Articles | Volume 17, issue 9
https://doi.org/10.5194/tc-17-3955-2023
© 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-17-3955-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Modeling of surface energy balance for Icelandic glaciers using remote-sensing albedo
Civil and Environmental Engineering, University of Iceland, Hjardarhagi 2–6, Reykjavik 107, Iceland
Department of Research and Development, Landsvirkjun, Reykjavík 107, Iceland
Sigurdur M. Gardarsson
Civil and Environmental Engineering, University of Iceland, Hjardarhagi 2–6, Reykjavik 107, Iceland
Finnur Pálsson
Institute of Earth Sciences, University of Iceland, Sturlugata 7, Reykjavík 101, Iceland
Related authors
Darri Eythorsson, Sigurdur M. Gardarsson, Andri Gunnarsson, and Oli Gretar Blondal Sveinsson
The Cryosphere, 17, 51–62, https://doi.org/10.5194/tc-17-51-2023, https://doi.org/10.5194/tc-17-51-2023, 2023
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In this study we researched past and predicted snow conditions in Iceland based on manual snow observations recorded in Iceland and compared these with satellite observations. Future snow conditions were predicted through numerical computer modeling based on climate models. The results showed that average snow depth and snow cover frequency have increased over the historical period but are projected to significantly decrease when projected into the future.
Andri Gunnarsson, Sigurdur M. Gardarsson, Finnur Pálsson, Tómas Jóhannesson, and Óli G. B. Sveinsson
The Cryosphere, 15, 547–570, https://doi.org/10.5194/tc-15-547-2021, https://doi.org/10.5194/tc-15-547-2021, 2021
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Surface albedo quantifies the fraction of the sunlight reflected by the surface of the Earth. During the melt season in the Northern Hemisphere solar energy absorbed by snow- and ice-covered surfaces is mainly controlled by surface albedo. For Icelandic glaciers, air temperature and surface albedo are the dominating factors governing annual variability of glacier surface melt. Satellite data from the MODIS sensor are used to create a data set spanning the glacier melt season.
Andri Gunnarsson, Sigurður M. Garðarsson, and Óli G. B. Sveinsson
Hydrol. Earth Syst. Sci., 23, 3021–3036, https://doi.org/10.5194/hess-23-3021-2019, https://doi.org/10.5194/hess-23-3021-2019, 2019
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In this study a gap-filled snow cover product for Iceland is developed using MODIS satellite data and validated with both in situ observations and alternative remote sensing data sources with good agreement. Information about snow cover extent, duration and changes over time is presented, indicating that snow cover extent has been increasing slightly for the past few years.
Greta Hoe Wells, Þorsteinn Sæmundsson, Finnur Pálsson, Guðfinna Aðalgeirsdóttir, Eyjólfur Magnússon, Reginald L. Hermanns, and Snævarr Guðmundsson
EGUsphere, https://doi.org/10.5194/egusphere-2024-2002, https://doi.org/10.5194/egusphere-2024-2002, 2024
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Glacier retreat elevates the risk of landslides released into proglacial lakes, which can trigger glacial lake outburst floods (GLOFs). This study maps proglacial lake evolution and GLOF hazard scenarios at Fjallsjökull glacier, Iceland. Lake volume increased from 1945–2021 and is estimated to triple over the next century. Three slopes are prone to landslides that may trigger GLOFs. Results will mitigate flood hazard at this popular tourism site and advance GLOF research in Iceland and globally.
Aude Vincent, Clémence Daigre, Ophélie Fischer, Guðfinna Aðalgeirsdóttir, Sophie Violette, Jane Hart, Snævarr Guðmundsson, and Finnur Pálsson
Hydrol. Earth Syst. Sci., 28, 3475–3494, https://doi.org/10.5194/hess-28-3475-2024, https://doi.org/10.5194/hess-28-3475-2024, 2024
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We studied groundwater near outlet glaciers of the main Icelandic ice cap. We acquired new data in the field. Two distinct groundwater compartments and their characteristics are identified. We demonstrate the glacial melt recharge impact on the groundwater dynamic. Knowing groundwater systems in a glacial context is crucial to forecast the evolution under climate change of water resources and of potential flood and landslide hazards.
Alexander H. Jarosch, Eyjólfur Magnússon, Krista Hannesdóttir, Joaquín M. C. Belart, and Finnur Pálsson
The Cryosphere, 18, 2443–2454, https://doi.org/10.5194/tc-18-2443-2024, https://doi.org/10.5194/tc-18-2443-2024, 2024
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Geothermally active regions beneath glaciers not only influence local ice flow as well as the mass balance of glaciers but also control changes of subglacial water reservoirs and possible subsequent glacier lake outburst floods. In Iceland, such outburst floods impose danger to people and infrastructure and are therefore monitored. We present a novel computer-simulation-supported method to estimate the activity of such geothermal areas and to monitor its evolution.
Darri Eythorsson, Sigurdur M. Gardarsson, Andri Gunnarsson, and Oli Gretar Blondal Sveinsson
The Cryosphere, 17, 51–62, https://doi.org/10.5194/tc-17-51-2023, https://doi.org/10.5194/tc-17-51-2023, 2023
Short summary
Short summary
In this study we researched past and predicted snow conditions in Iceland based on manual snow observations recorded in Iceland and compared these with satellite observations. Future snow conditions were predicted through numerical computer modeling based on climate models. The results showed that average snow depth and snow cover frequency have increased over the historical period but are projected to significantly decrease when projected into the future.
Eyjólfur Magnússon, Finnur Pálsson, Magnús T. Gudmundsson, Thórdís Högnadóttir, Cristian Rossi, Thorsteinn Thorsteinsson, Benedikt G. Ófeigsson, Erik Sturkell, and Tómas Jóhannesson
The Cryosphere, 15, 3731–3749, https://doi.org/10.5194/tc-15-3731-2021, https://doi.org/10.5194/tc-15-3731-2021, 2021
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We present a unique insight into the shape and development of a subglacial lake over a 7-year period, using repeated radar survey. The lake collects geothermal meltwater, which is released in semi-regular floods, often referred to as jökulhlaups. The applicability of our survey approach to monitor the water stored in the lake for a better assessment of the potential hazard of jökulhlaups is demonstrated by comparison with independent measurements of released water volume during two jökulhlaups.
Andri Gunnarsson, Sigurdur M. Gardarsson, Finnur Pálsson, Tómas Jóhannesson, and Óli G. B. Sveinsson
The Cryosphere, 15, 547–570, https://doi.org/10.5194/tc-15-547-2021, https://doi.org/10.5194/tc-15-547-2021, 2021
Short summary
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Surface albedo quantifies the fraction of the sunlight reflected by the surface of the Earth. During the melt season in the Northern Hemisphere solar energy absorbed by snow- and ice-covered surfaces is mainly controlled by surface albedo. For Icelandic glaciers, air temperature and surface albedo are the dominating factors governing annual variability of glacier surface melt. Satellite data from the MODIS sensor are used to create a data set spanning the glacier melt season.
Darri Eythorsson, Sigurdur M. Gardarsson, Shahryar K. Ahmad, and Oli Gretar Blondal Sveinsson
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2019-564, https://doi.org/10.5194/hess-2019-564, 2019
Preprint withdrawn
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We studied recent trends in the Icelandic climate and snow regimes. Climate was classified based on climate models and snow cover trends were assessed using satellite imagery. Our results showed a significant increase in the frequency of snow cover, especially in the eastern highlands. At the same our results show warmer climate classes spreading both northward and to higher elevations. Based on projected climate, we expect a significant warming of local climates in Iceland during this century.
Andri Gunnarsson, Sigurður M. Garðarsson, and Óli G. B. Sveinsson
Hydrol. Earth Syst. Sci., 23, 3021–3036, https://doi.org/10.5194/hess-23-3021-2019, https://doi.org/10.5194/hess-23-3021-2019, 2019
Short summary
Short summary
In this study a gap-filled snow cover product for Iceland is developed using MODIS satellite data and validated with both in situ observations and alternative remote sensing data sources with good agreement. Information about snow cover extent, duration and changes over time is presented, indicating that snow cover extent has been increasing slightly for the past few years.
Giri Gopalan, Birgir Hrafnkelsson, Guðfinna Aðalgeirsdóttir, Alexander H. Jarosch, and Finnur Pálsson
The Cryosphere, 12, 2229–2248, https://doi.org/10.5194/tc-12-2229-2018, https://doi.org/10.5194/tc-12-2229-2018, 2018
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Geophysical systems can often contain scientific parameters whose values are uncertain, complex underlying dynamics, and field measurements with errors. These components are naturally modeled together within what is known as a Bayesian hierarchical model (BHM). This paper constructs such a model for shallow glaciers based on an approximation of the underlying dynamics. The evaluation of this model is aided by the use of exact analytical solutions from the literature.
Louise Steffensen Schmidt, Guðfinna Aðalgeirsdóttir, Sverrir Guðmundsson, Peter L. Langen, Finnur Pálsson, Ruth Mottram, Simon Gascoin, and Helgi Björnsson
The Cryosphere, 11, 1665–1684, https://doi.org/10.5194/tc-11-1665-2017, https://doi.org/10.5194/tc-11-1665-2017, 2017
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The regional climate model HIRHAM5 is evaluated over Vatnajökull, Iceland, using automatic weather stations and mass balance observations from 1995 to 2014. From this we asses whether the model can be used to reconstruct the mass balance of the glacier. We find that the simulated energy balance is underestimated overall, but it has been improved by using a new albedo scheme. The specific mass balance is reconstructed back to 1980, thus expanding on the observational records of the mass balance.
Joaquín M. C. Belart, Etienne Berthier, Eyjólfur Magnússon, Leif S. Anderson, Finnur Pálsson, Thorsteinn Thorsteinsson, Ian M. Howat, Guðfinna Aðalgeirsdóttir, Tómas Jóhannesson, and Alexander H. Jarosch
The Cryosphere, 11, 1501–1517, https://doi.org/10.5194/tc-11-1501-2017, https://doi.org/10.5194/tc-11-1501-2017, 2017
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Sub-meter satellite stereo images (Pléiades and WorldView2) are used to accurately measure snow accumulation and winter mass balance of Drangajökull ice cap. This is done by creating and comparing accurate digital elevation models. A glacier-wide geodetic mass balance of 3.33 ± 0.23 m w.e. is derived between October 2014 and May 2015. This method could be easily transposable to remote glaciated areas where seasonal mass balance measurements (especially winter accumulation) are lacking.
Monika Wittmann, Christine Dorothea Groot Zwaaftink, Louise Steffensen Schmidt, Sverrir Guðmundsson, Finnur Pálsson, Olafur Arnalds, Helgi Björnsson, Throstur Thorsteinsson, and Andreas Stohl
The Cryosphere, 11, 741–754, https://doi.org/10.5194/tc-11-741-2017, https://doi.org/10.5194/tc-11-741-2017, 2017
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This work includes a study on the effects of dust deposition on the mass balance of Brúarjökull, an outlet glacier of Vatnajökull, Iceland's largest ice cap. A model was used to simulate dust deposition on the glacier, and these periods of dust were compared to albedo measurements at two weather stations on Brúarjökull to evaluate the dust impact. We determine the influence of dust events on the snow albedo and the surface energy balance.
Related subject area
Discipline: Glaciers | Subject: Energy Balance Obs/Modelling
Brief Communication: Accurate and autonomous snow water equivalent measurements using a cosmic ray sensor on a Himalayan glacier
Surface heat fluxes at coarse blocky Murtèl rock glacier (Engadine, eastern Swiss Alps)
Evaluation of reanalysis data and dynamical downscaling for surface energy balance modeling at mountain glaciers in western Canada
Strategies for regional modeling of surface mass balance at the Monte Sarmiento Massif, Tierra del Fuego
Long-term firn and mass balance modelling for Abramov Glacier in the data-scarce Pamir Alay
The surface energy balance during foehn events at Joyce Glacier, McMurdo Dry Valleys, Antarctica
Sub-seasonal variability of supraglacial ice cliff melt rates and associated processes from time-lapse photogrammetry
Cloud forcing of surface energy balance from in situ measurements in diverse mountain glacier environments
Modelling glacier mass balance and climate sensitivity in the context of sparse observations: application to Saskatchewan Glacier, western Canada
Understanding monsoon controls on the energy and mass balance of glaciers in the Central and Eastern Himalaya
SNICAR-ADv4: a physically based radiative transfer model to represent the spectral albedo of glacier ice
Firn changes at Colle Gnifetti revealed with a high-resolution process-based physical model approach
Seasonal and interannual variability of melt-season albedo at Haig Glacier, Canadian Rocky Mountains
Surface energy fluxes on Chilean glaciers: measurements and models
Using 3D turbulence-resolving simulations to understand the impact of surface properties on the energy balance of a debris-covered glacier
Incorporating moisture content in surface energy balance modeling of a debris-covered glacier
Surface melt and the importance of water flow – an analysis based on high-resolution unmanned aerial vehicle (UAV) data for an Arctic glacier
Glacio-hydrological melt and run-off modelling: application of a limits of acceptability framework for model comparison and selection
Navaraj Pokhrel, Patrick Wagnon, Fanny Brun, Arbindra Khadka, Tom Matthews, Audrey Goutard, Dibas Shrestha, Baker Perry, and Marion Réveillet
EGUsphere, https://doi.org/10.5194/egusphere-2024-1760, https://doi.org/10.5194/egusphere-2024-1760, 2024
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We studied snow processes in the accumulation area of Mera Glacier (Central Himalaya, Nepal) by deploying a cosmic ray counting sensor that allows to track the evolution of the snow water equivalent. We suspect significant surface melting, water percolation and refreezing within the snowpack, that might be missed by traditional mass balance surveys.
Dominik Amschwand, Martin Scherler, Martin Hoelzle, Bernhard Krummenacher, Anna Haberkorn, Christian Kienholz, and Hansueli Gubler
The Cryosphere, 18, 2103–2139, https://doi.org/10.5194/tc-18-2103-2024, https://doi.org/10.5194/tc-18-2103-2024, 2024
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Rock glaciers are coarse-debris permafrost landforms that are comparatively climate resilient. We estimate the surface energy balance of rock glacier Murtèl (Swiss Alps) based on a large surface and sub-surface sensor array. During the thaw seasons 2021 and 2022, 90 % of the net radiation was exported via turbulent heat fluxes and only 10 % was transmitted towards the ground ice table. However, early snowmelt and droughts make these permafrost landforms vulnerable to climate warming.
Christina Draeger, Valentina Radić, Rachel H. White, and Mekdes Ayalew Tessema
The Cryosphere, 18, 17–42, https://doi.org/10.5194/tc-18-17-2024, https://doi.org/10.5194/tc-18-17-2024, 2024
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Our study increases our confidence in using reanalysis data for reconstructions of past glacier melt and in using dynamical downscaling for long-term simulations from global climate models to project glacier melt. We find that the surface energy balance model, forced with reanalysis and dynamically downscaled reanalysis data, yields <10 % difference in the modeled total melt energy when compared to the same model being forced with observations at our glacier sites in western Canada.
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
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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.
Marlene Kronenberg, Ward van Pelt, Horst Machguth, Joel Fiddes, Martin Hoelzle, and Felix Pertziger
The Cryosphere, 16, 5001–5022, https://doi.org/10.5194/tc-16-5001-2022, https://doi.org/10.5194/tc-16-5001-2022, 2022
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The Pamir Alay is located at the edge of regions with anomalous glacier mass changes. Unique long-term in situ data are available for Abramov Glacier, located in the Pamir Alay. In this study, we use this extraordinary data set in combination with reanalysis data and a coupled surface energy balance–multilayer subsurface model to compute and analyse the distributed climatic mass balance and firn evolution from 1968 to 2020.
Marte G. Hofsteenge, Nicolas J. Cullen, Carleen H. Reijmer, Michiel van den Broeke, Marwan Katurji, and John F. Orwin
The Cryosphere, 16, 5041–5059, https://doi.org/10.5194/tc-16-5041-2022, https://doi.org/10.5194/tc-16-5041-2022, 2022
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In the McMurdo Dry Valleys (MDV), foehn winds can impact glacial meltwater production and the fragile ecosystem that depends on it. We study these dry and warm winds at Joyce Glacier and show they are caused by a different mechanism than that found for nearby valleys, demonstrating the complex interaction of large-scale winds with the mountains in the MDV. We find that foehn winds increase sublimation of ice, increase heating from the atmosphere, and increase the occurrence and rates of melt.
Marin Kneib, Evan S. Miles, Pascal Buri, Stefan Fugger, Michael McCarthy, Thomas E. Shaw, Zhao Chuanxi, Martin Truffer, Matthew J. Westoby, Wei Yang, and Francesca Pellicciotti
The Cryosphere, 16, 4701–4725, https://doi.org/10.5194/tc-16-4701-2022, https://doi.org/10.5194/tc-16-4701-2022, 2022
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Ice cliffs are believed to be important contributors to the melt of debris-covered glaciers, but this has rarely been quantified as the cliffs can disappear or rapidly expand within a few weeks. We used photogrammetry techniques to quantify the weekly evolution and melt of four cliffs. We found that their behaviour and melt during the monsoon is strongly controlled by supraglacial debris, streams and ponds, thus providing valuable insights on the melt and evolution of debris-covered glaciers.
Jonathan P. Conway, Jakob Abermann, Liss M. Andreassen, Mohd Farooq Azam, Nicolas J. Cullen, Noel Fitzpatrick, Rianne H. Giesen, Kirsty Langley, Shelley MacDonell, Thomas Mölg, Valentina Radić, Carleen H. Reijmer, and Jean-Emmanuel Sicart
The Cryosphere, 16, 3331–3356, https://doi.org/10.5194/tc-16-3331-2022, https://doi.org/10.5194/tc-16-3331-2022, 2022
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We used data from automatic weather stations on 16 glaciers to show how clouds influence glacier melt in different climates around the world. We found surface melt was always more frequent when it was cloudy but was not universally faster or slower than under clear-sky conditions. Also, air temperature was related to clouds in opposite ways in different climates – warmer with clouds in cold climates and vice versa. These results will help us improve how we model past and future glacier melt.
Christophe Kinnard, Olivier Larouche, Michael N. Demuth, and Brian Menounos
The Cryosphere, 16, 3071–3099, https://doi.org/10.5194/tc-16-3071-2022, https://doi.org/10.5194/tc-16-3071-2022, 2022
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This study implements a physically based, distributed glacier mass balance model in a context of sparse direct observations. Carefully constraining model parameters with ancillary data allowed for accurately reconstructing the mass balance of Saskatchewan Glacier over a 37-year period. We show that the mass balance sensitivity to warming is dominated by increased melting and that changes in glacier albedo and air humidity are the leading causes of increased glacier melt under warming scenarios.
Stefan Fugger, Catriona L. Fyffe, Simone Fatichi, Evan Miles, Michael McCarthy, Thomas E. Shaw, Baohong Ding, Wei Yang, Patrick Wagnon, Walter Immerzeel, Qiao Liu, and Francesca Pellicciotti
The Cryosphere, 16, 1631–1652, https://doi.org/10.5194/tc-16-1631-2022, https://doi.org/10.5194/tc-16-1631-2022, 2022
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The monsoon is important for the shrinking and growing of glaciers in the Himalaya during summer. We calculate the melt of seven glaciers in the region using a complex glacier melt model and weather data. We find that monsoonal weather affects glaciers that are covered with a layer of rocky debris and glaciers without such a layer in different ways. It is important to take so-called turbulent fluxes into account. This knowledge is vital for predicting the future of the Himalayan glaciers.
Chloe A. Whicker, Mark G. Flanner, Cheng Dang, Charles S. Zender, Joseph M. Cook, and Alex S. Gardner
The Cryosphere, 16, 1197–1220, https://doi.org/10.5194/tc-16-1197-2022, https://doi.org/10.5194/tc-16-1197-2022, 2022
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Snow and ice surfaces are important to the global climate. Current climate models use measurements to determine the reflectivity of ice. This model uses physical properties to determine the reflectivity of snow, ice, and darkly pigmented impurities that reside within the snow and ice. Therefore, the modeled reflectivity is more accurate for snow/ice columns under varying climate conditions. This model paves the way for improvements in the portrayal of snow and ice within global climate models.
Enrico Mattea, Horst Machguth, Marlene Kronenberg, Ward van Pelt, Manuela Bassi, and Martin Hoelzle
The Cryosphere, 15, 3181–3205, https://doi.org/10.5194/tc-15-3181-2021, https://doi.org/10.5194/tc-15-3181-2021, 2021
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In our study we find that climate change is affecting the high-alpine Colle Gnifetti glacier (Swiss–Italian Alps) with an increase in melt amounts and ice temperatures.
In the near future this trend could threaten the viability of the oldest ice core record in the Alps.
To reach our conclusions, for the first time we used the meteorological data of the highest permanent weather station in Europe (Capanna Margherita, 4560 m), together with an advanced numeric simulation of the glacier.
Shawn J. Marshall and Kristina Miller
The Cryosphere, 14, 3249–3267, https://doi.org/10.5194/tc-14-3249-2020, https://doi.org/10.5194/tc-14-3249-2020, 2020
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Surface-albedo measurements from 2002 to 2017 from Haig Glacier in the Canadian Rockies provide no evidence of long-term trends (i.e., the glacier does not appear to be darkening), but there are large variations in albedo over the melt season and from year to year. The glacier ice is exceptionally dark in association with forest fire fallout but is effectively cleansed by meltwater or rainfall. Summer snowfall plays an important role in refreshing the glacier surface and reducing summer melt.
Marius Schaefer, Duilio Fonseca-Gallardo, David Farías-Barahona, and Gino Casassa
The Cryosphere, 14, 2545–2565, https://doi.org/10.5194/tc-14-2545-2020, https://doi.org/10.5194/tc-14-2545-2020, 2020
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Chile hosts glaciers in a large range of latitudes and climates. To project future ice extent, a sound quantification of the energy exchange between atmosphere and glaciers is needed. We present new data for six Chilean glaciers belonging to three glaciological zones. In the Central Andes, the main energy source for glacier melt is the incoming solar radiation, while in southern Patagonia heat provided by the mild and humid air is also important. Total melt rates are higher in Patagonia.
Pleun N. J. Bonekamp, Chiel C. van Heerwaarden, Jakob F. Steiner, and Walter W. Immerzeel
The Cryosphere, 14, 1611–1632, https://doi.org/10.5194/tc-14-1611-2020, https://doi.org/10.5194/tc-14-1611-2020, 2020
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Drivers controlling melt of debris-covered glaciers are largely unknown. With a 3D turbulence-resolving model the impact of surface properties of debris on micrometeorological variables and the conductive heat flux is shown. Also, we show ice cliffs are local melt hot spots and that turbulent fluxes and local heat advection amplify spatial heterogeneity on the surface.This work is important for glacier mass balance modelling and for the understanding of the evolution of debris-covered glaciers.
Alexandra Giese, Aaron Boone, Patrick Wagnon, and Robert Hawley
The Cryosphere, 14, 1555–1577, https://doi.org/10.5194/tc-14-1555-2020, https://doi.org/10.5194/tc-14-1555-2020, 2020
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Rocky debris on glacier surfaces is known to affect the melt of mountain glaciers. Debris can be dry or filled to varying extents with liquid water and ice; whether debris is dry, wet, and/or icy affects how efficiently heat is conducted through debris from its surface to the ice interface. Our paper presents a new energy balance model that simulates moisture phase, evolution, and location in debris. ISBA-DEB is applied to West Changri Nup glacier in Nepal to reveal important physical processes.
Eleanor A. Bash and Brian J. Moorman
The Cryosphere, 14, 549–563, https://doi.org/10.5194/tc-14-549-2020, https://doi.org/10.5194/tc-14-549-2020, 2020
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High-resolution measurements from unmanned aerial vehicle (UAV) imagery allowed for examination of glacier melt model performance in detail at Fountain Glacier. This work capitalized on distributed measurements at 10 cm resolution to look at the spatial distribution of model errors in the ablation zone. Although the model agreed with measurements on average, strong correlation was found with surface water. The results highlight the contribution of surface water flow to melt at this location.
Jonathan D. Mackay, Nicholas E. Barrand, David M. Hannah, Stefan Krause, Christopher R. Jackson, Jez Everest, and Guðfinna Aðalgeirsdóttir
The Cryosphere, 12, 2175–2210, https://doi.org/10.5194/tc-12-2175-2018, https://doi.org/10.5194/tc-12-2175-2018, 2018
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We apply a framework to compare and objectively accept or reject competing melt and run-off process models. We found no acceptable models. Furthermore, increasing model complexity does not guarantee better predictions. The results highlight model selection uncertainty and the need for rigorous frameworks to identify deficiencies in competing models. The application of this approach in the future will help to better quantify model prediction uncertainty and develop improved process models.
Cited articles
Aðalgeirsdóttir, G., Magnússon, E., Pálsson, F., Thorsteinsson, T., Belart,
J. M. C., Jóhannesson, T., Hannesdóttir, H., Sigurðsson, O., Gunnarsson,
A., Einarsson, B., Berthier, E., Schmidt, L. S., Haraldsson, H. H., and
Björnsson, H.: Glacier Changes in Iceland from 1890 to 2019, Front.
Earth Sci., 8, 520, https://doi.org/10.3389/feart.2020.523646, 2020. a, b, c
Adam, J. C., Hamlet, A. F., and Lettenmaier, D. P.: Implications of Global
Climate Change for Snowmelt Hydrology in the Twenty-First Century,
Hydrol. Process., 23, 962–972, https://doi.org/10.1002/hyp.7201, 2008. a
Alexander, M. A., Scott, J. D., Friedland, K. D., Mills, K. E., Nye, J. A.,
Pershing, A. J., and Thomas, A. C.: Projected sea surface temperatures over
the 21st century: Changes in the mean, variability and extremes for large
marine ecosystem regions of Northern Oceans, Elementa: Science of the
Anthropocene, 6, 9, https://doi.org/10.1525/elementa.191, 2018. a
Arnalds, O., Dagsson-Waldhauserova, P., and Ólafsson, H.: The Icelandic
volcanic aeolian environment: Processes and impacts — A review, Aeolian
Res., 20, 176–195, https://doi.org/10.1016/j.aeolia.2016.01.004, 2016. a
Bair, E. H., Rittger, K., Davis, R. E., Painter, T. H., and Dozier, J.:
Validating reconstruction of snow water equivalent in California's Sierra
Nevada using measurements from the NASA Airborne Snow Observatory, Water
Resour. Res., 52, 8437–8460, https://doi.org/10.1002/2016WR018704, 2016. a
Barnett, T. P., Adam, J. C., and Lettenmaier, D. P.: Potential Impacts of a
Warming Climate on Water Availability in Snow-Dominated Regions, Nature, 438,
303–309, https://doi.org/10.1038/nature04141, 2005. a
Berrisford, P., Dee, D., Poli, P., Brugge, R., Fielding, M., Fuentes, M., Kållberg, P., Kobayashi, S., Uppala, S., and Simmons, A.: The ERA-Interim
archive Version 2.0, ERA Report Series, p. 23, 2011. a
Björnsson, H. and Pálsson, F.: Radio-echo soundings on Icelandic temperate
glaciers: history of techniques and findings, Ann. Glaciol., 61,
25–34, https://doi.org/10.1017/aog.2020.10, 2020. a
Björnsson, H., Pálsson, F., and Guðmundsson, M. T.: Surface and bedrock
topography of the Mýrdalsjökull ice cap, Iceland: The Katla caldera,
eruption sites and routes of jökulhlaups, Jökull, 49, 29–46,
2000a. a
Björnsson, H., Pálsson, F., and Guðmundsson, M. T.: Surface and bedrock
topography of the Mýrdalsjökull ice cap, Iceland: The Katla caldera,
eruption sites and routes of jökulhlaups, Jökull, 49, 29–46,
2000b. a
Björnsson, H., Pálsson, F., and Guðmundsson, S.: Jökulsárlón at
Breiðamerkursandur, Vatnajökull, Iceland: 20th century changes and future
outlook, Jökull, 50, 1–18, 2001. a
Björnsson, H., Pálsson, F., Gudmundsson, S., Magnússon, E.,
Adalgeirsdóttir, G., Jóhannesson, T., Berthier, E., Sigurdsson, O., and
Thorsteinsson, T.: Contribution of Icelandic ice caps to sea level rise:
Trends and variability since the Little Ice Age, Geophys. Res.
Lett., 40, 1546–1550, https://doi.org/10.1002/grl.50278, 2013. a
Bojinski, S., Verstraete, M., Peterson, T. C., Richter, C., Simmons, A., and
Zemp, M.: The Concept of Essential Climate Variables in Support of
Climate Research, Applications, and Policy, B. Am.
Meteorol. Soc., 95, 1431–1443, https://doi.org/10.1175/BAMS-D-13-00047.1,
2014. a
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. a, b
Brock, B. W., Willis, I. C., and Sharp, M. J.: 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. a, b
Charalampidis, C., van As, D., Box, J. E., van den Broeke, M. R., Colgan, W. T., Doyle, S. H., Hubbard, A. L., MacFerrin, M., Machguth, H., and Smeets, C. J. P. P.: Changing surface–atmosphere energy exchange and refreezing capacity of the lower accumulation area, West Greenland, The Cryosphere, 9, 2163–2181, https://doi.org/10.5194/tc-9-2163-2015, 2015. a
Chen, X., Liang, S., and Cao, Y.: Satellite Observed Changes in the Northern
Hemisphere Snow Cover Phenology and the Associated Radiative Forcing and
Feedback between 1982 and 2013, Environ. Res. Lett., 11, 084002,
https://doi.org/10.1088/1748-9326/11/8/084002, 2016. a
Choi, G., Robinson, D. A., and Kang, S.: Changing Northern Hemisphere Snow
Seasons, J. Climate, 23, 5305–5310, https://doi.org/10.1175/2010jcli3644.1,
2010. a
Crochet, P. and Jóhannesson, T.: A data set of gridded daily temperature in
Iceland, 1949–2010, Jökull, 61, 1–17, 2011. a
Dagsson-Waldhauserova, P., Arnalds, O., and Olafsson, H.: Long-term dust
aerosol production from natural sources in Iceland, J. Air
Waste Manage. A., 67, 173–181,
https://doi.org/10.1080/10962247.2013.805703, 2017. a
Denby, B. and Greuell, W.: The use of bulk and profile methods for determining
surface heat fluxes in the presence of glacier winds, J. Glaciol.,
46, 445–452, https://doi.org/10.3189/172756500781833124, 2000. a
Einarsson, M. A.: Climates of the Oceans, H. Van Loon (Ed.): Vol.
15 of World Survey of Climatology, J. Climatol., 5, 673–697,
https://doi.org/10.1002/joc.3370050110, 1984. a
Fausto, R. S., van As, D., Mankoff, K. D., Vandecrux, B., Citterio, M., Ahlstrøm, A. P., Andersen, S. B., Colgan, W., Karlsson, N. B., Kjeldsen, K. K., Korsgaard, N. J., Larsen, S. H., Nielsen, S., Pedersen, A. Ø., Shields, C. L., Solgaard, A. M., and Box, J. E.: Programme for Monitoring of the Greenland Ice Sheet (PROMICE) automatic weather station data, Earth Syst. Sci. Data, 13, 3819–3845, https://doi.org/10.5194/essd-13-3819-2021, 2021. a
Fernandes, R., Zhao, H. X., Wang, X. J., Key, J., Qu, X., and Hall, A.:
Controls on Northern Hemisphere Snow Albedo Feedback Quantified Using
Satellite Earth Observations, Geophys. Res. Lett., 36, L21702,
https://doi.org/10.1029/2009gl040057, 2009. a
Flanner, M. G., Shell, K. M., Barlage, M., Perovich, D. K., and Tschudi, M. A.:
Radiative Forcing and Albedo Feedback from the Northern Hemisphere
Cryosphere between 1979 and 2008, Nat. Geosci., 4, 151–155,
https://doi.org/10.1038/ngeo1062, 2011. a
Franco, B., Fettweis, X., and Erpicum, M.: Future projections of the Greenland ice sheet energy balance driving the surface melt, The Cryosphere, 7, 1–18, https://doi.org/10.5194/tc-7-1-2013, 2013. a
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. a
Gascoin, S., Guðmundsson, S., Aðalgeirsdóttir, G., Pálsson, F.,
Schmidt, L., Berthier, E., and Björnsson, H.: Evaluation of MODIS
Albedo Product over Ice Caps in Iceland and Impact of
Volcanic Eruptions on Their Albedo, Remote Sens., 9, 399,
https://doi.org/10.3390/rs9050399, 2017. a, b
Gervais, M., Shaman, J., and Kushnir, Y.: Impacts of the North Atlantic Warming
Hole in Future Climate Projections: Mean Atmospheric Circulation and the
North Atlantic Jet, J. Climate, 32, 2673–2689,
https://doi.org/10.1175/JCLI-D-18-0647.1, 2019. a
Goelzer, H., Nowicki, S., Payne, A., Larour, E., Seroussi, H., Lipscomb, W. H., Gregory, J., Abe-Ouchi, A., Shepherd, A., Simon, E., Agosta, C., Alexander, P., Aschwanden, A., Barthel, A., Calov, R., Chambers, C., Choi, Y., Cuzzone, J., Dumas, C., Edwards, T., Felikson, D., Fettweis, X., Golledge, N. R., Greve, R., Humbert, A., Huybrechts, P., Le clec'h, S., Lee, V., Leguy, G., Little, C., Lowry, D. P., Morlighem, M., Nias, I., Quiquet, A., Rückamp, M., Schlegel, N.-J., Slater, D. A., Smith, R. S., Straneo, F., Tarasov, L., van de Wal, R., and van den Broeke, M.: The future sea-level contribution of the Greenland ice sheet: a multi-model ensemble study of ISMIP6, The Cryosphere, 14, 3071–3096, https://doi.org/10.5194/tc-14-3071-2020, 2020. a
Gregory, J. M. and Oerlemans, J.: Simulated future sea-level rise due to
glacier melt based on regionally and seasonally resolved temperature changes,
Nature, 391, 474–476, https://doi.org/10.1038/35119, 1998. a
Guðmundsson, S., Björnsson, H., Pálsson, F., and Haraldsson, H. H.: Energy
balance of Brúarjökull and circumstances leading to the August 2004 floods
in the river Jökla, N-Vatnajökull, Jökull, 55, 121–138, 2005. a
Gudmundsson, M. T., Thordarson, T., Höskuldsson, A., Larsen, G., Björnsson,
H., Prata, F. J., Oddsson, B., Magnússon, E., Högnadóttir, T., Petersen,
G. N., Hayward, C. L., Stevenson, J. A., and Jónsdóttir, I.: Ash generation
and distribution from the April-May 2010 eruption of Eyjafjallajökull,
Iceland, Sci. Rep.-UK, 2, 572, 2012. a
Hall, D. K. and Riggs, G. A.: MODIS/Aqua Snow Cover Daily L3 Global 500m SIN Grid, Version 6, Boulder, Colorado USA, NASA National Snow and Ice Data Center Distributed Active Archive Center [data set], https://doi.org/10.5067/MODIS/MYD10A1.006, 2016a. a, b
Hall, D. K. and Riggs, G. A.: MODIS/Terra Snow Cover Daily L3 Global 500m SIN Grid, Version 6, Boulder, Colorado USA, NASA National Snow and Ice Data Center Distributed Active Archive Center [data set], https://doi.org/10.5067/MODIS/MOD10A1.006, 2016b. a, b
Hannesdóttir, H., Sigurðsson, O., Þrastarson, R. H., Guðmundsson, S.,
Belart, J. M., Pálsson, F., Magnússon, E., Víkingsson, S., Kaldal, I., and
Jóhannesson, T.: A national glacier inventory and variations in glacier
extent in Iceland from the Little Ice Age maximum to 2019, Jökull, 12,
1–34, 2020. a, b, c
Helgason, G. B.: Varmaleiðing í einvíðu fjöllaga hjarnlíkani; Heat
conduction in a one dimensional multilayer firnmodel, http://hdl.handle.net/1946/35967 (last access: 1 March 2023), Jarðvísindadeild Verkfræðiog náttúruvísindasvið, Háskóli íslands, Reykjavík, 2020. a
Hinkelman, L. M., Lapo, K. E., Cristea, N. C., and Lundquist, J. D.: Using
CERES SYN Surface Irradiance Data as Forcing for Snowmelt Simulation in
Complex Terrain, J. Hydrometeorol., 16, 2133–2152,
https://doi.org/10.1175/JHM-D-14-0179.1, 2015. a
Hjaltason, S., Guðmundsdóttir, M., Haukdal, J. Á., and Guðmundsson,
J. R.: Energy Statistics in Iceland 2019, Annual report, Orkustofnun,
Reykjavík, Iceland, 2020. a
Hock, R.: Glacier melt: a review of processes and their modelling, Prog.
Phys. Geogr.-Earth and Environment, 29, 362–391,
https://doi.org/10.1191/0309133305pp453ra, 2005. a
Hodgkins, R., Carr, S., Pálsson, F., Guðmundsson, S., and Björnsson, H.:
Modelling variable glacier lapse rates using ERA-Interim reanalysis
climatology: an evaluation at Vestari- Hagafellsjökull, Langjökull,
Iceland, International J. Climatol., 33, 410–421,
https://doi.org/10.1002/joc.3440, 2013. a, b
Hofer, S., Lang, C., Amory, C., Kittel, C., Delhasse, A., Tedstone, A., and
Fettweis, X.: Greater Greenland Ice Sheet contribution to global sea level
rise in CMIP6, Nat. Commun., 11, 6289,
https://doi.org/10.1038/s41467-020-20011-8, 2020. a
Holtslag, A. A. M. and Bruin, H. A. R. D.: Applied Modeling of the Nighttime
Surface Energy Balance over Land, J. Appl. Meteorol.
Climatol., 27, 689–704,
https://doi.org/10.1175/1520-0450(1988)027<0689:AMOTNS>2.0.CO;2, 1988. a
Hreinsdóttir, S., Sigmundsson, F., Roberts, M. J., Björnsson, H., Grapenthin,
R., Arason, P., Árnadóttir, T., Hólmjárn, J., Geirsson, H., Bennett,
R. A., Gudmundsson, M. T., Oddsson, B., Ófeigsson, B. G., Villemin, T.,
Jónsson, T., Sturkell, E., Höskuldsson, A., Larsen, G., Thordarson, T., and
Óladóttir, B. A.: Volcanic plume height correlated with magma-pressure
change at Grímsvötn Volcano, Iceland, Nat. Geosci., 7, 214–218,
https://doi.org/10.1038/ngeo2044, 2014. a, b
Huai, B., van den Broeke, M. R., and Reijmer, C. H.: Long-term surface energy balance of the western Greenland Ice Sheet and the role of large-scale circulation variability, The Cryosphere, 14, 4181–4199, https://doi.org/10.5194/tc-14-4181-2020, 2020. a, b
Hudson, S. R.: Estimating the Global Radiative Impact of the Sea Ice-Albedo
Feedback in the Arctic, J. Geophys. Res.-Atmos., 116,
D16102, https://doi.org/10.1029/2011jd015804, 2011. a, b
Jennings, K. S., Kittel, T. G. F., and Molotch, N. P.: Observations and simulations of the seasonal evolution of snowpack cold content and its relation to snowmelt and the snowpack energy budget, The Cryosphere, 12, 1595–1614, https://doi.org/10.5194/tc-12-1595-2018, 2018. a
Jóhannesson, T.: The Response Time of Glaciers in Iceland to Changes in
climate, Ann. Glaciol., 8, 100–101, https://doi.org/10.3189/S0260305500001233,
1986. a
Jóhannesson, T., Raymond, C., and Waddington, E.: Time–Scale for Adjustment
of Glaciers to Changes in Mass Balance, J. Glaciol., 35, 355–369,
https://doi.org/10.3189/S002214300000928X, 1989. a
Jóhannesson, T., Aðalgeirsdóttir, G., Björnsson, H., Crochet,
P., Elíasson, E. B., Guðmundsson, S., Jónsdóttir, J.,
Ólafsson, H., Pálsson, F., Rögnvaldsson, Ó., Sigurðsson,
O., Snorrason, Á., Sveinsson, Ó. G. B., and Þorsteinsson, Þ.:
Effect of Climate Change on Hydrology and Hydro-Resources in Iceland.,
Orkustofnun, Reykjavík, Iceland, ISBN 978-9979-68-224-0, 2007. a, b
Jóhannesson, T., Björnsson, H., Magnússon, E., Guðmundsson, S., Pálsson,
F., Sigurðsson, O., Thorsteinsson, T., and Berthier, E.: Ice-volume changes,
bias estimation of mass-balance measurements and changes in subglacial lakes
derived by lidar mapping of the surface of Icelandic glaciers, Ann. Glaciol., 54, 63–74, https://doi.org/10.3189/2013AoG63A422, 2013. a, b
Jóhannesson, T., Pálmason, B.and Hjartarson, A., Jarosch, A. H., Magnússon,
E., Belart, J. M. C., and Gudmundsson, M. T.: Non-surface mass balance of
glaciers in Iceland, J. Glaciol., 66, 685–697,
https://doi.org/10.1017/jog.2020.37, 2020. a
Jude-Eton, T., Thordarson, T., Gudmundsson, M., and Oddsson, B.: Dynamics,
stratigraphy and proximal dispersal of supraglacial tephra during the
ice-confined 2004 eruption at Grímsvötn Volcano, Iceland, B.
Volcanol., 74, 1057–1082, https://doi.org/10.1007/s00445-012-0583-3, 2012. a
Karner, F., Obleitner, F., Krismer, T., Kohler, J., and Greuell, W.: A decade
of energy and mass balance investigations on the glacier Kongsvegen,
Svalbard, J. Geophys. Res.-Atmos., 118, 3986–4000,
https://doi.org/10.1029/2012JD018342, 2013. a
Keil, P., Mauritsen, T., Jungclaus, J., Hedemann, C., Olonscheck, D., and
Ghosh, R.: Multiple drivers of the North Atlantic warming hole, Nat. Clim. Change, 10, 667–671, https://doi.org/10.1038/s41558-020-0819-8, 2020. a, b
Knudsen, K. L., Eiríksson, J., and Bartels-Jónsdóttir, H. B.: Oceanographic
changes through the last millennium off North Iceland: Temperature and
salinity reconstructions based on foraminifera and stable isotopes, Marine Micropaleontol., 84-85, 54 – 73, https://doi.org/10.1016/j.marmicro.2011.11.002,
2012. a
Lozier, M., Owens, W., and Curry, R. G.: The climatology of the North Atlantic,
Prog. Oceanogr., 36, 1–44, https://doi.org/10.1016/0079-6611(95)00013-5,
1995. a
Magnússon, E., Belart, J. M., Pálsson, F., Anderson, L. S., Ágúst
Þ. Gunnlaugsson, Berthier, E., Ágústsson, H., and Áslaug Geirsdóttir:
The subglacial topography of Drangajökull ice cap, NW-Iceland, deduced from
dense RES-profiling, Jökull, 66, 1–26, 2016a. a
Magnússon, E., Belart, J. M. C., Pálsson, F., Anderson, L. S., Gunnlaugsson,
A., Berthier, E., Ágústsson, H., and Geirsdóttir, A.: The subglacial
topography of Drangajökull ice cap, NW-Iceland, deduced from dense
RES-profiling, Jökull, 66, 1–26, 2016b. a
Male, D. H. and Granger, R. J.: Snow surface energy exchange, Water Resour.
Res., 17, 609–627, https://doi.org/10.1029/WR017i003p00609, 1981. a
Marty, C., Philipona, R., Fröhlich, C., and Ohmura, A.: Altitude dependence of
surface radiation fluxes and cloud forcing in the alps: results from the
alpine surface radiation budget network, Theor. Appl. Climatol.,
72, 137–155, https://doi.org/10.1007/s007040200019, 2002. a
MathWorks: MATLAB version: 9.13.0 (R2022b),
https://www.mathworks.com (last access: 12 September 2023), 2022. a
Möller, R., Möller, M., Björnsson, H., Gudmundsson, S., Pálsson, F.,
Oddsson, B., Kukla, P., and Schneider, C.: MODIS-derived albedo changes of
Vatnajökull (Iceland) due to tephra deposition from the 2004 Grimsvötn
eruption, Int. J. Appl. Earth Obs., 26, 256–269, https://doi.org/10.1016/j.jag.2013.08.005, 2014. a
Möller, R., Dagsson-Waldhauserova, P., Möller, M., Kukla, P. A., Schneider,
C., and Gudmundsson, M. T.: Persistent albedo reduction on southern Icelandic
glaciers due to ashfall from the 2010 Eyjafjallajökull eruption, Remote
Sens. Environ., 233, 111396, https://doi.org/10.1016/j.rse.2019.111396, 2019. a
National Centers for Environmental Prediction: NCEP GFS 0.25 Degree Global
Forecast Grids Historical Archive [data set], https://doi.org/10.5065/D65D8PWK, 2015. a
National Land Survey of Iceland: IcelandDEM v.1, National Land Survey of Iceland [data set], https://gatt.lmi.is/geonetwork/srv/metadata/e6712430-a63c-4ae5-9158-c89d16da6361, last access: 1 December 2022. a
Nawri, N., Björnsson, H., Petersen, G. N., and Jónasson, K.: Empirical
Terrain Models for Surface Wind and Air Temperature over Iceland, VÍ,
2012-009, Veðurstofa Íslands, Reykjavík, Iceland, 2012. a
Noël, B., Aðalgeirsdóttir, G., Pálsson, F., Wouters, B., Lhermitte, S.,
Haacker, J. M., and van den Broeke, M. R.: North Atlantic Cooling is Slowing
Down Mass Loss of Icelandic Glaciers, Geophys. Res. Lett., 49,
e2021GL095697, https://doi.org/10.1029/2021GL095697, 2022. a, b, c
Oddsson, B., Gudmundsson, M., Larsen, G., and Karlsdóttir, S.: Monitoring of
the plume from the basaltic phreatomagmatic 2004 Grímsvötn
eruption–application of weather radar and comparison with plume models,
B. Volcanol., 74, 1395–1407, https://doi.org/10.1007/s00445-012-0598-9, 2012. a, b
Oerlemans, J., Giesen, R., and Van Den Broeke, M.: Retreating alpine glaciers:
increased melt rates due to accumulation of dust (Vadret da Morteratsch,
Switzerland), J. Glaciol., 55, 729–736,
https://doi.org/10.3189/002214309789470969, 2009. a
Ohmura, A.: Physical Basis for the Temperature-Based Melt-Index Method, J. Appl. Meteorol., 40, 753–761,
https://doi.org/10.1175/1520-0450(2001)040<0753:PBFTTB>2.0.CO;2, 2001. a
Ólafsdóttir, S., Jennings, A. E., Áslaug Geirsdóttir, Andrews, J., and
Miller, G. H.: Holocene variability of the North Atlantic Irminger current on
the south- and northwest shelf of Iceland, Marine Micropaleontol., 77, 101–118, https://doi.org/10.1016/j.marmicro.2010.08.002, 2010. a
Pálsson, F. and Gunnarsson, A.: Afkomu- og hraðamælingar á
Langjökli : jökulárið 2012–2013., Tech. Rep.
LV-2015-076, Landsvirkjun, Reykjavík, Iceland, 2015. a
Pálsson, F., Guðmundsson, S., and Björnsson, H.: Afkomu- og
hraðamælingar á Langjökli jökulárið
2011–2012., Tech. Rep. LV-2014-076, Landsvirkjun, Reykjavík, Iceland, 2013. a
Pálsson, F., Gunnarsson, A., Pálsson, H. S., and Steinþórsson, S.: Afkomu-
og hraðamælingar á Langjökli jökulárið 2012–2013, Landsvirkjun,
Reykjavík, Iceland, LV-2015-076, 1–37, 2015. a
Pálsson, F., Gunnarsson, A., Jónsson, G., Pálsson, H. S., and
Steinþórsson, S.: Vatnajökull: Mass balance, meltwater drainage and
surface velocity of the glacial year 2014–15, Tech. Rep. LV-2016-031,
Landsvirkjun, Reykjavík, Iceland, 2016. a
Pálsson, F., Gunnarsson, A., Magnússon, E., Pálsson, H. S., Hannesdóttir,
H., Þórhallsson, R., and Steinþórsson, S.: Vatnajökull: Mass balance,
meltwater drainage and surface velocity of the glacial year 2020–21,
Landsvirkjun, Reykjavík, LV-2022-009, 62, 2022. a
Paulson, C. A.: The Mathematical Representation of Wind Speed and Temperature
Profiles in the Unstable Atmospheric Surface Layer, J. Appl. Meteorol. Climatol., 9, 857–861,
https://doi.org/10.1175/1520-0450(1970)009<0857:TMROWS>2.0.CO;2, 1970. a
Perkins, H., Hopkins, T. S., Malmberg, S.-A., Poulain, P.-M., and Warn-Varnas,
A.: Oceanographic conditions east of Iceland, J. Geophys. Res.-Oceans, 103, 21531–21542, https://doi.org/10.1029/98JC00890,
1998. a
Plüss, C. and Ohmura, A.: Longwave Radiation on Snow-Covered Mountainous
Surfaces, J. Appl. Meteorol., 36, 818–824,
https://doi.org/10.1175/1520-0450-36.6.818, 1997. a
Rahmstorf, S., Box, J. E., Feulner, G., Mann, M. E., Robinson, A., Rutherford,
S., and Schaffernicht, E. J.: Exceptional twentieth-century slowdown in
Atlantic Ocean overturning circulation, Nat. Clim. Change, 5, 475–480,
https://doi.org/10.1038/nclimate2554, 2015. a
Renner, A. H. H., Sundfjord, A., Janout, M. A., Ingvaldsen, R. B.,
Beszczynska-Möller, A., Pickart, R. S., and Pérez-Hernández, M. D.:
Variability and Redistribution of Heat in the Atlantic Water Boundary Current
North of Svalbard, J. Geophys. Res.-Oceans, 123, 6373–6391,
https://doi.org/10.1029/2018JC013814, 2018. a
Rittger, K., Bair, E. H., Kahl, A., and Dozier, J.: Spatial estimates of snow
water equivalent from reconstruction, Adv. Water Resour., 94,
345–363, https://doi.org/10.1016/j.advwatres.2016.05.015, 2016. a
Rögnvaldsson, Ó. A.: Technical description of two different dynamical
downscaling time series for Icelandi, Tech. rep., Belgingur – Reiknistofa í
Veðurfræði, Belgingur, Reykjavik, Iceland, 2020. a
Rossby, T.: The North Atlantic Current and surrounding waters: At the
crossroads, Rev. Geophys., 34, 463–481, https://doi.org/10.1029/96RG02214,
1996. a
Salisbury, J. W., D'Aria, D. M., and Wald, A.: Measurements of thermal infrared
spectral reflectance of frost, snow, and ice, J. Geophys.
Res.-Sol. Ea., 99, 24235–24240, https://doi.org/10.1029/94JB00579, 1994. a
Schmidt, L. S., Adalgeirsdóttir, G., Guðmundsson, S., Langen, P. L., Pálsson, F., Mottram, R., Gascoin, S., and Björnsson, H.: The importance of accurate glacier albedo for estimates of surface mass balance on Vatnajökull: evaluating the surface energy budget in a regional climate model with automatic weather station observations, The Cryosphere, 11, 1665–1684, https://doi.org/10.5194/tc-11-1665-2017, 2017. a, b, c, d, e, f
Schmidt, L. S., Adalgeirsdóttir, G., Pálsson, F., Langen, P. L.,
Gudmundsson, S., and Björnsson, H.: Dynamic simulations of Vatnajökull ice
cap from 1980 to 2300, J. Glaciol., 66, 97–112,
https://doi.org/10.1017/jog.2019.90, 2020. a, b, c
Sicart, J. E., Pomeroy, J. W., Essery, R. L. H., and Bewley, D.: Incoming
longwave radiation to melting snow: observations, sensitivity and estimation
in Northern environments, Hydrol. Process., 20, 3697–3708,
https://doi.org/10.1002/hyp.6383, 2006. a
Sicart, J. E., Hock, R., and Six, D.: Glacier melt, air temperature, and energy
balance in different climates: The Bolivian Tropics, the French Alps, and
northern Sweden, J. Geophys. Res.-Atmos., 113, D24113,
https://doi.org/10.1029/2008JD010406, 2008. a
Six, D., Wagnon, P., Sicart, J., 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. a
Slater, T., Lawrence, I. R., Otosaka, I. N., Shepherd, A., Gourmelen, N., Jakob, L., Tepes, P., Gilbert, L., and Nienow, P.: Review article: Earth's ice imbalance, The Cryosphere, 15, 233–246, https://doi.org/10.5194/tc-15-233-2021, 2021. a
Smeets, C. J. P. P. and van den Broeke, M. R.: The Parameterisation of Scalar
Transfer over Rough Ice, Bound.-Lay. Meteorol., 128, 339,
https://doi.org/10.1007/s10546-008-9292-z, 2008a. a
Smeets, C. J. P. P. and van den Broeke, M. R.: Temporal and Spatial Variations
of the Aerodynamic Roughness Length in the Ablation Zone of the Greenland Ice
Sheet, Bound.-Lay. Meteorol., 128, 315–338,
https://doi.org/10.1007/s10546-008-9291-0, 2008b. a
Smeets, C. J. P. P., Duynkerke, P. G., and Vugts, H. F.: Observed Wind Profiles
and Turbulence Fluxes over an ice Surface with Changing Surface Roughness,
Bound.-Lay. Meteorol., 92, 99–121, https://doi.org/10.1023/A:1001899015849, 1999. a
Stone, P. H. and Carlson, J. H.: Atmospheric Lapse Rate Regimes and Their
Parameterization, J. Atmos. Sci., 36, 415–423,
https://doi.org/10.1175/1520-0469(1979)036<0415:ALRRAT>2.0.CO;2, 1979. a
Sveinsson, Ó.: Energy in Iceland: Adaptation to Climate Change,
UNU-FLORES Policy Briefs, United Nations University Institute for
Integrated Management of Material Fluxes and of Resources (UNU-FLORES),
Dresden, 2016. a
Van As, D.: Warming, glacier melt and surface energy budget from weather
station observations in the Melville Bay region of northwest Greenland,
J. Glaciol., 57, 208–220, https://doi.org/10.3189/002214311796405898, 2011. a, b, c
van As, D., Broeke, M. V. D., Reijmer, C., and Wal, R. V. D.: The Summer
Surface Energy Balance of the High Antarctic Plateau, Bound.-Lay. Meteorol., 115, 289–317, https://doi.org/10.1007/s10546-004-4631-1, 2005. a, b
van As, D., Bech Mikkelsen, A., Holtegaard Nielsen, M., Box, J. E., Claesson Liljedahl, L., Lindbäck, K., Pitcher, L., and Hasholt, B.: Hypsometric amplification and routing moderation of Greenland ice sheet meltwater release, The Cryosphere, 11, 1371–1386, https://doi.org/10.5194/tc-11-1371-2017, 2017. a
van den Broeke, M. R., Smeets, C. J. P. P., and van de Wal, R. S. W.: The seasonal cycle and interannual variability of surface energy balance and melt in the ablation zone of the west Greenland ice sheet, The Cryosphere, 5, 377–390, https://doi.org/10.5194/tc-5-377-2011, 2011. a
Vandecrux, B., Fausto, R. S., Langen, P. L., van As, D., MacFerrin, M., Colgan,
W. T., Ingeman-Nielsen, T., Steffen, K., Jensen, N. S., Möller, M. T., and
Box, J. E.: Drivers of Firn Density on the Greenland Ice Sheet Revealed by
Weather Station Observations and Modeling, J. Geophys. Res.-Earth Surf., 123, 2563–2576, https://doi.org/10.1029/2017JF004597, 2018. a
Veðurstofa Íslands: Tíðarfar ársins 2021,
https://www.vedur.is/um-vi/frettir/tidarfar-arsins-2021 (last access: 1 September 2022),
2022. a
Warren, S. G. and Wiscombe, W. J.: A Model for the Spectral Albedo of Snow. II:
Snow Containing Atmospheric Aerosols, J. Atmos. Sci.,
37, 2734–2745, https://doi.org/10.1175/1520-0469(1980)037<2734:AMFTSA>2.0.CO;2, 1980. a
Wittmann, M., Groot Zwaaftink, C. D., Steffensen Schmidt, L., Guðmundsson, S., Pálsson, F., Arnalds, O., Björnsson, H., Thorsteinsson, T., and Stohl, A.: Impact of dust deposition on the albedo of Vatnajökull ice cap, Iceland, The Cryosphere, 11, 741–754, https://doi.org/10.5194/tc-11-741-2017, 2017. a, b, c
WMO: Systematic Observation Requirements for Satellite-based Products for
Climate Supplemental details to the satellite-based component of the
Implementation Plan for the Global Observing System for Climate in Support of
the UNFCCC: 2011 update, GCOS- No. 154, p. 138, 2011. 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
Zhao, J., Yang, J., Semper, S., Pickart, R. S., Våge, K., Valdimarsson, H.,
and Jónsson, S.: A Numerical Study of Interannual Variability in the North
Icelandic Irminger Current, J. Geophys. Res.-Oceans, 123,
8994–9009, https://doi.org/10.1029/2018JC013800, 2018. a
Short summary
A model was developed with the possibility of utilizing satellite-derived daily surface albedo driven by high-resolution climate data to estimate the surface energy balance (SEB) for all Icelandic glaciers for the period 2000–2021.
A model was developed with the possibility of utilizing satellite-derived daily surface albedo...