X. and Sheng, V. S.: Class
Imbalance Problem, in: Encyclopedia of Machine Learning, Springer US, Boston, MA, USA, 171–171,
https://doi.org/10.1007/978-0-387-30164-8_110, 2010. a
Lippl, S.: Glacier Surface Velocities and Outlet Areas from 2014–2018 on
James Ross Island, Northern Antarctic Peninsula, PANGAEA [data set],
https://doi.org/10.1594/PANGAEA.907062, 2019. a, b, c
Liu, H. and Jezek, K. C.: Automated extraction of coastline from satellite
imagery by integrating Canny edge detection and locally adaptive thresholding
methods, Int. J. Remote Sens., 25, 937–958,
https://doi.org/10.1080/0143116031000139890, 2004. a
McNabb, R., Hock, R., O'Neel, S., Rasmussen, L., Ahn, Y., Braun, M., Conway,
H., Herreid, S., Joughin, I., Pfeffer, W., Smith, B., and Truffer, M.: Using
surface velocities to calculate ice thickness and bed topography: a case
study at Columbia Glacier, Alaska, USA, J Glaciol., 58, 1151–1164,
https://doi.org/10.3189/2012JoG11J249, 2012. a
McNabb, R. W., Hock, R., and Huss, M.: Variations in Alaska tidewater glacier
frontal ablation, 1985–2013, J. Geophys. Res.-Earth, 120, 120–136,
https://doi.org/10.1002/2014JF003276, 2015. a, b
Minowa, M., Schaefer, M., Sugiyama, S., Sakakibara, D., and Skvarca, P.:
Frontal ablation and mass loss of the Patagonian icefields, Earth Planet. Sc.
Lett., 561, 116811, https://doi.org/10.1016/j.epsl.2021.116811, 2021. a
Mohajerani, Y., Jeong, S., Scheuchl, B., Velicogna, I., Rignot, E., and
Milillo, P.: Automatic delineation of glacier grounding lines in differential
interferometric synthetic-aperture radar data using deep learning, Sci. Rep.,
11, 4992, https://doi.org/10.1038/s41598-021-84309-3, 2021. a
Nick, F. M., van der Veen, C. J., Vieli, A., and Benn, D. I.: A physically
based calving model applied to marine outlet glaciers and implications for
the glacier dynamics, J. Glaciol., 56, 781–794,
https://doi.org/10.3189/002214310794457344, 2010. a
Nicolaou, A., Christlein, V., Riba, E., Shi, J., Vogeler, G., and Seuret, M.:
TorMentor: Deterministic dynamic-path, data augmentations with fractals, arXiv [preprint],
https://doi.org/10.48550/arxiv.2204.03776, 7 April 2022. a
Oliva, M., Navarro, F., Hrbáček, F., Hernández, A., Nývlt, D., Pereira, P.,
Ruiz-Fernández, J., and Trigo, R.: Recent regional climate cooling on the
Antarctic Peninsula and associated impacts on the cryosphere, Sci. Total Environ., 580, 210–223, https://doi.org/10.1016/j.scitotenv.2016.12.030,
2017. a
Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Thirion, B., Grisel,
O., Blondel, M., Prettenhofer, P., Weiss, R., Dubourg, V., Vanderplas, J.,
Passos, A., Cournapeau, D., Brucher, M., Perrot, M., and Duchesnay, E.:
Scikit-learn: Machine Learning in Python, J. Mach. Learn. Res., 12,
2825–2830, http://jmlr.org/papers/v12/pedregosa11a.html (last access: 20 September 2022), 2011. a
Periyasamy, M., Davari, A., Seehaus, T., Braun, M., Maier, A., and Christlein,
V.: How to Get the Most Out of U-Net for Glacier Calving Front Segmentation,
IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens., 15, 1712–1723,
https://doi.org/10.1109/JSTARS.2022.3148033, 2022. a, b, c, d
Quinonero-Candela, J., Sugiyama, M., Schwaighofer, A., and Lawrence, N.:
Dataset Shift in Machine Learning, Neural Information Processing series, MIT
Press, ISBN 978-0-262-17005-5, 2008. a
Raup, B., Racoviteanu, A., Khalsa, S., Helm, C., Armstrong, R., and Arnaud, Y.:
GLIMS and NSIDC (2005, updated 2018): Global Land Ice Measurements from
Space glacier database. Compiled and made available by the international
GLIMS community and the National Snow and Ice Data Center, Boulder CO,
USA, GLIMS [data set], https://doi.org/10.7265/N5V98602, 2018. a, b
Recinos, B., Maussion, F., Rothenpieler, T., and Marzeion, B.: Impact of frontal ablation on the ice thickness estimation of marine-terminating glaciers in Alaska, The Cryosphere, 13, 2657–2672, https://doi.org/10.5194/tc-13-2657-2019, 2019. a, b, c
Recinos, B., Maussion, F., Noël, B., Möller, M., and Marzeion, B.:
Calibration of a frontal ablation parameterisation applied to Greenland's
peripheral calving glaciers, J. Glaciol., 67, 1177–1189,
https://doi.org/10.1017/jog.2021.63, 2021. a
Robel, A. A.: Thinning sea ice weakens buttressing force of iceberg mélange
and promotes calving, Nat. Commun., 8, 14596, https://doi.org/10.1038/ncomms14596,
2017. a
Ronneberger, O., Fischer, P., and Brox, T.: U-Net: Convolutional Networks for
Biomedical Image Segmentation, in: Proceedings of the 18th International
Conference on Medical Image Computing and Computer Assisted Interventions,
Munich, Germany, 5–9 October 2015, 234–241,
https://doi.org/10.1007/978-3-319-24574-4_28, 2015. a, b
Rosenau, R., Schwalbe, E., Maas, H.-G., Baessler, M., and Dietrich, R.:
Grounding line migration and high-resolution calving dynamics of Jakobshavn
Isbræ, West Greenland, J. Geophys. Res.-Earth., 118, 382–395,
https://doi.org/10.1029/2012JF002515, 2013. a
Rott, H., Floricioiu, D., Wuite, J., Scheiblauer, S., Nagler, T., and Kern, M.:
Mass changes of outlet glaciers along the Nordensjköld Coast, northern
Antarctic Peninsula, based on TanDEM-X satellite measurements,
Geophys. Res. Lett., 41, 8123–8129, https://doi.org/10.1002/2014GL061613, 2014. a, b
Rott, H., Abdel Jaber, W., Wuite, J., Scheiblauer, S., Floricioiu, D., van Wessem, J. M., Nagler, T., Miranda, N., and van den Broeke, M. R.: Changing pattern of ice flow and mass balance for glaciers discharging into the Larsen A and B embayments, Antarctic Peninsula, 2011 to 2016, The Cryosphere, 12, 1273–1291, https://doi.org/10.5194/tc-12-1273-2018, 2018. a
Scambos, T. A., Bohlander, J., Shuman, C. A., and Skvarca, P.: Glacier
acceleration and thinning after ice shelf collapse in the Larsen B
embayment, Antarctica, Geophys. Res. Lett., 31, L18402,
https://doi.org/10.1029/2004GL020670, 2004. a
Schild, K. and Hamilton, G.: Terminus position time series: Helheim and
Kangerdlugssuaq glaciers, Greenland, Arctic Data Center [data set],
https://doi.org/10.18739/A2W93G, 2013. a, b, c
Seehaus, T., Marinsek, S., Helm, V., Skvarca, P., and Braun, M.: Changes in ice
dynamics, elevation and mass discharge of
Dinsmoor–Bombardier–Edgeworth glacier system, Antarctic
Peninsula, Earth Planet. Sc. Lett., 427, 125–135,
https://doi.org/10.1016/j.epsl.2015.06.047, 2015. a, b, c, d
Seehaus, T. C., Marinsek, S., Skvarca, P., van Wessem, J. M., Reijmer, C. H.,
Seco, J. L., and Braun, M. H.: Dynamic Response of Sjögren Inlet
Glaciers, Antarctic Peninsula, to Ice Shelf Breakup Derived
from Multi-Mission Remote Sensing Time Series, Front. Earth Sci.,
4, 66, https://doi.org/10.3389/feart.2016.00066, 2016. a, b, c, d
Sheperd, A., Ivins, E., Rignot, E., Smith, B., van den Broeke, M., Velicogna,
I., Whitehouse, P., Briggs, K., and Joughin, I.: Mass balance of the
Antarctic Ice Sheet from 1992 to 2017, Nature, 558, 219–222,
https://doi.org/10.1038/s41586-018-0179-y, 2018. a, b
Skvarca, P., Rack, W., Rott, H., and Y Donángelo, T. I.: Evidence of
recent climatic warming on the eastern Antarctic Peninsula, Ann.
Glaciol., 27, 628–632, https://doi.org/10.3189/S0260305500018164, 1998. a
Smith, L. N.: Cyclical learning rates for training neural networks, in: 2017
IEEE winter conference on applications of computer vision (WACV), Santa Rosa,
CA, USA, 24–31 March 2017, 464–472, https://doi.org/10.1109/WACV.2017.58, 2017. a, b
Sudre, C. H., Li, W., Vercauteren, T., Ourselin, S., and Jorge Cardoso, M.:
Generalised Dice Overlap as a Deep Learning Loss Function for Highly
Unbalanced Segmentations, in: Deep Learning in Medical Image Analysis and
Multimodal Learning for Clinical Decision Support, Québec City, QC, Canada,
14 September 2017, 240–248, https://doi.org/10.1007/978-3-319-67558-9_28, 2017. a
Tedesco, M.: Remote sensing of the cryosphere, in: The Cryosphere Science Series, 1st edn., edited by: Knight, P. G.,
Wiley Blackwell, Hoboken, NJ, USA, https://doi.org/10.1002/9781118368909, 2014. a
Todd, J. and Christoffersen, P.: Are seasonal calving dynamics forced by buttressing from ice mélange or undercutting by melting? Outcomes from full-Stokes simulations of Store Glacier, West Greenland, The Cryosphere, 8, 2353–2365, https://doi.org/10.5194/tc-8-2353-2014, 2014. a
Turner, J., Lu, H., White, I., King, J. C., Phillips, T., Hosking, J. S.,
Bracegirdle, T. J., Marshall, G. J., Mulvaney, R., and Deb, P.: Absence of
21st century warming on Antarctic Peninsula consistent with natural
variability, Nature, 535, 411–415, https://doi.org/10.1038/nature18645, 2016.
a
Ultee, L. and Bassis, J.: The future is Nye: an extension of the perfect
plastic approximation to tidewater glaciers, J. Glaciol., 62, 1143–1152,
https://doi.org/10.1017/jog.2016.108, 2016. a
Vijay, S. and Braun, M.: Seasonal and Interannual Variability of Columbia
Glacier, Alaska (2011–2016): Ice Velocity, Mass Flux, Surface
Elevation and Front Position, Remote Sens., 9, 635,
https://doi.org/10.3390/rs9060635, 2017. a, b
Wuite, J., Rott, H., Hetzenecker, M., Floricioiu, D., De Rydt, J., Gudmundsson, G. H., Nagler, T., and Kern, M.: Evolution of surface velocities and ice discharge of Larsen B outlet glaciers from 1995 to 2013, The Cryosphere, 9, 957–969, https://doi.org/10.5194/tc-9-957-2015, 2015. a
Zemp, M., Huss, M., Thibert, E., Eckert, N., McNabb, R., Huber, J., Barandun,
M., Machguth, H., Nussbaumer, S. U., Gärtner-Roer, I., Thomson, L., Paul,
F., Maussion, F., Kutuzov, S., and Cogley, J. G.: Global glacier mass changes
and their contributions to sea-level rise from 1961 to 2016, Nature, 568,
382–386, https://doi.org/10.1038/s41586-019-1071-0, 2019. a
Zhang, E.: The ground truth of the calving fronts in Jakobshavn Isbræ,
PANGAEA [data set], https://doi.org/10.1594/PANGAEA.897065, 2019a. a, b, c
Zhang, E.: The calving fronts delineated by the network in Jakobshavn
Isbræ, PANGAEA [data set], https://doi.org/10.1594/PANGAEA.897064,
2019b. a, b
Zhang, E., Liu, L., Huang, L., and Ng, K. S.: Manually delineated
calving fronts at Jakobshavn Isbræ, Kangerlussuaq, and Helheim,
PANGAEA [data set], https://doi.org/10.1594/PANGAEA.923270, 2020a. a, b, c
Zhang, E., Liu, L., Huang, L., and Ng, K. S.: Network delineated
calving fronts at Jakobshavn Isbræ, Kangerlussuaq, and Helheim,
PANGAEA [data set], https://doi.org/10.1594/PANGAEA.923272, 2020b. a, b
Zhang, E., Liu, L., Huang, L., and Ng, K. S.: An automated, generalized,
deep-learning-based method for delineating the calving fronts of Greenland
glaciers from multi-sensor remote sensing imagery, Remote Sens. Environ.,
254, 112265, https://doi.org/10.1016/j.rse.2020.112265, 2021. a, b, c, d, e, f
Short summary
Ice loss of glaciers shows in retreating calving fronts (i.e., the position where icebergs break off the glacier and drift into the ocean). This paper presents a benchmark dataset for calving front delineation in synthetic aperture radar (SAR) images. The dataset can be used to train and test deep learning techniques, which automate the monitoring of the calving front. Provided example models achieve front delineations with an average distance of 887 m to the correct calving front.
Ice loss of glaciers shows in retreating calving fronts (i.e., the position where icebergs break...
Altmetrics
Final-revised paper
Preprint