Articles | Volume 16, issue 7
https://doi.org/10.5194/essd-16-3149-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-16-3149-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
08 Jul 2024
Data description paper |
| 08 Jul 2024
| 08 Jul 2024
SMOS-derived Antarctic thin sea ice thickness: data description and validation in the Weddell Sea
Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven, Germany
Xiangshan Tian-Kunze
Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven, Germany
Stefan Hendricks
Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven, Germany
Robert Ricker
NORCE Norwegian Research Center, Tromsø, Norway
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Basal melting of ice shelves impacts the mass loss of the Antarctic Ice Sheet. This study focuses on the Ekström Ice Shelf in East Antarctica, using multi-year data from an autonomous radar system. Results show a surprising seasonal pattern of high melt rates in winter and spring. Sea-ice growth correlates with melt rates, indicating that in winter, dense water enhances plume activity and melt rates. Understanding these dynamics is crucial for improving future mass balance projections.
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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.
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Basal melting of ice shelves impacts the mass loss of the Antarctic Ice Sheet. This study focuses on the Ekström Ice Shelf in East Antarctica, using multi-year data from an autonomous radar system. Results show a surprising seasonal pattern of high melt rates in winter and spring. Sea-ice growth correlates with melt rates, indicating that in winter, dense water enhances plume activity and melt rates. Understanding these dynamics is crucial for improving future mass balance projections.
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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.
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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.
Karina von Schuckmann, Audrey Minière, Flora Gues, Francisco José Cuesta-Valero, Gottfried Kirchengast, Susheel Adusumilli, Fiammetta Straneo, Michaël Ablain, Richard P. Allan, Paul M. Barker, Hugo Beltrami, Alejandro Blazquez, Tim Boyer, Lijing Cheng, John Church, Damien Desbruyeres, Han Dolman, Catia M. Domingues, Almudena García-García, Donata Giglio, John E. Gilson, Maximilian Gorfer, Leopold Haimberger, Maria Z. Hakuba, Stefan Hendricks, Shigeki Hosoda, Gregory C. Johnson, Rachel Killick, Brian King, Nicolas Kolodziejczyk, Anton Korosov, Gerhard Krinner, Mikael Kuusela, Felix W. Landerer, Moritz Langer, Thomas Lavergne, Isobel Lawrence, Yuehua Li, John Lyman, Florence Marti, Ben Marzeion, Michael Mayer, Andrew H. MacDougall, Trevor McDougall, Didier Paolo Monselesan, Jan Nitzbon, Inès Otosaka, Jian Peng, Sarah Purkey, Dean Roemmich, Kanako Sato, Katsunari Sato, Abhishek Savita, Axel Schweiger, Andrew Shepherd, Sonia I. Seneviratne, Leon Simons, Donald A. Slater, Thomas Slater, Andrea K. Steiner, Toshio Suga, Tanguy Szekely, Wim Thiery, Mary-Louise Timmermans, Inne Vanderkelen, Susan E. Wjiffels, Tonghua Wu, and Michael Zemp
Earth Syst. Sci. Data, 15, 1675–1709, https://doi.org/10.5194/essd-15-1675-2023, https://doi.org/10.5194/essd-15-1675-2023, 2023
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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.
Felix L. Müller, Stephan Paul, Stefan Hendricks, and Denise Dettmering
The Cryosphere, 17, 809–825, https://doi.org/10.5194/tc-17-809-2023, https://doi.org/10.5194/tc-17-809-2023, 2023
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Thinning sea ice has significant impacts on the energy exchange between the atmosphere and the ocean. In this study we present visual and quantitative comparisons of thin-ice detections obtained from classified Cryosat-2 radar reflections and thin-ice-thickness estimates derived from MODIS thermal-infrared imagery. In addition to good comparability, the results of the study indicate the potential for a deeper understanding of sea ice in the polar seas and improved processing of altimeter data.
Guillaume Boutin, Einar Ólason, Pierre Rampal, Heather Regan, Camille Lique, Claude Talandier, Laurent Brodeau, and Robert Ricker
The Cryosphere, 17, 617–638, https://doi.org/10.5194/tc-17-617-2023, https://doi.org/10.5194/tc-17-617-2023, 2023
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Sea ice cover in the Arctic is full of cracks, which we call leads. We suspect that these leads play a role for atmosphere–ocean interactions in polar regions, but their importance remains challenging to estimate. We use a new ocean–sea ice model with an original way of representing sea ice dynamics to estimate their impact on winter sea ice production. This model successfully represents sea ice evolution from 2000 to 2018, and we find that about 30 % of ice production takes place in leads.
Marco Brogioni, Mark J. Andrews, Stefano Urbini, Kenneth C. Jezek, Joel T. Johnson, Marion Leduc-Leballeur, Giovanni Macelloni, Stephen F. Ackley, Alexandra Bringer, Ludovic Brucker, Oguz Demir, Giacomo Fontanelli, Caglar Yardim, Lars Kaleschke, Francesco Montomoli, Leung Tsang, Silvia Becagli, and Massimo Frezzotti
The Cryosphere, 17, 255–278, https://doi.org/10.5194/tc-17-255-2023, https://doi.org/10.5194/tc-17-255-2023, 2023
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In 2018 the first Antarctic campaign of UWBRAD was carried out. UWBRAD is a new radiometer able to collect microwave spectral signatures over 0.5–2 GHz, thus outperforming existing similar sensors. It allows us to probe thicker sea ice and ice sheet down to the bedrock. In this work we tried to assess the UWBRAD potentials for sea ice, glaciers, ice shelves and buried lakes. We also highlighted the wider range of information the spectral signature can provide to glaciological studies.
Francesca Doglioni, Robert Ricker, Benjamin Rabe, Alexander Barth, Charles Troupin, and Torsten Kanzow
Earth Syst. Sci. Data, 15, 225–263, https://doi.org/10.5194/essd-15-225-2023, https://doi.org/10.5194/essd-15-225-2023, 2023
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This paper presents a new satellite-derived gridded dataset, including 10 years of sea surface height and geostrophic velocity at monthly resolution, over the Arctic ice-covered and ice-free regions, up to 88° N. We assess the dataset by comparison to independent satellite and mooring data. Results correlate well with independent satellite data at monthly timescales, and the geostrophic velocity fields can resolve seasonal to interannual variability of boundary currents wider than about 50 km.
Jinfei Wang, Chao Min, Robert Ricker, Qian Shi, Bo Han, Stefan Hendricks, Renhao Wu, and Qinghua Yang
The Cryosphere, 16, 4473–4490, https://doi.org/10.5194/tc-16-4473-2022, https://doi.org/10.5194/tc-16-4473-2022, 2022
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The differences between Envisat and ICESat sea ice thickness (SIT) reveal significant temporal and spatial variations. Our findings suggest that both overestimation of Envisat sea ice freeboard, potentially caused by radar backscatter originating from inside the snow layer, and the AMSR-E snow depth biases and sea ice density uncertainties can possibly account for the differences between Envisat and ICESat SIT.
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.
David N. Wagner, Matthew D. Shupe, Christopher Cox, Ola G. Persson, Taneil Uttal, Markus M. Frey, Amélie Kirchgaessner, Martin Schneebeli, Matthias Jaggi, Amy R. Macfarlane, Polona Itkin, Stefanie Arndt, Stefan Hendricks, Daniela Krampe, Marcel Nicolaus, Robert Ricker, Julia Regnery, Nikolai Kolabutin, Egor Shimanshuck, Marc Oggier, Ian Raphael, Julienne Stroeve, and Michael Lehning
The Cryosphere, 16, 2373–2402, https://doi.org/10.5194/tc-16-2373-2022, https://doi.org/10.5194/tc-16-2373-2022, 2022
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Based on measurements of the snow cover over sea ice and atmospheric measurements, we estimate snowfall and snow accumulation for the MOSAiC ice floe, between November 2019 and May 2020. For this period, we estimate 98–114 mm of precipitation. We suggest that about 34 mm of snow water equivalent accumulated until the end of April 2020 and that at least about 50 % of the precipitated snow was eroded or sublimated. Further, we suggest explanations for potential snowfall overestimation.
Klaus Dethloff, Wieslaw Maslowski, Stefan Hendricks, Younjoo J. Lee, Helge F. Goessling, Thomas Krumpen, Christian Haas, Dörthe Handorf, Robert Ricker, Vladimir Bessonov, John J. Cassano, Jaclyn Clement Kinney, Robert Osinski, Markus Rex, Annette Rinke, Julia Sokolova, and Anja Sommerfeld
The Cryosphere, 16, 981–1005, https://doi.org/10.5194/tc-16-981-2022, https://doi.org/10.5194/tc-16-981-2022, 2022
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Sea ice thickness anomalies during the MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate) winter in January, February and March 2020 were simulated with the coupled Regional Arctic climate System Model (RASM) and compared with CryoSat-2/SMOS satellite data. Hindcast and ensemble simulations indicate that the sea ice anomalies are driven by nonlinear interactions between ice growth processes and wind-driven sea-ice transports, with dynamics playing a dominant role.
Arttu Jutila, Stefan Hendricks, Robert Ricker, Luisa von Albedyll, Thomas Krumpen, and Christian Haas
The Cryosphere, 16, 259–275, https://doi.org/10.5194/tc-16-259-2022, https://doi.org/10.5194/tc-16-259-2022, 2022
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Sea-ice thickness retrieval from satellite altimeters relies on assumed sea-ice density values because density cannot be measured from space. We derived bulk densities for different ice types using airborne laser, radar, and electromagnetic induction sounding measurements. Compared to previous studies, we found high bulk density values due to ice deformation and younger ice cover. Using sea-ice freeboard, we derived a sea-ice bulk density parameterisation that can be applied to satellite data.
Marek Muchow, Amelie U. Schmitt, and Lars Kaleschke
The Cryosphere, 15, 4527–4537, https://doi.org/10.5194/tc-15-4527-2021, https://doi.org/10.5194/tc-15-4527-2021, 2021
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Linear-like openings in sea ice, also called leads, occur with widths from meters to kilometers. We use satellite images from Sentinel-2 with a resolution of 10 m to identify leads and measure their widths. With that we investigate the frequency of lead widths using two different statistical methods, since other studies have shown a dependency of heat exchange on the lead width. We are the first to address the sea-ice lead-width distribution in the Weddell Sea, Antarctica.
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.
H. Jakob Belter, Thomas Krumpen, Luisa von Albedyll, Tatiana A. Alekseeva, Gerit Birnbaum, Sergei V. Frolov, Stefan Hendricks, Andreas Herber, Igor Polyakov, Ian Raphael, Robert Ricker, Sergei S. Serovetnikov, Melinda Webster, and Christian Haas
The Cryosphere, 15, 2575–2591, https://doi.org/10.5194/tc-15-2575-2021, https://doi.org/10.5194/tc-15-2575-2021, 2021
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Summer sea ice thickness observations based on electromagnetic induction measurements north of Fram Strait show a 20 % reduction in mean and modal ice thickness from 2001–2020. The observed variability is caused by changes in drift speeds and consequential variations in sea ice age and number of freezing-degree days. Increased ocean heat fluxes measured upstream in the source regions of Arctic ice seem to precondition ice thickness, which is potentially still measurable more than a year later.
Francesca Doglioni, Robert Ricker, Benjamin Rabe, and Torsten Kanzow
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2021-170, https://doi.org/10.5194/essd-2021-170, 2021
Manuscript not accepted for further review
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This paper presents a new satellite-derived gridded dataset of sea surface height and geostrophic velocity, over the Arctic ice-covered and ice-free regions up to 88° N. The dataset includes velocities north of 82° N, which were not available before. We assess the dataset by comparison to one independent satellite dataset and to independent mooring data. Results show that the geostrophic velocity fields can resolve seasonal to interannual variability of boundary currents wider than about 50 km.
Chao Min, Qinghua Yang, Longjiang Mu, Frank Kauker, and Robert Ricker
The Cryosphere, 15, 169–181, https://doi.org/10.5194/tc-15-169-2021, https://doi.org/10.5194/tc-15-169-2021, 2021
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An ensemble of four estimates of the sea-ice volume (SIV) variations in Baffin Bay from 2011 to 2016 is generated from the locally merged satellite observations, three modeled sea ice thickness sources (CMST, NAOSIM, and PIOMAS) and NSIDC ice drift data (V4). Results show that the net increase of the ensemble mean SIV occurs from October to April with the largest SIV increase in December, and the reduction occurs from May to September with the largest SIV decline in July.
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.
Zoé Rehder, Anne Laura Niederdrenk, Lars Kaleschke, and Lars Kutzbach
The Cryosphere, 14, 4201–4215, https://doi.org/10.5194/tc-14-4201-2020, https://doi.org/10.5194/tc-14-4201-2020, 2020
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To better understand the connection between sea ice and permafrost, we investigate how sea ice interacts with the atmosphere over the adjacent landmass in the Laptev Sea region using a climate model. Melt of sea ice in spring is mainly controlled by the atmosphere; in fall, feedback mechanisms are important. Throughout summer, lower-than-usual sea ice leads to more southward transport of heat and moisture, but these links from sea ice to the atmosphere over land are weak.
H. Jakob Belter, Thomas Krumpen, Stefan Hendricks, Jens Hoelemann, Markus A. Janout, Robert Ricker, and Christian Haas
The Cryosphere, 14, 2189–2203, https://doi.org/10.5194/tc-14-2189-2020, https://doi.org/10.5194/tc-14-2189-2020, 2020
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The validation of satellite sea ice thickness (SIT) climate data records with newly acquired moored sonar SIT data shows that satellite products provide modal rather than mean SIT in the Laptev Sea region. This tendency of satellite-based SIT products to underestimate mean SIT needs to be considered for investigations of sea ice volume transports. Validation of satellite SIT in the first-year-ice-dominated Laptev Sea will support algorithm development for more reliable SIT records in the Arctic.
Thomas Krumpen, Florent Birrien, Frank Kauker, Thomas Rackow, Luisa von Albedyll, Michael Angelopoulos, H. Jakob Belter, Vladimir Bessonov, Ellen Damm, Klaus Dethloff, Jari Haapala, Christian Haas, Carolynn Harris, Stefan Hendricks, Jens Hoelemann, Mario Hoppmann, Lars Kaleschke, Michael Karcher, Nikolai Kolabutin, Ruibo Lei, Josefine Lenz, Anne Morgenstern, Marcel Nicolaus, Uwe Nixdorf, Tomash Petrovsky, Benjamin Rabe, Lasse Rabenstein, Markus Rex, Robert Ricker, Jan Rohde, Egor Shimanchuk, Suman Singha, Vasily Smolyanitsky, Vladimir Sokolov, Tim Stanton, Anna Timofeeva, Michel Tsamados, and Daniel Watkins
The Cryosphere, 14, 2173–2187, https://doi.org/10.5194/tc-14-2173-2020, https://doi.org/10.5194/tc-14-2173-2020, 2020
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In October 2019 the research vessel Polarstern was moored to an ice floe in order to travel with it on the 1-year-long MOSAiC journey through the Arctic. Here we provide historical context of the floe's evolution and initial state for upcoming studies. We show that the ice encountered on site was exceptionally thin and was formed on the shallow Siberian shelf. The analyses presented provide the initial state for the analysis and interpretation of upcoming biogeochemical and ecological studies.
Marco Meloni, Jerome Bouffard, Tommaso Parrinello, Geoffrey Dawson, Florent Garnier, Veit Helm, Alessandro Di Bella, Stefan Hendricks, Robert Ricker, Erica Webb, Ben Wright, Karina Nielsen, Sanggyun Lee, Marcello Passaro, Michele Scagliola, Sebastian Bjerregaard Simonsen, Louise Sandberg Sørensen, David Brockley, Steven Baker, Sara Fleury, Jonathan Bamber, Luca Maestri, Henriette Skourup, René Forsberg, and Loretta Mizzi
The Cryosphere, 14, 1889–1907, https://doi.org/10.5194/tc-14-1889-2020, https://doi.org/10.5194/tc-14-1889-2020, 2020
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This manuscript aims to describe the evolutions which have been implemented in the new CryoSat Ice processing chain Baseline-D and the validation activities carried out in different domains such as sea ice, land ice and hydrology.
This new CryoSat processing Baseline-D will maximise the uptake and use of CryoSat data by scientific users since it offers improved capability for monitoring the complex and multiscale changes over the cryosphere.
Jinfei Wang, Chao Min, Robert Ricker, Qinghua Yang, Qian Shi, Bo Han, and Stefan Hendricks
The Cryosphere Discuss., https://doi.org/10.5194/tc-2020-48, https://doi.org/10.5194/tc-2020-48, 2020
Revised manuscript not accepted
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To get a better understanding of the characteristics of the newly-released Envisat sea ice data in the Antarctic, we firstly conduct a comprehensive comparison between Envisat and ICESat sea ice thickness. Their deviations are different considering different seasons, years and regions. Potential reasons mainly deduce from the limitations of radar altimeter, the surface roughness and different retrieval algorithms. The smaller deviation in spring has a potential relation with relative humidity.
Maciej Miernecki, Lars Kaleschke, Nina Maaß, Stefan Hendricks, and Sten Schmidl Søbjærg
The Cryosphere, 14, 461–476, https://doi.org/10.5194/tc-14-461-2020, https://doi.org/10.5194/tc-14-461-2020, 2020
Valeria Selyuzhenok, Igor Bashmachnikov, Robert Ricker, Anna Vesman, and Leonid Bobylev
The Cryosphere, 14, 477–495, https://doi.org/10.5194/tc-14-477-2020, https://doi.org/10.5194/tc-14-477-2020, 2020
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This study explores a link between the long-term variations in the integral sea ice volume in the Greenland Sea and oceanic processes. We link the changes in the Pan-Arctic Ice Ocean Modeling and Assimilation System (PIOMAS) regional sea ice volume with the mixed layer, depth and upper-ocean heat content derived using the ARMOR dataset.
Chao Min, Longjiang Mu, Qinghua Yang, Robert Ricker, Qian Shi, Bo Han, Renhao Wu, and Jiping Liu
The Cryosphere, 13, 3209–3224, https://doi.org/10.5194/tc-13-3209-2019, https://doi.org/10.5194/tc-13-3209-2019, 2019
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Sea ice volume export through the Fram Strait has been studied using varied methods, however, mostly in winter months. Here we report sea ice volume estimates that extend over summer seasons. A recent developed sea ice thickness dataset, in which CryoSat-2 and SMOS sea ice thickness together with SSMI/SSMIS sea ice concentration are assimilated, is used and evaluated in the paper. Results show our estimate is more reasonable than that calculated by satellite data only.
Robert Ricker, Fanny Girard-Ardhuin, Thomas Krumpen, and Camille Lique
The Cryosphere, 12, 3017–3032, https://doi.org/10.5194/tc-12-3017-2018, https://doi.org/10.5194/tc-12-3017-2018, 2018
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We present ice volume flux estimates through the Fram Strait using CryoSat-2 ice thickness data. This study presents a detailed analysis of temporal and spatial variability of ice volume export through the Fram Strait and shows the impact of ice volume export on Arctic ice mass balance.
Thomas Kaminski, Frank Kauker, Leif Toudal Pedersen, Michael Voßbeck, Helmuth Haak, Laura Niederdrenk, Stefan Hendricks, Robert Ricker, Michael Karcher, Hajo Eicken, and Ola Gråbak
The Cryosphere, 12, 2569–2594, https://doi.org/10.5194/tc-12-2569-2018, https://doi.org/10.5194/tc-12-2569-2018, 2018
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We present mathematically rigorous assessments of the observation impact (added value) of remote-sensing products and in terms of the uncertainty reduction in a 4-week forecast of sea ice volume and snow volume for three regions along the Northern Sea Route by a coupled model of the sea-ice–ocean system. We quantify the difference in impact between rawer (freeboard) and higher-level (sea ice thickness) products, and the impact of adding a snow depth product.
Stephan Paul, Stefan Hendricks, Robert Ricker, Stefan Kern, and Eero Rinne
The Cryosphere, 12, 2437–2460, https://doi.org/10.5194/tc-12-2437-2018, https://doi.org/10.5194/tc-12-2437-2018, 2018
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During ESA's second phase of the Sea Ice Climate Change Initiative (SICCI-2), we developed a novel approach to creating a consistent freeboard data set from Envisat and CryoSat-2. We used consistent procedures that are directly related to the sensors' waveform-echo parameters, instead of applying corrections as a post-processing step. This data set is to our knowledge the first of its kind providing consistent freeboard for the Arctic as well as the Antarctic.
Graham D. Quartly, Eero Rinne, Marcello Passaro, Ole B. Andersen, Salvatore Dinardo, Sara Fleury, Kevin Guerreiro, Amandine Guillot, Stefan Hendricks, Andrey A. Kurekin, Felix L. Müller, Robert Ricker, Henriette Skourup, and Michel Tsamados
The Cryosphere Discuss., https://doi.org/10.5194/tc-2018-148, https://doi.org/10.5194/tc-2018-148, 2018
Revised manuscript not accepted
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Radar altimetry is a high-precision technique for measuring sea level and sea ice thickness from space, which are important for monitoring ocean circulation, sea level rise and changes in the Arctic ice cover. This paper reviews the processing techniques needed to best extract the information from complicated radar echoes, and considers the likely developments in the coming decade.
Steffen Tietsche, Magdalena Alonso-Balmaseda, Patricia Rosnay, Hao Zuo, Xiangshan Tian-Kunze, and Lars Kaleschke
The Cryosphere, 12, 2051–2072, https://doi.org/10.5194/tc-12-2051-2018, https://doi.org/10.5194/tc-12-2051-2018, 2018
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We compare Arctic sea-ice thickness from L-band microwave satellite observations and an ocean–sea ice reanalysis. There is good agreement for some regions and times but systematic discrepancy in others. Errors in both the reanalysis and observational products contribute to these discrepancies. Thus, we recommend proceeding with caution when using these observations for model validation or data assimilation. At the same time we emphasise their unique value for improving sea-ice forecast models.
Friedrich Richter, Matthias Drusch, Lars Kaleschke, Nina Maaß, Xiangshan Tian-Kunze, and Susanne Mecklenburg
The Cryosphere, 12, 921–933, https://doi.org/10.5194/tc-12-921-2018, https://doi.org/10.5194/tc-12-921-2018, 2018
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L-band (1.4 GHz) brightness temperatures from ESA's Soil Moisture and Ocean Salinity SMOS mission have been used to derive thin sea ice thickness. However, the brightness temperature measurements can potentially be assimilated directly in forecasting systems reducing the data latency and providing a more consistent first guess. We studied the forward (observation) operator that translates geophysical sea ice parameters from the ECMWF Ocean ReAnalysis Pilot 5 (ORAP5) into brightness temperatures.
Christian Katlein, Stefan Hendricks, and Jeffrey Key
The Cryosphere, 11, 2111–2116, https://doi.org/10.5194/tc-11-2111-2017, https://doi.org/10.5194/tc-11-2111-2017, 2017
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In the public debate, increasing sea ice extent in the Antarctic is often highlighted as counter-indicative of global warming. Here we show that the slight increases in Antarctic sea ice extent are not able to counter Arctic losses. Using bipolar satellite observations, we demonstrate that even in the Antarctic polar ocean solar shortwave energy absorption is increasing in accordance with strongly increasing shortwave energy absorption in the Arctic Ocean rather than compensating Arctic losses.
Robert Ricker, Stefan Hendricks, Lars Kaleschke, Xiangshan Tian-Kunze, Jennifer King, and Christian Haas
The Cryosphere, 11, 1607–1623, https://doi.org/10.5194/tc-11-1607-2017, https://doi.org/10.5194/tc-11-1607-2017, 2017
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We developed the first merging of CryoSat-2 and SMOS sea-ice thickness retrievals. ESA’s Earth Explorer SMOS satellite can detect thin sea ice, whereas its companion CryoSat-2, designed to observe thicker perennial sea ice, lacks sensitivity. Using these satellite missions together completes the picture of the changing Arctic sea ice and provides a more accurate and comprehensive view on the actual state of Arctic sea-ice thickness.
Jiping Xie, François Counillon, Laurent Bertino, Xiangshan Tian-Kunze, and Lars Kaleschke
The Cryosphere, 10, 2745–2761, https://doi.org/10.5194/tc-10-2745-2016, https://doi.org/10.5194/tc-10-2745-2016, 2016
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As a potentially operational daily product, the SMOS-Ice can improve the statements of sea ice thickness and concentration. In this study, focusing on the SMOS-Ice data assimilated into the TOPAZ system, the quantitative evaluation for the impacts and the concerned comparison with the present observation system are valuable to understand the further improvement of the accuracy of operational ocean forecasting system.
Sandra Schwegmann, Eero Rinne, Robert Ricker, Stefan Hendricks, and Veit Helm
The Cryosphere, 10, 1415–1425, https://doi.org/10.5194/tc-10-1415-2016, https://doi.org/10.5194/tc-10-1415-2016, 2016
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Our study aimed to investigate whether CS-2 and Envisat radar freeboard can be merged without intermission biases in order to obtain a 20-year data set. The comparison revealed a reasonable regional agreement between radar freeboards derived from both sensors. Differences are mostly below 0.1 m for modal freeboard and even less for mean freeboard over winter months (May–October). The highest differences occur in regions with multi-year sea ice and along the coasts.
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.-M. Blechschmidt, A. Richter, J. P. Burrows, L. Kaleschke, K. Strong, N. Theys, M. Weber, X. Zhao, and A. Zien
Atmos. Chem. Phys., 16, 1773–1788, https://doi.org/10.5194/acp-16-1773-2016, https://doi.org/10.5194/acp-16-1773-2016, 2016
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A comprehensive case study of a comma-shaped bromine monoxide plume in the Arctic, which was transported by a polar cyclone and was observed by the GOME-2 satellite sensor over several days, is presented. By making combined use of different kinds of satellite data and numerical models, we demonstrate the important role of the frontal weather system in favouring the bromine activation cycle and blowing snow production, which may have acted as a bromine source during the bromine explosion event.
F. Kauker, T. Kaminski, R. Ricker, L. Toudal-Pedersen, G. Dybkjaer, C. Melsheimer, S. Eastwood, H. Sumata, M. Karcher, and R. Gerdes
The Cryosphere Discuss., https://doi.org/10.5194/tcd-9-5521-2015, https://doi.org/10.5194/tcd-9-5521-2015, 2015
Revised manuscript not accepted
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The manuscript describes the use of remotely sensed sea ice observations for the initialization of seasonal sea ice predictions. Among other observations, CryoSat-2 ice thickness is, to our knowledge for the first time, utilized. While a direct assimilation with CryoSat ice thickness could improve the predictions only locally, the use an advanced data assimilation system (4dVar) allows to establish a bias correction scheme, which is shown to improve the seasonal predictions Arctic wide.
A. Wernecke and L. Kaleschke
The Cryosphere, 9, 1955–1968, https://doi.org/10.5194/tc-9-1955-2015, https://doi.org/10.5194/tc-9-1955-2015, 2015
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Leads in Arctic sea ice have a dominant effect on the exchange between the ocean and the atmosphere. Visual MODIS scenes are used to validate and improve the detection of leads from altimeter measurements of the satellite CryoSat-2. The rarely used maximum power of the returning signal shows the best classification properties. Lead area fraction and width distribution estimates based on CryoSat-2 complement other studies and deepen our understanding of lead characteristics.
R. Ricker, S. Hendricks, V. Helm, H. Skourup, and M. Davidson
The Cryosphere, 8, 1607–1622, https://doi.org/10.5194/tc-8-1607-2014, https://doi.org/10.5194/tc-8-1607-2014, 2014
X. Tian-Kunze, L. Kaleschke, N. Maaß, M. Mäkynen, N. Serra, M. Drusch, and T. Krumpen
The Cryosphere, 8, 997–1018, https://doi.org/10.5194/tc-8-997-2014, https://doi.org/10.5194/tc-8-997-2014, 2014
M. Huntemann, G. Heygster, L. Kaleschke, T. Krumpen, M. Mäkynen, and M. Drusch
The Cryosphere, 8, 439–451, https://doi.org/10.5194/tc-8-439-2014, https://doi.org/10.5194/tc-8-439-2014, 2014
N. Maaß, L. Kaleschke, X. Tian-Kunze, and M. Drusch
The Cryosphere, 7, 1971–1989, https://doi.org/10.5194/tc-7-1971-2013, https://doi.org/10.5194/tc-7-1971-2013, 2013
L. Rabenstein, T. Krumpen, S. Hendricks, C. Koeberle, C. Haas, and J. A. Hoelemann
The Cryosphere, 7, 947–959, https://doi.org/10.5194/tc-7-947-2013, https://doi.org/10.5194/tc-7-947-2013, 2013
A. Tetzlaff, L. Kaleschke, C. Lüpkes, F. Ament, and T. Vihma
The Cryosphere, 7, 153–166, https://doi.org/10.5194/tc-7-153-2013, https://doi.org/10.5194/tc-7-153-2013, 2013
Related subject area
Domain: ESSD – Ice | Subject: Snow and Sea Ice
Time series of alpine snow surface radiative-temperature maps from high-precision thermal-infrared imaging
Operational and experimental snow observation systems in the upper Rofental: data from 2017 to 2023
A sea ice deformation and rotation rates dataset (2017–2023) from the Environment and Climate Change Canada Automated Sea Ice Tracking System (ECCC-ASITS)
An Arctic sea ice concentration data record on a 6.25 km polar stereographic grid from three-years’ Landsat-8 imagery
A 12-year climate record of wintertime wave-affected marginal ice zones in the Atlantic Arctic based on CryoSat-2
MODIS daily cloud-gap-filled fractional snow cover dataset of the Asian Water Tower region (2000–2022)
Mapping of sea ice concentration using the NASA NIMBUS 5 Electrically Scanning Microwave Radiometer data from 1972–1977
A climate data record of year-round global sea-ice drift from the EUMETSAT Ocean and Sea Ice Satellite Application Facility (OSI SAF)
Snow accumulation and ablation measurements in a midlatitude mountain coniferous forest (Col de Porte, France, 1325 m altitude): the Snow Under Forest (SnoUF) field campaign data set
A new sea ice concentration product in the polar regions derived from the FengYun-3 MWRI sensors
NH-SWE: Northern Hemisphere Snow Water Equivalent dataset based on in situ snow depth time series
IT-SNOW: a snow reanalysis for Italy blending modeling, in situ data, and satellite observations (2010–2021)
HMRFS–TP: long-term daily gap-free snow cover products over the Tibetan Plateau from 2002 to 2021 based on hidden Markov random field model
Sara Arioli, Ghislain Picard, Laurent Arnaud, Simon Gascoin, Esteban Alonso-González, Marine Poizat, and Mark Irvine
Earth Syst. Sci. Data, 16, 3913–3934, https://doi.org/10.5194/essd-16-3913-2024, https://doi.org/10.5194/essd-16-3913-2024, 2024
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High-accuracy precision maps of the surface temperature of snow were acquired with an uncooled thermal-infrared camera during winter 2021–2022 and spring 2023. The accuracy – i.e., mean absolute error – improved from 1.28 K to 0.67 K between the seasons thanks to an improved camera setup and temperature stabilization. The dataset represents a major advance in the validation of satellite measurements and physical snow models over a complex topography.
Michael Warscher, Thomas Marke, Erwin Rottler, and Ulrich Strasser
Earth Syst. Sci. Data, 16, 3579–3599, https://doi.org/10.5194/essd-16-3579-2024, https://doi.org/10.5194/essd-16-3579-2024, 2024
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Continuous observations of snow and climate at high altitudes are still sparse. We present a unique collection of weather and snow cover data from three automatic weather stations at remote locations in the Ötztal Alps (Austria) that include continuous recordings of snow cover properties. The data are available over multiple winter seasons and enable new insights for snow hydrological research. The data are also used in operational applications, i.e., for avalanche warning and flood forecasting.
Mathieu Plante, Jean-François Lemieux, L. Bruno Tremblay, Amélie Bouchat, Damien Ringeisen, Philippe Blain, Stephen Howell, Mike Brady, Alexander S. Komarov, Béatrice Duval, and Lekima Yakuden
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-227, https://doi.org/10.5194/essd-2024-227, 2024
Revised manuscript accepted for ESSD
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Sea ice forms a thin boundary between the ocean and the atmosphere, with a complex crust-like dynamics and ever-changing networks of sea ice leads and ridges. Statistics of these dynamical features are often used to evaluate sea ice models. Here, we present a new pan-Arctic dataset of sea ice deformations derived from satellite imagery, from 01 September 2017 to 31 August 2023. We discuss the dataset coverage and some limitations associated with uncertainties in the computed values.
Hee-Sung Jung, Sang-Moo Lee, Joo-Hong Kim, and Kyungsoo Lee
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-264, https://doi.org/10.5194/essd-2024-264, 2024
Revised manuscript accepted for ESSD
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This dataset consists of true-like sea ice concentration (SIC) data records over the Arctic Ocean, which was derived from the 30 m resolution imagery from the Operational Land Imager (OLI) onboard Landsat-8. Each SIC map are given in a 6.25 km polar stereographic grid, and are catalogued into one of the twelve sub-regions of the Arctic Ocean. This dataset was produced to be used as reference in validation of various SIC products.
Weixin Zhu, Siqi Liu, Shiming Xu, and Lu Zhou
Earth Syst. Sci. Data, 16, 2917–2940, https://doi.org/10.5194/essd-16-2917-2024, https://doi.org/10.5194/essd-16-2917-2024, 2024
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In the polar ocean, wind waves generate and propagate into the sea ice cover, forming marginal ice zones (MIZs). Using ESA's CryoSat-2, we construct a 12-year dataset of the MIZ in the Atlantic Arctic, a key region for climate change and human activities. The dataset is validated with high-resolution observations by ICESat2 and Sentinel-1. MIZs over 300 km wide are found under storms in the Barents Sea. The new dataset serves as the basis for research areas, including wave–ice interactions.
Fangbo Pan, Lingmei Jiang, Gongxue Wang, Jinmei Pan, Jinyu Huang, Cheng Zhang, Huizhen Cui, Jianwei Yang, Zhaojun Zheng, Shengli Wu, and Jiancheng Shi
Earth Syst. Sci. Data, 16, 2501–2523, https://doi.org/10.5194/essd-16-2501-2024, https://doi.org/10.5194/essd-16-2501-2024, 2024
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It is important to strengthen the continuous monitoring of snow cover as a key indicator of imbalance in the Asian Water Tower (AWT) region. We generate long-term daily gap-free fractional snow cover products over the AWT at 0.005° resolution from 2000 to 2022 based on the multiple-endmember spectral mixture analysis algorithm and the gap-filling algorithm. They can provide highly accurate, quantitative fractional snow cover information for subsequent studies on hydrology and climate.
Wiebke Margitta Kolbe, Rasmus T. Tonboe, and Julienne Stroeve
Earth Syst. Sci. Data, 16, 1247–1264, https://doi.org/10.5194/essd-16-1247-2024, https://doi.org/10.5194/essd-16-1247-2024, 2024
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Current satellite-based sea-ice climate data records (CDRs) usually begin in October 1978 with the first multichannel microwave radiometer data. Here, we present a sea ice dataset based on the single-channel Electrical Scanning Microwave Radiometer (ESMR) that operated from 1972-1977 onboard NASA’s Nimbus 5 satellite. The data were processed using modern methods and include uncertainty estimations in order to provide an important, easy-to-use reference period of good quality for current CDRs.
Thomas Lavergne and Emily Down
Earth Syst. Sci. Data, 15, 5807–5834, https://doi.org/10.5194/essd-15-5807-2023, https://doi.org/10.5194/essd-15-5807-2023, 2023
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Sea ice in the Arctic and Antarctic can move several tens of kilometers per day due to wind and ocean currents. By analysing thousands of satellite images, we measured how sea ice has been moving every single day from 1991 through to 2020. We compare our data to how buoys attached to the ice moved and find good agreement. Other scientists will now use our data to better understand if climate change has modified the way sea ice moves and in what way.
Jean Emmanuel Sicart, Victor Ramseyer, Ghislain Picard, Laurent Arnaud, Catherine Coulaud, Guilhem Freche, Damien Soubeyrand, Yves Lejeune, Marie Dumont, Isabelle Gouttevin, Erwan Le Gac, Frédéric Berger, Jean-Matthieu Monnet, Laurent Borgniet, Éric Mermin, Nick Rutter, Clare Webster, and Richard Essery
Earth Syst. Sci. Data, 15, 5121–5133, https://doi.org/10.5194/essd-15-5121-2023, https://doi.org/10.5194/essd-15-5121-2023, 2023
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Forests strongly modify the accumulation, metamorphism and melting of snow in midlatitude and high-latitude regions. Two field campaigns during the winters 2016–17 and 2017–18 were conducted in a coniferous forest in the French Alps to study interactions between snow and vegetation. This paper presents the field site, instrumentation and collection methods. The observations include forest characteristics, meteorology, snow cover and snow interception by the canopy during precipitation events.
Ying Chen, Ruibo Lei, Xi Zhao, Shengli Wu, Yue Liu, Pei Fan, Qing Ji, Peng Zhang, and Xiaoping Pang
Earth Syst. Sci. Data, 15, 3223–3242, https://doi.org/10.5194/essd-15-3223-2023, https://doi.org/10.5194/essd-15-3223-2023, 2023
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The sea ice concentration product derived from the Microwave Radiation Image sensors on board the FengYun-3 satellites can reasonably and independently identify the seasonal and long-term changes of sea ice, as well as extreme cases of annual maximum and minimum sea ice extent in polar regions. It is comparable with other sea ice concentration products and applied to the studies of climate and marine environment.
Adrià Fontrodona-Bach, Bettina Schaefli, Ross Woods, Adriaan J. Teuling, and Joshua R. Larsen
Earth Syst. Sci. Data, 15, 2577–2599, https://doi.org/10.5194/essd-15-2577-2023, https://doi.org/10.5194/essd-15-2577-2023, 2023
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We provide a dataset of snow water equivalent, the depth of liquid water that results from melting a given depth of snow. The dataset contains 11 071 sites over the Northern Hemisphere, spans the period 1950–2022, and is based on daily observations of snow depth on the ground and a model. The dataset fills a lack of accessible historical ground snow data, and it can be used for a variety of applications such as the impact of climate change on global and regional snow and water resources.
Francesco Avanzi, Simone Gabellani, Fabio Delogu, Francesco Silvestro, Flavio Pignone, Giulia Bruno, Luca Pulvirenti, Giuseppe Squicciarino, Elisabetta Fiori, Lauro Rossi, Silvia Puca, Alexander Toniazzo, Pietro Giordano, Marco Falzacappa, Sara Ratto, Hervè Stevenin, Antonio Cardillo, Matteo Fioletti, Orietta Cazzuli, Edoardo Cremonese, Umberto Morra di Cella, and Luca Ferraris
Earth Syst. Sci. Data, 15, 639–660, https://doi.org/10.5194/essd-15-639-2023, https://doi.org/10.5194/essd-15-639-2023, 2023
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Snow cover has profound implications for worldwide water supply and security, but knowledge of its amount and distribution across the landscape is still elusive. We present IT-SNOW, a reanalysis comprising daily maps of snow amount and distribution across Italy for 11 snow seasons from September 2010 to August 2021. The reanalysis was validated using satellite images and snow measurements and will provide highly needed data to manage snow water resources in a warming climate.
Yan Huang, Jiahui Xu, Jingyi Xu, Yelei Zhao, Bailang Yu, Hongxing Liu, Shujie Wang, Wanjia Xu, Jianping Wu, and Zhaojun Zheng
Earth Syst. Sci. Data, 14, 4445–4462, https://doi.org/10.5194/essd-14-4445-2022, https://doi.org/10.5194/essd-14-4445-2022, 2022
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Reliable snow cover information is important for understating climate change and hydrological cycling. We generate long-term daily gap-free snow products over the Tibetan Plateau (TP) at 500 m resolution from 2002 to 2021 based on the hidden Markov random field model. The accuracy is 91.36 %, and is especially improved during snow transitional period and over complex terrains. This dataset has great potential to study climate change and to facilitate water resource management in the TP.
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Short summary
We describe a sea ice thickness dataset based on SMOS satellite measurements, initially designed for the Arctic but adapted for Antarctica. We validated it using limited Antarctic measurements. Our findings show promising results, with a small difference in thickness estimation and a strong correlation with validation data within the valid thickness range. However, improvements and synergies with other sensors are needed, especially for sea ice thicker than 1 m.
We describe a sea ice thickness dataset based on SMOS satellite measurements, initially designed...
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