Articles | Volume 15, issue 6
https://doi.org/10.5194/tc-15-2819-2021
© Author(s) 2021. 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-15-2819-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
22 Jun 2021
Research article |
| 22 Jun 2021
| 22 Jun 2021
Implications of surface flooding on airborne estimates of snow depth on sea ice
Norwegian Polar Institute, Fram Centre, Tromsø, Norway
now at: Remote Sensing Technology Institute, German Aerospace Center
(DLR), Wessling, Germany
Sinead Louise Farrell
Department of Geographical Sciences, University of Maryland, College
Park, MD, USA
Vishnu Nandan
Centre for Earth Observation Science (CEOS), University of Manitoba, Manitoba,
MB, Canada
Jaqueline Richter-Menge
Institute of Northern Engineering, University of Alaska Fairbanks, Fairbanks, AK, USA
Gunnar Spreen
Institute of Environmental Physics, University of Bremen, Bremen,
Germany
Norwegian Polar Institute, Fram Centre, Tromsø, Norway
Dmitry V. Divine
Norwegian Polar Institute, Fram Centre, Tromsø, Norway
Adam Steer
Norwegian Polar Institute, Fram Centre, Tromsø, Norway
Jean-Charles Gallet
Norwegian Polar Institute, Fram Centre, Tromsø, Norway
Sebastian Gerland
Norwegian Polar Institute, Fram Centre, Tromsø, Norway
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Manfred Wendisch, Susanne Crewell, André Ehrlich, Andreas Herber, Benjamin Kirbus, Christof Lüpkes, Mario Mech, Steven J. Abel, Elisa F. Akansu, Felix Ament, Clémantyne Aubry, Sebastian Becker, Stephan Borrmann, Heiko Bozem, Marlen Brückner, Hans-Christian Clemen, Sandro Dahlke, Georgios Dekoutsidis, Julien Delanoë, Elena De La Torre Castro, Henning Dorff, Regis Dupuy, Oliver Eppers, Florian Ewald, Geet George, Irina V. Gorodetskaya, Sarah Grawe, Silke Groß, Jörg Hartmann, Silvia Henning, Lutz Hirsch, Evelyn Jäkel, Philipp Joppe, Olivier Jourdan, Zsofia Jurányi, Michail Karalis, Mona Kellermann, Marcus Klingebiel, Michael Lonardi, Johannes Lucke, Anna Luebke, Maximilian Maahn, Nina Maherndl, Marion Maturilli, Bernhard Mayer, Johanna Mayer, Stephan Mertes, Janosch Michaelis, Michel Michalkov, Guillaume Mioche, Manuel Moser, Hanno Müller, Roel Neggers, Davide Ori, Daria Paul, Fiona Paulus, Christian Pilz, Felix Pithan, Mira Pöhlker, Veronika Pörtge, Maximilian Ringel, Nils Risse, Gregory C. Roberts, Sophie Rosenburg, Johannes Röttenbacher, Janna Rückert, Michael Schäfer, Jonas Schäfer, Vera Schemannn, Imke Schirmacher, Jörg Schmidt, Sebastian Schmidt, Johannes Schneider, Sabrina Schnitt, Anja Schwarz, Holger Siebert, Harald Sodemann, Tim Sperzel, Gunnar Spreen, Bjorn Stevens, Frank Stratmann, Gunilla Svensson, Christian Tatzelt, Thomas Tuch, Timo Vihma, Christiane Voigt, Lea Volkmer, Andreas Walbröl, Anna Weber, Birgit Wehner, Bruno Wetzel, Martin Wirth, and Tobias Zinner
EGUsphere, https://doi.org/10.5194/egusphere-2024-783, https://doi.org/10.5194/egusphere-2024-783, 2024
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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The Arctic is warming faster than the rest of the globe. Warm air intrusions (WAIs) into the Arctic may play an important role in explaining this phenomenon. Cold air outbreaks (CAOs) out of the Arctic may link the Arctic climate changes to the mid-latitude weather. In our article we describe how to observe air mass transformations during CAOs and WAIs using three research aircraft instrumented wit state-of-the-art remote sensing and in-situ measurement devices.
Luisa von Albedyll, Stefan Hendricks, Nils Hutter, Dmitrii Murashkin, Lars Kaleschke, Sascha Willmes, Linda Thielke, Xiangshan Tian-Kunze, Gunnar Spreen, and Christian Haas
The Cryosphere, 18, 1259–1285, https://doi.org/10.5194/tc-18-1259-2024, https://doi.org/10.5194/tc-18-1259-2024, 2024
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Leads (openings in sea ice cover) are created by sea ice dynamics. Because they are important for many processes in the Arctic winter climate, we aim to detect them with satellites. We present two new techniques to detect lead widths of a few hundred meters at high spatial resolution (700 m) and independent of clouds or sun illumination. We use the MOSAiC drift 2019–2020 in the Arctic for our case study and compare our new products to other existing lead products.
Evelyn Jäkel, Sebastian Becker, Tim R. Sperzel, Hannah Niehaus, Gunnar Spreen, Ran Tao, Marcel Nicolaus, Wolfgang Dorn, Annette Rinke, Jörg Brauchle, and Manfred Wendisch
The Cryosphere, 18, 1185–1205, https://doi.org/10.5194/tc-18-1185-2024, https://doi.org/10.5194/tc-18-1185-2024, 2024
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The results of the surface albedo scheme of a coupled regional climate model were evaluated against airborne and ground-based measurements conducted in the European Arctic in different seasons between 2017 and 2022. We found a seasonally dependent bias between measured and modeled surface albedo for cloudless and cloudy situations. The strongest effects of the albedo model bias on the net irradiance were most apparent in the presence of optically thin clouds.
Nils Risse, Mario Mech, Catherine Prigent, Gunnar Spreen, and Susanne Crewell
EGUsphere, https://doi.org/10.5194/egusphere-2024-179, https://doi.org/10.5194/egusphere-2024-179, 2024
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Satellite passive microwave observations are crucial for monitoring the Arctic's sea ice and atmosphere. To do this effectively, it's important to understand how sea ice emits microwaves. Through unique Arctic sea ice observations, we've improved our understanding, identifying four distinct emission types and expanding current knowledge towards higher frequencies. These findings will enhance our ability to monitor the Arctic climate and provide valuable information for new satellite missions.
Hannah Niehaus, Larysa Istomina, Marcel Nicolaus, Ran Tao, Aleksey Malinka, Eleonora Zege, and Gunnar Spreen
The Cryosphere, 18, 933–956, https://doi.org/10.5194/tc-18-933-2024, https://doi.org/10.5194/tc-18-933-2024, 2024
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Melt ponds are puddles of meltwater which form on Arctic sea ice in the summer period. They are darker than the ice cover and lead to increased absorption of solar energy. Global climate models need information about the Earth's energy budget. Thus satellite observations are used to monitor the surface fractions of melt ponds, ocean, and sea ice in the entire Arctic. We present a new physically based algorithm that can separate these three surface types with uncertainty below 10 %.
Andrea Spolaor, Federico Scoto, Catherine Larose, Elena Barbaro, Francois Burgay, Mats P. Bjorkman, David Cappelletti, Federico Dallo, Fabrizio de Blasi, Dmitry Divine, Giuliano Dreossi, Jacopo Gabrieli, Elisabeth Isaksson, Jack Kohler, Tonu Martma, Louise S. Schmidt, Thomas V. Schuler, Barbara Stenni, Clara Turetta, Bartłomiej Luks, Mathieu Casado, and Jean-Charles Gallet
The Cryosphere, 18, 307–320, https://doi.org/10.5194/tc-18-307-2024, https://doi.org/10.5194/tc-18-307-2024, 2024
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We evaluate the impact of the increased snowmelt on the preservation of the oxygen isotope (δ18O) signal in firn records recovered from the top of the Holtedahlfonna ice field located in the Svalbard archipelago. Thanks to a multidisciplinary approach we demonstrate a progressive deterioration of the isotope signal in the firn core. We link the degradation of the δ18O signal to the increased occurrence and intensity of melt events associated with the rapid warming occurring in the archipelago.
Emma Nilsson, Carmen Paulina Vega, Dmitry Divine, Anja Eichler, Tonu Martma, Robert Mulvaney, Elisabeth Schlosser, Margit Schwikowski, and Elisabeth Isaksson
EGUsphere, https://doi.org/10.5194/egusphere-2023-3156, https://doi.org/10.5194/egusphere-2023-3156, 2024
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To project future climate change it is necessary to understand paleoclimate including past sea ice conditions. We have investigated methane sulphonic acid (MSA) in Antarctic firn and ice cores to reconstruct sea ice extent (SIE) and found that the MSA – SIE as well as the MSA – phytoplankton biomass relationship varies across the different firn and ice cores. These inconsistencies in correlations across records suggest that MSA in Fimbul Ice Shelf cores does not reliably indicate regional SIE.
Pablo Saavedra Garfias, Heike Kalesse-Los, Luisa von Albedyll, Hannes Griesche, and Gunnar Spreen
Atmos. Chem. Phys., 23, 14521–14546, https://doi.org/10.5194/acp-23-14521-2023, https://doi.org/10.5194/acp-23-14521-2023, 2023
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An important Arctic climate process is the release of heat fluxes from sea ice openings to the atmosphere that influence the clouds. The characterization of this process is the objective of this study. Using synergistic observations from the MOSAiC expedition, we found that single-layer cloud properties show significant differences when clouds are coupled or decoupled to the water vapour transport which is used as physical link between the upwind sea ice openings and the cloud under observation.
Larysa Istomina, Hannah Niehaus, and Gunnar Spreen
The Cryosphere Discuss., https://doi.org/10.5194/tc-2023-142, https://doi.org/10.5194/tc-2023-142, 2023
Preprint under review for TC
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Melt water puddles, or melt ponds on top of the Arctic sea ice are a good measure of the Arctic climate state. In the context of the recent climate warming, the Arctic has warmed about 4 times faster than the rest of the world, and a long-term dataset of the melt pond fraction is needed to be able to model the future development of the Arctic climate. We present such a dataset, produce 2002–2023 trends and highlight a potential melt regime shift with drastic regional trends of +20 % per decade.
Alexander Mchedlishvili, Christof Lüpkes, Alek Petty, Michel Tsamados, and Gunnar Spreen
The Cryosphere, 17, 4103–4131, https://doi.org/10.5194/tc-17-4103-2023, https://doi.org/10.5194/tc-17-4103-2023, 2023
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In this study we looked at sea ice–atmosphere drag coefficients, quantities that help with characterizing the friction between the atmosphere and sea ice, and vice versa. Using ICESat-2, a laser altimeter that measures elevation differences by timing how long it takes for photons it sends out to return to itself, we could map the roughness, i.e., how uneven the surface is. From roughness we then estimate drag force, the frictional force between sea ice and the atmosphere, across the Arctic.
Olivia Linke, Johannes Quaas, Finja Baumer, Sebastian Becker, Jan Chylik, Sandro Dahlke, André Ehrlich, Dörthe Handorf, Christoph Jacobi, Heike Kalesse-Los, Luca Lelli, Sina Mehrdad, Roel A. J. Neggers, Johannes Riebold, Pablo Saavedra Garfias, Niklas Schnierstein, Matthew D. Shupe, Chris Smith, Gunnar Spreen, Baptiste Verneuil, Kameswara S. Vinjamuri, Marco Vountas, and Manfred Wendisch
Atmos. Chem. Phys., 23, 9963–9992, https://doi.org/10.5194/acp-23-9963-2023, https://doi.org/10.5194/acp-23-9963-2023, 2023
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Lapse rate feedback (LRF) is a major driver of the Arctic amplification (AA) of climate change. It arises because the warming is stronger at the surface than aloft. Several processes can affect the LRF in the Arctic, such as the omnipresent temperature inversion. Here, we compare multimodel climate simulations to Arctic-based observations from a large research consortium to broaden our understanding of these processes, find synergy among them, and constrain the Arctic LRF and AA.
Philip Rostosky and Gunnar Spreen
The Cryosphere, 17, 3867–3881, https://doi.org/10.5194/tc-17-3867-2023, https://doi.org/10.5194/tc-17-3867-2023, 2023
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During winter, storms entering the Arctic region can bring warm air into the cold environment. Strong increases in air temperature modify the characteristics of the Arctic snow and ice cover. The Arctic sea ice cover can be monitored by satellites observing the natural emission of the Earth's surface. In this study, we show that during warm air intrusions the change in the snow characteristics influences the satellite-derived sea ice cover, leading to a false reduction of the estimated ice area.
Ellen M. Buckley, Sinéad L. Farrell, Ute C. Herzfeld, Melinda A. Webster, Thomas Trantow, Oliwia N. Baney, Kyle A. Duncan, Huilin Han, and Matthew Lawson
The Cryosphere, 17, 3695–3719, https://doi.org/10.5194/tc-17-3695-2023, https://doi.org/10.5194/tc-17-3695-2023, 2023
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In this study, we use satellite observations to investigate the evolution of melt ponds on the Arctic sea ice surface. We derive melt pond depth from ICESat-2 measurements of the pond surface and bathymetry and melt pond fraction (MPF) from the classification of Sentinel-2 imagery. MPF increases to a peak of 16 % in late June and then decreases, while depth increases steadily. This work demonstrates the ability to track evolving melt conditions in three dimensions throughout the summer.
Karl Kortum, Suman Singha, Gunnar Spreen, Nils Hutter, Arttu Jutila, and Christian Haas
The Cryosphere Discuss., https://doi.org/10.5194/tc-2023-72, https://doi.org/10.5194/tc-2023-72, 2023
Revised manuscript accepted for TC
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A dataset of 20 radar satellite acquisitions and near simultaneous helicopter-based measurements of the ice topography during an expedition is constructed and used to train a variety of deep learning algorithms. The results show, that the ice types derived directly from the helicopter measurement are harder to retrieve than those from human annotations. Models that can learn from the spatial distribution of measured sea ice classes are shown to have a clear advantage over those that cannot.
Vishnu Nandan, Rosemary Willatt, Robbie Mallett, Julienne Stroeve, Torsten Geldsetzer, Randall Scharien, Rasmus Tonboe, John Yackel, Jack Landy, David Clemens-Sewall, Arttu Jutila, David N. Wagner, Daniela Krampe, Marcus Huntemann, Mallik Mahmud, David Jensen, Thomas Newman, Stefan Hendricks, Gunnar Spreen, Amy Macfarlane, Martin Schneebeli, James Mead, Robert Ricker, Michael Gallagher, Claude Duguay, Ian Raphael, Chris Polashenski, Michel Tsamados, Ilkka Matero, and Mario Hoppmann
The Cryosphere, 17, 2211–2229, https://doi.org/10.5194/tc-17-2211-2023, https://doi.org/10.5194/tc-17-2211-2023, 2023
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We show that wind redistributes snow on Arctic sea ice, and Ka- and Ku-band radar measurements detect both newly deposited snow and buried snow layers that can affect the accuracy of snow depth estimates on sea ice. Radar, laser, meteorological, and snow data were collected during the MOSAiC expedition. With frequent occurrence of storms in the Arctic, our results show that
wind-redistributed snow needs to be accounted for to improve snow depth estimates on sea ice from satellite radars.
Robert Ricker, Steven Fons, Arttu Jutila, Nils Hutter, Kyle Duncan, Sinead L. Farrell, Nathan T. Kurtz, and Renée Mie Fredensborg Hansen
The Cryosphere, 17, 1411–1429, https://doi.org/10.5194/tc-17-1411-2023, https://doi.org/10.5194/tc-17-1411-2023, 2023
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Information on sea ice surface topography is important for studies of sea ice as well as for ship navigation through ice. The ICESat-2 satellite senses the sea ice surface with six laser beams. To examine the accuracy of these measurements, we carried out a temporally coincident helicopter flight along the same ground track as the satellite and measured the sea ice surface topography with a laser scanner. This showed that ICESat-2 can see even bumps of only few meters in the sea ice cover.
Wenkai Guo, Polona Itkin, Suman Singha, Anthony P. Doulgeris, Malin Johansson, and Gunnar Spreen
The Cryosphere, 17, 1279–1297, https://doi.org/10.5194/tc-17-1279-2023, https://doi.org/10.5194/tc-17-1279-2023, 2023
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Sea ice maps are produced to cover the MOSAiC Arctic expedition (2019–2020) and divide sea ice into scientifically meaningful classes. We use a high-resolution X-band synthetic aperture radar dataset and show how image brightness and texture systematically vary across the images. We use an algorithm that reliably corrects this effect and achieve good results, as evaluated by comparisons to ground observations and other studies. The sea ice maps are useful as a basis for future MOSAiC studies.
Christian Melsheimer, Gunnar Spreen, Yufang Ye, and Mohammed Shokr
The Cryosphere, 17, 105–126, https://doi.org/10.5194/tc-17-105-2023, https://doi.org/10.5194/tc-17-105-2023, 2023
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It is necessary to know the type of Antarctic sea ice present – first-year ice (grown in one season) or multiyear ice (survived one summer melt) – to understand and model its evolution, as the ice types behave and react differently. We have adapted and extended an existing method (originally for the Arctic), and now, for the first time, daily maps of Antarctic sea ice types can be derived from microwave satellite data. This will allow a new data set from 2002 well into the future to be built.
Julienne Stroeve, Vishnu Nandan, Rosemary Willatt, Ruzica Dadic, Philip Rostosky, Michael Gallagher, Robbie Mallett, Andrew Barrett, Stefan Hendricks, Rasmus Tonboe, Michelle McCrystall, Mark Serreze, Linda Thielke, Gunnar Spreen, Thomas Newman, John Yackel, Robert Ricker, Michel Tsamados, Amy Macfarlane, Henna-Reetta Hannula, and Martin Schneebeli
The Cryosphere, 16, 4223–4250, https://doi.org/10.5194/tc-16-4223-2022, https://doi.org/10.5194/tc-16-4223-2022, 2022
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Impacts of rain on snow (ROS) on satellite-retrieved sea ice variables remain to be fully understood. This study evaluates the impacts of ROS over sea ice on active and passive microwave data collected during the 2019–20 MOSAiC expedition. Rainfall and subsequent refreezing of the snowpack significantly altered emitted and backscattered radar energy, laying important groundwork for understanding their impacts on operational satellite retrievals of various sea ice geophysical variables.
Alexander Mchedlishvili, Gunnar Spreen, Christian Melsheimer, and Marcus Huntemann
The Cryosphere, 16, 471–487, https://doi.org/10.5194/tc-16-471-2022, https://doi.org/10.5194/tc-16-471-2022, 2022
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In this paper we show that the activity leading to the open-ocean polynyas near the Maud Rise seamount that have occurred repeatedly from 1974–1976 as well as 2016–2017 does not simply stop for polynya-free years. Using apparent sea ice thickness retrieval, we have identified anomalies where there is thinning of sea ice on a scale that is comparable to that of the polynya events of 2016–2017. These anomalies took place in 2010, 2013, 2014 and 2018.
Thomas Krumpen, Luisa von Albedyll, Helge F. Goessling, Stefan Hendricks, Bennet Juhls, Gunnar Spreen, Sascha Willmes, H. Jakob Belter, Klaus Dethloff, Christian Haas, Lars Kaleschke, Christian Katlein, Xiangshan Tian-Kunze, Robert Ricker, Philip Rostosky, Janna Rückert, Suman Singha, and Julia Sokolova
The Cryosphere, 15, 3897–3920, https://doi.org/10.5194/tc-15-3897-2021, https://doi.org/10.5194/tc-15-3897-2021, 2021
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We use satellite data records collected along the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) drift to categorize ice conditions that shaped and characterized the floe and surroundings during the expedition. A comparison with previous years is made whenever possible. The aim of this analysis is to provide a basis and reference for subsequent research in the six main research areas of atmosphere, ocean, sea ice, biogeochemistry, remote sensing and ecology.
Michele Bertò, David Cappelletti, Elena Barbaro, Cristiano Varin, Jean-Charles Gallet, Krzysztof Markowicz, Anna Rozwadowska, Mauro Mazzola, Stefano Crocchianti, Luisa Poto, Paolo Laj, Carlo Barbante, and Andrea Spolaor
Atmos. Chem. Phys., 21, 12479–12493, https://doi.org/10.5194/acp-21-12479-2021, https://doi.org/10.5194/acp-21-12479-2021, 2021
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We present the daily and seasonal variability in black carbon (BC) in surface snow inferred from two specific experiments based on the hourly and daily time resolution sampling during the Arctic spring in Svalbard. These unique data sets give us, for the first time, the opportunity to evaluate the associations between the observed surface snow BC mass concentration and a set of predictors corresponding to the considered meteorological and snow physico-chemical parameters.
Susanne Crewell, Kerstin Ebell, Patrick Konjari, Mario Mech, Tatiana Nomokonova, Ana Radovan, David Strack, Arantxa M. Triana-Gómez, Stefan Noël, Raul Scarlat, Gunnar Spreen, Marion Maturilli, Annette Rinke, Irina Gorodetskaya, Carolina Viceto, Thomas August, and Marc Schröder
Atmos. Meas. Tech., 14, 4829–4856, https://doi.org/10.5194/amt-14-4829-2021, https://doi.org/10.5194/amt-14-4829-2021, 2021
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Water vapor (WV) is an important variable in the climate system. Satellite measurements are thus crucial to characterize the spatial and temporal variability in WV and how it changed over time. In particular with respect to the observed strong Arctic warming, the role of WV still needs to be better understood. However, as shown in this paper, a detailed understanding is still hampered by large uncertainties in the various satellite WV products, showing the need for improved methods to derive WV.
Robbie D. C. Mallett, Julienne C. Stroeve, Michel Tsamados, Jack C. Landy, Rosemary Willatt, Vishnu Nandan, and Glen E. Liston
The Cryosphere, 15, 2429–2450, https://doi.org/10.5194/tc-15-2429-2021, https://doi.org/10.5194/tc-15-2429-2021, 2021
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We re-estimate pan-Arctic sea ice thickness (SIT) values by combining data from the Envisat and CryoSat-2 missions with data from a new, reanalysis-driven snow model. Because a decreasing amount of ice is being hidden below the waterline by the weight of overlying snow, we argue that SIT may be declining faster than previously calculated in some regions. Because the snow product varies from year to year, our new SIT calculations also display much more year-to-year variability.
Renée Mie Fredensborg Hansen, Eero Rinne, Sinéad Louise Farrell, and Henriette Skourup
The Cryosphere, 15, 2511–2529, https://doi.org/10.5194/tc-15-2511-2021, https://doi.org/10.5194/tc-15-2511-2021, 2021
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Ice navigators rely on timely information about ice conditions to ensure safe passage through ice-covered waters, and one parameter, the degree of ice ridging (DIR), is particularly useful. We have investigated the possibility of estimating DIR from the geolocated photons of ICESat-2 (IS2) in the Bay of Bothnia, show that IS2 retrievals from different DIR areas differ significantly, and present some of the first steps in creating sea ice applications beyond e.g. thickness retrieval.
Rasmus T. Tonboe, Vishnu Nandan, John Yackel, Stefan Kern, Leif Toudal Pedersen, and Julienne Stroeve
The Cryosphere, 15, 1811–1822, https://doi.org/10.5194/tc-15-1811-2021, https://doi.org/10.5194/tc-15-1811-2021, 2021
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A relationship between the Ku-band radar scattering horizon and snow depth is found using a radar scattering model. This relationship has implications for (1) the use of snow climatology in the conversion of satellite radar freeboard into sea ice thickness and (2) the impact of variability in measured snow depth on the derived ice thickness. For both 1 and 2, the impact of using a snow climatology versus the actual snow depth is relatively small.
Yu Zhang, Tingting Zhu, Gunnar Spreen, Christian Melsheimer, Marcus Huntemann, Nick Hughes, Shengkai Zhang, and Fei Li
The Cryosphere Discuss., https://doi.org/10.5194/tc-2021-85, https://doi.org/10.5194/tc-2021-85, 2021
Revised manuscript not accepted
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We developed an algorithm for ice-water classification using Sentinel-1 data during melting seasons in the Fram Strait. The proposed algorithm has the OA of nearly 90 % with STD less than 10 %. The comparison of sea ice concentration demonstrate that it can provide detailed information of sea ice with the spatial resolution of 1km. The time series shows the average June to September sea ice area does not change so much in 2015–2017 and 2019–2020, but it has a significant decrease in 2018.
Elena Barbaro, Krystyna Koziol, Mats P. Björkman, Carmen P. Vega, Christian Zdanowicz, Tonu Martma, Jean-Charles Gallet, Daniel Kępski, Catherine Larose, Bartłomiej Luks, Florian Tolle, Thomas V. Schuler, Aleksander Uszczyk, and Andrea Spolaor
Atmos. Chem. Phys., 21, 3163–3180, https://doi.org/10.5194/acp-21-3163-2021, https://doi.org/10.5194/acp-21-3163-2021, 2021
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This paper shows the most comprehensive seasonal snow chemistry survey to date, carried out in April 2016 across 22 sites on 7 glaciers across Svalbard. The dataset consists of the concentration, mass loading, spatial and altitudinal distribution of major ion species (Ca2+, K+,
Na2+, Mg2+,
NH4+, SO42−,
Br−, Cl− and
NO3−), together with its stable oxygen and hydrogen isotope composition (δ18O and
δ2H) in the snowpack. This study was part of the larger Community Coordinated Snow Study in Svalbard.
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.
Julienne Stroeve, Vishnu Nandan, Rosemary Willatt, Rasmus Tonboe, Stefan Hendricks, Robert Ricker, James Mead, Robbie Mallett, Marcus Huntemann, Polona Itkin, Martin Schneebeli, Daniela Krampe, Gunnar Spreen, Jeremy Wilkinson, Ilkka Matero, Mario Hoppmann, and Michel Tsamados
The Cryosphere, 14, 4405–4426, https://doi.org/10.5194/tc-14-4405-2020, https://doi.org/10.5194/tc-14-4405-2020, 2020
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This study provides a first look at the data collected by a new dual-frequency Ka- and Ku-band in situ radar over winter sea ice in the Arctic Ocean. The instrument shows potential for using both bands to retrieve snow depth over sea ice, as well as sensitivity of the measurements to changing snow and atmospheric conditions.
Larysa Istomina, Henrik Marks, Marcus Huntemann, Georg Heygster, and Gunnar Spreen
Atmos. Meas. Tech., 13, 6459–6472, https://doi.org/10.5194/amt-13-6459-2020, https://doi.org/10.5194/amt-13-6459-2020, 2020
Bronwen L. Konecky, Nicholas P. McKay, Olga V. Churakova (Sidorova), Laia Comas-Bru, Emilie P. Dassié, Kristine L. DeLong, Georgina M. Falster, Matt J. Fischer, Matthew D. Jones, Lukas Jonkers, Darrell S. Kaufman, Guillaume Leduc, Shreyas R. Managave, Belen Martrat, Thomas Opel, Anais J. Orsi, Judson W. Partin, Hussein R. Sayani, Elizabeth K. Thomas, Diane M. Thompson, Jonathan J. Tyler, Nerilie J. Abram, Alyssa R. Atwood, Olivier Cartapanis, Jessica L. Conroy, Mark A. Curran, Sylvia G. Dee, Michael Deininger, Dmitry V. Divine, Zoltán Kern, Trevor J. Porter, Samantha L. Stevenson, Lucien von Gunten, and Iso2k Project Members
Earth Syst. Sci. Data, 12, 2261–2288, https://doi.org/10.5194/essd-12-2261-2020, https://doi.org/10.5194/essd-12-2261-2020, 2020
Lisa Claire Orme, Xavier Crosta, Arto Miettinen, Dmitry V. Divine, Katrine Husum, Elisabeth Isaksson, Lukas Wacker, Rahul Mohan, Olivier Ther, and Minoru Ikehara
Clim. Past, 16, 1451–1467, https://doi.org/10.5194/cp-16-1451-2020, https://doi.org/10.5194/cp-16-1451-2020, 2020
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A record of past sea temperature in the Indian sector of the Southern Ocean, spanning the last 14 200 years, has been developed by analysis of fossil diatoms in marine sediment. During the late deglaciation the reconstructed temperature changes were highly similar to those over Antarctica, most likely due to a reorganisation of global ocean and atmospheric circulation. During the last 11 600 years temperatures gradually cooled and became increasingly variable.
Arantxa M. Triana-Gómez, Georg Heygster, Christian Melsheimer, Gunnar Spreen, Monia Negusini, and Boyan H. Petkov
Atmos. Meas. Tech., 13, 3697–3715, https://doi.org/10.5194/amt-13-3697-2020, https://doi.org/10.5194/amt-13-3697-2020, 2020
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In the Arctic, in situ measurements are sparse and standard remote sensing retrieval methods have problems. We present advances in a retrieval algorithm for vertically integrated water vapour tuned for polar regions. In addition to the initial sensor used (AMSU-B), we can now also use data from the successor instrument (MHS). Additionally, certain artefacts are now filtered out. Comparison with radiosondes shows the overall good performance of the updated algorithm.
Michele Bertò, David Cappelletti, Elena Barbaro, Cristiano Varin, Jean-Charles Gallet, Krzysztof Markowicz, Anna Rozwadowska, Mauro Mazzola, Stefano Crocchianti, Luisa Poto, Paolo Laj, Carlo Barbante, and Andrea Spolaor
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2020-574, https://doi.org/10.5194/acp-2020-574, 2020
Preprint withdrawn
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We present the daily and seasonal variability of Black carbon inferred from two specific experiment based on the hourly and daily time resolution sampling strategy. These unique datasets give us for the first time the opportunity to evaluate the associations between the observed surface snow rBC mass concentration and a set of predictors corresponding to the considered meteorological and snow physico-chemical parameters, via a multiple linear regression approach.
Xiaoyong Yu, Annette Rinke, Wolfgang Dorn, Gunnar Spreen, Christof Lüpkes, Hiroshi Sumata, and Vladimir M. Gryanik
The Cryosphere, 14, 1727–1746, https://doi.org/10.5194/tc-14-1727-2020, https://doi.org/10.5194/tc-14-1727-2020, 2020
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This study presents an evaluation of Arctic sea ice drift speed for the period 2003–2014 in a state-of-the-art coupled regional model for the Arctic, called HIRHAM–NAOSIM. In particular, the dependency of the drift speed on the near-surface wind speed and sea ice conditions is presented. Effects of sea ice form drag included by an improved parameterization of the transfer coefficients for momentum and heat over sea ice are discussed.
Christine Pohl, Larysa Istomina, Steffen Tietsche, Evelyn Jäkel, Johannes Stapf, Gunnar Spreen, and Georg Heygster
The Cryosphere, 14, 165–182, https://doi.org/10.5194/tc-14-165-2020, https://doi.org/10.5194/tc-14-165-2020, 2020
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A spectral to broadband conversion is developed empirically that can be used in combination with the Melt Pond Detector algorithm to derive broadband albedo (300–3000 nm) of Arctic sea ice from MERIS data. It is validated and shows better performance compared to existing conversion methods. A comparison of MERIS broadband albedo with respective values from ERA5 reanalysis suggests a revision of the albedo values used in ERA5. MERIS albedo might be useful for improving albedo representation.
Tine Nilsen, Dmitry V. Divine, Annika Hofgaard, Andreas Born, Johann Jungclaus, and Igor Drobyshev
Clim. Past Discuss., https://doi.org/10.5194/cp-2019-123, https://doi.org/10.5194/cp-2019-123, 2019
Revised manuscript not accepted
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Using a set of three climate model simulations we cannot find a consistent relationship between atmospheric conditions favorable for forest fire activity in northern Scandinavia and weaker ocean circulation in the North Atlantic subpolar gyre on seasonal timescales. In the literature there is support of such a relationship for longer timescales. With the motivation to improve seasonal prediction systems, we conclude that the gyre circulation alone does not indicate forthcoming model drought.
Valentin Ludwig, Gunnar Spreen, Christian Haas, Larysa Istomina, Frank Kauker, and Dmitrii Murashkin
The Cryosphere, 13, 2051–2073, https://doi.org/10.5194/tc-13-2051-2019, https://doi.org/10.5194/tc-13-2051-2019, 2019
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Sea-ice concentration, the fraction of an area covered by sea ice, can be observed from satellites with different methods. We combine two methods to obtain a product which is better than either of the input measurements alone. The benefit of our product is demonstrated by observing the formation of an open water area which can now be observed with more detail. Additionally, we find that the open water area formed because the sea ice drifted in the opposite direction and faster than usual.
Caixin Wang, Robert M. Graham, Keguang Wang, Sebastian Gerland, and Mats A. Granskog
The Cryosphere, 13, 1661–1679, https://doi.org/10.5194/tc-13-1661-2019, https://doi.org/10.5194/tc-13-1661-2019, 2019
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A warm bias and higher total precipitation and snowfall were found in ERA5 compared with ERA-Interim (ERA-I) over Arctic sea ice. The warm bias in ERA5 was larger in the cold season when 2 m air temperature was < −25 °C and smaller in the warm season than in ERA-I. Substantial anomalous Arctic rainfall in ERA-I was reduced in ERA5, particularly in summer and autumn. When using ERA5 and ERA-I to force a 1-D sea ice model, the effects on ice growth are very small (cm) during the freezing period.
Elena Barbaro, Cristiano Varin, Xanthi Pedeli, Jean Marc Christille, Torben Kirchgeorg, Fabio Giardi, David Cappelletti, Clara Turetta, Andrea Gambaro, Andrea Bernagozzi, Jean Charles Gallet, Mats P. Björkman, and Andrea Spolaor
The Cryosphere Discuss., https://doi.org/10.5194/tc-2019-124, https://doi.org/10.5194/tc-2019-124, 2019
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Cătălin Paţilea, Georg Heygster, Marcus Huntemann, and Gunnar Spreen
The Cryosphere, 13, 675–691, https://doi.org/10.5194/tc-13-675-2019, https://doi.org/10.5194/tc-13-675-2019, 2019
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Sea ice thickness is important for representing atmosphere–ocean interactions in climate models. A validated satellite sea ice thickness measurement algorithm is transferred to a new sensor. The results offer a better temporal and spatial coverage of satellite measurements in the polar regions. Here we describe the calibration procedure between the two sensors, taking into account their technical differences. In addition a new filter for interference from artificial radio sources is implemented.
Michael Boy, Erik S. Thomson, Juan-C. Acosta Navarro, Olafur Arnalds, Ekaterina Batchvarova, Jaana Bäck, Frank Berninger, Merete Bilde, Zoé Brasseur, Pavla Dagsson-Waldhauserova, Dimitri Castarède, Maryam Dalirian, Gerrit de Leeuw, Monika Dragosics, Ella-Maria Duplissy, Jonathan Duplissy, Annica M. L. Ekman, Keyan Fang, Jean-Charles Gallet, Marianne Glasius, Sven-Erik Gryning, Henrik Grythe, Hans-Christen Hansson, Margareta Hansson, Elisabeth Isaksson, Trond Iversen, Ingibjorg Jonsdottir, Ville Kasurinen, Alf Kirkevåg, Atte Korhola, Radovan Krejci, Jon Egill Kristjansson, Hanna K. Lappalainen, Antti Lauri, Matti Leppäranta, Heikki Lihavainen, Risto Makkonen, Andreas Massling, Outi Meinander, E. Douglas Nilsson, Haraldur Olafsson, Jan B. C. Pettersson, Nønne L. Prisle, Ilona Riipinen, Pontus Roldin, Meri Ruppel, Matthew Salter, Maria Sand, Øyvind Seland, Heikki Seppä, Henrik Skov, Joana Soares, Andreas Stohl, Johan Ström, Jonas Svensson, Erik Swietlicki, Ksenia Tabakova, Throstur Thorsteinsson, Aki Virkkula, Gesa A. Weyhenmeyer, Yusheng Wu, Paul Zieger, and Markku Kulmala
Atmos. Chem. Phys., 19, 2015–2061, https://doi.org/10.5194/acp-19-2015-2019, https://doi.org/10.5194/acp-19-2015-2019, 2019
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The Nordic Centre of Excellence CRAICC (Cryosphere–Atmosphere Interactions in a Changing Arctic Climate), funded by NordForsk in the years 2011–2016, is the largest joint Nordic research and innovation initiative to date and aimed to strengthen research and innovation regarding climate change issues in the Nordic region. The paper presents an overview of the main scientific topics investigated and provides a state-of-the-art comprehensive summary of what has been achieved in CRAICC.
Tine Nilsen, Johannes P. Werner, Dmitry V. Divine, and Martin Rypdal
Clim. Past, 14, 947–967, https://doi.org/10.5194/cp-14-947-2018, https://doi.org/10.5194/cp-14-947-2018, 2018
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The BARCAST climate field reconstruction method is tested using synthetic data experiments. It is demonstrated that the output reconstructions have altered statistical properties compared with the input data, but they are also not necessarily consistent with the model assumption of the reconstruction method. The conclusion is that the statistical properties of a reconstruction not only reflect the statistics of the real climate, but they may very well be affected by the manipulation of the data.
Aleksey Malinka, Eleonora Zege, Larysa Istomina, Georg Heygster, Gunnar Spreen, Donald Perovich, and Chris Polashenski
The Cryosphere, 12, 1921–1937, https://doi.org/10.5194/tc-12-1921-2018, https://doi.org/10.5194/tc-12-1921-2018, 2018
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Melt ponds occupy a large part of the Arctic sea ice in summer and strongly affect the radiative budget of the atmosphere–ice–ocean system. The melt pond reflectance is modeled in the framework of the radiative transfer theory and validated with field observations. It improves understanding of melting sea ice and enables better parameterization of the surface in Arctic atmospheric remote sensing (clouds, aerosols, trace gases) and re-evaluating Arctic climatic feedbacks at a new accuracy level.
Meri M. Ruppel, Joana Soares, Jean-Charles Gallet, Elisabeth Isaksson, Tõnu Martma, Jonas Svensson, Jack Kohler, Christina A. Pedersen, Sirkku Manninen, Atte Korhola, and Johan Ström
Atmos. Chem. Phys., 17, 12779–12795, https://doi.org/10.5194/acp-17-12779-2017, https://doi.org/10.5194/acp-17-12779-2017, 2017
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Black carbon (BC) deposition enhances Arctic warming and melting. We present Svalbard ice core BC data from 2005 to 2015, comparing the results with chemical transport model data. The ice core and modelled BC deposition trends clearly deviate from measured and observed atmospheric concentration trends, and thus meteorological processes such as precipitation and scavenging efficiency seem to have a stronger influence on the BC deposition trend than BC emission or atmospheric concentration trends.
Gunnar Spreen, Ron Kwok, Dimitris Menemenlis, and An T. Nguyen
The Cryosphere, 11, 1553–1573, https://doi.org/10.5194/tc-11-1553-2017, https://doi.org/10.5194/tc-11-1553-2017, 2017
John Faulkner Burkhart, Arve Kylling, Crystal B. Schaaf, Zhuosen Wang, Wiley Bogren, Rune Storvold, Stian Solbø, Christina A. Pedersen, and Sebastian Gerland
The Cryosphere, 11, 1575–1589, https://doi.org/10.5194/tc-11-1575-2017, https://doi.org/10.5194/tc-11-1575-2017, 2017
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We present the first use of spectrometer measurements from a drone to assess reflectance and albedo over the Greenland Ice Sheet. In order to measure albedo – a critical parameter in the earth's energy balance – a drone was flown along 200 km transects coincident with Terra and Aqua satellites flying MODIS. We present a direct comparison of UAV-measured reflectance with satellite data over Greenland and provide a new method to study cryospheric surfaces using UAV with spectral instruments.
Ane S. Fors, Dmitry V. Divine, Anthony P. Doulgeris, Angelika H. H. Renner, and Sebastian Gerland
The Cryosphere, 11, 755–771, https://doi.org/10.5194/tc-11-755-2017, https://doi.org/10.5194/tc-11-755-2017, 2017
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This paper investigates the signature of melt ponds in satellite-borne synthetic aperture radar (SAR) imagery. A comparison between helicopter-borne images of drifting first-year ice and polarimetric X-band SAR images shows relations between observed melt pond fraction and several polarimetric SAR features. Melt ponds strongly influence the Arctic sea ice energy budget, and the results imply prospective opportunities for expanded monitoring of melt ponds from space.
Paul Vallelonga, Niccolo Maffezzoli, Andrew D. Moy, Mark A. J. Curran, Tessa R. Vance, Ross Edwards, Gwyn Hughes, Emily Barker, Gunnar Spreen, Alfonso Saiz-Lopez, J. Pablo Corella, Carlos A. Cuevas, and Andrea Spolaor
Clim. Past, 13, 171–184, https://doi.org/10.5194/cp-13-171-2017, https://doi.org/10.5194/cp-13-171-2017, 2017
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We present a study of bromine, iodine and sodium in an ice core from Law Dome, in coastal East Antarctica. We find that bromine and iodine variability at Law Dome is correlated to changes in the area of sea ice along the Law Dome coast as observed by satellite since the early 1970s. These findings are in agreement with a previous study based on MSA and confirm a long-term trend of sea ice decrease for this sector of Antarctica over the 20th century.
T. Krumpen, R. Gerdes, C. Haas, S. Hendricks, A. Herber, V. Selyuzhenok, L. Smedsrud, and G. Spreen
The Cryosphere, 10, 523–534, https://doi.org/10.5194/tc-10-523-2016, https://doi.org/10.5194/tc-10-523-2016, 2016
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We present an extensive data set of ground-based and airborne electromagnetic ice thickness measurements covering Fram Strait in summer between 2001 and 2012. An investigation of back trajectories of surveyed sea ice using satellite-based sea ice motion data allows us to examine the connection between thickness variability, ice age and source area. In addition, we determine across and along strait gradients in ice thickness and associated volume fluxes.
A. Spolaor, T. Opel, J. R. McConnell, O. J. Maselli, G. Spreen, C. Varin, T. Kirchgeorg, D. Fritzsche, A. Saiz-Lopez, and P. Vallelonga
The Cryosphere, 10, 245–256, https://doi.org/10.5194/tc-10-245-2016, https://doi.org/10.5194/tc-10-245-2016, 2016
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The role of sea ice in the Earth climate system is still under debate, although it is known to influence albedo, ocean circulation, and atmosphere-ocean heat and gas exchange. Here we present a reconstruction of 1950 to 1998 AD sea ice in the Laptev Sea based on the Akademii Nauk ice core (Severnaya Zemlya, Russian Arctic) and halogen measurements. The results suggest a connection between bromine and sea ice, as well as a connection between iodine concentration in snow and summer sea ice.
J.-C. Gallet, F. Domine, J. Savarino, M. Dumont, and E. Brun
The Cryosphere, 8, 1205–1215, https://doi.org/10.5194/tc-8-1205-2014, https://doi.org/10.5194/tc-8-1205-2014, 2014
J.-C. Gallet, F. Domine, and M. Dumont
The Cryosphere, 8, 1139–1148, https://doi.org/10.5194/tc-8-1139-2014, https://doi.org/10.5194/tc-8-1139-2014, 2014
Z. W. Wang, J. C. Gallet, C. A. Pedersen, X. S. Zhang, J. Ström, and Z. J. Ci
Atmos. Chem. Phys., 14, 629–640, https://doi.org/10.5194/acp-14-629-2014, https://doi.org/10.5194/acp-14-629-2014, 2014
Related subject area
Discipline: Snow | Subject: Field Studies
Spatially distributed snow depth, bulk density, and snow water equivalent from ground-based and airborne sensor integration at Grand Mesa, Colorado, USA
Evaluating a prediction system for snow management
A low-cost method for monitoring snow characteristics at remote field sites
The RHOSSA campaign: multi-resolution monitoring of the seasonal evolution of the structure and mechanical stability of an alpine snowpack
Measurement of specific surface area of fresh solid precipitation particles in heavy snowfall regions of Japan
The evolution of snow bedforms in the Colorado Front Range and the processes that shape them
Estimating the snow water equivalent on a glacierized high elevation site (Forni Glacier, Italy)
Snowmobile impacts on snowpack physical and mechanical properties
Tate G. Meehan, Ahmad Hojatimalekshah, Hans-Peter Marshall, Elias J. Deeb, Shad O'Neel, Daniel McGrath, Ryan W. Webb, Randall Bonnell, Mark S. Raleigh, Christopher Hiemstra, and Kelly Elder
The Cryosphere Discuss., https://doi.org/10.5194/tc-2023-141, https://doi.org/10.5194/tc-2023-141, 2023
Revised manuscript accepted for TC
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Snow water equivalent (SWE) is a critical parameter for yearly water supply forecasting and can be calculated by multiplying the snow depth by the snow density. We combined high-spatial resolution snow depth information with ground-based radar measurements to solve for snow density. Extrapolated density estimates over our study area resolved detailed patterns that agree with the known interactions of snow with wind, terrain, and vegetation and were utilized in the calculation of SWE.
Pirmin Philipp Ebner, Franziska Koch, Valentina Premier, Carlo Marin, Florian Hanzer, Carlo Maria Carmagnola, Hugues François, Daniel Günther, Fabiano Monti, Olivier Hargoaa, Ulrich Strasser, Samuel Morin, and Michael Lehning
The Cryosphere, 15, 3949–3973, https://doi.org/10.5194/tc-15-3949-2021, https://doi.org/10.5194/tc-15-3949-2021, 2021
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A service to enable real-time optimization of grooming and snow-making at ski resorts was developed and evaluated using both GNSS-measured snow depth and spaceborne snow maps derived from Copernicus Sentinel-2. The correlation to the ground observation data was high. Potential sources for the overestimation of the snow depth by the simulations are mainly the impact of snow redistribution by skiers, compensation of uneven terrain, or spontaneous local adaptions of the snow management.
Rosamond J. Tutton and Robert G. Way
The Cryosphere, 15, 1–15, https://doi.org/10.5194/tc-15-1-2021, https://doi.org/10.5194/tc-15-1-2021, 2021
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Snow cover is critical to everyday life for people around the globe. Regular measurements of snow cover usually occur only in larger communities because snow monitoring equipment is costly. In this study, we developed a new low-cost method for estimating snow depth and tested it continuously for 1 year at six remote field locations in coastal Labrador, Canada. Field testing suggests that this new method provides a promising option for researchers in need of a low-cost snow measurement system.
Neige Calonne, Bettina Richter, Henning Löwe, Cecilia Cetti, Judith ter Schure, Alec Van Herwijnen, Charles Fierz, Matthias Jaggi, and Martin Schneebeli
The Cryosphere, 14, 1829–1848, https://doi.org/10.5194/tc-14-1829-2020, https://doi.org/10.5194/tc-14-1829-2020, 2020
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During winter 2015–2016, the standard program to monitor the structure and stability of the snowpack at Weissflujoch, Swiss Alps, was complemented by additional measurements to compare between various traditional and newly developed techniques. Snow micro-penetrometer measurements allowed monitoring of the evolution of the snowpack's internal structure at a daily resolution throughout the winter. We show the potential of such high-resolution data for detailed evaluations of snowpack models.
Satoru Yamaguchi, Masaaki Ishizaka, Hiroki Motoyoshi, Sent Nakai, Vincent Vionnet, Teruo Aoki, Katsuya Yamashita, Akihiro Hashimoto, and Akihiro Hachikubo
The Cryosphere, 13, 2713–2732, https://doi.org/10.5194/tc-13-2713-2019, https://doi.org/10.5194/tc-13-2713-2019, 2019
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The specific surface area (SSA) of solid precipitation particles (PPs) includes detailed information of PP. This work is based on field measurement of SSA of PPs in Nagaoka, the city with the heaviest snowfall in Japan. The values of SSA strongly depend on wind speed (WS) and wet-bulb temperature (Tw) on the ground. An equation to empirically estimate the SSA of fresh PPs with WS and Tw was established and the equation successfully reproduced the fluctuation of SSA in Nagaoka.
Kelly Kochanski, Robert S. Anderson, and Gregory E. Tucker
The Cryosphere, 13, 1267–1281, https://doi.org/10.5194/tc-13-1267-2019, https://doi.org/10.5194/tc-13-1267-2019, 2019
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Wind-blown snow does not lie flat. It forms dunes, ripples, and anvil-shaped sastrugi. These features ornament much of the snow on Earth and change the snow's effects on polar climates, but they have rarely been studied. We spent three winters watching snow move through the Colorado Front Range and present our findings here, including the first time-lapse videos of snow dune and sastrugi growth.
Antonella Senese, Maurizio Maugeri, Eraldo Meraldi, Gian Pietro Verza, Roberto Sergio Azzoni, Chiara Compostella, and Guglielmina Diolaiuti
The Cryosphere, 12, 1293–1306, https://doi.org/10.5194/tc-12-1293-2018, https://doi.org/10.5194/tc-12-1293-2018, 2018
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We present and compare 11 years of snow data measured by an automatic weather station and corroborated by data from field campaigns on the Forni Glacier in Italy. The methodology we present is interesting for remote locations such as glaciers or high alpine regions, as it makes it possible to estimate the total snow water equivalent (SWE) using a relatively inexpensive, low-power, low-maintenance, and reliable instrument such as the sonic ranger.
Steven R. Fassnacht, Jared T. Heath, Niah B. H. Venable, and Kelly J. Elder
The Cryosphere, 12, 1121–1135, https://doi.org/10.5194/tc-12-1121-2018, https://doi.org/10.5194/tc-12-1121-2018, 2018
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We conducted a series of experiments to determine how snowpack properties change with varying snowmobile traffic. Experiments were initiated at a shallow (30 cm) and deep (120 cm) snow depth at two locations. Except for initiation at 120 cm, snowmobiles significantly changed the density, hardness, ram resistance, and basal layer crystal size. Temperature was not changed. A density change model was developed and tested. The results inform management of lands with snowmobile traffic.
Cited articles
Barber, D., Fung, A., Grenfell, T., Nghiem, S., Onstott, R., Lytle, V.,
Perovich, D., and Gow, A.: The Role of Snow on Microwave Emission and
Scattering over First-Year Sea Ice, IEEE T. Geosci.
Remote Sens., 36, 1750–1763, 1998.
Barber, D. G. and Nghiem, S. V.: The role of snow on the thermal dependence
of microwave backscatter over sea ice, J. Geophys. Res.-Oceans, 104, 25789–25803, 1999.
Beaven, S. G., Lockhart, G. L., Gogineni, S. P., Hossetnmostafa, A. R.,
Jezek, K., Gow, A. J., Perovich, D. K., Fung, A. K., and Tjuatja, S.:
Laboratory measurements of radar backscatter from bare and snow-covered
saline ice sheets, Int. J. Remote Sens., 16, 851–876,
1995.
Dominguez, R.: Icebridge DMS L1B geolocated and orthorectified images,
(IODMS1B), Boulder, Colorado USA. NASA National Snow and Ice Data Center
Distributed Active Archive Center., 2010, updated 2018.
Drinkwater, M. R. and Crocker, G.: Modelling Changes in Scattering
Properties of the Dielectric and Young Snow-Covered Sea Ice at GHz
Frequencies, J. Glaciol., 34, 274–282, 1988.
EarthData: Operation IceBridge Data Portal, available at: https://nsidc.org/icebridge/portal/map, last access: 12 May 2021.
Eicken, H., Grenfell, T. C., Perovich, D. K., Richter-Menge, J. A., and
Frey, K.: Hydraulic controls of summer Arctic pack ice albedo, J.
Geophys. Res.-Oceans, 109, C08007, https://doi.org/10.1029/2003JC001989, 2004.
Farrell, S. L., Kurtz, N., Connor, L. N., Elder, B. C., Leuschen, C.,
Markus, T., McAdoo, D. C., Panzer, B., Richter-Menge, J., and Sonntag, J.
G.: A First Assessment of IceBridge Snow and Ice Thickness Data Over Arctic
Sea Ice, IEEE T. Geosci. Remote Sens., 50, 2098–2111,
2012.
Geldsetzer, T., Langlois, A., and Yackel, J.: Dielectric properties of
brine-wetted snow on first-year sea ice, Cold Reg. Sci.
Technol., 58, 47–56, 2009.
Gerland, S., Renner, A. H. H., Spreen, G., Wang, C., Beckers, J., Dumont,
M., Granskog, M. A., Haapala, J., Haas, C., Helm, V., Hudson, S. R., Lensu,
M., Ricker, R., Sandven, S., Skourup, H., and Zygmuntowska, M.: In-situ
calibration and validation of CryoSat-2 Observations Over Arctic sea ice
north of Svalbard, in: Proc. Earth Observation and Cryosphere Science Conf.,
Frascati, Italy, 13–16 November 2012, ESA SP-712, 2013.
Gerland, S., Granskog, M. A., King, J., and Rösel, A.:
N-ICE2015 ice core physics: temperature, salinity and density, Norwegian Polar Institute [data set],
https://doi.org/10.21334/npolar.2017.c3db82e3, 2017.
Giles, K. A., Laxon, S. W., Wingham, D. J., Wallis, D. W., Krabill, W. B.,
Leuschen, C. J., McAdoo, D., Manizade, S. S., and Raney, R. K.: Combined
airborne laser and radar altimeter measurements over the Fram Strait in May
2002, Remote Sens. Environ., 111, 182–194, 2007.
Graham, R. M., Cohen, L., Petty, A. A., Boisvert, L. N., Rinke, A., Hudson,
S. R., Nicolaus, M., and Granskog, M. A.: Increasing frequency and duration
of Arctic winter warming events, Geophys. Res. Lett., 44,
6974–6983, 2017.
Granskog, M., Assmy, P., Gerland, S., Spreen, G., Steen, H., and Smedsrud,
L.: Arctic Research on Thin Ice: Consequences of Arctic Sea Ice Loss, EOS
T. Am. Geophys. Un., 97, https://doi.org/10.1029/2016EO044097, 2016.
Granskog, M. A., Rösel, A., Dodd, P. A., Divine, D., Gerland, S.,
Martma, T., and Leng, M. J.: Snow contribution to first-year and second-year
Arctic sea ice mass balance north of Svalbard, J. Geophys.
Res.-Oceans, 122, 2539–2549, 2017.
Granskog, M. A., Fer, I., Rinke, A., and Steen, H.: Atmosphere‐ice‐ocean‐ecosystem
processes in a thinner Arctic sea ice regime: The Norwegian young sea iCE (N‐ICE2015)
expedition, J. Geophys. Res.-Oceans, 123, 1586–1594,
https://doi.org/10.1002/2017JC013328, 2018.
Grenfell, T. C. and Maykut, G. A.: The Optical Properties of Ice and Snow in
the Arctic Basin, J. Glaciol., 18, 445–463, 1977.
Haas, C., Gerland, S., Eicken, H., and Miller, H.: Comparison of sea-ice
thickness measurements under summer and winter conditions in the Arctic
using a small electromagnetic induction device, Geophysics, 62, 749–757,
1997.
Haas, C., Lobach, J., Hendricks, S., Rabenstein, L., and Pfaffling, A.:
Helicopter-borne measurements of sea ice thickness, using a small and
lightweight, digital EM system, Journal of Applied Geophysics, 67, 234–241,
2009.
Hendricks, S., Stenseng, L., Helm, V., and Haas, C.: Effects of Surface
Roughness on Sea Ice Freeboard Retrieval with an Airborne Ku-Band SAR Radar
Altimeter, in: Geoscience and Remote Sensing (IGARSS 2010), IEEE
International Symposium, https://doi.org/10.1109/IGARSS.2010.5654350, 2010.
Holt, B., Johnson, M. P., Perkovic-Martin, D., and Panzer, B.: Snow depth on
Arctic sea ice derived from radar: In situ comparisons and time series
analysis, J. Geophys. Res.-Oceans, 120, 4260–4287, 2015.
Kern, S., Khvorostovsky, K., Skourup, H., Rinne, E., Parsakhoo, Z. S., Djepa, V., Wadhams, P., and Sandven, S.: The impact of snow depth, snow density and ice density on sea ice thickness retrieval from satellite radar altimetry: results from the ESA-CCI Sea Ice ECV Project Round Robin Exercise, The Cryosphere, 9, 37–52, https://doi.org/10.5194/tc-9-37-2015, 2015.
King, J., Howell, S., Derksen, C., Rutter, N., Toose, P., Beckers, J. F.,
Haas, C., Kurtz, N., and Richter-Menge, J.: Evaluation of Operation
IceBridge quick-look snow depth estimates on sea ice, Geophys. Res.
Lett., 42, 9302–9310, 2015.
King, J., Skourup, H., Hvidegaard, S. M., Rösel, A., Gerland, S.,
Spreen, G., Polashenski, C., Helm, V., and Liston, G. E.: Comparison of
Free- board Retrieval and Ice Thickness Calculation From ALS, ASIRAS, and
CryoSat-2 in the Norwegian Arctic to Field Measurements Made During the
N-ICE2015 Expedition, J. Geophys. Res.-Oceans, 123,
1123–1141, 2018.
Koenig, L., Martin, S., Studinger, M., and Sonntag, J.: Polar Airborne
Observations Fill Gap in Satellite Data, EOS T. Am.
Geophys. Un., 91, 333–334, 2010.
Krabill, W., Abdalati, W., Frederick, E., Manizade, S., Martin, C., Sonntag,
J., Swift, R., Thomas, R., and Yungel, J.: Aircraft laser altimetry
measurement of elevation changes of the greenland ice sheet: technique and
accuracy assessment, J. Geodyn., 34, 357–376, 2002.
Kurtz, N. T., Farrell, S. L., Studinger, M., Galin, N., Harbeck, J. P., Lindsay, R., Onana, V. D., Panzer, B., and Sonntag, J. G.: Sea ice thickness, freeboard, and snow depth products from Operation IceBridge airborne data, The Cryosphere, 7, 1035–1056, https://doi.org/10.5194/tc-7-1035-2013, 2013.
Kurtz, N. T., Galin, N., and Studinger, M.: An improved CryoSat-2 sea ice freeboard retrieval algorithm through the use of waveform fitting, The Cryosphere, 8, 1217–1237, https://doi.org/10.5194/tc-8-1217-2014, 2014.
Kwok, R.: Simulated effects of a snow layer on retrieval of CryoSat-2 sea
ice freeboard, Geophys. Res. Lett., 41, 5014–5020, 2014.
Kwok, R. and Kacimi, S.: Three years of sea ice freeboard, snow depth, and ice thickness of the Weddell Sea from Operation IceBridge and CryoSat-2, The Cryosphere, 12, 2789–2801, https://doi.org/10.5194/tc-12-2789-2018, 2018.
Kwok, R. and Maksym, T.: Snow depth of the Weddell and Bellingshausen sea
ice covers from IceBridge surveys in 2010 and 2011: An examination, J. Geophys. Res.-Oceans, 119, 4141–4167, 2014.
Kwok, R., Kurtz, N. T., Brucker, L., Ivanoff, A., Newman, T., Farrell, S. L., King, J., Howell, S., Webster, M. A., Paden, J., Leuschen, C., MacGregor, J. A., Richter-Menge, J., Harbeck, J., and Tschudi, M.: Intercomparison of snow depth retrievals over Arctic sea ice from radar data acquired by Operation IceBridge, The Cryosphere, 11, 2571–2593, https://doi.org/10.5194/tc-11-2571-2017, 2017.
Lawrence, I. R., Tsamados, M. C., Stroeve, J. C., Armitage, T. W. K., and Ridout, A. L.: Estimating snow depth over Arctic sea ice from calibrated dual-frequency radar freeboards, The Cryosphere, 12, 3551–3564, https://doi.org/10.5194/tc-12-3551-2018, 2018.
Marshall, H. P., Koh, G., Sturm, M., Johnson, J., Demuth, M., Landry, C.,
Deems, J., and Gleason, A.: Spatial variability of the snowpack: Experiences
with measurements at a wide range of length scales with several different
high precision instruments, Proc. ISSW 2006, 359–364, Telluride, CO, International Snow Science Workshop Proceedings – Montana State University Library, 2006.
Massom, R. A., Eicken, H., Hass, C., Jeffries, M. O., Drinkwater, M. R.,
Sturm, M., Worby, A. P., Wu, X., Lytle, V. I., Ushio, S., Morris, K., Reid,
P. A., Warren, S. G., and Allison, I.: Snow on Antarctic sea ice, Rev.
Geophys., 39, 413–445, 2001.
Merkouriadi, I., Cheng, B., Graham, R. M., Rösel, A., and Granskog, M.
A.: Critical Role of Snow on Sea Ice Growth in the Atlantic Sector of the
Arctic Ocean, Geophys. Res. Lett., 44, 10479–10485, 2017a.
Merkouriadi, I., Gallet, J.-C., Liston, G., Polashenski, C., Itkin, P.,
King, J., Espeseth, M., Gierisch, A., Oikkonen, A., Orsi, A., and Gerland,
S.: N-ICE2015 snow pit data, Norwegian Polar Institute [data set],
https://doi.org/10.21334/npolar.2017.d2be5f05, 2017b.
Merkouriadi, I., Gallet, J.-C., Liston, G. E., Polashenski, C., Rösel,
A., and Gerland, S.: Winter snow conditions over the Arctic Ocean north of
Svalbard during the Norwegian young sea ICE (N-ICE2015) expedition, J. Geophys. Res.-Atmos., 122, 10837–10854, https://doi.org/10.1002/2017JD026753, 2017c.
Meyer, A., Sundfjord, A., Fer, I., Provost, C., Robineau, N. V., Koenig, Z.,
Onarheim, I. H., Smedsrud, L. H., Duarte, P., Dodd, P. A., Graham, R. M.,
and Kauko, H.: Winter to summer hydrographic and current observations in the
Arctic Ocean north of Svalbard, J. Geophys. Res.-Oceans,
122, 6218–6237, https://doi.org/10.1002/2016JC012391, 2017.
Mundy, C. J., Ehn, J. K., Barber, D. G., and Michel, C.: Influence of snow
cover and algae on the spectral dependence of transmitted irradiance through
Arctic landfast first-year sea ice, J. Geophys. Res.-Oceans, 112, C03007, https://doi.org/10.1029/2006JC003683, 2007.
Nandan, V., Geldsetzer, T., Islam, T., Yackel, J. J., Gill, J. P., Fuller,
M. C., Gunn, G., and Duguay, C.: Ku-, X- and C-band measured and modeled
microwave backscatter from a highly saline snow cover on first-year sea ice,
Remote Sens. Environ., 187, 62–75, 2016.
Nandan, V., Geldsetzer, T., Yackel, J., Mahmud, M., Scharien, R., Howell,
S., King, J., Ricker, R., and Else, B.: Effect of Snow Salinity on CryoSat-2
Arctic First-Year Sea Ice Freeboard Measurements, Geophys. Res. Lett., 44, 10419–10426, 2017.
Nandan, V., Scharien, R. K., Geldsetzer, T., Kwok, R., Yackel, J. J.,
Mahmud, M., Rösel, A., Tonboe, R., Granskog, M., Willatt, R., Stroeve,
J., Nomura, D., and Frey, M.: Snow Property Controls on Modeled Ku-Band
Altimeter Estimates of First-Year Sea Ice Thickness: Case Studies from the
Canadian and Norwegian Arctic, IEEE J. Sel. Top.
Appl., 13, 1082–1096, 2020.
Newman, T., Farrell, S. L., Richter-Menge, J., Connor, L. N., Kurtz, N. T.,
Elder, B. C., and McAdoo, D.: Assessment of radar-derived snow depth over
Arctic sea ice, J. Geophys. Res.-Oceans, 119, 8578–8602,
2014.
Nghiem, S. V., Kwok, R., Yueh, S. H., and Drinkwater, M. R.: Polarimetric
signatures of sea ice: 2. Experimental observations, J. Geophys. Res.-Oceans, 100, 13681–13698, 1995.
Ozsoy-Cicek, B., Ackley, S., Xie, H., Yi, D., and Zwally, J.: Sea ice
thickness retrieval algorithms based on in situ surface elevation and
thickness values for application to altimetry, J. Geophys. Res.-Oceans, 118, 3807–3822, 2013.
Perovich, D. K.: The Optical Properties of Sea Ice, Vol. 96, CRREL
Monography, 31 pp., 1996.
Perovich, D. K.: Thin and thinner: Sea ice mass balance measurements during
SHEBA, J. Geophys. Res.-Oceans, 108, 8050, https://doi.org/10.1029/2001JC001079, 2003.
Renner, A. H. H., Gerland, S., Haas, C., Spreen, G., Beckers, J. F., Hansen,
E., Nicolaus, M., and Goodwin, H.: Evidence of Arctic sea ice thinning from
direct observations, Geophys. Res. Lett., 41, 5029–5036, 2014.
Ricker, R., Hendricks, S., Helm, V., Skourup, H., and Davidson, M.: Sensitivity of CryoSat-2 Arctic sea-ice freeboard and thickness on radar-waveform interpretation, The Cryosphere, 8, 1607–1622, https://doi.org/10.5194/tc-8-1607-2014, 2014.
Ricker, R., Hendricks, S., Perovich, D. K., Helm, V., and Gerdes, R.: Impact
of snow accumulation on CryoSat-2 range retrievals over Arctic sea ice: An
observational approach with buoy data, Geophys. Res. Lett., 42,
4447–4455, 2015.
Rinke, A., Maturilli, M., Graham, R. M., H., M., Handorf, D., Cohen, L.,
Hudson, S. R., and Moore, J. C.: Extreme cyclone events in the Arctic:
Wintertime variability and trends, Environ. Res. Lett., 12, 094006, 2017.
Rösel, A., Divine, D., King, J. A., Nicolaus, M., Spreen, G., Itkin, P., Polashenski, C. M., Liston, G. E., Ervik, Å., Espeseth, M., Gierisch, A., Haapala, J., Maaß, N., Oikkonen, A., Orsi, A., Shestov, A., Wang, C., Gerland, S., and Granskog, M. A.: N-ICE2015 total (snow and ice) thickness data from EM31, Norwegian Polar Institute [data set],
https://doi.org/10.21334/npolar.2016.70352512, 2016a.
Rösel, A., Polashenski, C. M., Liston, G. E., King, J. A., Nicolaus, M., Gallet, J.-C., Divine, D., Itkin, P., Spreen, G., Ervik, Å., Espeseth, M., Gierisch, A., Haapala, J., Maaß, N., Oikkonen, A., Orsi, A., Shestov, A., Wang, C., Gerland, S., and Granskog, M. A.: N-ICE2015 snow depth data with Magnaprobe, Norwegian Polar Institute [data set], https://doi.org/10.21334/npolar.2016.3d72756d, 2016b.
Rösel, A., King, J., Doulgeris, A. P., Wagner, P. M., Johansson, A. M.,
and Gerland, S.: Can we extend local sea-ice measurements to satellite
scale? An example from the N-ICE2015 expedition, Ann. Glaciol., 59,
163–172, https://doi.org/10.1017/aog.2017.37, 2017.
Rösel, A., Itkin, P., King, J., Divine, D., Wang, C., Granskog, M. A.,
Krumpen, T., and Gerland, S.: Thin sea ice, thick snow and widespread
negative freeboard observed during N-ICE2015 north of Svalbard, J. Geophys. Res.-Oceans, 123, 1156–1176, https://doi.org/10.1002/2017JC012865, 2018.
Sallila, H., Farrell, S. L., McCurry, J., and Rinne, E.: Assessment of contemporary satellite sea ice thickness products for Arctic sea ice, The Cryosphere, 13, 1187–1213, https://doi.org/10.5194/tc-13-1187-2019, 2019.
Skourup, H., Farrell, S. L., Hendricks, S., Ricker, R., Armitage, T. W.,
Ridout, A., Andersen, O. B., Haas, C., and Baker, S.: An Assessment of
State-of-the-Art Mean Sea Surface and Geoid Models of the Arctic Ocean:
Implications for Sea Ice Freeboard Retrieval, J. Geophys. Res.-Oceans, 122, 8593–8613, 2017.
Steer, A.: Code supporting the publication “Implications of surface flooding on airborne thickness measurements of snow on sea ice”, available at: https://gitlab.com/npolar/oceanseaice/roesel-cryosphere-2020,
last access: 28 May 2021.
Sturm, M.: Winter snow cover on the sea ice of the Arctic Ocean at the
Surface Heat Budget of the Arctic Ocean (SHEBA): Temporal evolution and
spatial variability, J. Geophys. Res.-Oceans, 107, 8047, https://doi.org/10.1029/2000JC000400, 2002.
Sturm, M. and Holmgren, J.: Self-recording snow depth probe, Tech. rep., US
patent number: 5,864,059, 1999.
Sturm, M. and Holmgren, J.: An automatic snow depth probe for field
validation campaigns, Water Resour. Res., 54, 9695–9701, 2018.
Tilling, R. L., Ridout, A., and Shepherd, A.: Estimating Arctic sea ice thickness and volume using CryoSat-2 radar altimeter data, Adv. Space Res., 62, 1203–1225, https://doi.org/10.1016/j.asr.2017.10.051, 2018.
Wang, C., Cheng, B., Wang, K., Gerland, S., and Pavlova, O.: Modelling snow
ice and superimposed ice on landfast sea ice in Kongsfjorden, Svalbard,
Polar Res., 34, https://doi.org/10.3402/polar.v34.20828, 2015.
Warren, S. G., Rigor, I. G., Untersteiner, N., Radionov, V. F., Bryazgin, N.
N., Aleksandrov, Y. I., and Colony, R.: Snow Depth on Arctic Sea Ice,
J. Climate, 12, 1814–1829, 1999.
Webster, M., Gerland, S., Holland, M., Hunke, E., Kwok, R., Lecomte, O., Massom, R., Perovich, D., and Sturm, M.: Snow in the changing sea-ice systems. Nat. Clim. Change, 8, 946–953, https://doi.org/10.1038/s41558-018-0286-7, 2018.
Webster, M. A., Rigor, I. G., Nghiem, S. V., Kurtz, N. T., Farrell, S. L.,
Perovich, D. K., and Sturm, M.: Interdecadal changes in snow depth on Arctic
sea ice, J. Geophys. Res.-Oceans, 119, 5395–5406, 2014.
Willatt, R., Laxon, S., Giles, K., Cullen, R., Haas, C., and Helm, V.:
Ku-band radar penetration into snow cover on Arctic sea ice using airborne
data, Ann. Glaciol., 52, 197–205, 2011.
Willatt, R. C., Giles, K. A., Laxon, S. W., Stone-Drake, L., and Worby, A.
P.: Field investigations of Ku-band radar penetration into snow cover on
Antarctic sea ice, IEEE T. Geosci. Remote Sens., 48, 365–372, 2010.
Woods, C. and Caballero, R.: The Role of Moist Intrusions in Winter Arctic
Warming and Sea Ice Decline, J. Climate, 29, 4473–4485,
https://doi.org/10.1175/jcli-d-15-0773.1, 2016.
Yan, J., Alvestegui, D. G.-G., McDaniel, J. W., Li, Y., Gogineni, S.,
Rodriguez-Morales, F., Brozena, J., and Leuschen, C. J.: Ultrawideband FMCW
Radar for Airborne Measurements of Snow Over Sea Ice and Land, IEEE T. Geosci. Remote Sens., 55, 834–843, 2017.
Zwally, H. J., Yi, D., Kwok, R., and Zhao, Y.: ICESat measurements of sea
ice freeboard and estimates of sea ice thickness in the Weddell Sea, J. Geeophys. Res.-Oceans, 113, C02S15, https://doi.org/10.1029/2007JC004284, 2008.
Short summary
Recent observations in the Arctic suggest a significant shift towards a snow–ice regime caused by deep snow on thin sea ice which may result in a flooding of the snowpack. These conditions cause the brine wicking and saturation of the basal snow layers which lead to a subsequent underestimation of snow depth from snow radar mesurements. As a consequence the calculated sea ice thickness will be biased towards higher values.
Recent observations in the Arctic suggest a significant shift towards a snow–ice regime caused...
