Articles | Volume 17, issue 6
https://doi.org/10.5194/tc-17-2343-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-17-2343-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
12 Jun 2023
Research article |
| 12 Jun 2023
| 12 Jun 2023
Strategies for regional modeling of surface mass balance at the Monte Sarmiento Massif, Tierra del Fuego
Institut für Geographie, Friedrich-Alexander-Universität
Erlangen-Nürnberg, Erlangen 91058, Germany
David Farías-Barahona
Departamento de Geografía, Universidad de Concepción,
Concepción, 4030000, Chile
Institut für Geographie, Friedrich-Alexander-Universität
Erlangen-Nürnberg, Erlangen 91058, Germany
Thorsten Seehaus
Institut für Geographie, Friedrich-Alexander-Universität
Erlangen-Nürnberg, Erlangen 91058, Germany
Ricardo Jaña
Departamento Científico, Instituto Antártico Chileno, Punta
Arenas, 6200000, Chile
Jorge Arigony-Neto
Instituto de Oceanografia, Universidade Federal do Rio Grande, Rio
Grande, 96203, Brazil
Instituto Nacional de Ciência e Tecnologia da Criosfera, Universidade Federal do Rio Grande, Porto Alegre, 91501-970, Brazil
Inti Gonzalez
Centro de Estudios del Cuaternario de Fuego-Patagonia y
Antárctica, Punta Arenas, 6200000, Chile
Programa Doctorado Ciencias Antárticas y Subantárticas,
Universidad de Magallanes, Punta Arenas, 6200000, Chile
Anselm Arndt
Geography Department, Humboldt-Universität zu Berlin, Berlin 10099, Germany
Tobias Sauter
Geography Department, Humboldt-Universität zu Berlin, Berlin 10099, Germany
Christoph Schneider
Geography Department, Humboldt-Universität zu Berlin, Berlin 10099, Germany
Johannes J. Fürst
Institut für Geographie, Friedrich-Alexander-Universität
Erlangen-Nürnberg, Erlangen 91058, Germany
Related authors
No articles found.
Kristine Flacké Haualand, Marie Pontoppidan, Henning Åkesson, and Tobias Sauter
EGUsphere, https://doi.org/10.5194/egusphere-2026-643, https://doi.org/10.5194/egusphere-2026-643, 2026
This preprint is open for discussion and under review for Weather and Climate Dynamics (WCD).
Short summary
Short summary
Melting glaciers worldwide cause changes in land surface type and elevation that may impact regional climate. In a weather and climate model, we find that these changes result in warming and less precipitation, particularly less snow, over Jostedalsbreen ice cap in western Norway. Most of these impacts are related to thinning of the ice cap and the associated lowering of the surface and reduction in orographic lifting of moist air masses. The findings suggest accelerated melting of the ice cap.
Thorsten Seehaus, Alex S. Gardner, and Johan Nilsson
EGUsphere, https://doi.org/10.5194/egusphere-2025-6417, https://doi.org/10.5194/egusphere-2025-6417, 2026
This preprint is open for discussion and under review for The Cryosphere (TC).
Short summary
Short summary
Satellite altimeters only sample surface heights at scattered points. We developed a method to turn these measurements into maps of glacier height change while also estimating how reliable the results are. Applying this approach to glaciers in Svalbard and Antarctica shows strong ice loss and clearly captures short-lived events such as glacier surges. Our results improve the ability to monitor glacier change in difficult terrain and help better assess future contributions to sea level rise.
Vijaya Kumar Thota, Thorsten Seehaus, Friedrich Knuth, Amaury Dehecq, Christian Salewski, David Farías-Barahona, and Matthias H. Braun
Earth Syst. Sci. Data, 18, 597–615, https://doi.org/10.5194/essd-18-597-2026, https://doi.org/10.5194/essd-18-597-2026, 2026
Short summary
Short summary
We reconstruct historical topography for a rapidly warming Antarctic region with limited existing data. Using approximately 2000 aerial photographs from the year 1989 over the western Antarctic Peninsula and nearby islands, we created detailed elevation models and orthoimages that have high accuracy compared to recent satellite data. This open dataset aids tracking historical ice loss and its role in sea level rise.
Oskar Herrmann, Veena Prasad, Anna Zöller, Alexander R. Groos, Samuel Cook, Christian Sommer, and Johannes J. Fürst
EGUsphere, https://doi.org/10.5194/egusphere-2025-5486, https://doi.org/10.5194/egusphere-2025-5486, 2026
This preprint is open for discussion and under review for The Cryosphere (TC).
Short summary
Short summary
Glaciers in the European Alps are shrinking rapidly due to climate change. We developed a new open-source method to estimate where ice is gained or lost on glacier surfaces using satellite data and computer models. Our results agree well with direct field measurements. This approach helps to better track how glaciers respond to warming and improves projections of their future evolution.
Moritz Koch, Jorge Berkhoff, Norbert Blindow, David Farías-Barahona, Pedro Skvarca, Johannes J. Fürst, and Matthias Braun
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-678, https://doi.org/10.5194/essd-2025-678, 2026
Preprint under review for ESSD
Short summary
Short summary
The Southern Patagonian Icefield is losing glacier area and ice volume rapidly. Although its glaciers share the same plateau, they retreat at different speeds and times. One reason for these differences lies in the unknown landscape beneath the ice. To reveal it, we used helicopter-based radar to measure the ice thickness and map the bedrock of Viedma, Upsala, and Perito Moreno Glaciers.
Phillip Schuster, Ana-Lena Tappe, Alexander Georgi, Christoph Schneider, Mia Janzen, and Tobias Sauter
EGUsphere, https://doi.org/10.5194/egusphere-2025-3461, https://doi.org/10.5194/egusphere-2025-3461, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary
Short summary
We present MATILDA-Online, an open-source, cloud-based modeling toolkit, to support integrated water management in glacierized mountain regions. It integrates glacier and hydrology models with open data and cloud computing. Despite data scarcity, this tool empowers local professionals, students, and researchers to generate climate impact assessments, promoting informed decision-making. Despite its accessibility, effective calibration and interpretation still require expert knowledge.
Phillip Schuster, Azamat Osmonov, Alexander Georgi, Christoph Schneider, and Tobias Sauter
EGUsphere, https://doi.org/10.5194/egusphere-2025-3462, https://doi.org/10.5194/egusphere-2025-3462, 2025
Short summary
Short summary
This study examines water resources in a high-mountain basin in Kyrgyzstan facing climate change. The applied MATILDA-Online toolkit aims to integrate scientific research with practical water management. Projections indicate severe glacier melt and a significant reduction in runoff by 2100, with earlier peak flows and increased dry periods. The main challenges are the limited number of observations and their low accuracy, as well as the substantial effort required for model calibration.
Akash M. Patil, Christoph Mayer, Thorsten Seehaus, Alexander R. Groos, and Andreas Bauder
The Cryosphere, 19, 5547–5577, https://doi.org/10.5194/tc-19-5547-2025, https://doi.org/10.5194/tc-19-5547-2025, 2025
Short summary
Short summary
We studied how the density of snow to ice transition varies with depth in the Aletsch glacier using radar-based field measurements and some simple models. We showed that it is possible to track how much snow has accumulated in the last 10–14 years. This helps improve the uncertainties in glacier mass balance estimates. Overall, by utilising non-invasive radar techniques and models, we provide a novel approach to understanding the evolution of glaciers under regional climate conditions.
Marcel Dreier, Moritz Koch, Nora Gourmelon, Norbert Blindow, Daniel Steinhage, Fei Wu, Thorsten Seehaus, Matthias Braun, Andreas Maier, and Vincent Christlein
The Cryosphere, 19, 5337–5359, https://doi.org/10.5194/tc-19-5337-2025, https://doi.org/10.5194/tc-19-5337-2025, 2025
Short summary
Short summary
In this paper, we present a ready-to-use benchmark dataset to train machine learning approaches for detecting ice thickness from radar data. It includes radargrams of glaciers and ice sheets alongside annotations for their air–ice and ice–bedrock boundary. Furthermore, we introduce a baseline model and evaluate the influence of several geographical and glaciological factors on the performance of our model.
Pedro Henrique Lima Alencar, Saskia Arndt, Kei Namba, Márk Somogyvári, Frederik Bart, Fabio Brill, Juan F. Dueñas, Peter Feindt, Daniel Johnson, Nariman Mahmoodi, Christoph Merz, Subham Mukherjee, Katrin Nissen, Eva Nora Paton, Tobias Sauter, Dörthe Tetzlaff, Franziska Tügel, Thomas Vogelpohl, Stenka Valentinova Vulova, Behnam Zamani, and Hui Hui Zhang
Nat. Hazards Earth Syst. Sci., 25, 4043–4051, https://doi.org/10.5194/nhess-25-4043-2025, https://doi.org/10.5194/nhess-25-4043-2025, 2025
Short summary
Short summary
As climate change escalates, the Berlin-Brandenburg region faces new challenges. Climate change-induced extreme events are expected to cause new conflicts to emerge and aggravate existing ones. To guide future research, we co-develop a list of key questions on climate and water challenges in the region. Our findings highlight the need for new research approaches. We expect this list to provide a roadmap for actionable knowledge production to address climate and water challenges in the region.
Wilhelm Furian and Tobias Sauter
Nat. Hazards Earth Syst. Sci., 25, 3779–3802, https://doi.org/10.5194/nhess-25-3779-2025, https://doi.org/10.5194/nhess-25-3779-2025, 2025
Short summary
Short summary
Glacial lake outburst floods (GLOFs) continue to threaten high-mountain communities in Nepal. We simulate potential GLOF events from five glacial lakes in the Everest region during the 21st century using a 3D flood model and several breach and SSP scenarios. Large GLOFs could extend over 100 km and inundate 80 to 100 km of roads/trails, 735 to 1989 houses and 0.85 to 3.52 km2 of agricultural land. The results help to assess the changing GLOF impacts and support more accurate risk assessments.
Marius Schaefer, Ilaria Tabone, Ralf Greve, Johannes Fürst, and Matthias Braun
EGUsphere, https://doi.org/10.5194/egusphere-2025-4167, https://doi.org/10.5194/egusphere-2025-4167, 2025
Short summary
Short summary
The Northern Patagonian Icefield is the second largest ice mass of South America, located at moderate latitudes. Using an ice-flow model which uses available atmosphere data as input and explicitly models iceberg discharge, we assess its evolution. With present climate, it will lose about 25 % of its mass during this century. Climate change strongly accelerates losses and under Paris Agreement compliance it is 36 % until 2200 and up to 68 % under a business-as-usual fossil fuel scenario.
Johannes J. Fürst, David Farías-Barahona, Thomas Bruckner, Lucia Scaff, Martin Mergili, Santiago Montserrat, and Humberto Peña
Nat. Hazards Earth Syst. Sci., 25, 3559–3579, https://doi.org/10.5194/nhess-25-3559-2025, https://doi.org/10.5194/nhess-25-3559-2025, 2025
Short summary
Short summary
The 1987 Parraguirre ice–rock avalanche developed into a devastating debris flow, causing the loss of many lives and inflicting severe damage near Santiago, Chile. Here, we revise this event, combining various observational records with modelling techniques. In that year, important snow cover coincided with persistent warm periods in spring. We also put forward upward corrections for the trigger and flood volumes involved in this debris flow. Finally, temporary river damming was key for the flow ferocity.
Theresa Dobler, Wilfried Hagg, Martin Rückamp, Thorsten Seehaus, and Christoph Mayer
EGUsphere, https://doi.org/10.5194/egusphere-2025-2513, https://doi.org/10.5194/egusphere-2025-2513, 2025
Short summary
Short summary
We studied how a glacier in the Austrian Alps moves more slowly over time due to climate change. By combining long-term field data with recent aerial images, we show how thinning reduce glacier flow. Standard satellite methods failed to detect this slow movement, so we used manual tracking to create a reliable map. Our findings help understand changes in glacier behavior in a warming climate.
Hanwu Zheng, Doerthe Tetzlaff, Christian Birkel, Songjun Wu, Tobias Sauter, and Chris Soulsby
EGUsphere, https://doi.org/10.5194/egusphere-2025-2166, https://doi.org/10.5194/egusphere-2025-2166, 2025
Short summary
Short summary
Ecohydrological processes in heavily managed catchments are often incorrectly represented in models. We applied a tracer-aided model STARR in an ET-dominated region (the Middle Spree, NE Germany) with major management impacts. Water isotopes were useful in identifying runoff contributions and partitioning ET even at sparse resolution. Trade-offs between discharge- and isotope-based calibrations could be partially mitigated by integrating more process-based conceptualizations into the model.
Kaian Shahateet, Johannes J. Fürst, Francisco Navarro, Thorsten Seehaus, Daniel Farinotti, and Matthias Braun
The Cryosphere, 19, 1577–1597, https://doi.org/10.5194/tc-19-1577-2025, https://doi.org/10.5194/tc-19-1577-2025, 2025
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 using inversion modeling. This model consists of two steps: the first uses basic assumptions of the rheology of the glacier, and the second uses mass conservation to improve the reconstruction where the assumptions made previously are expected to fail. Validation with independent data showed that our reconstruction improved compared to other reconstructions that are available.
Felix Pfluger, Samuel Weber, Joseph Steinhauser, Christian Zangerl, Christine Fey, Johannes Fürst, and Michael Krautblatter
Earth Surf. Dynam., 13, 41–70, https://doi.org/10.5194/esurf-13-41-2025, https://doi.org/10.5194/esurf-13-41-2025, 2025
Short summary
Short summary
Our study explores permafrost–glacier interactions with a focus on their implications for preparing or triggering high-volume rock slope failures. Using the Bliggspitze rock slide as a case study, we demonstrate a new type of rock slope failure mechanism triggered by the uplift of the cold–warm dividing line in polythermal alpine glaciers, a widespread and currently under-explored phenomenon in alpine environments worldwide.
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.
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.
Bastian Morales, Marcelo Somos-Valenzuela, Mario Lillo, Iñigo Irarrazaval, David Farias, Elizabet Lizama, Diego Rivera, and Alfonso Fernández
EGUsphere, https://doi.org/10.5194/egusphere-2024-1053, https://doi.org/10.5194/egusphere-2024-1053, 2024
Preprint archived
Short summary
Short summary
Through a physical model, we explored how lacier geometry and topography configuration constrains glacier thinning in the Patagonian Icefields, the world's main glacial freshwater reservoir after Antarctica and Greenland. Our results indicate that about 53 % of the Patagonian Icefield ice flow is susceptible to thinning. Our findings allow for identifying priority glaciers for future research considering climate change projections.
Annelies Voordendag, Brigitta Goger, Rainer Prinz, Tobias Sauter, Thomas Mölg, Manuel Saigger, and Georg Kaser
The Cryosphere, 18, 849–868, https://doi.org/10.5194/tc-18-849-2024, https://doi.org/10.5194/tc-18-849-2024, 2024
Short summary
Short summary
Wind-driven snow redistribution affects glacier mass balance. A case study of Hintereisferner glacier in Austria used high-resolution observations and simulations to model snow redistribution. Simulations matched observations, showing the potential of the model for studying snow redistribution on other mountain glaciers.
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).
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.
Nora Gourmelon, Thorsten Seehaus, Matthias Braun, Andreas Maier, and Vincent Christlein
Earth Syst. Sci. Data, 14, 4287–4313, https://doi.org/10.5194/essd-14-4287-2022, https://doi.org/10.5194/essd-14-4287-2022, 2022
Short summary
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.
Mohamed H. Salim, Sebastian Schubert, Jaroslav Resler, Pavel Krč, Björn Maronga, Farah Kanani-Sühring, Matthias Sühring, and Christoph Schneider
Geosci. Model Dev., 15, 145–171, https://doi.org/10.5194/gmd-15-145-2022, https://doi.org/10.5194/gmd-15-145-2022, 2022
Short summary
Short summary
Radiative transfer processes are the main energy transport mechanism in urban areas which influence the surface energy budget and drive local convection. We show here the importance of each process to help modellers decide on how much detail they should include in their models to parameterize radiative transfer in urban areas. We showed how the flow field may change in response to these processes and the essential processes needed to assure acceptable quality of the numerical simulations.
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.
Cited articles
Albrecht, T., Winkelmann, R., and Levermann, A.: Glacial-cycle simulations of the Antarctic Ice Sheet with the Parallel Ice Sheet Model (PISM) – Part 2: Parameter ensemble analysis, The Cryosphere, 14, 633–656, https://doi.org/10.5194/tc-14-633-2020, 2020.
Arigony-Neto, J., Jaña, R., Gonzalez, Inti, Schneider, C., and Temme, F.: Meteorological Observations at Schiaparelli Glacier Automatic Weather Station (AWSglacier), Cordillera Darwin, Chile, 2013–2019, PANGAEA [data set], https://doi.org/10.1594/PANGAEA.958694, 2023.
Arndt, A., Scherer, D., and Schneider, C.: Atmosphere Driven Mass-Balance
Sensitivity of Halji Glacier, Himalayas, Atmosphere, 12, 426,
https://doi.org/10.3390/atmos12040426, 2021a.
Arndt, A., Sauter, T., and Saß, B.: COSIPY v1.4, Zenodo [code], https://doi.org/10.5281/zenodo.4439551, 2021b.
Ayala, A., Pellicciotti, F., and Shea, J. M.: Modeling 2 m air temperatures
over mountain glaciers: Exploring the influence of katabatic cooling and
external warming, J. Geophys. Res.-Atmos., 120, 3139–3157,
https://doi.org/10.1002/2015JD023137, 2015.
Barandun, M., Pohl, E., Naegeli, K., McNabb, R., Huss, M., Berthier, E., Saks, T., and Heolzle, M.: Hot spots of glacier mass balance variability in Central Asia, Geophys. Res. Lett., 48, e2020GL092084, https://doi.org/10.1029/2020GL092084, 2021.
Barcaza, G., Nussbaumer, S. U., Tapia, G., Valdés, J., García, J.
L., Videla, Y., Albornoz, A., and Arias, V.: Glacier inventory and recent
glacier variations in the Andes of Chile, South America, Ann. Glaciol., 58,
166–180, https://doi.org/10.1017/aog.2017.28, 2017.
Barstad, I. and Smith, R. B.: Evaluation of an orographic precipitation
model, J. Hydrometeorol., 6, 85–99, https://doi.org/10.1175/JHM-404.1, 2005.
Bentley, C. R.: Mass balance of the Antarctic ice sheet: observational
aspects, in: Mass Balance of the Cryosphere, Observations and Modelling of Contemporary and Future Changes, edited by: Houghton, J., Bamber, J., and Payne, A., Cambridge University Press, Cambridge, 459–490,
https://doi.org/10.1017/cbo9780511535659.014, 2009.
Bown, F., Rivera, A., Zenteno, P., Bravo, C., and Cawkwell, F.: First
Glacier Inventory and Recent Glacier Variation on Isla Grande de Tierra Del
Fuego and Adjacent Islands in Southern Chile, in: Global Land Ice Measurements
from Space, edited by: Kargel, J., Leonard, G., Bishop, M., Kääb, A., and Raup, B., Springer, Berlin, Heidelberg, 661–674,
https://doi.org/10.1007/978-3-540-79818-7_28, 2014.
Bown, F., Rivera, A., Peȩtlicki, M., Bravo, C., Oberreuter, J., and Moffat,
C.: Recent ice dynamics and mass balance of Jorge Montt Glacier, Southern
Patagonia Icefield, J. Glaciol., 65, 732–744,
https://doi.org/10.1017/jog.2019.47, 2019.
Braithwaite, R.: Positive degree-day factors for ablation on the Greenland
ice sheet studied by energy-balance modelling, J. Glaciol., 41, 153–160,
https://doi.org/10.3189/S0022143000017846, 1995.
Braun, M. H., Malz, P., Sommer, C., Farías-Barahona, D., Sauter, T.,
Casassa, G., Soruco, A., Skvarca, P., and Seehaus, T. C.: Constraining
glacier elevation and mass changes in South America, Nat. Clim. Change, 9,
130–136, https://doi.org/10.1038/s41558-018-0375-7, 2019.
Bravo, C., Quincey, D. J., Ross, A. N., Rivera, A., Brock, B., Miles, E.,
and Silva, A.: Air Temperature Characteristics, Distribution, and Impact on
Modeled Ablation for the South Patagonia Icefield, J. Geophys. Res.-Atmos., 124,
907–925, https://doi.org/10.1029/2018JD028857, 2019a.
Bravo, C., Bozkurt, D., Gonzalez-Reyes, Á., Quincey, D. J., Ross, A. N.,
Farías-Barahona, D., and Rojas, M.: Assessing snow accumulation
patterns and changes on the Patagonian Icefields, Front. Environ. Sci., 7,
1–18, https://doi.org/10.3389/fenvs.2019.00030, 2019b.
Brock, B., Willis, I., and Sharp, M.: Measurement and parameterization of aerodynamic roughness length variations at Haut Glacier d’Arolla, Switzerland, J. Glaciol., 52, 281–297, https://doi.org/10.3189/172756506781828746, 2006.
Buisán, S. T., Earle, M. E., Collado, J. L., Kochendorfer, J., Alastrué, J., Wolff, M., Smith, C. D., and López-Moreno, J. I.: Assessment of snowfall accumulation underestimation by tipping bucket gauges in the Spanish operational network, Atmos. Meas. Tech., 10, 1079–1091, https://doi.org/10.5194/amt-10-1079-2017, 2017.
Buttstädt, M., Möller, M., Iturraspe, R., and Schneider, C.: Mass balance evolution of Martial Este Glacier, Tierra del Fuego (Argentina) for the period 1960–2099, Adv. Geosci., 22, 117–124, https://doi.org/10.5194/adgeo-22-117-2009, 2009.
Cannon, A. J., Sobie, S. R., and Murdock, T. Q.: Bias correction of GCM
precipitation by quantile mapping: How well do methods preserve changes in
quantiles and extremes?, J. Climate, 28, 6938–6959,
https://doi.org/10.1175/JCLI-D-14-00754.1, 2015.
Carrivick, J. L., Davies, B. J., James, W. H. M., Quincey, D. J., and
Glasser, N. F.: Distributed ice thickness and glacier volume in southern
South America, Global Planet. Change, 146, 122–132,
https://doi.org/10.1016/j.gloplacha.2016.09.010, 2016.
Cogley, J. C., Rasmussen, L. A., Arendt, A. A., Bauder, A., Braithwaite, R.
J., Jansson, P., Kaser, G., Möller, M., Nicholson, M., and Zemp, M.:
Glossary of Glacier Mass Balance and Related Terms, IACS Contrib. No. 2,
2011.
Cullen, N., Mölg, T., Kaser, G., Steffen, K., and Hardy, D.: Energy-balance model validation on the top of Kilimanjaro, Tanzania, using eddy covariance data, Ann. Glaciol., 46, 227–233, https://doi.org/10.3189/172756407782871224, 2007.
Dadic, R., Mott, R., Lehning, M., and Burlando, P.: Parameterization for
wind-induced preferential deposition of snow, Hydrol. Process., 24,
1994–2006, https://doi.org/10.1002/hyp.7776, 2010.
DGA: Metodología de inventario público de glaciares, SDT
No. 447, 2022. Ministerio de Obras Públicas, Dirección
General de Aguas Unidad de Glaciología y Nieves, realizado por:
Casassa, G., Espinoza, A., Segovia, A., and Huenante, J., 2022.
Dussaillant, I., Berthier, E., Brun, F., Masiokas, M., Hugonnet, R., Favier,
V., Rabatel, A., Pitte, P., and Ruiz, L.: Two decades of glacier mass loss
along the Andes, Nat. Geosci., 12, 802–808,
https://doi.org/10.1038/s41561-019-0432-5, 2019.
Farinotti, D., Huss, M., Fürst, J. J., Landmann, J., Machguth, H.,
Maussion, F., and Pandit, A.: A consensus estimate for the ice thickness
distribution of all glaciers on Earth, Nat. Geosci., 12, 168–173,
https://doi.org/10.1038/s41561-019-0300-3, 2019.
Gabbi, J., Carenzo, M., Pellicciotti, F., Bauder, A., and Funk, M.: A
comparison of empirical and physically based glacier surface melt models for
long-term simulations of glacier response, J. Glaciol., 60, 1199–1207,
https://doi.org/10.3189/2014JoG14J011, 2014.
Gacitúa, G., Schneider, C., and Casassa, G.: Ice thickness observations in Glacier Schiaparelli, Cordillera Darwin, Chile, PANGAEA [data set], https://doi.org/10.1594/PANGAEA.919331, 2020.
Gacitúa, G., Schneider, C., Arigony, J., González, I., Jaña, R., and Casassa, G.: First ice thickness measurements in Tierra del Fuego at Schiaparelli Glacier, Chile, Earth Syst. Sci. Data, 13, 231–236, https://doi.org/10.5194/essd-13-231-2021, 2021.
Gardner, A. S. and Sharp, M.: Sensitivity of net mass-balance estimates to
near-surface temperature lapse rates when employing the degree-day method to
estimate glacier melt, Ann. Glaciol., 50, 80–86,
https://doi.org/10.3189/172756409787769663, 2009.
Gardner, A. S., Sharp, M. J., Koerner, R. M., Labine, C., Boon, S.,
Marshall, S. J., Burgess, D. O., and Lewis, D.: Near-surface temperature
lapse rates over arctic glaciers and their implications for temperature
downscaling, J. Climate, 22, 4281–4298,
https://doi.org/10.1175/2009JCLI2845.1, 2009.
Garreaud, R. D., Vuille, M., Compagnucci, R., and Marengo, J.: Present-day
South American climate, Palaeogeogr. Palaeocl., 281, 180–195,
https://doi.org/10.1016/j.palaeo.2007.10.032, 2009.
Glasser, N. F., Harrison, S., Winchester, V., and Aniya, M.: Late
Pleistocene and Holocene palaeoclimate and glacier fluctuations in
Patagonia, Global Planet. Change, 43, 79–101,
https://doi.org/10.1016/j.gloplacha.2004.03.002, 2004.
Groos, A. R., Mayer, C., Smiraglia, C., Diolaiuti, G., and Lambrecht, A.: A
first attempt to model region-wide glacier surface mass balances in the
Karakoram: Findings and future challenges,
Geogr. Fis. Din. Quat., 40, 137–159, https://doi.org/10.4461/GFDQ.2017.40.10, 2017.
Gudmundsson, L., Bremnes, J. B., Haugen, J. E., and Engen-Skaugen, T.: Technical Note: Downscaling RCM precipitation to the station scale using statistical transformations – a comparison of methods, Hydrol. Earth Syst. Sci., 16, 3383–3390, https://doi.org/10.5194/hess-16-3383-2012, 2012.
Gurgiser, W., Molg, T., Nicholson, L., and Kaser, G.: Mass-balance model
parameter transferability on a tropical glacier, J. Glaciol., 59, 845–858,
https://doi.org/10.3189/2013JoG12J226, 2013.
Hanna, E., Mernild, S., de Villiers, S., and Yde, J.: Surface air
temperature variations and lapse rates on Olivares Gamma Glacier, Rio
Olivares Basin, Central Chile, from a novel meteorological sensor network,
Meteorol. Appl., 2017, 12–14, 2017.
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A.,
Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D.,
Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P.,
Biavati, G., Bidlot, J., Bonavita, M., de Chiara, G., Dahlgren, P., Dee, D.,
Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer,
A., Haimberger, L., Healy, S., Hogan, R. J., Hólm, E., Janisková,
M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., de Rosnay,
P., Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J. N.: The ERA5
global reanalysis, Q. J. Roy. Meteor. Soc., 146, 1999–2049,
https://doi.org/10.1002/qj.3803, 2020.
Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D., and Thépaut, J. N.: ERA5 hourly data on single levels from 1940 to present, Copernicus Climate Change Service (C3S) Climate Data Store (CDS) [data set], https://doi.org/10.24381/cds.adbb2d47, 2023a.
Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D., and Thépaut, J. N.: ERA5 hourly data on pressure levels from 1940 to present, Copernicus Climate Change Service (C3S) Climate Data Store (CDS) [data set], https://doi.org/10.24381/cds.bd0915c6, 2023b.
Heynen, M., Miles, E., Ragettli, S., Buri, P., Immerzeel, W. W., and
Pellicciotti, F.: Air temperature variability in a high-elevation Himalayan
catchment, Ann. Glaciol., 57, 212–222, https://doi.org/10.3189/2016AoG71A076,
2016.
Hock, R.: A distributed temperature-index ice- and snowmelt model including
potential direct solar radiation, J. Glaciol., 45, 101–111, 1999.
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.
Huintjes, E., Sauter, T., Schroter, B., Maussion, F., Yang, W.,
Kropaček, J., Buchroithner, M., Scherer, D., Kang, S., and Schneider,
C.: Evaluation of a Coupled Snow and Energy Balance Model for Zhadang
Glacier, Tibetan Plateau, Using Glaciological Measurements and Time-Lapse
Photography, Arct. Antarct. Alp. Res., 47, 573–590,
https://doi.org/10.1657/AAAR0014-073, 2015.
Jaña, R., Gonzalez, I., Arigony-Neto, J., Izaguirre, E., Schneider, C., Weidemann, S. S., and Temme, F.: Ablation Stake Measurements at Schiaparelli Glacier, Cordillera Darwin, Chile, 2013–2019, PANGAEA [data set], https://doi.org/10.1594/PANGAEA.958668, 2023.
Jarosch, A. H., Anslow, F. S., and Clarke, G. K. C.: High-resolution
precipitation and temperature downscaling for glacier models, Clim. Dynam.,
38, 391–409, https://doi.org/10.1007/s00382-010-0949-1, 2012.
Jiang, Q. and Smith, R. B.: Cloud timescales and orographic precipitation,
J. Atmos. Sci., 60, 1543–1559, https://doi.org/10.1175/2995.1, 2003.
Koch, J.: Little Ice Age and recent glacier advances in the Cordillera
Darwin, Tierra del Fuego, Chile, Anales del Instituto de la Patagonia, 43,
127–136, https://doi.org/10.4067/s0718-686x2015000100011, 2015.
Koppes, M., Hallet, B., and Anderson, J.: Synchronous acceleration of ice
loss and glacial erosion, Glaciar olocenli, chilean Tierra del Fuego, J. Glaciol., 55, 207–220, https://doi.org/10.3189/002214309788608796, 2009.
Lehning, M., Löwe, H., Ryser, M., and Raderschall, N.: Inhomogeneous
precipitation distribution and snow transport in steep terrain, Water Resour.
Res., 44, 1–19, https://doi.org/10.1029/2007WR006545, 2008.
Lenaerts, J. T. M., van den Broeke, M. R., van Wessem, J. M., van de Berg,
W. J., van Meijgaard, E., van Ulft, L. H., and Schaefer, M.: Extreme
precipitation and climate grolocenen patagonia revealed by high-resolution
regional atmospheric climate modeling, J. Climate, 27, 4607–4621,
https://doi.org/10.1175/JCLI-D-13-00579.1, 2014.
Lopez, P., Chevallier, P., Favier, V., Pouyaud, B., Ordenes, F., and
Oerlemans, J.: A regional view of fluctuations in glacier length in southern
South America, Global Planet. Change, 71, 85–108,
https://doi.org/10.1016/j.gloplacha.2009.12.009, 2010.
MacDougall, A. H. and Flowers, G. E.: Spatial and temporal transferability
of a distributed energy-balance glacier melt model, J. Climate, 24,
1480–1498, https://doi.org/10.1175/2010JCLI3821.1, 2011.
Machguth, H., Paul, F., Hoelzle, M., and Haeberli, W.: Distributed glacier mass-balance modelling as an important component of modern multi-level glacier monitoring, Ann. Glaciol., 43, 335–343, https://doi.org/10.3189/172756406781812285, 2006.
Masiokas, M. H., Rivera, A., Espizua, L. E., Villalba, R., Delgado, S., and
Aravena, J. C.: Glacier fluctuations in extratropical South America during
the past 1000 years, Palaeogeogr. Palaeocl., 281, 242–268,
https://doi.org/10.1016/j.palaeo.2009.08.006, 2009.
Meier, W. J. H., Grießinger, J., Hochreuther, P., and Braun, M. H.: An
updated multi-temporal glacier inventoolocenen patagonian andes with changes
between the little ice age and 2016, Front. Earth Sci., 6, 62,
https://doi.org/10.3389/feart.2018.00062, 2018.
Meier, W. J. H., Aravena, J. C., Grießinger, J., Hochreuther, P.,
Soto-Rogel, P., Zhu, H., de Pol-Holz, R., Schneider, C., and Braun,
Molocenete holocene glacial fluctuations of Schiaparelli Glacier at Monte
Sarmiento Massif, Tierra del Fuego (54∘ 24′s),
Geosciences, 9, 340, https://doi.org/10.3390/geosciences9080340, 2019.
Melkonian, A. K., Willis, M. J., Pritchard, M. E., Rivera, A., Bown, F., and Bernstein, S. A.: Satellite-derived volume loss rates and glacier speeds for the Cordillera Darwin Icefield, Chile, The Cryosphere, 7, 823–839, https://doi.org/10.5194/tc-7-823-2013, 2013.
Millan, R., Mouginot, J., Rabatel, A., and Morlighem, M.: Ice velocity and
thickness of the world's glaciers, Nat. Geosci., 15, 124–129,
https://doi.org/10.1038/s41561-021-00885-z, 2022.
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.
Mölg, T., Cullen, N. J., Hardy, D. R., Winkler, M., and Kaser, G.:
Quantifying climate change in the tropical midtroposphere over East Africa
from glacier shrinkage on Kilimanjaro, J. Climate, 22, 4162–4181,
https://doi.org/10.1175/2009JCLI2954.1, 2009a.
Mölg, T., Cullen, N. J., and Kaser, G.: Solar radiation, cloudiness and
longwave radiation over low-latitude glaciers: Implications for mass-balance
modelling, J. Glaciol., 55, 292–302,
https://doi.org/10.3189/002214309788608822, 2009b.
Mölg, T., Maussion, F., Yang, W., and Scherer, D.: The footprint of Asian monsoon dynamics in the mass and energy balance of a Tibetan glacier, The Cryosphere, 6, 1445–1461, https://doi.org/10.5194/tc-6-1445-2012, 2012.
Mott, R., Faure, F., Lehning, M., Löwe, H., Hynek, B., Michlmayer, G.,
Prokop, A., and Schöner, W.: Simulation of seasonal snow-cover
distribution for glacierized sites on Sonnblick, Austria, with the Alpine3D
model, Ann. Glaciol., 49, 155–160,
https://doi.org/10.3189/172756408787814924, 2008.
Mutz, S. G. and Aschauer, J.: Empirical glacier mass-balance models for
South America, J. Glaciol., 68, 1–15, https://doi.org/10.1017/jog.2022.6, 2022.
Netto, G., Arigony-Neto, J., Jaña, R., Gonzalez, On, Schneider, C., and Temme, F.: Ablation Measurements at Schiaparelli Glacier, Cordillera Darwin, Chile, with an automatic ablation sensor, 2016–2017, PANGAEA [data set], https://doi.org/10.1594/PANGAEA.958623, 2023.
Oerlemans, J.: Glaciers and climate change, A.A. Balkema Publishers, Dordrecht, 2001.
Oerlemans, J. and Knap, W. H.: A 1 year record of global radiation and
albedo in the ablation zone of Morteratschgletscher, Switzerland, J. Glaciol.,
44, 231–238, https://doi.org/10.1017/S0022143000002574, 1998.
Pellicciotti, F., Brock, B., Strasser, U., Burlando, P., Funk, M., and
Corripio, J.: An enhanced temperature-index glacier melt model including the
shortwave radiation balance: Development and testing for Haut Glacier
d'Arolla, Switzerland, J. Glaciol., 51, 573–587,
https://doi.org/10.3189/172756505781829124, 2005.
Pellicciotti, F., Helbing, J., Rivera, A., Favier, V., Corripio, J., Araos,
J., Sicart, J.-E., and Carenzo, M.: A study of the energy balance and melt
regime on Juncal Norte Glacier, semi-arid Andes of central Chile, using melt
models of different complexity, Hydrol. Process., 22, 3980–3997, https://doi.org/10.1002/hyp.7085, 2008.
Petersen, L., Pellicciotti, F., Juszak, I., Carenzo, M., and Brock, B.:
Suitability of a constant air temperature lapse rate over an Alpine glacier:
testing the Greuell and Böhm model as an alternative, Ann. Glaciol., 54,
120–130, https://doi.org/10.3189/2013AoG63A477, 2013.
Pollard, D., Chang, W., Haran, M., Applegate, P., and DeConto, R.: Large ensemble modeling of the last deglacial retreat of the West Antarctic Ice Sheet: comparison of simple and advanced statistical techniques, Geosci. Model Dev., 9, 1697–1723, https://doi.org/10.5194/gmd-9-1697-2016, 2016.
Porter, C. and Santana, A.: Rapid 20th Century Retreat of Ventisquero
Marinelli in the Cordillera Darwin Icefield, Anales del Instituto de la
Patagonia, 31, 17–26, 2003.
Rada, C. and Martinez, N.: UNCHARTED: Cordillera Darwin v0.98,
figshare, https://doi.org/10.6084/m9.figshare.19246140.v1, 2022.
Rasmussen, R., Baker, B., Kochendorfer, J., Meyers, T., Landolt, S.,
Fischer, A.P., Black, J., Thériault, J.M., Kucera, P., Gochis, D.,
Smith, C., Nitu, R., Hall, M., Ikeda, K., and Gutmann, E.: How Well Are We
Measuring Snow: The NOAA/FAA/NCAR Winter Precipitation Test Bed, B. Am.
Meteorol. Soc., 93, 811–829, https://doi.org/10.1175/BAMS-D-11-00052.1, 2012.
Réveillet, M., Vincent, C., Six, D., and Rabatel, A.: Which empirical
model is best suited to simulate glacier mass balances?, J. Glaciol., 63,
39–54, https://doi.org/10.1017/jog.2016.110, 2017.
Rignot, E., Rivera, A., and Casassa, G.: Contribution of the Patagonia
Icefields of South America to Sea Level Rise, Science, 302, 434–437,
https://doi.org/10.1126/science.1087393, 2003.
Rott, H., Müller, F., Nagler, T., and Floricioiu, D.: The imbalance of glaciers after disintegration of Larsen-B ice shelf, Antarctic Peninsula, The Cryosphere, 5, 125–134, https://doi.org/10.5194/tc-5-125-2011, 2011.
Rounce, D. R., Khurana, T., Short, M. B., Hock, R., Shean, D. E., and Brinkerhoff, D. J.:
Quantifying parameter uncertainty in a largescale glacier evolution model
using Bayesian inference: application to High Mountain Asia, J. Glaciol., 66, 175–187, https://doi.org/10.1017/jog.2019.91, 2020.
Sauter, T.: Revisiting extreme precipitation amounts over southern South America and implications for the Patagonian Icefields, Hydrol. Earth Syst. Sci., 24, 2003–2016, https://doi.org/10.5194/hess-24-2003-2020, 2020.
Sauter, T. and Galos, S. P.: Effects of local advection on the spatial sensible heat flux variation on a mountain glacier, The Cryosphere, 10, 2887–2905, https://doi.org/10.5194/tc-10-2887-2016, 2016.
Sauter, T., Arndt, A., and Schneider, C.: COSIPY v1.3 – an open-source coupled snowpack and ice surface energy and mass balance model, Geosci. Model Dev., 13, 5645–5662, https://doi.org/10.5194/gmd-13-5645-2020, 2020.
Schaefer, M., Machguth, H., Falvey, M., and Casassa, G.: Modeling past and
future surface mass balance of the Northern Patagonia Icefield, J. Geophys.
Res.-Earth, 118, 571–588, https://doi.org/10.1002/jgrf.20038, 2013.
Schaefer, M., Machguth, H., Falvey, M., Casassa, G., and Rignot, E.: Quantifying mass balance processes on the Southern Patagonia Icefield, The Cryosphere, 9, 25–35, https://doi.org/10.5194/tc-9-25-2015, 2015.
Schneider, C., Glaser, M., Kilian, R., Santana, A., Butorovic, N., and
Casassa, G.: Weather Observations Across the Southern Andes at 53∘
S, Phys. Geogr., 24, 97–119, https://doi.org/10.2747/0272-3646.24.2.97, 2003.
Schneider, C., Kilian, R., and Glaser, M.: Energy balance in the ablation
zone during the summer season at the Gran Campo Nevado Ice Cap in the
Southern Andes, Global Planet. Change, 59, 175–188,
https://doi.org/10.1016/j.gloplacha.2006.11.033, 2007.
Schneider, C., Langhamer, L., Weidemann, S. S., and Temme, F.: Meteorological Observations at Schiaparelli Glacier Automatic Weather Station (AWSrock), Cordillera Darwin, Chile, 2015–2020, PANGAEA [data set], https://doi.org/10.1594/PANGAEA.956569, 2023.
Schuler, T. v., Crochet, P., Hock, R., Jackson, M., Barstad, I., and
Jóhannesson, T.: Distribution of snow accumulation on the Svartisen ice
cap, Norway, assessed by a model of orographic precipitation, Hydrol. Process., 22, 3998–4008, https://doi.org/10.1002/hyp.7073, 2008.
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.
Seehaus, T., Cook, A. J., Silva, A. B., and Braun, M.: Changes in glacier dynamics in the northern Antarctic Peninsula since 1985, The Cryosphere, 12, 577–594, https://doi.org/10.5194/tc-12-577-2018, 2018.
Seehaus, T., Malz, P., Sommer, C., Lippl, S., Cochachin, A., and Braun, M.: Changes of the tropical glaciers throughout Peru between 2000 and 2016 – mass balance and area fluctuations, The Cryosphere, 13, 2537–2556, https://doi.org/10.5194/tc-13-2537-2019, 2019.
Shaw, T. E., Brock, B. W., Fyffe, C. L., Pellicciotti, F., Rutter, N., and
Diotri, F.: Air temperature distribution and energy-balance modelling of a
debris-covered glacier, J. Glaciol., 62, 185–198,
https://doi.org/10.1017//jog.2016.31, 2016.
Shen, Y., Shen, Y., Goetz, J., and Brenning, A.: Spatial-temporal variation
of near-surface temperature lapse rates over the Tianshan Mountains, central
Asia, J. Geophys. Res.-Atmos., 121, 14006–14017,
https://doi.org/10.1002/2016JD025711, 2016.
Six, D., Wagnon, P., Sicart, J. E., and Vincent, C.: Meteorological controls
on snow and ice ablation for two contrasting months on Glacier de
Saint-Sorlin, France, Ann. Glaciol., 50, 66–72,
https://doi.org/10.3189/172756409787769537, 2009.
Smith, R. B. and Barstad, I.: A linear theory of orographic precipitation, J. Atmos. Sci., 61, 1377–1391,
https://doi.org/10.1175/1520-0469(2004)061<1377:ALTOOP>2.0.CO;2, 2004.
Smith, R. B. and Evans, J. P.: Orographic precipitation and water vapor
fractionation over the southern Andes, J. Hydrometeorol., 8, 3–19,
https://doi.org/10.1175/JHM555.1, 2007.
Strelin, J. and Iturraspe, R.: Recent evolution and mass balance of
Cordón Martial glaciers, Cordillera Fueguina Oriental, Global Planet. Change, 59, 17–26, https://doi.org/10.1016/j.gloplacha.2006.11.019, 2007.
Strelin, J., Casassa, G., Rosqvist, G., and Holmlund, P.: Holocene
glaciations in the Ema Glacier valley, Monte Sarmiento Massif, Tierra del
Fuego, Palaeogeogr. Palaeocl., 260, 299–314,
https://doi.org/10.1016/j.palaeo.2007.12.002, 2008.
Strozzi, T., Luckman, A., Murray, T., Wegmuller, U., and Werner, C. L.:
Glacier motion estimation using SAR offset-tracking procedures,
IEEE T. Geosci. Remote, 40, 2384–2391, https://doi.org/10.1109/TGRS.2002.805079, 2002.
Stuefer, M., Rott, H., and Skvarca, P.: Glaciar Perito Moreno, Patagonia:
Climate sensitivities and glacier characteristics preceding the 2003/04 and
2005/06 damming events, J. Glaciol., 53, 3–16,
https://doi.org/10.3189/172756507781833848, 2007.
Sommer, C., Malz, P., Seehaus, T. C., Lippl, S., Zemp, M., and Braun, M. H.: Rapid glacier retreat and downwasting throughout the European Alps in the early 21st century, Nat. Commun. 11, 3209, https://doi.org/10.1038/s41467-020-16818-0, 2020.
Temme, F.: positive-deg-day-model v1.0 (v1.0), Zenodo [code], https://doi.org/10.5281/zenodo.8009967, 2023a.
Temme, F.: simplified-energy-balance-model v1.0 (v1.0), Zenodo [code], https://doi.org/10.5281/zenodo.8009978, 2023b.
Temme, F., Turton, J. V., Mölg, T., and Sauter, T.: Flow regimes and
Föhn types characterize the local climate of Southern Patagonia,
Atmosphere, 11, 899, https://doi.org/10.3390/ATMOS11090899, 2020.
Temme, F., Farías-Barahona, D., Seehaus, T., Jaña, R., Arigony-Neto, J., Gonzalez, I., Arndt, A., Sauter, T., Schneider, C., and Fürst, J. J.: Surface mass balance of the Monte Sarmiento Massif (2000–2022), Tierra del Fuego, Chile, Zenodo [data set], https://doi.org/10.5281/zenodo.7798666, 2023.
van Pelt, W. J. J., Oerlemans, J., Reijmer, C. H., Pohjola, V. A., Pettersson, R., and van Angelen, J. H.: Simulating melt, runoff and refreezing on Nordenskiöldbreen, Svalbard, using a coupled snow and energy balance model, The Cryosphere, 6, 641–659, https://doi.org/10.5194/tc-6-641-2012, 2012.
Villalba, R., Lara, A., Boninsegna, J. A., Masiokas, M., Delgado, S.,
Aravena, J. C., Roig, F. A., Schmelter, A., Wolodarsky, A., and Ripalta, A.:
Large-Scale Temperature Changes Across the Southern Andes: 20th-Century
Variations in the Context of the Past 400 Years, in: Climate Variability and Change in High Elevation Regions: Past, Present & Future. Advances in Global Change Research, vol. 15, edited by: Diaz, H. F., Springer, Dordrecht, 177–232,
https://doi.org/10.1007/978-94-015-1252-7_10, 2003.
Warscher, M., Strasser, U., Kraller, G., Marke, T., Franz, H., and
Kunstmann, H.: Performance of complex snow cover descriptions in a
distributed hydrological model system: A case study for the high Alpine
terrain of the Berchtesgaden Alps, Water Resour. Res., 49, 2619–2637,
https://doi.org/10.1002/wrcr.20219, 2013.
Weidemann, S., Sauter, T., Schneider, L., and Schneider, C.: Impact of two
conceptual precipitation downscaling schemes on mass-balance modeling of
Gran Campo Nevado ice cap, Patagonia, J. Glaciol., 59, 1106–1116,
https://doi.org/10.3189/2013JoG13J046, 2013.
Weidemann, S. S., Sauter, T., Malz, P., Jaña, R., Arigony-Neto, J.,
Casassa, G., and Schneider, C.: Glacier mass changes of lake-terminating
grey and tyndall glaciers at the southern patagonia icefield derived from
geodetic observations and energy and mass balance modeling, Front. Earth Sci.,
6, 1–16, https://doi.org/10.3389/feart.2018.00081, 2018a.
Weidemann, S., Sauter, T., Kilian, R., Steger, D., Butorovic, N., and
Schneider, C.: A 17-year Record of Meteorological Observations Across the Gran
Campo Nevado Ice Cap in Southern Patagonia, Chile, Related to Synoptic
Weather Types and Climate Modes, Front. Earth Sci., 6, 53,
https://doi.org/10.3389/feart.2018.00053, 2018b.
Weidemann, S. S., Arigony-Neto, J., Jaña, R., Netto, G., Gonzalez, I.,
Casassa, G., and Schneider, C.: Recent climatic mass balance of the
schiaparelli glacier at the monte sarmiento massif and reconstruction of
little ice age climate by simulating steady-state glacier conditions,
Geosciences, 10, 1–17, https://doi.org/10.3390/geosciences10070272, 2020.
Willis, M. J., Melkonian, A. K., Pritchard, M. E., and Rivera, A.: Ice loss
from the Southern Patagonian Ice Field, South America, between 2000 and
2012, Geophys. Res. Lett., 39, 1–6, https://doi.org/10.1029/2012GL053136,
2012.
Winstral, A. and Marks, D.: Simulating wind fields and snow redistribution
using terrain-based parameters to model snow accumulation and melt over a
semi-arid mountain catchment, Hydrol. Process., 16, 3585–3603,
https://doi.org/10.1002/hyp.1238, 2002.
Ziemen, F. A., Hock, R., Aschwanden, A., Khroulev, C., Kienholz, C.,
Melkonian, A., and Zhang, J.: Modeling the evolution of the Juneau Icefield
between 1971 and 2100 using the Parallel Ice Sheet Model (PISM), J. Glaciol.,
62, 199–214, https://doi.org/10.1017/jog.2016.13, 2016.
Zolles, T., Maussion, F., Galos, S. P., Gurgiser, W., and Nicholson, L.: Robust uncertainty assessment of the spatio-temporal transferability of glacier mass and energy balance models, The Cryosphere, 13, 469–489, https://doi.org/10.5194/tc-13-469-2019, 2019.
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.
Calibration of surface mass balance (SMB) models on regional scales is challenging. We...
