Articles | Volume 13, issue 7
https://doi.org/10.5194/tc-13-1843-2019
© Author(s) 2019. 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-13-1843-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Thermal conductivity of firn at Lomonosovfonna, Svalbard, derived from subsurface temperature measurements
Sergey Marchenko
CORRESPONDING AUTHOR
Department of Earth Sciences, Uppsala University, Uppsala, Sweden
Gong Cheng
Department of Information Technology, Uppsala University, Uppsala, Sweden
Per Lötstedt
Department of Information Technology, Uppsala University, Uppsala, Sweden
Veijo Pohjola
Department of Earth Sciences, Uppsala University, Uppsala, Sweden
Rickard Pettersson
Department of Earth Sciences, Uppsala University, Uppsala, Sweden
Ward van Pelt
Department of Earth Sciences, Uppsala University, Uppsala, Sweden
Carleen Reijmer
Institute for Marine and Atmospheric Research, Utrecht University, Utrecht, the Netherlands
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The Cryosphere, 14, 3785–3810, https://doi.org/10.5194/tc-14-3785-2020, https://doi.org/10.5194/tc-14-3785-2020, 2020
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In the vast interior of the Greenland ice sheet, snow accumulates into a thick and porous layer called firn. Each summer, the firn retains part of the meltwater generated at the surface and buffers sea-level rise. In this study, we compare nine firn models traditionally used to quantify this retention at four sites and evaluate their performance against a set of in situ observations. We highlight limitations of certain model designs and give perspectives for future model development.
Ward van Pelt, Veijo Pohjola, Rickard Pettersson, Sergey Marchenko, Jack Kohler, Bartłomiej Luks, Jon Ove Hagen, Thomas V. Schuler, Thorben Dunse, Brice Noël, and Carleen Reijmer
The Cryosphere, 13, 2259–2280, https://doi.org/10.5194/tc-13-2259-2019, https://doi.org/10.5194/tc-13-2259-2019, 2019
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The climate in Svalbard is undergoing amplified change compared to the global mean, which has a strong impact on the climatic mass balance of glaciers and the state of seasonal snow in land areas. In this study we analyze a coupled energy balance–subsurface model dataset, which provides detailed information on distributed climatic mass balance, snow conditions, and runoff across Svalbard between 1957 and 2018.
Shfaqat A. Khan, Helene Seroussi, Mathieu Morlighem, William Colgan, Veit Helm, Gong Cheng, Danjal Berg, Valentina R. Barletta, Nicolaj K. Larsen, William Kochtitzky, Michiel van den Broeke, Kurt H. Kjær, Andy Aschwanden, Brice Noël, Jason E. Box, Joseph A. MacGregor, Robert S. Fausto, Kenneth D. Mankoff, Ian M. Howat, Kuba Oniszk, Dominik Fahrner, Anja Løkkegaard, Eigil Y. H. Lippert, and Javed Hassan
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-348, https://doi.org/10.5194/essd-2024-348, 2024
Preprint under review for ESSD
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The surface elevation of the Greenland Ice Sheet is changing due to surface mass balance processes and ice dynamics, each exhibiting distinct spatiotemporal patterns. Here, we employ satellite and airborne altimetry data with fine spatial (1 km) and temporal (monthly) resolutions to document this spatiotemporal evolution from 2003 to 2023. This dataset of fine-resolution altimetry data in both space and time will support studies of ice mass loss and useful for GIS ice sheet modelling.
Gong Cheng, Mathieu Morlighem, and G. Hilmar Gudmundsson
Geosci. Model Dev., 17, 6227–6247, https://doi.org/10.5194/gmd-17-6227-2024, https://doi.org/10.5194/gmd-17-6227-2024, 2024
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We conducted a comprehensive analysis of the stabilization and reinitialization techniques currently employed in ISSM and Úa for solving level-set equations, specifically those related to the dynamic representation of moving ice fronts within numerical ice sheet models. Our results demonstrate that the streamline upwind Petrov–Galerkin (SUPG) method outperforms the other approaches. We found that excessively frequent reinitialization can lead to exceptionally high errors in simulations.
Younghyun Koo, Gong Cheng, Mathieu Morlighem, and Maryam Rahnemoonfar
EGUsphere, https://doi.org/10.5194/egusphere-2024-1620, https://doi.org/10.5194/egusphere-2024-1620, 2024
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Calving, the breaking of ice bodies from the terminus of a glacier, plays an important role in the mass losses of Greenland ice sheets. However, calving parameters have been poorly understood because of the intensive computational demands of traditional numerical models. To address this issue and find the optimal calving parameter that best represents real observations, we develop deep-learning emulators based on graph neural network architectures.
Ward van Pelt and Thomas Frank
EGUsphere, https://doi.org/10.5194/egusphere-2024-1525, https://doi.org/10.5194/egusphere-2024-1525, 2024
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Accurate information on the ice thickness of Svalbard’s glaciers is important for assessing the contribution to sea level rise in a present and future climate. However, direct observations of the glacier bed are scarce. Here, we use an inverse approach and high-resolution surface observations, to infer basal conditions. We present and analyze the new bed and thickness maps, quantify the ice volume (6,800 km3), and compare against radar data and previous studies.
Tim van den Akker, Ward van Pelt, Rickard Petterson, and Veijo A. Pohjola
EGUsphere, https://doi.org/10.5194/egusphere-2024-1345, https://doi.org/10.5194/egusphere-2024-1345, 2024
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Liquid water can persist within old snow on glaciers and ice caps, if it can percolate into it before it refreezes. Snow is a good insulator, and snow is porous where the percolated water can be stored. If this happens, the water piles up and forms a groundwater-like system. Here, we show observations of such a groundwater-like system found in Svalbard. We demonstrate that it behaves like a groundwater system, and use that to model the development of the water table from 1957 until present day.
Joel A. Wilner, Mathieu Morlighem, and Gong Cheng
The Cryosphere, 17, 4889–4901, https://doi.org/10.5194/tc-17-4889-2023, https://doi.org/10.5194/tc-17-4889-2023, 2023
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We use numerical modeling to study iceberg calving off of ice shelves in Antarctica. We examine four widely used mathematical descriptions of calving (
calving laws), under the assumption that Antarctic ice shelf front positions should be in steady state under the current climate forcing. We quantify how well each of these calving laws replicates the observed front positions. Our results suggest that the eigencalving and von Mises laws are most suitable for Antarctic ice shelves.
Thomas Frank, Ward J. J. van Pelt, and Jack Kohler
The Cryosphere, 17, 4021–4045, https://doi.org/10.5194/tc-17-4021-2023, https://doi.org/10.5194/tc-17-4021-2023, 2023
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Since the ice thickness of most glaciers worldwide is unknown, and since it is not feasible to visit every glacier and observe their thickness directly, inverse modelling techniques are needed that can calculate ice thickness from abundant surface observations. Here, we present a new method for doing that. Our methodology relies on modelling the rate of surface elevation change for a given glacier, compare this with observations of the same quantity and change the bed until the two are in line.
Yetang Wang, Xueying Zhang, Wentao Ning, Matthew A. Lazzara, Minghu Ding, Carleen H. Reijmer, Paul C. J. P. Smeets, Paolo Grigioni, Petra Heil, Elizabeth R. Thomas, David Mikolajczyk, Lee J. Welhouse, Linda M. Keller, Zhaosheng Zhai, Yuqi Sun, and Shugui Hou
Earth Syst. Sci. Data, 15, 411–429, https://doi.org/10.5194/essd-15-411-2023, https://doi.org/10.5194/essd-15-411-2023, 2023
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Here we construct a new database of Antarctic automatic weather station (AWS) meteorological records, which is quality-controlled by restrictive criteria. This dataset compiled all available Antarctic AWS observations, and its resolutions are 3-hourly, daily and monthly, which is very useful for quantifying spatiotemporal variability in weather conditions. Furthermore, this compilation will be used to estimate the performance of the regional climate models or meteorological reanalysis products.
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.
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.
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.
Yetang Wang, Minghu Ding, Carleen H. Reijmer, Paul C. J. P. Smeets, Shugui Hou, and Cunde Xiao
Earth Syst. Sci. Data, 13, 3057–3074, https://doi.org/10.5194/essd-13-3057-2021, https://doi.org/10.5194/essd-13-3057-2021, 2021
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Accurate observation of surface mass balance (SMB) under climate change is essential for the reliable present and future assessment of Antarctic contribution to global sea level. This study presents a new quality-controlled dataset of Antarctic SMB observations at different temporal resolutions and is the first ice-sheet-scale compilation of multiple types of measurements. The dataset can be widely applied to climate model validation, remote sensing retrievals, and data assimilation.
Maurice van Tiggelen, Paul C. J. P. Smeets, Carleen H. Reijmer, Bert Wouters, Jakob F. Steiner, Emile J. Nieuwstraten, Walter W. Immerzeel, and Michiel R. van den Broeke
The Cryosphere, 15, 2601–2621, https://doi.org/10.5194/tc-15-2601-2021, https://doi.org/10.5194/tc-15-2601-2021, 2021
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We developed a method to estimate the aerodynamic properties of the Greenland Ice Sheet surface using either UAV or ICESat-2 elevation data. We show that this new method is able to reproduce the important spatiotemporal variability in surface aerodynamic roughness, measured by the field observations. The new maps of surface roughness can be used in atmospheric models to improve simulations of surface turbulent heat fluxes and therefore surface energy and mass balance over rough ice worldwide.
Christian Zdanowicz, Jean-Charles Gallet, Mats P. Björkman, Catherine Larose, Thomas Schuler, Bartłomiej Luks, Krystyna Koziol, Andrea Spolaor, Elena Barbaro, Tõnu Martma, Ward van Pelt, Ulla Wideqvist, and Johan Ström
Atmos. Chem. Phys., 21, 3035–3057, https://doi.org/10.5194/acp-21-3035-2021, https://doi.org/10.5194/acp-21-3035-2021, 2021
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Black carbon (BC) aerosols are soot-like particles which, when transported to the Arctic, darken snow surfaces, thus indirectly affecting climate. Information on BC in Arctic snow is needed to measure their impact and monitor the efficacy of pollution-reduction policies. This paper presents a large new set of BC measurements in snow in Svalbard collected between 2007 and 2018. It describes how BC in snow varies across the archipelago and explores some factors controlling these variations.
Eric Keenan, Nander Wever, Marissa Dattler, Jan T. M. Lenaerts, Brooke Medley, Peter Kuipers Munneke, and Carleen Reijmer
The Cryosphere, 15, 1065–1085, https://doi.org/10.5194/tc-15-1065-2021, https://doi.org/10.5194/tc-15-1065-2021, 2021
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Snow density is required to convert observed changes in ice sheet volume into mass, which ultimately drives ice sheet contribution to sea level rise. However, snow properties respond dynamically to wind-driven redistribution. Here we include a new wind-driven snow density scheme into an existing snow model. Our results demonstrate an improved representation of snow density when compared to observations and can therefore be used to improve retrievals of ice sheet mass balance.
Gong Cheng, Nina Kirchner, and Per Lötstedt
The Cryosphere, 15, 715–742, https://doi.org/10.5194/tc-15-715-2021, https://doi.org/10.5194/tc-15-715-2021, 2021
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We present an inverse modeling approach to improve the understanding of spatiotemporally variable processes at the inaccessible base of an ice sheet by determining the sensitivity of direct surface observations to perturbations of basal conditions. Time dependency is proved to be important in these types of problems. The effect of perturbations is analyzed based on analytical and numerical solutions.
Baojuan Huai, Michiel R. van den Broeke, and Carleen H. Reijmer
The Cryosphere, 14, 4181–4199, https://doi.org/10.5194/tc-14-4181-2020, https://doi.org/10.5194/tc-14-4181-2020, 2020
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This study presents the surface energy balance (SEB) of the Greenland Ice Sheet (GrIS) using a SEB model forced with observations from automatic weather stations (AWSs). We correlate ERA5 with AWSs to show a significant positive correlation of GrIS summer surface temperature and melt with the Greenland Blocking Index and weaker and opposite correlations with the North Atlantic Oscillation. This analysis may help explain melting patterns in the GrIS with respect to circulation anomalies.
Baptiste Vandecrux, Ruth Mottram, Peter L. Langen, Robert S. Fausto, Martin Olesen, C. Max Stevens, Vincent Verjans, Amber Leeson, Stefan Ligtenberg, Peter Kuipers Munneke, Sergey Marchenko, Ward van Pelt, Colin R. Meyer, Sebastian B. Simonsen, Achim Heilig, Samira Samimi, Shawn Marshall, Horst Machguth, Michael MacFerrin, Masashi Niwano, Olivia Miller, Clifford I. Voss, and Jason E. Box
The Cryosphere, 14, 3785–3810, https://doi.org/10.5194/tc-14-3785-2020, https://doi.org/10.5194/tc-14-3785-2020, 2020
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In the vast interior of the Greenland ice sheet, snow accumulates into a thick and porous layer called firn. Each summer, the firn retains part of the meltwater generated at the surface and buffers sea-level rise. In this study, we compare nine firn models traditionally used to quantify this retention at four sites and evaluate their performance against a set of in situ observations. We highlight limitations of certain model designs and give perspectives for future model development.
Ankit Pramanik, Jack Kohler, Katrin Lindbäck, Penelope How, Ward Van Pelt, Glen Liston, and Thomas V. Schuler
The Cryosphere Discuss., https://doi.org/10.5194/tc-2020-197, https://doi.org/10.5194/tc-2020-197, 2020
Revised manuscript not accepted
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Freshwater discharge from tidewater glaciers influences fjord circulation and fjord ecosystem. Glacier hydrology plays crucial role in transporting water underneath glacier ice. We investigated hydrology beneath the tidewater glaciers of Kongsfjord basin in Northwest Svalbard and found that subglacial water flow differs substantially from surface flow of glacier ice. Furthermore, we derived freshwater discharge time-series from all the glaciers to the fjord.
Gong Cheng, Per Lötstedt, and Lina von Sydow
Geosci. Model Dev., 13, 2245–2258, https://doi.org/10.5194/gmd-13-2245-2020, https://doi.org/10.5194/gmd-13-2245-2020, 2020
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A full Stokes subgrid scheme in two dimensions for the grounding line migration problem is presented in the open-source finite-element framework Elmer/ICE. This method can achieve comparable results to previous research using a more than 20 times larger mesh size, which can be used to improve the efficiency in marine ice sheet simulations.
Gong Cheng and Per Lötstedt
The Cryosphere, 14, 673–691, https://doi.org/10.5194/tc-14-673-2020, https://doi.org/10.5194/tc-14-673-2020, 2020
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We present a time-dependent inverse method for ice sheet modeling. By investigating the sensitivity of the observations of the velocity and the height at the surface to the basal conditions of the ice, we show that if the basal parameters are time dependent, then time cannot be ignored in the inversion. By looking at the numerical features, we conclude that adding the height information of an ice sheet in the velocity inversion procedure could improve the robustness of the inference.
Ward van Pelt, Veijo Pohjola, Rickard Pettersson, Sergey Marchenko, Jack Kohler, Bartłomiej Luks, Jon Ove Hagen, Thomas V. Schuler, Thorben Dunse, Brice Noël, and Carleen Reijmer
The Cryosphere, 13, 2259–2280, https://doi.org/10.5194/tc-13-2259-2019, https://doi.org/10.5194/tc-13-2259-2019, 2019
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The climate in Svalbard is undergoing amplified change compared to the global mean, which has a strong impact on the climatic mass balance of glaciers and the state of seasonal snow in land areas. In this study we analyze a coupled energy balance–subsurface model dataset, which provides detailed information on distributed climatic mass balance, snow conditions, and runoff across Svalbard between 1957 and 2018.
Thomas J. Ballinger, Thomas L. Mote, Kyle Mattingly, Angela C. Bliss, Edward Hanna, Dirk van As, Melissa Prieto, Saeideh Gharehchahi, Xavier Fettweis, Brice Noël, Paul C. J. P. Smeets, Carleen H. Reijmer, Mads H. Ribergaard, and John Cappelen
The Cryosphere, 13, 2241–2257, https://doi.org/10.5194/tc-13-2241-2019, https://doi.org/10.5194/tc-13-2241-2019, 2019
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Arctic sea ice and the Greenland Ice Sheet (GrIS) are melting later in the year due to a warming climate. Through analyses of weather station, climate model, and reanalysis data, physical links are evaluated between Baffin Bay open water duration and western GrIS melt conditions. We show that sub-Arctic air mass movement across this portion of the GrIS strongly influences late summer and autumn melt, while near-surface, off-ice winds inhibit westerly atmospheric heat transfer from Baffin Bay.
Constantijn L. Jakobs, Carleen H. Reijmer, Peter Kuipers Munneke, Gert König-Langlo, and Michiel R. van den Broeke
The Cryosphere, 13, 1473–1485, https://doi.org/10.5194/tc-13-1473-2019, https://doi.org/10.5194/tc-13-1473-2019, 2019
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We use 24 years of observations at Neumayer Station, East Antarctica, to calculate the surface energy balance and the associated surface melt, which we find to be mainly driven by the absorption of solar radiation. Meltwater can refreeze in the subsurface snow layers, thereby decreasing the surface albedo and hence allowing for more absorption of solar radiation. By implementing an albedo parameterisation, we show that this feedback accounts for a threefold increase in surface melt at Neumayer.
Dorothée Vallot, Sigit Adinugroho, Robin Strand, Penelope How, Rickard Pettersson, Douglas I. Benn, and Nicholas R. J. Hulton
Geosci. Instrum. Method. Data Syst., 8, 113–127, https://doi.org/10.5194/gi-8-113-2019, https://doi.org/10.5194/gi-8-113-2019, 2019
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This paper presents a novel method to quantify the sizes and frequency of calving events from time-lapse camera images. The calving front of a tidewater glacier experiences different episodes of iceberg deliveries that can be captured by a time-lapse camera situated in front of the glacier. An automatic way of detecting calving events is presented here and compared to manually detected events.
Eef C. H. van Dongen, Nina Kirchner, Martin B. van Gijzen, Roderik S. W. van de Wal, Thomas Zwinger, Gong Cheng, Per Lötstedt, and Lina von Sydow
Geosci. Model Dev., 11, 4563–4576, https://doi.org/10.5194/gmd-11-4563-2018, https://doi.org/10.5194/gmd-11-4563-2018, 2018
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Ice flow forced by gravity is governed by the full Stokes (FS) equations, which are computationally expensive to solve. Therefore, approximations to the FS equations are used, especially when modeling an ice sheet on long time spans. Here, we report a combination of an approximation with the FS equations that allows simulating the dynamics of ice sheets over long time spans without introducing artifacts caused by application of approximations in parts of the domain where they are not valid.
Katrin Lindbäck, Jack Kohler, Rickard Pettersson, Christopher Nuth, Kirsty Langley, Alexandra Messerli, Dorothée Vallot, Kenichi Matsuoka, and Ola Brandt
Earth Syst. Sci. Data, 10, 1769–1781, https://doi.org/10.5194/essd-10-1769-2018, https://doi.org/10.5194/essd-10-1769-2018, 2018
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Tidewater glaciers terminate directly into the sea and the glacier fronts are important feeding areas for birds and marine mammals. Svalbard tidewater glaciers are retreating, which will affect fjord circulation and ecosystems when glacier fronts end on land. In this paper, we present digital maps of ice thickness and topography under five tidewater glaciers in Kongsfjorden, northwestern Svalbard, which will be useful in studies of future glacier changes in the area.
Jiangjun Ran, Miren Vizcaino, Pavel Ditmar, Michiel R. van den Broeke, Twila Moon, Christian R. Steger, Ellyn M. Enderlin, Bert Wouters, Brice Noël, Catharina H. Reijmer, Roland Klees, Min Zhong, Lin Liu, and Xavier Fettweis
The Cryosphere, 12, 2981–2999, https://doi.org/10.5194/tc-12-2981-2018, https://doi.org/10.5194/tc-12-2981-2018, 2018
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To accurately predict future sea level rise, the mechanisms driving the observed mass loss must be better understood. Here, we combine data from the satellite gravimetry, surface mass balance, and ice discharge to analyze the mass budget of Greenland at various temporal scales. This study, for the first time, suggests the existence of a substantial meltwater storage during summer, with a peak value of 80–120 Gt in July. We highlight its importance for understanding ice sheet mass variability
Jan Melchior van Wessem, Willem Jan van de Berg, Brice P. Y. Noël, Erik van Meijgaard, Charles Amory, Gerit Birnbaum, Constantijn L. Jakobs, Konstantin Krüger, Jan T. M. Lenaerts, Stef Lhermitte, Stefan R. M. Ligtenberg, Brooke Medley, Carleen H. Reijmer, Kristof van Tricht, Luke D. Trusel, Lambertus H. van Ulft, Bert Wouters, Jan Wuite, and Michiel R. van den Broeke
The Cryosphere, 12, 1479–1498, https://doi.org/10.5194/tc-12-1479-2018, https://doi.org/10.5194/tc-12-1479-2018, 2018
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We present a detailed evaluation of the latest version of the regional atmospheric climate model RACMO2.3p2 (1979-2016) over the Antarctic ice sheet. The model successfully reproduces the present-day climate and surface mass balance (SMB) when compared with an extensive set of observations and improves on previous estimates of the Antarctic climate and SMB.
This study shows that the latest version of RACMO2 can be used for high-resolution future projections over the AIS.
Solveig H. Winsvold, Andreas Kääb, Christopher Nuth, Liss M. Andreassen, Ward J. J. van Pelt, and Thomas Schellenberger
The Cryosphere, 12, 867–890, https://doi.org/10.5194/tc-12-867-2018, https://doi.org/10.5194/tc-12-867-2018, 2018
Dorothée Vallot, Jan Åström, Thomas Zwinger, Rickard Pettersson, Alistair Everett, Douglas I. Benn, Adrian Luckman, Ward J. J. van Pelt, Faezeh Nick, and Jack Kohler
The Cryosphere, 12, 609–625, https://doi.org/10.5194/tc-12-609-2018, https://doi.org/10.5194/tc-12-609-2018, 2018
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This paper presents a new perspective on the role of ice dynamics and ocean interaction in glacier calving processes applied to Kronebreen, a tidewater glacier in Svalbard. A global modelling approach includes ice flow modelling, undercutting estimation by a combination of glacier energy balance and plume modelling as well as calving by a discrete particle model. We show that modelling undercutting is necessary and calving is influenced by basal friction velocity and geometry.
Penelope How, Douglas I. Benn, Nicholas R. J. Hulton, Bryn Hubbard, Adrian Luckman, Heïdi Sevestre, Ward J. J. van Pelt, Katrin Lindbäck, Jack Kohler, and Wim Boot
The Cryosphere, 11, 2691–2710, https://doi.org/10.5194/tc-11-2691-2017, https://doi.org/10.5194/tc-11-2691-2017, 2017
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This study provides valuable insight into subglacial hydrology and dynamics at tidewater glaciers, which remains a poorly understood area of glaciology. It is a unique study because of the wealth of information provided by simultaneous observations of glacier hydrology at Kronebreen, a tidewater glacier in Svalbard. All these elements build a strong conceptual picture of the glacier's hydrological regime over the 2014 melt season.
Christian R. Steger, Carleen H. Reijmer, and Michiel R. van den Broeke
The Cryosphere, 11, 2507–2526, https://doi.org/10.5194/tc-11-2507-2017, https://doi.org/10.5194/tc-11-2507-2017, 2017
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Mass loss from the Greenland Ice Sheet, which contributes to sea level rise, is currently dominated by surface melt and run-off. The relation between these two variables is rather uncertain due to the firn layer’s potential to buffer melt in solid (refreezing) or liquid (firn aquifer) form. To address this uncertainty, we analyse output of a numerical firn model run over 1960–2014. Results show a spatially variable response of the ice sheet to increasing melt and an upward migration of aquifers.
Johannes Jakob Fürst, Fabien Gillet-Chaulet, Toby J. Benham, Julian A. Dowdeswell, Mariusz Grabiec, Francisco Navarro, Rickard Pettersson, Geir Moholdt, Christopher Nuth, Björn Sass, Kjetil Aas, Xavier Fettweis, Charlotte Lang, Thorsten Seehaus, and Matthias Braun
The Cryosphere, 11, 2003–2032, https://doi.org/10.5194/tc-11-2003-2017, https://doi.org/10.5194/tc-11-2003-2017, 2017
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For the large majority of glaciers and ice caps, there is no information on the thickness of the ice cover. Any attempt to predict glacier demise under climatic warming and to estimate the future contribution to sea-level rise is limited as long as the glacier thickness is not well constrained. Here, we present a two-step mass-conservation approach for mapping ice thickness. Measurements are naturally reproduced. The reliability is readily assessible from a complementary map of error estimates.
Daniel Farinotti, Douglas J. Brinkerhoff, Garry K. C. Clarke, Johannes J. Fürst, Holger Frey, Prateek Gantayat, Fabien Gillet-Chaulet, Claire Girard, Matthias Huss, Paul W. Leclercq, Andreas Linsbauer, Horst Machguth, Carlos Martin, Fabien Maussion, Mathieu Morlighem, Cyrille Mosbeux, Ankur Pandit, Andrea Portmann, Antoine Rabatel, RAAJ Ramsankaran, Thomas J. Reerink, Olivier Sanchez, Peter A. Stentoft, Sangita Singh Kumari, Ward J. J. van Pelt, Brian Anderson, Toby Benham, Daniel Binder, Julian A. Dowdeswell, Andrea Fischer, Kay Helfricht, Stanislav Kutuzov, Ivan Lavrentiev, Robert McNabb, G. Hilmar Gudmundsson, Huilin Li, and Liss M. Andreassen
The Cryosphere, 11, 949–970, https://doi.org/10.5194/tc-11-949-2017, https://doi.org/10.5194/tc-11-949-2017, 2017
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ITMIX – the Ice Thickness Models Intercomparison eXperiment – was the first coordinated performance assessment for models inferring glacier ice thickness from surface characteristics. Considering 17 different models and 21 different test cases, we show that although solutions of individual models can differ considerably, an ensemble average can yield uncertainties in the order of 10 ± 24 % the mean ice thickness. Ways forward for improving such estimates are sketched.
Thomas Schellenberger, Thorben Dunse, Andreas Kääb, Thomas Vikhamar Schuler, Jon Ove Hagen, and Carleen H. Reijmer
The Cryosphere Discuss., https://doi.org/10.5194/tc-2017-5, https://doi.org/10.5194/tc-2017-5, 2017
Preprint withdrawn
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Basin-3, NE-Svalbard, was still surging with 10 m d-1 in July 2016. After a speed peak of 18.8 m d-1 in Dec 2012/Jan 2013, speed-ups are overlying the fast flow every summer. The glacier is massively calving icebergs (5.2 Gt yr-1 ~ 2 L drinking water for every human being daily!) which in the same order of magnitude as all other Svalbard glaciers together.
Since autumn 2015 also Basin-2 is surging with maximum velocities of 8.7 m d-1, an advance of more than 2 km and a mass loss of 0.7 Gt yr-1.
Torbjørn Ims Østby, Thomas Vikhamar Schuler, Jon Ove Hagen, Regine Hock, Jack Kohler, and Carleen H. Reijmer
The Cryosphere, 11, 191–215, https://doi.org/10.5194/tc-11-191-2017, https://doi.org/10.5194/tc-11-191-2017, 2017
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We present modelled climatic mass balance for all glaciers in Svalbard for the period 1957–2014 at 1 km resolution using a coupled surface energy balance and snowpack model, thereby closing temporal and spatial gaps in direct and geodetic mass balance estimates.
Supporting previous studies, our results indicate increased mass loss over the period.
A detailed analysis of the involved energy fluxes reveals that increased mass loss is caused by atmospheric warming further amplified by feedbacks.
Andreas Bech Mikkelsen, Alun Hubbard, Mike MacFerrin, Jason Eric Box, Sam H. Doyle, Andrew Fitzpatrick, Bent Hasholt, Hannah L. Bailey, Katrin Lindbäck, and Rickard Pettersson
The Cryosphere, 10, 1147–1159, https://doi.org/10.5194/tc-10-1147-2016, https://doi.org/10.5194/tc-10-1147-2016, 2016
Carmen P. Vega, Veijo A. Pohjola, Emilie Beaudon, Björn Claremar, Ward J. J. van Pelt, Rickard Pettersson, Elisabeth Isaksson, Tõnu Martma, Margit Schwikowski, and Carl E. Bøggild
The Cryosphere, 10, 961–976, https://doi.org/10.5194/tc-10-961-2016, https://doi.org/10.5194/tc-10-961-2016, 2016
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To quantify post-depositional relocation of major ions by meltwater in snow and firn at Lomonosovfonna, Svalbard, consecutive ice cores drilled at this site were used to construct a synthetic core. The relocation length of most of the ions was on the order of 1 m between 2007 and 2010. Considering the ionic relocation lengths and annual melt percentages, we estimate that the atmospheric ionic signal remains preserved in recently drilled Lomonosovfonna ice cores at an annual or bi-annual resolution.
J. M. van Wessem, S. R. M. Ligtenberg, C. H. Reijmer, W. J. van de Berg, M. R. van den Broeke, N. E. Barrand, E. R. Thomas, J. Turner, J. Wuite, T. A. Scambos, and E. van Meijgaard
The Cryosphere, 10, 271–285, https://doi.org/10.5194/tc-10-271-2016, https://doi.org/10.5194/tc-10-271-2016, 2016
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This study presents the first high-resolution (5.5 km) modelled estimate of surface mass balance (SMB) over the period 1979–2014 for the Antarctic Peninsula (AP). Precipitation (snowfall and rain) largely determines the SMB, and is exceptionally high over the western mountain slopes, with annual values > 4 m water equivalent. Snowmelt is widespread over the AP, but only runs off into the ocean at some locations: the Larsen B,C, and Wilkins ice shelves, and along the north-western mountains.
T. Schellenberger, T. Dunse, A. Kääb, J. Kohler, and C. H. Reijmer
The Cryosphere, 9, 2339–2355, https://doi.org/10.5194/tc-9-2339-2015, https://doi.org/10.5194/tc-9-2339-2015, 2015
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Kronebreen and Kongsbreen are among the fastest flowing glaciers on Svalbard, and surface speeds reached up to 3.2m d-1 at Kronebreen in summer 2013 and 2.7m d-1 at Kongsbreen in late autumn 2012 as retrieved from SAR satellite data. Both glaciers retreated significantly during the observation period, Kongsbreen up to 1800m or 2.5km2 and Kronebreen up to 850m or 2.8km2. Both glaciers are important contributors to the total dynamic mass loss from the Svalbard archipelago.
Y. Sjöberg, P. Marklund, R. Pettersson, and S. W. Lyon
The Cryosphere, 9, 465–478, https://doi.org/10.5194/tc-9-465-2015, https://doi.org/10.5194/tc-9-465-2015, 2015
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Permafrost peatlands are hydrological and biogeochemical hotspots in discontinuous permafrost areas. We estimate the depths to the permafrost table surface and base across a peatland in northern Sweden using ground penetrating radar and electrical resistivity tomography. Seasonal frost tables, taliks, and the permafrost base could be detected. The results highlight the added value of combining techniques for assessing distributions of permafrost in the rapidly changing sporadic permafrost zone.
T. Dunse, T. Schellenberger, J. O. Hagen, A. Kääb, T. V. Schuler, and C. H. Reijmer
The Cryosphere, 9, 197–215, https://doi.org/10.5194/tc-9-197-2015, https://doi.org/10.5194/tc-9-197-2015, 2015
M. Schäfer, F. Gillet-Chaulet, R. Gladstone, R. Pettersson, V. A. Pohjola, T. Strozzi, and T. Zwinger
The Cryosphere, 8, 1951–1973, https://doi.org/10.5194/tc-8-1951-2014, https://doi.org/10.5194/tc-8-1951-2014, 2014
K. Lindbäck, R. Pettersson, S. H. Doyle, C. Helanow, P. Jansson, S. S. Kristensen, L. Stenseng, R. Forsberg, and A. L. Hubbard
Earth Syst. Sci. Data, 6, 331–338, https://doi.org/10.5194/essd-6-331-2014, https://doi.org/10.5194/essd-6-331-2014, 2014
H. Fréville, E. Brun, G. Picard, N. Tatarinova, L. Arnaud, C. Lanconelli, C. Reijmer, and M. van den Broeke
The Cryosphere, 8, 1361–1373, https://doi.org/10.5194/tc-8-1361-2014, https://doi.org/10.5194/tc-8-1361-2014, 2014
J. M. van Wessem, C. H. Reijmer, J. T. M. Lenaerts, W. J. van de Berg, M. R. van den Broeke, and E. van Meijgaard
The Cryosphere, 8, 125–135, https://doi.org/10.5194/tc-8-125-2014, https://doi.org/10.5194/tc-8-125-2014, 2014
J. Ahlkrona, N. Kirchner, and P. Lötstedt
Geosci. Model Dev., 6, 2135–2152, https://doi.org/10.5194/gmd-6-2135-2013, https://doi.org/10.5194/gmd-6-2135-2013, 2013
C. Nuth, J. Kohler, M. König, A. von Deschwanden, J. O. Hagen, A. Kääb, G. Moholdt, and R. Pettersson
The Cryosphere, 7, 1603–1621, https://doi.org/10.5194/tc-7-1603-2013, https://doi.org/10.5194/tc-7-1603-2013, 2013
A. P. Ahlstrøm, S. B. Andersen, M. L. Andersen, H. Machguth, F. M. Nick, I. Joughin, C. H. Reijmer, R. S. W. van de Wal, J. P. Merryman Boncori, J. E. Box, M. Citterio, D. van As, R. S. Fausto, and A. Hubbard
Earth Syst. Sci. Data, 5, 277–287, https://doi.org/10.5194/essd-5-277-2013, https://doi.org/10.5194/essd-5-277-2013, 2013
W. J. J. van Pelt, J. Oerlemans, C. H. Reijmer, R. Pettersson, V. A. Pohjola, E. Isaksson, and D. Divine
The Cryosphere, 7, 987–1006, https://doi.org/10.5194/tc-7-987-2013, https://doi.org/10.5194/tc-7-987-2013, 2013
S. H. Doyle, A. L. Hubbard, C. F. Dow, G. A. Jones, A. Fitzpatrick, A. Gusmeroli, B. Kulessa, K. Lindback, R. Pettersson, and J. E. Box
The Cryosphere, 7, 129–140, https://doi.org/10.5194/tc-7-129-2013, https://doi.org/10.5194/tc-7-129-2013, 2013
M. A. G. den Ouden, C. H. Reijmer, V. Pohjola, R. S. W. van de Wal, J. Oerlemans, and W. Boot
The Cryosphere, 4, 593–604, https://doi.org/10.5194/tc-4-593-2010, https://doi.org/10.5194/tc-4-593-2010, 2010
Cited articles
Bartelt, P. and Lehning, M.: A physical SNOWPACK model for the Swiss avalanche warning: Part I: numerical model, Cold Reg. Sci. Tech., 35, 123–145, https://doi.org/10.1016/S0165-232X(02)00074-5, 2002. a
Brandt, R. E. and Warren, S. G.: Temperature measurements and heat transfer in near-surface snow at the South Pole, J. Glaciol., 43, 339–351, https://doi.org/10.3189/S0022143000003294, 1997. a
Dalrymple, P. C., Lettau, H. H., and Wollaston, S. H.: South Pole Micrometeorology Program: Data Analysis1, American Geophysical Union, 13–57, https://doi.org/10.1029/AR009p0013, 1966. a
Dunse, T., Eisen, O., Helm, V., Rack, W., Steinhage, D., and Parry, V.: Characteristics and small-scale variability of GPR signals and their relation to snow accumulation in Greenland's percolation zone, J. Glaciol., 54, 333–342, https://doi.org/10.3189/002214308784886207, 2008. a
Jordan, R., Albert, M., and Brun, E.: Physical processes within the snow cover and their parameterization, in: Snow and climate: physical processes, surface energy exchange and modeling, Cambridge University Press, Cambridge, England, 12–69, 2008. a
Kaempfer, T. U., Schneebeli, M., and Sokratov, S. A.: A microstructural approach to model heat transfer in snow, Geophys. Res. Lett., 32, L21503, https://doi.org/10.1029/2005GL023873, 2005. a, b
Lange, M. A.: Measurements of thermal parameters in antarctic snow and firn, Ann. Glaciol., 6, 100–104, https://doi.org/10.3189/1985AoG6-1-100-104, 1985. a
Ligtenberg, S. R. M., Helsen, M. M., and van den Broeke, M. R.: An improved semi-empirical model for the densification of Antarctic firn, The Cryosphere, 5, 809–819, https://doi.org/10.5194/tc-5-809-2011, 2011. a
Löwe, H., Riche, F., and Schneebeli, M.: A general treatment of snow microstructure exemplified by an improved relation for thermal conductivity, The Cryosphere, 7, 1473–1480, https://doi.org/10.5194/tc-7-1473-2013, 2013. a
Marchenko, S., Pohjola, V. A., Pettersson, R., van Pelt, W. J. J., Vega, C. P., Machguth, H., Bøggild, C. E., and Isaksson, E.: A plot-scale study of firn stratigraphy at Lomonosovfonna, Svalbard, using ice cores, borehole video and GPR surveys in 2012–14, J. Glaciol., 63, 67–78, https://doi.org/10.1017/jog.2016.118, 2017a. a, b, c, d, e
Marchenko, S., van Pelt, W. J. J., Claremar, B., Pohjola, V., Pettersson, R., Machguth, H., and Reijmer, C.: Parameterizing Deep Water Percolation Improves Subsurface Temperature Simulations by a Multilayer Firn Model, Frontiers in Earth Science, 5, 16, https://doi.org/10.3389/feart.2017.00016, 2017b. a, b, c, d
Marchenko, S., Pohjola, V., and Pettersson, R.: Subsurface temperature at Lomonosovfonna, Svalbard, April 2012–2016, PANGAEA, https://doi.org/10.1594/PANGAEA.902613, 2019a. a
Marchenko, S., Pohjola, V., Pettersson, R., van Pelt, W., Vega, C., and Isaksson, E.: Density and stratigraphy of firn at Lomonosovfonna derived from shallow cores in 1997–2015, PANGAEA, https://doi.org/10.1594/PANGAEA.902221, 2019b. a
Morin, S., Domine, F., Arnaud, L., and Picard, G.: In-situ monitoring of the time evolution of the effective thermal conductivity of snow, Cold Reg. Sci. Technol., 64, 73–80, https://doi.org/10.1016/j.coldregions.2010.02.008, 2010. a
Nicolsky, D. J., Romanovsky, V. E., and Tipenko, G. S.: Using in-situ temperature measurements to estimate saturated soil thermal properties by solving a sequence of optimization problems, The Cryosphere, 1, 41–58, https://doi.org/10.5194/tc-1-41-2007, 2007. a
Oldroyd, H., Higgins, C., Huwald, H., Selker, J., and Parlange, M.: Thermal diffusivity of seasonal snow determined from temperature profiles, Adv. Water Resour., 55, 121–130, https://doi.org/10.1016/j.advwatres.2012.06.011, 2013. a
Osokin, N. and Sosnovsky, A.: Field investigation of efficient thermal conductivity of snow cover on Spitsbergen, Ice and Snow, 54, 50–58, https://doi.org/10.15356/2076-6734-2014-3-50-58, 2014 (in Russian). a
Pälli, A., Kohler, J. C., Isaksson, E., Moore, J. C., Pinglot, J. F., Pohjola, V. A., and Samuelsson, H.: Spatial and temporal variability of snow accumulation using ground-penetrating radar and ice cores on a Svalbard glacier, J. Glaciol., 48, 417–424, https://doi.org/10.3189/172756502781831205, 2002. a
Riche, F. and Schneebeli, M.: Microstructural change around a needle probe to measure thermal conductivity of snow, J. Glaciol., 56, 871–876, https://doi.org/10.3189/002214310794457164, 2010. a
Sergienko, O. V., MacAyeal, D. R., and Thom, J. E.: Reconstruction of snow/firn thermal diffusivities from observed temperature variation: application to iceberg C16, Ross Sea, Antarctica, 2004–07, Ann. Glaciol., 49, 91–95, https://doi.org/10.3189/172756408787814906, 2008. a, b, c
Singh, A. K.: An investigation of the thermal conductivity of snow, J.
Glaciol., 45, 346–351, https://doi.org/10.3189/S0022143000001842, 1999. a
Tervola, P.: A method to determine the thermal conductivity from measured temperature profiles, Int. J. Heat Mass Tran., 32, 1425 – 1430, https://doi.org/10.1016/0017-9310(89)90066-5, 1989. a
Trabant, D. C. and Mayo, L. R.: Estimation and effects of internal accumulation on five glaciers in Alaska, Ann. Glaciol., 6, 113–117, https://doi.org/10.3189/1985AoG6-1-113-117, 1985. a
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. a, b
van Pelt, W. J. J., Oerlemans, J., Reijmer, C. H., Pettersson, R., Pohjola, V. A., Isaksson, E., and Divine, D.: An iterative inverse method to estimate basal topography and initialize ice flow models, The Cryosphere, 7, 987–1006, https://doi.org/10.5194/tc-7-987-2013, 2013. a
van Pelt, W. J. J., Pettersson, R., Pohjola, V. A., Marchenko, S., Claremar, B., and Oerlemans, J.: Inverse estimation of snow accumulation along a radar transect on Nordenskiöldbreen, Svalbard, J. Geophys. Res.-Earth, 119, 816–835, https://doi.org/10.1002/2013JF003040, 2014. a
Weertman, J.: Creep Deformation of Ice, Annu. Rev. Earth Pl. Sc., 11, 215–240, https://doi.org/10.1146/annurev.ea.11.050183.001243, 1983. a
Weller, G. E. and Schwerdtfeger, P.: Short Notes: New Data on the Thermal Conductivity of Natural Snow, J. Glaciol., 10, 309–311, https://doi.org/10.3189/S0022143000013277, 1971. a
Wendl, I. A.: High resolution records of black carbon and other aerosol constituents from the Lomonosovfonna 2009 ice core, PhD thesis, Departement für Chemie und Biochemie der Universität Bern, 2014. a
Yang, C.-Y.: A linear inverse model for the temperature-dependent thermal conductivity determination in one-dimensional problems, Appl. Math. Model., 22, 1–9, https://doi.org/10.1016/S0307-904X(97)00101-7, 1998. a
Zhang, T. and Osterkamp, T.: Considerations in determining thermal diffusivity from temperature time series using finite difference methods, Cold Reg. Sci. Tech., 23, 333–341, https://doi.org/10.1016/0165-232X(94)00021-O, 1995. a
Short summary
Thermal conductivity (k) of firn at Lomonosovfonna, Svalbard, is estimated using measured temperature evolution and density. The optimized k values (0.2–1.6 W (m K)−1) increase downwards and over time and are most sensitive to systematic errors in measured temperature values and their depths, particularly in the lower part of the profile. Compared to the density-based parameterizations, derived k values are consistently larger, suggesting a faster conductive heat exchange in firn.
Thermal conductivity (k) of firn at Lomonosovfonna, Svalbard, is estimated using measured...