Articles | Volume 14, issue 11
https://doi.org/10.5194/tc-14-4063-2020
© Author(s) 2020. 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-14-4063-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
16 Nov 2020
Research article |
| 16 Nov 2020
| 16 Nov 2020
Small-scale spatial variability in bare-ice reflectance at Jamtalferner, Austria
Institute for Interdisciplinary Mountain Research, Austrian Academy of
Sciences, Technikerstraße, 21a, ICT, 6020 Innsbruck, Austria
Lucia Felbauer
Institute for Interdisciplinary Mountain Research, Austrian Academy of
Sciences, Technikerstraße, 21a, ICT, 6020 Innsbruck, Austria
Gabriele Schwaizer
ENVEO IT GmbH, Fürstenweg 176, 6020 Innsbruck, Austria
Andrea Fischer
Institute for Interdisciplinary Mountain Research, Austrian Academy of
Sciences, Technikerstraße, 21a, ICT, 6020 Innsbruck, Austria
Related authors
Lea Hartl, Federico Covi, Martin Stocker-Waldhuber, Anna Baldo, Davide Fugazza, Biagio Di Mauro, and Kathrin Naegeli
The Cryosphere, 19, 3329–3353, https://doi.org/10.5194/tc-19-3329-2025, https://doi.org/10.5194/tc-19-3329-2025, 2025
Short summary
Short summary
Glacier albedo determines how much solar radiation is absorbed by the glacier surface and is a key driver of glacier melt. Alpine glaciers are losing their snow and firn cover, and the underlying darker ice is becoming exposed. This means that more solar radiation is absorbed by the ice, which leads to increased melt. To quantify these processes, we explore data from a high-elevation, on-ice weather station that measures albedo and combine this information with satellite imagery.
Lea Hartl, Patrick Schmitt, Lilian Schuster, Kay Helfricht, Jakob Abermann, and Fabien Maussion
The Cryosphere, 19, 1431–1452, https://doi.org/10.5194/tc-19-1431-2025, https://doi.org/10.5194/tc-19-1431-2025, 2025
Short summary
Short summary
We use regional observations of glacier area and volume change to inform glacier evolution modeling in the Ötztal and Stubai range (Austrian Alps) until 2100 in different climate scenarios. Glaciers in the region lost 23 % of their volume between 2006 and 2017. Under current warming trajectories, glacier loss in the region is expected to be near-total by 2075. We show that integrating regional calibration and validation data in glacier models is important to improve confidence in projections.
Florina Roana Schalamon, Sebastian Scher, Andreas Trügler, Lea Hartl, Wolfgang Schöner, and Jakob Abermann
EGUsphere, https://doi.org/10.5194/egusphere-2024-4060, https://doi.org/10.5194/egusphere-2024-4060, 2025
Short summary
Short summary
Atmospheric patterns influence the air temperature in Greenland. We investigate two warming periods, from 1922–1932 and 1993–2007, both showing similar temperature increases. Using a neural network-based clustering method, we defined predominant atmospheric patterns for further analysis. Our findings reveal that while the connection between these patterns and local air temperature remains stable, the distribution of patterns changes between the warming periods and the full period (1900–2015).
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.
Lea Hartl, Thomas Zieher, Magnus Bremer, Martin Stocker-Waldhuber, Vivien Zahs, Bernhard Höfle, Christoph Klug, and Alessandro Cicoira
Earth Surf. Dynam., 11, 117–147, https://doi.org/10.5194/esurf-11-117-2023, https://doi.org/10.5194/esurf-11-117-2023, 2023
Short summary
Short summary
The rock glacier in Äußeres Hochebenkar (Austria) moved faster in 2021–2022 than it has in about 70 years of monitoring. It is currently destabilizing. Using a combination of different data types and methods, we show that there have been two cycles of destabilization at Hochebenkar and provide a detailed analysis of velocity and surface changes. Because our time series are very long and show repeated destabilization, this helps us better understand the processes of rock glacier destabilization.
Lea Hartl, Federico Covi, Martin Stocker-Waldhuber, Anna Baldo, Davide Fugazza, Biagio Di Mauro, and Kathrin Naegeli
The Cryosphere, 19, 3329–3353, https://doi.org/10.5194/tc-19-3329-2025, https://doi.org/10.5194/tc-19-3329-2025, 2025
Short summary
Short summary
Glacier albedo determines how much solar radiation is absorbed by the glacier surface and is a key driver of glacier melt. Alpine glaciers are losing their snow and firn cover, and the underlying darker ice is becoming exposed. This means that more solar radiation is absorbed by the ice, which leads to increased melt. To quantify these processes, we explore data from a high-elevation, on-ice weather station that measures albedo and combine this information with satellite imagery.
David Wachs, Azzurra Spagnesi, Pascal Bohleber, Andrea Fischer, Martin Stocker-Waldhuber, Alexander Junkermann, Carl Kindermann, Linus Langenbacher, Niclas Mandaric, Joshua Marks, Florian Meienburg, Theo Jenk, Markus Oberthaler, and Werner Aeschbach
EGUsphere, https://doi.org/10.5194/egusphere-2025-3681, https://doi.org/10.5194/egusphere-2025-3681, 2025
This preprint is open for discussion and under review for Climate of the Past (CP).
Short summary
Short summary
This study presents an age profile of the summit glacier of Weißseespitze in the Austrian Alps. The ages were obtained by combining 14C dating with the novel atom trap trace analysis for 39Ar. The data was used to constrain glacier age models. The results show that the surface ice is ~400 a old due to recent ice loss. The remaining ice continuously covers ages up to 6000 a. This work underscores the utility of 39Ar dating in glaciology, enabling precise reconstruction of age-depth relationships.
Lea Hartl, Patrick Schmitt, Lilian Schuster, Kay Helfricht, Jakob Abermann, and Fabien Maussion
The Cryosphere, 19, 1431–1452, https://doi.org/10.5194/tc-19-1431-2025, https://doi.org/10.5194/tc-19-1431-2025, 2025
Short summary
Short summary
We use regional observations of glacier area and volume change to inform glacier evolution modeling in the Ötztal and Stubai range (Austrian Alps) until 2100 in different climate scenarios. Glaciers in the region lost 23 % of their volume between 2006 and 2017. Under current warming trajectories, glacier loss in the region is expected to be near-total by 2075. We show that integrating regional calibration and validation data in glacier models is important to improve confidence in projections.
Florina Roana Schalamon, Sebastian Scher, Andreas Trügler, Lea Hartl, Wolfgang Schöner, and Jakob Abermann
EGUsphere, https://doi.org/10.5194/egusphere-2024-4060, https://doi.org/10.5194/egusphere-2024-4060, 2025
Short summary
Short summary
Atmospheric patterns influence the air temperature in Greenland. We investigate two warming periods, from 1922–1932 and 1993–2007, both showing similar temperature increases. Using a neural network-based clustering method, we defined predominant atmospheric patterns for further analysis. Our findings reveal that while the connection between these patterns and local air temperature remains stable, the distribution of patterns changes between the warming periods and the full period (1900–2015).
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.
Azzurra Spagnesi, Pascal Bohleber, Elena Barbaro, Matteo Feltracco, Fabrizio De Blasi, Giuliano Dreossi, Martin Stocker-Waldhuber, Daniela Festi, Jacopo Gabrieli, Andrea Gambaro, Andrea Fischer, and Carlo Barbante
EGUsphere, https://doi.org/10.5194/egusphere-2023-1625, https://doi.org/10.5194/egusphere-2023-1625, 2023
Preprint archived
Short summary
Short summary
We present new data from a 10 m ice core drilled in 2019 and a 8.4 m parallel ice core drilled in 2021 at the summit of Weißseespitze glacier. In a new combination of proxies, we discuss profiles of stable water isotopes, major ion chemistry as well as a full profile of microcharcoal and levoglucosan. We find that the chemical and isotopic signals are preserved, despite the ongoing surface mass loss. This is not be to expected considering what has been found at other glaciers at similar locations.
Lea Hartl, Thomas Zieher, Magnus Bremer, Martin Stocker-Waldhuber, Vivien Zahs, Bernhard Höfle, Christoph Klug, and Alessandro Cicoira
Earth Surf. Dynam., 11, 117–147, https://doi.org/10.5194/esurf-11-117-2023, https://doi.org/10.5194/esurf-11-117-2023, 2023
Short summary
Short summary
The rock glacier in Äußeres Hochebenkar (Austria) moved faster in 2021–2022 than it has in about 70 years of monitoring. It is currently destabilizing. Using a combination of different data types and methods, we show that there have been two cycles of destabilization at Hochebenkar and provide a detailed analysis of velocity and surface changes. Because our time series are very long and show repeated destabilization, this helps us better understand the processes of rock glacier destabilization.
Andrea Fischer, Gabriele Schwaizer, Bernd Seiser, Kay Helfricht, and Martin Stocker-Waldhuber
The Cryosphere, 15, 4637–4654, https://doi.org/10.5194/tc-15-4637-2021, https://doi.org/10.5194/tc-15-4637-2021, 2021
Short summary
Short summary
Eastern Alpine glaciers have been receding since the Little Ice Age maximum, but until now the majority of glacier margins could be delineated unambiguously. Today the outlines of totally debris-covered glacier ice are fuzzy and raise the discussion if these features are still glaciers. We investigated the fate of glacier remnants with high-resolution elevation models, analyzing also thickness changes in buried ice. In the past 13 years, the 46 glaciers of Silvretta lost one-third of their area.
Cited articles
Alexander, P. M., Tedesco, M., Fettweis, X., van de Wal, R. S. W., Smeets, C. J. P. P., and van den Broeke, M. R.: Assessing spatio-temporal variability and trends in modelled and measured Greenland Ice Sheet albedo (2000–2013), The Cryosphere, 8, 2293–2312, https://doi.org/10.5194/tc-8-2293-2014, 2014.
ASD Inc.: FieldSpec® HandHeld2™ Spectroradiometer
User Manual, available at:
https://www.malvernpanalytical.com/en/support/product-support/asd-range/fieldspec-range/handheld-2-hand-held-vnir-spectroradiometer#manuals,
last access: 22 September 2020.
Azzoni, R. S., Senese, A., Zerboni, A., Maugeri, M., Smiraglia, C., and Diolaiuti, G. A.: Estimating ice albedo from fine debris cover quantified by a semi-automatic method: the case study of Forni Glacier, Italian Alps, The Cryosphere, 10, 665–679, https://doi.org/10.5194/tc-10-665-2016, 2016.
Box, J. E., Fettweis, X., Stroeve, J. C., Tedesco, M., Hall, D. K., and Steffen, K.: Greenland ice sheet albedo feedback: thermodynamics and atmospheric drivers, The Cryosphere, 6, 821–839, https://doi.org/10.5194/tc-6-821-2012, 2012.
Box J. E., van As D., and Steffen, K.: Greenland, Canadian and Icelandic
land-ice albedo grids (2000–2016), Geological Survey of Denmark and
Greenland Bulletin, 38, 53–56, 2017.
Brun, F., Dumont, M., Wagnon, P., Berthier, E., Azam, M. F., Shea, J. M., Sirguey, P., Rabatel, A., and Ramanathan, Al.: Seasonal changes in surface albedo of Himalayan glaciers from MODIS data and links with the annual mass balance, The Cryosphere, 9, 341–355, https://doi.org/10.5194/tc-9-341-2015, 2015.
Charalampidis, C., Fischer, A., Kuhn, M., Lambrecht, A., Mayer, C.,
Thomaidis, K., and Weber, M.: Mass-budget anomalies and geometry signals of
three Austrian glaciers, Front. Earth Sci., 6, 218, https://doi.org/10.3389/feart.2018.00218, 2018.
Claverie, M., Ju, J., Masek, J. G., Dungan, J. L., Vermote, E. F., Roger, J. C.,
Skakun, S. V., and Justice, C.: The Harmonized Landsat and Sentinel-2 surface
reflectance data set, Remote Sens. Environ., 219, 145–161, 2018.
Cook, J. M., Hodson, A. J., and Irvine-Fynn, T. D.: Supraglacial weathering
crust dynamics inferred from cryoconite hole hydrology, Hydrol.
Proc., 30, 433–446, 2016.
Di Mauro, B., Baccolo, G., Garzonio, R., Giardino, C., Massabò, D., Piazzalunga, A., Rossini, M., and Colombo, R.: Impact of impurities and cryoconite on the optical properties of the Morteratsch Glacier (Swiss Alps), The Cryosphere, 11, 2393–2409, https://doi.org/10.5194/tc-11-2393-2017, 2017.
Di Mauro, B., Garzonio, R., Baccolo, G., Franzetti, A., Pittino, F., Leoni,
B., Remias, D., Colombo, R., and Rossini, M.: Glacier algae foster ice-albedo
feedback in the European Alps, Sci. Rep., 10, 1–9, 2020.
Dirmhirn, I. and Trojer, E.: Albedountersuchungen auf dem Hintereisferner,
Arch. Meteor. Geophy. B, 6,
400–416, 1955.
Dumont, M., Brun, E., Picard, G., Michou, M., Libois, Q., Petit, J. R.,
Geyer, S., and Josse, B.: Contribution of light-absorbing impurities in snow
to Greenland's darkening since 2009, Nat. Geosci., 7, 509–512, 2014.
Fischer, A.: Comparison of direct and geodetic mass balances on a multi-annual time scale, The Cryosphere, 5, 107–124, https://doi.org/10.5194/tc-5-107-2011, 2011.
Fischer, A., Helfricht, K., Wiesenegger, H., Hartl, L., Seiser, B., and
Stocker-Waldhuber, M.: What Future for Mountain Glaciers?
Insights and Implications From Long-Term Monitoring in the Austrian Alps, chap. 9,
in: Developments in Earth Surface Processes, edited by: Greenwood, G. B.
and Shroder, J. F., Elsevier, 21, 325–382, 2016.
Fischer, A., Markl, G., and Kuhn, M.: Glacier mass balances and elevation
zones of Jamtalferner, Silvretta, Austria, 1988/1989 to 2016/2017, Institut
für Interdisziplinäre Gebirgsforschung der Österreichischen
Akademie der Wissenschaften, Innsbruck, PANGAEA, https://doi.org/10.1594/PANGAEA.818772, 2016.
Fischer, A., Fickert, T., Schwaizer, G., Patzelt, G., and Groß, G.:
Vegetation dynamics in Alpine glacier forelands tackled from space,
Sci. Rep., 9, 1–13, 2019.
Gabbi, J., Huss, M., Bauder, A., Cao, F., and Schwikowski, M.: The impact of Saharan dust and black carbon on albedo and long-term mass balance of an Alpine glacier, The Cryosphere, 9, 1385–1400, https://doi.org/10.5194/tc-9-1385-2015, 2015.
Gardner, A. S. and Sharp, M. J.: A review of snow and ice albedo and the
development of a new physically based broadband albedo parameterization,
J. Geophys. Res.-Earth Surf., 115, F01009, https://doi.org/10.1029/2009JF001444, 2010.
GeoPandas developers: GeoPandas 0.8.0, available at: https://geopandas.org/ (last access: 2020),
2013–2019.
Gillies, S. and others: Rasterio: Geospatial raster i/o for Python
programmers, Mapbox, available at: https://github.com/mapbox/rasterio (last access: 2020), 2013.
Gorelick, N., Hancher, M., Dixon, M., Ilyushchenko, S., Thau, D., and Moore,
R.: Google Earth Engine: Planetary-scale geospatial analysis for everyone,
Remote Sens. Environ., 202, 18–27, 2017.
Greuell, W. and de Wildt, M. D. R.: Anisotropic reflection by melting glacier
ice: Measurements and parametrizations in Landsat TM bands 2 and 4, Remote
Sens. Environ., 70, 265–277, 1999.
Hall, D. K., Chang, A. T. C., Foster, J. L., Benson, C. S., and Kovalick, W.
M.: Comparison of in situ and Landsat derived reflectance of Alaskan
glaciers, Remote Sens. Environ., 28, 23–31, 1989.
Hall, D. K., Bindschadler, R. A., Foster, J. L., Chang, A. T. C., and
Siddalingaiah, H.: Comparison of in situ and satellite-derived reflectances
of Forbindels Glacier, Greenland, Remote Sensing, 11, 493–504, 1990.
Hartl, L., Felbauer, L., Schwaizer, G., Fischer, A.: Spectral reflectance of Jamtalferner ablation zone, PANGAEA, https://doi.org/10.1594/PANGAEA.915932, 2020.
Henderson-Sellers, A. and Wilson, M. F.: Surface albedo data for climatic
modeling, Rev. Geophys., 21, 1743–1778, 1983.
Hendriksa, J., Pellikkaa, P., and Peltoniemib, J.: Estimation of anisotropic radiance
from a glacier surface-Ground based spectrometer measurements and
satellite-derived reflectances, in: Proceedings, 30th International Symposium
on Remote Sensing of Environment: Information for Risk Management and
Sustainable Development, Honolulu, Hawaii, 10–14 November 2003.
Hoinkes, H. and Wendler, G.: Der Anteil der Strahlung an der Ablation von
Hintereis-und Kesselwandferner (Ötztaler Alpen, Tirol) im Sommer 1958,
Arch. Meteor. Geophy. B,
16, 195–236, 1968.
Hunter, J. D.: Matplotlib: A 2D Graphics Environment, Comput. Sci.
Eng., 9, 90–95, 2007.
Jaffé, A.: Über Strahlungseigenschaften des Gletschereises, Arch. Meteor. Geophy. B, 10, 376–395, 1960.
Kääb, A., Winsvold, S. H., Altena, B., Nuth, C., Nagler, T., and
Wuite, J.: Glacier remote sensing using Sentinel-2. part I: Radiometric and
geometric performance, and application to ice velocity, Remote Sens.,
8, 598, https://doi.org/10.3390/rs8070598, 2016.
Klok, E. L., Greuell, W., and Oerlemans, J.: Temporal and spatial variation of
the surface albedo of Morteratschgletscher, Switzerland, as derived from 12
Landsat images, J. Glaciol., 49, 491–502, 2003.
Knap, W. H., Brock, B. W., Oerlemans, J., and Willis, I. C.: Comparison of
Landsat TM-derived and ground-based albedos of Haut Glacier d'Arolla,
Switzerland, Int. J. Remote Sens., 20, 3293–3310,
1999.
Koelemeijer, R., Oerlemans, J., and Tjemkes, S.: Surface reflectance of
Hintereisferner, Austria, from Landsat 5 TM imagery, Ann. Glaciol.,
17, 17–22, 1993.
Lee, Y.: SpecDAL Reference, available at: https://specdal.readthedocs.io/en/latest/ (last access: September 2019), 2017.
Li, Z., Erb, A., Sun, Q., Liu, Y., Shuai, Y., Wang, Z., Boucher, P., and
Schaaf, C.: Preliminary assessment of 20-m surface albedo retrievals from
sentinel-2A surface reflectance and MODIS/VIIRS surface anisotropy measures,
Remote Sens. Environ., 217, 352–365, 2018.
Malinka, A., Zege, E., Heygster, G., and Istomina, L.: Reflective properties of white sea ice and snow, The Cryosphere, 10, 2541–2557, https://doi.org/10.5194/tc-10-2541-2016, 2016.
Main-Knorn, M., Pflug, B., Louis, J., Debaecker, V., Müller-Wilm, U.,
and Gascon, F.: Sen2Cor for Sentinel-2, in: Image and Signal Processing for
Remote Sensing XXIII, International Society for Optics and Photonics,
Warsaw, Poland, 11–13 September 2017, 1042704, 2017.
McKinney W.: Data structures for statistical computing in python, in:
Proceedings of the 9th Python in Science Conference 2010 Jun 28, Vol. 445,
51–56, 2010.
Nicholson, L. and Benn, D. I.: Properties of natural supraglacial debris in
relation to modelling sub-debris ice ablation, Earth Surf. Proc.
Land., 38, 490–501, 2012.
Ming, J., Du, Z., Xiao, C., Xu, X., and Zhang, D.: Darkening of the
mid-Himalaya glaciers since 2000 and the potential causes, Environ.
Res. Lett., 7, 014021, https://doi.org/10.1088/1748-9326/7/1/014021, 2012.
Ming, J., Wang, Y., Du, Z., Zhang, T., Guo, W., Xiao, C., Xu, X., Ding, M.,
Zhang, D., and Yang, W.: Widespread albedo decreasing and induced melting of
Himalayan snow and ice in the early 21st century, PLoS One, 10, e0126235, https://doi.org/10.1371/journal.pone.0126235,
2015.
Moller, M. and Moller, R.: Modeling glacier-surface albedo across Svalbard
for the 1979–2015 period: The HiRSvaC500-a data set, J. Adv. Model. Earth
Sy., 9, 404–422, 2017.
Naegeli, K., Damm, A., Huss, M., Schaepman, M., and Hoelzle, M.: Imaging
spectroscopy to assess the composition of ice surface materials and their
impact on glacier mass balance, Remote Sens. Environ., 168, 388–402,
2015.
Naegeli, K. and Huss, M.: Mass balance sensitivity of mountain glaciers to
changes in bare-ice albedo, Ann. Glaciol., 58, 119–129, 2017.
Naegeli, K., Damm, A., Huss, M., Wulf, H., Schaepman, M., and Hoelzle, M.:
Cross-Comparison of albedo products for glacier surfaces derived from
airborne and satellite (Sentinel-2 and Landsat 8) optical data, Remote
Sensing, 9, 110, https://doi.org/10.3390/rs9020110, 2017.
Naegeli, K., Huss, M., and Hoelzle, M.: Change detection of bare-ice albedo in the Swiss Alps, The Cryosphere, 13, 397–412, https://doi.org/10.5194/tc-13-397-2019, 2019.
Nicholson, L. and Benn, D. I.: Calculating ice melt beneath a debris layer using meteorological data, J. Glaciol., 52, 463–470, 2006.
Nicholson, L. and Benn, D. I.: Properties of natural supraglacial debris in relation to modelling sub‐debris ice ablation, Earth Surf. Proc. Land., 38, 490–501, 2013.
Nicodemus, F. E., Richmond, J. C., Hsia, J. J., Ginsberg, I. W., and Limperis,
T.: Geometrical considerations and nomenclature for reflectance, Vol. 160,
Washington, DC: US Department of Commerce, National Bureau of Standards,
1977.
Oerlemans, J., Giesen, R. H., and Van den Broeke, M. R.: Retreating alpine
glaciers: increased melt rates due to accumulation of dust (Vadret da
Morteratsch, Switzerland), J. Glaciol., 55, 729–736,
2009.
Painter, T. H., Flanner, M. G., Kaser, G., Marzeion, B., VanCuren, R. A.,
and Abdalati, W.: End of the Little Ice Age in the Alps forced by industrial
black carbon, P. Natl. Acad. Sci. USA, 110,
15216–15221, 2013.
Pandzić, M., Mihajlović, D., Pandzić, J., and Pfeifer, N.:
Assessment of the geometric quality of sentinel-2 data, in: XXIII ISPRS
Congress, Commission I, International Society for
Photogrammetry and Remote Sensing, 41, 489–494, 2016.
Paul, F., Machguth, H., and Kääb, A.: On the impact of glacier
albedo under conditions of extreme glacier melt: the summer of 2003 in the
Alps, EARSeL eProceedings, 4, 139–149, 2005.
Perry, M.: rasterstats, available at: https://pythonhosted.org/rasterstats/index.html (last access: November 2020), 2015.
Qu, B., Ming, J., Kang, S.-C., Zhang, G.-S., Li, Y.-W., Li, C.-D., Zhao, S.-Y., Ji, Z.-M., and Cao, J.-J.: The decreasing albedo of the Zhadang glacier on western Nyainqentanglha and the role of light-absorbing impurities, Atmos. Chem. Phys., 14, 11117–11128, https://doi.org/10.5194/acp-14-11117-2014, 2014.
Richter, R. and Schläpfer, D.: Atmospheric/Topographic Correction for
Satellite Imagery: ATCOR-2/3 UserGuide, DLR IB 565-01/11, Wessling,
Germany, 2011.
Rhodes, B.: PyEphem, available at: https://rhodesmill.org/pyephem/toc.html, last access: 10 November 2020.
Sauberer, F.: Versuche über spektrale Messungen der
Strahlungseigenschaften von Schnee und Eis mit Photoelementen, Meteorol. Z.,
55, 250–255, 1938.
Sauberer, F. and Dirmhirn, I.: Untersuchungen über die
Strahlungsverhältnisse auf den Alpengletschern, Arch. Meteor. Geophy. B, 3, 256–269, 1951.
Sauberer, F. and Dirmhirn, I.: Der Strahlungshaushalt horizontaler
Gletscherflächen auf dem Hohen Sonnblick, Geogr. Ann., 34, 261–290, 1952.
Schaepman-Strub, G., Painter, T., Huber, S., Dangel, S., Schaepman, M. E.,
Martonchik, J., and Berendse, F.: About the importance of the definition of
reflectance quantities-results of case studies, in: Proceedings of the XXth
ISPRS Congress, 361–366, 2004.
Schaepman-Strub, G., Schaepman, M. E., Painter, T. H., Dangel, S., and
Martonchik, J. V.: Reflectance quantities in optical remote
sensing – Definitions and case studies, Remote Sens. Rnviron.,
103, 27–42, 2006.
Shuai, Y., Masek, J. G., Gao, F., and Schaaf, C. B.: An algorithm for the
retrieval of 30-m snow-free albedo from Landsat surface reflectance and
MODIS BRDF, Remote Sens. Environ., 115, 2204–2216, 2011.
Storey, J., Choate, M., and Lee, K.: Landsat 8 Operational Land Imager
on-orbit geometric calibration and performance, Remote Sens., 6,
11127–11152, 2014.
U.S. Geological Survey: Landsat 8 Collection 1 (C1) Land Surface Reflectance
Code (LaSRC) Product Guide Version 3.0, available at:
https://www.usgs.gov/media/files/landsat-8-collection-1-land-surface-reflectance-code-product-guide, last access: 17 September 2020.
van As, D., Fausto, R. S., Colgan, W. T., and Box, J. E.: Darkening of the
Greenland ice sheet due to the melt albedo feedback observed at PROMICE
weather stations, Geological Survey of Denmark and Greenland (GEUS) Bulletin,
28, 69–72, 2013.
Van de Wal, R. S. W., Oerlemans, J., and Van der Hage, J. C.: A study of
ablation variations on the tongue of Hintereisferner, Austrian Alps, J. Glaciol., 38, 319–324, 1992.
Van der Walt, S., Colbert, C., and Varoquaux, G.: The NumPy Array: A
Structure for Efficient Numerical Computation, Comput. Sci.
Eng., 13, 22–30, 2011.
Van Rossum, G. and Drake, F. L.: Python 3 Reference Manual,
CreateSpace, Scotts Valley, CA, USA, 2009.
Vermote, E., Justice, C., Claverie, M., and Franch, B.: Preliminary analysis
of the performance of the Landsat 8/OLI land surface reflectance product,
Remote Sens. Environ., 185, 46–56, 2016.
Winther, J. G.: Landsat TM derived and in situ summer reflectance of
glaciers in Svalbard, Polar Res., 12, 37–55, 1993.
Wu, X., Wen, J., Xiao, Q., You, D., Lin, X., Wu, S., and Zhong, S.: Impacts
and Contributors of Representativeness Errors of In Situ Albedo Measurements
for the Validation of Remote Sensing Products, IEEE T.
Geosci. Remote, 57, 9740–9755, 2019.
Zemp, M., Frey, H., Gärtner-Roer, I., Nussbaumer, S. U., Hoelzle, M.,
Paul, F., Haeberli, W., Denzinger, F., Ahlstrøm, A. P., Anderson, B., and
Bajracharya, S.: Historically unprecedented global glacier decline in the
early 21st century, J. Glaciol., 61, 745–762, 2015.
Zemp, M., Huss, M., Thibert, E., Eckert, N., McNabb, R., Huber, J.,
Barandun, M., Machguth, H., Nussbaumer, S. U., Gärtner-Roer, I., and
Thomson, L.: Global glacier mass changes and their contributions to
sea-level rise from 1961 to 2016, Nature, 568, 382–386, 2019.
Zeng, Q., Cao, M., Feng, X., Liang, F., Chen, X., and Sheng, W.: A study of
spectral reflection characteristics for snow, ice and water in the north of
China, Hydrological applications of remote sensing and remote data
transmission, 145, 451–462, 1984.
Short summary
When glaciers become snow-free in summer, darker glacier ice is exposed. The ice surface is darker than snow and absorbs more radiation, which increases ice melt. We measured how much radiation is reflected at different wavelengths in the ablation zone of Jamtalferner, Austria. Due to impurities and water on the ice surface there are large variations in reflectance. Landsat 8 and Sentinel-2 surface reflectance products do not capture the full range of reflectance found on the glacier.
When glaciers become snow-free in summer, darker glacier ice is exposed. The ice surface is...
