Articles | Volume 12, issue 8
https://doi.org/10.5194/tc-12-2569-2018
© Author(s) 2018. 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-12-2569-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
13 Aug 2018
Research article |
| 13 Aug 2018
Arctic Mission Benefit Analysis: impact of sea ice thickness, freeboard, and snow depth products on sea ice forecast performance
Thomas Kaminski
CORRESPONDING AUTHOR
The Inversion Lab, Hamburg, Germany
Frank Kauker
Ocean Atmosphere Systems, Hamburg, Germany
Alfred Wegener Institute, Bremerhaven, Germany
Leif Toudal Pedersen
eolab.dk, Copenhagen, Denmark
DTU-Space, Technical University of Denmark, Lyngby, Denmark
Michael Voßbeck
The Inversion Lab, Hamburg, Germany
Helmuth Haak
Max Planck Institute for Meteorology, Hamburg, Germany
Laura Niederdrenk
Max Planck Institute for Meteorology, Hamburg, Germany
Stefan Hendricks
Alfred Wegener Institute, Bremerhaven, Germany
Robert Ricker
Alfred Wegener Institute, Bremerhaven, Germany
Michael Karcher
Ocean Atmosphere Systems, Hamburg, Germany
Alfred Wegener Institute, Bremerhaven, Germany
Hajo Eicken
University of Alaska Fairbanks, Fairbanks, USA
Ola Gråbak
European Space Agency ESRIN, Frascati, Rome, Italy
Related authors
Nemesio J. Rodríguez-Fernández, Arnaud Mialon, Stephane Mermoz, Alexandre Bouvet, Philippe Richaume, Ahmad Al Bitar, Amen Al-Yaari, Martin Brandt, Thomas Kaminski, Thuy Le Toan, Yann H. Kerr, and Jean-Pierre Wigneron
Biogeosciences, 15, 4627–4645, https://doi.org/10.5194/bg-15-4627-2018, https://doi.org/10.5194/bg-15-4627-2018, 2018
Short summary
Short summary
Existing global scale above-ground biomass (AGB) maps are made at very high spatial resolution collecting data during several years. In this paper we discuss the use of a new data set from the SMOS satellite: the vegetation optical depth estimated from low microwave frequencies. It is shown that this new data set is highly sensitive to AGB. The spacial resolution of SMOS is coarse (40 km) but the new data set can be used to monitor AGB variations with time due to its high revisit frequency.
Thomas Kaminski and Peter Julian Rayner
Biogeosciences, 14, 4755–4766, https://doi.org/10.5194/bg-14-4755-2017, https://doi.org/10.5194/bg-14-4755-2017, 2017
Short summary
Short summary
Observations can reduce uncertainties in past, current, and predicted natural and anthropogenic CO2 fluxes. They provide independent information for verification of actions as requested by the Paris Agreement. Quantitative network design (QND) is an objective approach to optimise in situ networks and space missions to achieve an optimal use of the observational capabilities. We describe recent progress and advocate an integrated QND system that simultaneously evaluates multiple data streams.
Miguel D. Mahecha, Fabian Gans, Sebastian Sippel, Jonathan F. Donges, Thomas Kaminski, Stefan Metzger, Mirco Migliavacca, Dario Papale, Anja Rammig, and Jakob Zscheischler
Biogeosciences, 14, 4255–4277, https://doi.org/10.5194/bg-14-4255-2017, https://doi.org/10.5194/bg-14-4255-2017, 2017
Short summary
Short summary
We investigate the likelihood of ecological in situ networks to detect and monitor the impact of extreme events in the terrestrial biosphere.
Thomas Kaminski, Bernard Pinty, Michael Voßbeck, Maciej Lopatka, Nadine Gobron, and Monica Robustelli
Biogeosciences, 14, 2527–2541, https://doi.org/10.5194/bg-14-2527-2017, https://doi.org/10.5194/bg-14-2527-2017, 2017
Short summary
Short summary
We present the Joint Research Centre Two-stream Inversion Package (JRC-TIP) for retrieval of variables characterising the state of the vegetation–soil system. The system provides a set of land surface variables that satisfy all requirements for assimilation into the land component of climate and numerical weather prediction models.
Thomas Kaminski and Pierre-Philippe Mathieu
Biogeosciences, 14, 2343–2357, https://doi.org/10.5194/bg-14-2343-2017, https://doi.org/10.5194/bg-14-2343-2017, 2017
Short summary
Short summary
This paper provides the formalism and examples of how observation operators can be used, in combination with data assimilation or retrieval techniques, to better ingest satellite products in a manner consistent with the dynamics of the Earth system expressed by models.
Sander Houweling, Peter Bergamaschi, Frederic Chevallier, Martin Heimann, Thomas Kaminski, Maarten Krol, Anna M. Michalak, and Prabir Patra
Atmos. Chem. Phys., 17, 235–256, https://doi.org/10.5194/acp-17-235-2017, https://doi.org/10.5194/acp-17-235-2017, 2017
Short summary
Short summary
The aim of this paper is to present an overview of inverse modeling methods, developed over the years, for estimating the global sources and sinks of the greenhouse gas methane from atmospheric measurements. It provides insight into how techniques and estimates have evolved over time, what the remaining shortcomings are, new developments, and promising future directions.
Gregor J. Schürmann, Thomas Kaminski, Christoph Köstler, Nuno Carvalhais, Michael Voßbeck, Jens Kattge, Ralf Giering, Christian Rödenbeck, Martin Heimann, and Sönke Zaehle
Geosci. Model Dev., 9, 2999–3026, https://doi.org/10.5194/gmd-9-2999-2016, https://doi.org/10.5194/gmd-9-2999-2016, 2016
Short summary
Short summary
We describe the Max Planck Institute Carbon Cycle Data Assimilation System (MPI-CCDAS). The system improves the modelled carbon cycle of the terrestrial biosphere by systematically confronting (or assimilating) the model with observations of atmospheric CO2 and fractions of absorbed photosynthetically active radiation. Jointly assimilating both data streams outperforms the single-data stream experiments, thus showing the value of a multi-data stream assimilation.
Dmitry A. Belikov, Shamil Maksyutov, Alexey Yaremchuk, Alexander Ganshin, Thomas Kaminski, Simon Blessing, Motoki Sasakawa, Angel J. Gomez-Pelaez, and Alexander Starchenko
Geosci. Model Dev., 9, 749–764, https://doi.org/10.5194/gmd-9-749-2016, https://doi.org/10.5194/gmd-9-749-2016, 2016
T. Kaminski, F. Kauker, H. Eicken, and M. Karcher
The Cryosphere, 9, 1721–1733, https://doi.org/10.5194/tc-9-1721-2015, https://doi.org/10.5194/tc-9-1721-2015, 2015
Short summary
Short summary
We present a quantitative network design study of the Arctic sea ice-ocean system. For a demonstration, we evaluate two idealised hypothetical flight transects derived from NASA’s Operation IceBridge airborne ice surveys in terms of their potential to improve 10-day to 5-month sea ice forecasts. Our analysis quantifies the benefits of sampling upstream of the target area and of reducing the sampling uncertainty. It further quantifies the complementarity of combining two flight transects.
S. Kemp, M. Scholze, T. Ziehn, and T. Kaminski
Geosci. Model Dev., 7, 1609–1619, https://doi.org/10.5194/gmd-7-1609-2014, https://doi.org/10.5194/gmd-7-1609-2014, 2014
W. Knorr, T. Kaminski, A. Arneth, and U. Weber
Biogeosciences, 11, 1085–1102, https://doi.org/10.5194/bg-11-1085-2014, https://doi.org/10.5194/bg-11-1085-2014, 2014
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
Short summary
Short summary
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
Short summary
Short summary
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.
Cathy Hohenegger, Peter Korn, Leonidas Linardakis, René Redler, Reiner Schnur, Panagiotis Adamidis, Jiawei Bao, Swantje Bastin, Milad Behravesh, Martin Bergemann, Joachim Biercamp, Hendryk Bockelmann, Renate Brokopf, Nils Brüggemann, Lucas Casaroli, Fatemeh Chegini, George Datseris, Monika Esch, Geet George, Marco Giorgetta, Oliver Gutjahr, Helmuth Haak, Moritz Hanke, Tatiana Ilyina, Thomas Jahns, Johann Jungclaus, Marcel Kern, Daniel Klocke, Lukas Kluft, Tobias Kölling, Luis Kornblueh, Sergey Kosukhin, Clarissa Kroll, Junhong Lee, Thorsten Mauritsen, Carolin Mehlmann, Theresa Mieslinger, Ann Kristin Naumann, Laura Paccini, Angel Peinado, Divya Sri Praturi, Dian Putrasahan, Sebastian Rast, Thomas Riddick, Niklas Roeber, Hauke Schmidt, Uwe Schulzweida, Florian Schütte, Hans Segura, Radomyra Shevchenko, Vikram Singh, Mia Specht, Claudia Christine Stephan, Jin-Song von Storch, Raphaela Vogel, Christian Wengel, Marius Winkler, Florian Ziemen, Jochem Marotzke, and Bjorn Stevens
Geosci. Model Dev., 16, 779–811, https://doi.org/10.5194/gmd-16-779-2023, https://doi.org/10.5194/gmd-16-779-2023, 2023
Short summary
Short summary
Models of the Earth system used to understand climate and predict its change typically employ a grid spacing of about 100 km. Yet, many atmospheric and oceanic processes occur on much smaller scales. In this study, we present a new model configuration designed for the simulation of the components of the Earth system and their interactions at kilometer and smaller scales, allowing an explicit representation of the main drivers of the flow of energy and matter by solving the underlying equations.
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
Short summary
Short summary
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.
Laura Claire Jackson, Eduardo Alastrué de Asenjo, Katinka Bellomo, Gokhan Danabasoglu, Helmuth Haak, Aixue Hu, Johann Jungclaus, Warren Lee, Virna L. Meccia, Oleg Saenko, Andrew Shao, and Didier Swingedouw
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-277, https://doi.org/10.5194/gmd-2022-277, 2022
Revised manuscript accepted for GMD
Short summary
Short summary
The Atlantic meridional overturning circulation (AMOC) has an important impact on the climate. There are theories that freshening of the ocean might cause the AMOC to cross a tipping point (TP) beyond which recovery is difficult, however it is unclear whether TP exist in global climate models. Here we outline a set of experiments designed to explore AMOC tipping points and sensitivity to additional freshwater input as part of the North Atlantic hosing model intercomparison project (NAHosMIP).
John E. Walsh, Hajo Eicken, Kyle Redilla, and Mark Johnson
The Cryosphere, 16, 4617–4635, https://doi.org/10.5194/tc-16-4617-2022, https://doi.org/10.5194/tc-16-4617-2022, 2022
Short summary
Short summary
Indicators for the start and end of annual breakup and freeze-up of sea ice at various coastal locations around the Arctic are developed. Relative to broader offshore areas, some of the coastal indicators show an earlier freeze-up and later breakup, especially at locations where landfast ice is prominent. However, the trends towards earlier breakup and later freeze-up are unmistakable over the post-1979 period in synthesized metrics of the coastal breakup/freeze-up indicators.
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
Short summary
Short summary
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.
Robert Ricker, Steven Fons, Arttu Jutila, Nils Hutter, Kyle Duncan, Sinead L. Farrell, Nathan T. Kurtz, and Renée Mie Fredensborg Hansen
EGUsphere, https://doi.org/10.5194/egusphere-2022-1122, https://doi.org/10.5194/egusphere-2022-1122, 2022
Short summary
Short summary
Information on the sea ice surface topography are important for studies of sea ice, and ship navigation through the ice. The satellite called "ICESat-2" senses the sea ice surface with six laser beams. To proof the accuracy of those measurements, we have carried out a helicopter flight at the same time and along the same ground track as the satellite and measured the sea ice surface topography with a laser scanner, showing that ICESat-2 can see even bumps of only few meters in the sea ice cover.
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
Short summary
Short summary
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.
Karina von Schuckmann, Audrey Minère, Flora Gues, Francisco José Cuesta-Valero, Gottfried Kirchengast, Susheel Adusumilli, Fiammetta Straneo, Richard Allan, Paul M. Barker, Hugo Beltrami, 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, Stefan Hendricks, Shigeki Hosoda, Gregory C. Johnson, Rachel Killick, Brian King, Nikolas Kolodziejczyk, Anton Korosov, Gerhard Krinner, Mikael Kuusela, Moritz Langer, Thomas Lavergne, Isobel Lawrence, Yuehua Li, John Lyman, 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, Noah Smith, Andrea Steiner, Toshio Suga, Tanguy Szekely, Wim Thiery, Mary-Louise Timmermans, Inne Vanderkelen, Susan E. Wjiffels, Tonghua Wu, and Michael Zemp
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2022-239, https://doi.org/10.5194/essd-2022-239, 2022
Revised manuscript accepted for ESSD
Short summary
Short summary
Earth climate is out of energy balance and this study quantifies how much heat has consequently accumulated over the past decades (89 %: ocean, 6 %: land, 4 %: cryosphere, 1 %: atmosphere). Since 1971, this accumulated heat reached record values at an increasing pace. The Earth heat inventory provides a comprehensive view on the status and expectation of global warming, and we call for an implementation of this global climate indicator into the Paris agreement’s global stocktake.
Vishnu Nandan, Rosemary Willatt, Robbie Mallett, Julienne Stroeve, Torsten Geldsetzer, Randall Scharien, Rasmus Tonboe, Jack Landy, David Clemens-Sewall, Arttu Jutila, David N. Wagner, Daniela Krampe, Marcus Huntemann, John Yackel, 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 Hoppman
The Cryosphere Discuss., https://doi.org/10.5194/tc-2022-116, https://doi.org/10.5194/tc-2022-116, 2022
Revised manuscript under review for TC
Short summary
Short summary
We show that, wind blows and redistributes snow on sea ice, and Ka- and Ku-band radar signatures detect both newly deposited and buried snow layers that can critically affect snow depth measurements on ice. Radar measurements, meteorological and snow physical data were collected during the MOSAiC Expedition. With frequent occurrence of storms in the Arctic, our results provide baseline information that are vitally important for accurately calculating snow depth on sea ice from satellite radars.
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
Short summary
Short summary
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.
Fengguan Gu, Qinghua Yang, Frank Kauker, Changwei Liu, Guanghua Hao, Chao-Yuan Yang, Jiping Liu, Petra Heil, Xuewei Li, and Bo Han
The Cryosphere, 16, 1873–1887, https://doi.org/10.5194/tc-16-1873-2022, https://doi.org/10.5194/tc-16-1873-2022, 2022
Short summary
Short summary
The sea ice thickness was simulated by a single-column model and compared with in situ observations obtained off Zhongshan Station in the Antarctic. It is shown that the unrealistic precipitation in the atmospheric forcing data leads to the largest bias in sea ice thickness and snow depth modeling. In addition, the increasing snow depth gradually inhibits the growth of sea ice associated with thermal blanketing by the snow.
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Oliver Gutjahr, Nils Brüggemann, Helmuth Haak, Johann H. Jungclaus, Dian A. Putrasahan, Katja Lohmann, and Jin-Song von Storch
Geosci. Model Dev., 14, 2317–2349, https://doi.org/10.5194/gmd-14-2317-2021, https://doi.org/10.5194/gmd-14-2317-2021, 2021
Short summary
Short summary
We compare four ocean vertical mixing schemes in 100-year coupled simulations with the Max Planck Institute Earth System Model (MPI-ESM1.2) and analyse their model biases. Overall, the mixing schemes modify biases in the ocean interior that vary with region and variable but produce a similar global bias pattern. We therefore cannot classify any scheme as superior but conclude that the chosen mixing scheme may be important for regional biases.
Daniela Krampe, Frank Kauker, Marie Dumont, and Andreas Herber
The Cryosphere Discuss., https://doi.org/10.5194/tc-2021-100, https://doi.org/10.5194/tc-2021-100, 2021
Manuscript not accepted for further review
Short summary
Short summary
Reliable and detailed Arctic snow data are limited. Evaluation of the performance of atmospheric reanalysis compared to measurements in northeast Greenland generally show good agreement. Both data sets are applied to an Alpine snow model and the performance for Arctic conditions is investigated: Simulated snow depth evolution is reliable, but vertical snow profiles show weaknesses. These are smaller with an adapted parametrisation for the density of newly fallen snow for harsh Arctic conditions.
Tingfeng Dou, Cunde Xiao, Jiping Liu, Qiang Wang, Shifeng Pan, Jie Su, Xiaojun Yuan, Minghu Ding, Feng Zhang, Kai Xue, Peter A. Bieniek, and Hajo Eicken
The Cryosphere, 15, 883–895, https://doi.org/10.5194/tc-15-883-2021, https://doi.org/10.5194/tc-15-883-2021, 2021
Short summary
Short summary
Rain-on-snow (ROS) events can accelerate the surface ablation of sea ice, greatly influencing the ice–albedo feedback. We found that spring ROS events have shifted to earlier dates over the Arctic Ocean in recent decades, which is correlated with sea ice melt onset in the Pacific sector and most Eurasian marginal seas. There has been a clear transition from solid to liquid precipitation, leading to a reduction in spring snow depth on sea ice by more than −0.5 cm per decade since the 1980s.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Marc Oggier, Hajo Eicken, Meibing Jin, and Knut Høyland
The Cryosphere Discuss., https://doi.org/10.5194/tc-2020-52, https://doi.org/10.5194/tc-2020-52, 2020
Publication in TC not foreseen
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
Oliver Gutjahr, Dian Putrasahan, Katja Lohmann, Johann H. Jungclaus, Jin-Song von Storch, Nils Brüggemann, Helmuth Haak, and Achim Stössel
Geosci. Model Dev., 12, 3241–3281, https://doi.org/10.5194/gmd-12-3241-2019, https://doi.org/10.5194/gmd-12-3241-2019, 2019
Short summary
Short summary
We analyse how climatic mean states of the atmosphere and ocean change with increasing the horizontal model resolution of the Max Planck Institute Earth System Model (MPI-ESM1.2) and how they are affected by the representation of vertical mixing in the ocean. It is in particular a high-resolution ocean that reduces biases not only in the ocean but also in the atmosphere. The vertical mixing scheme affects the strength and stability of the Atlantic meridional overturning circulation (AMOC).
Dyre Oliver Dammann, Leif E. B. Eriksson, Joshua M. Jones, Andrew R. Mahoney, Roland Romeiser, Franz J. Meyer, Hajo Eicken, and Yasushi Fukamachi
The Cryosphere, 13, 1395–1408, https://doi.org/10.5194/tc-13-1395-2019, https://doi.org/10.5194/tc-13-1395-2019, 2019
Short summary
Short summary
We evaluate single-pass synthetic aperture radar interferometry (InSAR) as a tool to assess sea ice drift and deformation. Initial validation shows that TanDEM-X phase-derived drift speed corresponds well with ground-based radar-derived motion. We further show that InSAR enables the identification of potentially important short-lived dynamic processes otherwise difficult to observe, with possible implication for engineering and sea ice modeling.
Tingfeng Dou, Cunde Xiao, Jiping Liu, Wei Han, Zhiheng Du, Andrew R. Mahoney, Joshua Jones, and Hajo Eicken
The Cryosphere, 13, 1233–1246, https://doi.org/10.5194/tc-13-1233-2019, https://doi.org/10.5194/tc-13-1233-2019, 2019
Short summary
Short summary
The variability and potential trends of rain-on-snow events over Arctic sea ice and their role in sea-ice losses are poorly understood. This study demonstrates that rain-on-snow events are a critical factor in initiating the onset of surface melt over Arctic sea ice, and onset of spring rainfall over sea ice has shifted to earlier dates since the 1970s, which may have profound impacts on ice melt through feedbacks involving earlier onset of surface melt.
Dyre O. Dammann, Leif E. B. Eriksson, Andrew R. Mahoney, Hajo Eicken, and Franz J. Meyer
The Cryosphere, 13, 557–577, https://doi.org/10.5194/tc-13-557-2019, https://doi.org/10.5194/tc-13-557-2019, 2019
Short summary
Short summary
We present an approach for mapping bottomfast sea ice and landfast sea ice stability using Synthetic Aperture Radar Interferometry. This is the first comprehensive assessment of Arctic bottomfast sea ice extent with implications for subsea permafrost and marine habitats. Our pan-Arctic analysis also provides a new understanding of sea ice dynamics in five marginal seas of the Arctic Ocean relevant for strategic planning and tactical decision-making for different uses of coastal ice.
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
Short summary
Short summary
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.
Nemesio J. Rodríguez-Fernández, Arnaud Mialon, Stephane Mermoz, Alexandre Bouvet, Philippe Richaume, Ahmad Al Bitar, Amen Al-Yaari, Martin Brandt, Thomas Kaminski, Thuy Le Toan, Yann H. Kerr, and Jean-Pierre Wigneron
Biogeosciences, 15, 4627–4645, https://doi.org/10.5194/bg-15-4627-2018, https://doi.org/10.5194/bg-15-4627-2018, 2018
Short summary
Short summary
Existing global scale above-ground biomass (AGB) maps are made at very high spatial resolution collecting data during several years. In this paper we discuss the use of a new data set from the SMOS satellite: the vegetation optical depth estimated from low microwave frequencies. It is shown that this new data set is highly sensitive to AGB. The spacial resolution of SMOS is coarse (40 km) but the new data set can be used to monitor AGB variations with time due to its high revisit frequency.
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
Short summary
Short summary
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
Short summary
Short summary
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.
Thomas Kaminski and Peter Julian Rayner
Biogeosciences, 14, 4755–4766, https://doi.org/10.5194/bg-14-4755-2017, https://doi.org/10.5194/bg-14-4755-2017, 2017
Short summary
Short summary
Observations can reduce uncertainties in past, current, and predicted natural and anthropogenic CO2 fluxes. They provide independent information for verification of actions as requested by the Paris Agreement. Quantitative network design (QND) is an objective approach to optimise in situ networks and space missions to achieve an optimal use of the observational capabilities. We describe recent progress and advocate an integrated QND system that simultaneously evaluates multiple data streams.
Miguel D. Mahecha, Fabian Gans, Sebastian Sippel, Jonathan F. Donges, Thomas Kaminski, Stefan Metzger, Mirco Migliavacca, Dario Papale, Anja Rammig, and Jakob Zscheischler
Biogeosciences, 14, 4255–4277, https://doi.org/10.5194/bg-14-4255-2017, https://doi.org/10.5194/bg-14-4255-2017, 2017
Short summary
Short summary
We investigate the likelihood of ecological in situ networks to detect and monitor the impact of extreme events in the terrestrial biosphere.
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
Short summary
Short summary
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
Short summary
Short summary
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.
Thomas Kaminski, Bernard Pinty, Michael Voßbeck, Maciej Lopatka, Nadine Gobron, and Monica Robustelli
Biogeosciences, 14, 2527–2541, https://doi.org/10.5194/bg-14-2527-2017, https://doi.org/10.5194/bg-14-2527-2017, 2017
Short summary
Short summary
We present the Joint Research Centre Two-stream Inversion Package (JRC-TIP) for retrieval of variables characterising the state of the vegetation–soil system. The system provides a set of land surface variables that satisfy all requirements for assimilation into the land component of climate and numerical weather prediction models.
Thomas Kaminski and Pierre-Philippe Mathieu
Biogeosciences, 14, 2343–2357, https://doi.org/10.5194/bg-14-2343-2017, https://doi.org/10.5194/bg-14-2343-2017, 2017
Short summary
Short summary
This paper provides the formalism and examples of how observation operators can be used, in combination with data assimilation or retrieval techniques, to better ingest satellite products in a manner consistent with the dynamics of the Earth system expressed by models.
Sander Houweling, Peter Bergamaschi, Frederic Chevallier, Martin Heimann, Thomas Kaminski, Maarten Krol, Anna M. Michalak, and Prabir Patra
Atmos. Chem. Phys., 17, 235–256, https://doi.org/10.5194/acp-17-235-2017, https://doi.org/10.5194/acp-17-235-2017, 2017
Short summary
Short summary
The aim of this paper is to present an overview of inverse modeling methods, developed over the years, for estimating the global sources and sinks of the greenhouse gas methane from atmospheric measurements. It provides insight into how techniques and estimates have evolved over time, what the remaining shortcomings are, new developments, and promising future directions.
Megan O'Sadnick, Malcolm Ingham, Hajo Eicken, and Erin Pettit
The Cryosphere, 10, 2923–2940, https://doi.org/10.5194/tc-10-2923-2016, https://doi.org/10.5194/tc-10-2923-2016, 2016
Short summary
Short summary
Non-destructive in situ monitoring of sea-ice microstructure is of value to sea-ice research and operations but remains elusive to date. We relate in situ measurements of sea-ice dielectric properties at frequencies of 10 to 95 Hz to ice temperature, salinity, and microstructure. Results support the possible use of low-frequency electric measurements to monitor the seasonal evolution of brine volume fraction, pore volume, and connectivity of pore space in sea ice.
Jonathan M. Gregory, Nathaelle Bouttes, Stephen M. Griffies, Helmuth Haak, William J. Hurlin, Johann Jungclaus, Maxwell Kelley, Warren G. Lee, John Marshall, Anastasia Romanou, Oleg A. Saenko, Detlef Stammer, and Michael Winton
Geosci. Model Dev., 9, 3993–4017, https://doi.org/10.5194/gmd-9-3993-2016, https://doi.org/10.5194/gmd-9-3993-2016, 2016
Short summary
Short summary
As a consequence of greenhouse gas emissions, changes in ocean temperature, salinity, circulation and sea level are expected in coming decades. Among the models used for climate projections for the 21st century, there is a large spread in projections of these effects. The Flux-Anomaly-Forced Model Intercomparison Project (FAFMIP) aims to investigate and explain this spread by prescribing a common set of changes in the input of heat, water and wind stress to the ocean in the participating models.
Stephen M. Griffies, Gokhan Danabasoglu, Paul J. Durack, Alistair J. Adcroft, V. Balaji, Claus W. Böning, Eric P. Chassignet, Enrique Curchitser, Julie Deshayes, Helge Drange, Baylor Fox-Kemper, Peter J. Gleckler, Jonathan M. Gregory, Helmuth Haak, Robert W. Hallberg, Patrick Heimbach, Helene T. Hewitt, David M. Holland, Tatiana Ilyina, Johann H. Jungclaus, Yoshiki Komuro, John P. Krasting, William G. Large, Simon J. Marsland, Simona Masina, Trevor J. McDougall, A. J. George Nurser, James C. Orr, Anna Pirani, Fangli Qiao, Ronald J. Stouffer, Karl E. Taylor, Anne Marie Treguier, Hiroyuki Tsujino, Petteri Uotila, Maria Valdivieso, Qiang Wang, Michael Winton, and Stephen G. Yeager
Geosci. Model Dev., 9, 3231–3296, https://doi.org/10.5194/gmd-9-3231-2016, https://doi.org/10.5194/gmd-9-3231-2016, 2016
Short summary
Short summary
The Ocean Model Intercomparison Project (OMIP) aims to provide a framework for evaluating, understanding, and improving the ocean and sea-ice components of global climate and earth system models contributing to the Coupled Model Intercomparison Project Phase 6 (CMIP6). This document defines OMIP and details a protocol both for simulating global ocean/sea-ice models and for analysing their output.
Gregor J. Schürmann, Thomas Kaminski, Christoph Köstler, Nuno Carvalhais, Michael Voßbeck, Jens Kattge, Ralf Giering, Christian Rödenbeck, Martin Heimann, and Sönke Zaehle
Geosci. Model Dev., 9, 2999–3026, https://doi.org/10.5194/gmd-9-2999-2016, https://doi.org/10.5194/gmd-9-2999-2016, 2016
Short summary
Short summary
We describe the Max Planck Institute Carbon Cycle Data Assimilation System (MPI-CCDAS). The system improves the modelled carbon cycle of the terrestrial biosphere by systematically confronting (or assimilating) the model with observations of atmospheric CO2 and fractions of absorbed photosynthetically active radiation. Jointly assimilating both data streams outperforms the single-data stream experiments, thus showing the value of a multi-data stream assimilation.
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
Short summary
Short summary
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
Short summary
Short summary
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.
Dmitry A. Belikov, Shamil Maksyutov, Alexey Yaremchuk, Alexander Ganshin, Thomas Kaminski, Simon Blessing, Motoki Sasakawa, Angel J. Gomez-Pelaez, and Alexander Starchenko
Geosci. Model Dev., 9, 749–764, https://doi.org/10.5194/gmd-9-749-2016, https://doi.org/10.5194/gmd-9-749-2016, 2016
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
Short summary
Short summary
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.
T. Kaminski, F. Kauker, H. Eicken, and M. Karcher
The Cryosphere, 9, 1721–1733, https://doi.org/10.5194/tc-9-1721-2015, https://doi.org/10.5194/tc-9-1721-2015, 2015
Short summary
Short summary
We present a quantitative network design study of the Arctic sea ice-ocean system. For a demonstration, we evaluate two idealised hypothetical flight transects derived from NASA’s Operation IceBridge airborne ice surveys in terms of their potential to improve 10-day to 5-month sea ice forecasts. Our analysis quantifies the benefits of sampling upstream of the target area and of reducing the sampling uncertainty. It further quantifies the complementarity of combining two flight transects.
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
S. Kemp, M. Scholze, T. Ziehn, and T. Kaminski
Geosci. Model Dev., 7, 1609–1619, https://doi.org/10.5194/gmd-7-1609-2014, https://doi.org/10.5194/gmd-7-1609-2014, 2014
W. Knorr, T. Kaminski, A. Arneth, and U. Weber
Biogeosciences, 11, 1085–1102, https://doi.org/10.5194/bg-11-1085-2014, https://doi.org/10.5194/bg-11-1085-2014, 2014
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
Related subject area
Discipline: Sea ice | Subject: Arctic (e.g. Greenland)
Causes and evolution of winter polynyas north of Greenland
Winter Arctic sea ice thickness from ICESat-2: upgrades to freeboard and snow loading estimates and an assessment of the first three winters of data collection
Sea ice breakup and freeze-up indicators for users of the Arctic coastal environment
Improving model-satellite comparisons of sea ice melt onset with a satellite simulator
Rapid Sea Ice Changes in the Future Barents Sea
Kara and Barents sea ice thickness estimation based on CryoSat-2 radar altimeter and Sentinel-1 dual-polarized synthetic aperture radar
Contribution of warm and moist atmospheric flow to a record minimum July sea ice extent of the Arctic in 2020
Perspectives on future sea ice and navigability in the Arctic
Lasting impact of winds on Arctic sea ice through the ocean's memory
Holocene sea-ice dynamics in Petermann Fjord in relation to ice tongue stability and Nares Strait ice arch formation
Presentation and evaluation of the Arctic sea ice forecasting system neXtSIM-F
Combined influence of oceanic and atmospheric circulations on Greenland sea ice concentration
Seasonal changes in sea ice kinematics and deformation in the Pacific sector of the Arctic Ocean in 2018/19
Year-round impact of winter sea ice thickness observations on seasonal forecasts
Ensemble-based estimation of sea-ice volume variations in the Baffin Bay
Sea ice drift and arch evolution in the Robeson Channel using the daily coverage of Sentinel-1 SAR data for the 2016–2017 freezing season
Brief communication: Arctic sea ice thickness internal variability and its changes under historical and anthropogenic forcing
Seasonal transition dates can reveal biases in Arctic sea ice simulations
The Copernicus Polar Ice and Snow Topography Altimeter (CRISTAL) high-priority candidate mission
The MOSAiC ice floe: sediment-laden survivor from the Siberian shelf
Spectral attenuation of ocean waves in pack ice and its application in calibrating viscoelastic wave-in-ice models
New observations of the distribution, morphology and dissolution dynamics of cryogenic gypsum in the Arctic Ocean
Evaluation of Arctic sea ice drift and its dependency on near-surface wind and sea ice conditions in the coupled regional climate model HIRHAM–NAOSIM
Multidecadal Arctic sea ice thickness and volume derived from ice age
Going with the floe: tracking CESM Large Ensemble sea ice in the Arctic provides context for ship-based observations
The Arctic sea ice extent change connected to Pacific decadal variability
Impact of sea ice floe size distribution on seasonal fragmentation and melt of Arctic sea ice
Induced surface fluxes: a new framework for attributing Arctic sea ice volume balance biases to specific model errors
Comparison of ERA5 and ERA-Interim near-surface air temperature, snowfall and precipitation over Arctic sea ice: effects on sea ice thermodynamics and evolution
Benchmark seasonal prediction skill estimates based on regional indices
On the timescales and length scales of the Arctic sea ice thickness anomalies: a study based on 14 reanalyses
Past and future interannual variability in Arctic sea ice in coupled climate models
Arctic sea-ice-free season projected to extend into autumn
Definition differences and internal variability affect the simulated Arctic sea ice melt season
The potential of sea ice leads as a predictor for summer Arctic sea ice extent
Arctic climate: changes in sea ice extent outweigh changes in snow cover
Thin Arctic sea ice in L-band observations and an ocean reanalysis
Snow depth on Arctic sea ice from historical in situ data
Impacts of a lengthening open water season on Alaskan coastal communities: deriving locally relevant indices from large-scale datasets and community observations
Thermodynamic and dynamic ice thickness contributions in the Canadian Arctic Archipelago in NEMO-LIM2 numerical simulations
Younjoo J. Lee, Wieslaw Maslowski, John J. Cassano, Jaclyn Clement Kinney, Anthony P. Craig, Samy Kamal, Robert Osinski, Mark W. Seefeldt, Julienne Stroeve, and Hailong Wang
The Cryosphere, 17, 233–253, https://doi.org/10.5194/tc-17-233-2023, https://doi.org/10.5194/tc-17-233-2023, 2023
Short summary
Short summary
During 1979–2020, four winter polynyas occurred in December 1986 and February 2011, 2017, and 2018 north of Greenland. Instead of ice melting due to the anomalous warm air intrusion, the extreme wind forcing resulted in greater ice transport offshore. Based on the two ensemble runs, representing a 1980s thicker ice vs. a 2010s thinner ice, a dominant cause of these winter polynyas stems from internal variability of atmospheric forcing rather than from the forced response to a warming climate.
Alek A. Petty, Nicole Keeney, Alex Cabaj, Paul Kushner, and Marco Bagnardi
The Cryosphere, 17, 127–156, https://doi.org/10.5194/tc-17-127-2023, https://doi.org/10.5194/tc-17-127-2023, 2023
Short summary
Short summary
We present upgrades to winter Arctic sea ice thickness estimates from NASA's ICESat-2. Our new thickness results show better agreement with independent data from ESA's CryoSat-2 compared to our first data release, as well as new, very strong comparisons with data collected by moorings in the Beaufort Sea. We analyse three winters of thickness data across the Arctic, including 50 cm thinning of the multiyear ice over this 3-year period.
John E. Walsh, Hajo Eicken, Kyle Redilla, and Mark Johnson
The Cryosphere, 16, 4617–4635, https://doi.org/10.5194/tc-16-4617-2022, https://doi.org/10.5194/tc-16-4617-2022, 2022
Short summary
Short summary
Indicators for the start and end of annual breakup and freeze-up of sea ice at various coastal locations around the Arctic are developed. Relative to broader offshore areas, some of the coastal indicators show an earlier freeze-up and later breakup, especially at locations where landfast ice is prominent. However, the trends towards earlier breakup and later freeze-up are unmistakable over the post-1979 period in synthesized metrics of the coastal breakup/freeze-up indicators.
Abigail Smith, Alexandra Jahn, Clara Burgard, and Dirk Notz
The Cryosphere, 16, 3235–3248, https://doi.org/10.5194/tc-16-3235-2022, https://doi.org/10.5194/tc-16-3235-2022, 2022
Short summary
Short summary
The timing of Arctic sea ice melt each year is an important metric for assessing how sea ice in climate models compares to satellite observations. Here, we utilize a new tool for creating more direct comparisons between climate model projections and satellite observations of Arctic sea ice, such that the melt onset dates are defined the same way. This tool allows us to identify climate model biases more clearly and gain more information about what the satellites are observing.
Ole Rieke, Marius Årthun, and Jakob Simon Dörr
EGUsphere, https://doi.org/10.5194/egusphere-2022-324, https://doi.org/10.5194/egusphere-2022-324, 2022
Short summary
Short summary
The Barents Sea is the area of most intense winter sea ice loss and future projections show a continued decline towards ice-free conditions by the end of this century, but with large interannual to decadal fluctuations. Here we use climate model simulations to look at the occurrence and drivers of rapid ice change events in the Barents Sea that are much stronger than the average ice loss. A better understanding of these events will contribute to improved sea ice predictions in the Barents Sea.
Juha Karvonen, Eero Rinne, Heidi Sallila, Petteri Uotila, and Marko Mäkynen
The Cryosphere, 16, 1821–1844, https://doi.org/10.5194/tc-16-1821-2022, https://doi.org/10.5194/tc-16-1821-2022, 2022
Short summary
Short summary
We propose a method to provide sea ice thickness (SIT) estimates over a test area in the Arctic utilizing radar altimeter (RA) measurement lines and C-band SAR imagery. The RA data are from CryoSat-2, and SAR imagery is from Sentinel-1. By combining them we get a SIT grid covering the whole test area instead of only narrow measurement lines from RA. This kind of SIT estimation can be extended to cover the whole Arctic (and Antarctic) for operational SIT monitoring.
Yu Liang, Haibo Bi, Haijun Huang, Ruibo Lei, Xi Liang, Bin Cheng, and Yunhe Wang
The Cryosphere, 16, 1107–1123, https://doi.org/10.5194/tc-16-1107-2022, https://doi.org/10.5194/tc-16-1107-2022, 2022
Short summary
Short summary
A record minimum July sea ice extent, since 1979, was observed in 2020. Our results reveal that an anomalously high advection of energy and water vapor prevailed during spring (April to June) 2020 over regions with noticeable sea ice retreat. The large-scale atmospheric circulation and cyclones act in concert to trigger the exceptionally warm and moist flow. The convergence of the transport changed the atmospheric characteristics and the surface energy budget, thus causing a severe sea ice melt.
Jinlei Chen, Shichang Kang, Wentao Du, Junming Guo, Min Xu, Yulan Zhang, Xinyue Zhong, Wei Zhang, and Jizu Chen
The Cryosphere, 15, 5473–5482, https://doi.org/10.5194/tc-15-5473-2021, https://doi.org/10.5194/tc-15-5473-2021, 2021
Short summary
Short summary
Sea ice is retreating with rapid warming in the Arctic. It will continue and approach the worst predicted pathway released by the IPCC. The irreversible tipping point might show around 2060 when the oldest ice will have completely disappeared. It has a huge impact on human production. Ordinary merchant ships will be able to pass the Northeast Passage and Northwest Passage by the midcentury, and the opening time will advance to the next 10 years for icebreakers with moderate ice strengthening.
Qiang Wang, Sergey Danilov, Longjiang Mu, Dmitry Sidorenko, and Claudia Wekerle
The Cryosphere, 15, 4703–4725, https://doi.org/10.5194/tc-15-4703-2021, https://doi.org/10.5194/tc-15-4703-2021, 2021
Short summary
Short summary
Using simulations, we found that changes in ocean freshwater content induced by wind perturbations can significantly affect the Arctic sea ice drift, thickness, concentration and deformation rates years after the wind perturbations. The impact is through changes in sea surface height and surface geostrophic currents and the most pronounced in warm seasons. Such a lasting impact might become stronger in a warming climate and implies the importance of ocean initialization in sea ice prediction.
Henrieka Detlef, Brendan Reilly, Anne Jennings, Mads Mørk Jensen, Matt O'Regan, Marianne Glasius, Jesper Olsen, Martin Jakobsson, and Christof Pearce
The Cryosphere, 15, 4357–4380, https://doi.org/10.5194/tc-15-4357-2021, https://doi.org/10.5194/tc-15-4357-2021, 2021
Short summary
Short summary
Here we examine the Nares Strait sea ice dynamics over the last 7000 years and their implications for the late Holocene readvance of the floating part of Petermann Glacier. We propose that the historically observed sea ice dynamics are a relatively recent feature, while most of the mid-Holocene was marked by variable sea ice conditions in Nares Strait. Nonetheless, major advances of the Petermann ice tongue were preceded by a shift towards harsher sea ice conditions in Nares Strait.
Timothy Williams, Anton Korosov, Pierre Rampal, and Einar Ólason
The Cryosphere, 15, 3207–3227, https://doi.org/10.5194/tc-15-3207-2021, https://doi.org/10.5194/tc-15-3207-2021, 2021
Short summary
Short summary
neXtSIM (neXt-generation Sea Ice Model) includes a novel and extremely realistic way of modelling sea ice dynamics – i.e. how the sea ice moves and deforms in response to the drag from winds and ocean currents. It has been developed over the last few years for a variety of applications, but this paper represents its first demonstration in a forecast context. We present results for the time period from November 2018 to June 2020 and show that it agrees well with satellite observations.
Sourav Chatterjee, Roshin P. Raj, Laurent Bertino, Sebastian H. Mernild, Meethale Puthukkottu Subeesh, Nuncio Murukesh, and Muthalagu Ravichandran
The Cryosphere, 15, 1307–1319, https://doi.org/10.5194/tc-15-1307-2021, https://doi.org/10.5194/tc-15-1307-2021, 2021
Short summary
Short summary
Sea ice in the Greenland Sea (GS) is important for its climatic (fresh water), economical (shipping), and ecological contribution (light availability). The study proposes a mechanism through which sea ice concentration in GS is partly governed by the atmospheric and ocean circulation in the region. The mechanism proposed in this study can be useful for assessing the sea ice variability and its future projection in the GS.
Ruibo Lei, Mario Hoppmann, Bin Cheng, Guangyu Zuo, Dawei Gui, Qiongqiong Cai, H. Jakob Belter, and Wangxiao Yang
The Cryosphere, 15, 1321–1341, https://doi.org/10.5194/tc-15-1321-2021, https://doi.org/10.5194/tc-15-1321-2021, 2021
Short summary
Short summary
Quantification of ice deformation is useful for understanding of the role of ice dynamics in climate change. Using data of 32 buoys, we characterized spatiotemporal variations in ice kinematics and deformation in the Pacific sector of Arctic Ocean for autumn–winter 2018/19. Sea ice in the south and west has stronger mobility than in the east and north, which weakens from autumn to winter. An enhanced Arctic dipole and weakened Beaufort Gyre in winter lead to an obvious turning of ice drifting.
Beena Balan-Sarojini, Steffen Tietsche, Michael Mayer, Magdalena Balmaseda, Hao Zuo, Patricia de Rosnay, Tim Stockdale, and Frederic Vitart
The Cryosphere, 15, 325–344, https://doi.org/10.5194/tc-15-325-2021, https://doi.org/10.5194/tc-15-325-2021, 2021
Short summary
Short summary
Our study for the first time shows the impact of measured sea ice thickness (SIT) on seasonal forecasts of all the seasons. We prove that the long-term memory present in the Arctic winter SIT is helpful to improve summer sea ice forecasts. Our findings show that realistic SIT initial conditions to start a forecast are useful in (1) improving seasonal forecasts, (2) understanding errors in the forecast model, and (3) recognizing the need for continuous monitoring of world's ice-covered oceans.
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
Short summary
Short summary
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.
Mohammed E. Shokr, Zihan Wang, and Tingting Liu
The Cryosphere, 14, 3611–3627, https://doi.org/10.5194/tc-14-3611-2020, https://doi.org/10.5194/tc-14-3611-2020, 2020
Short summary
Short summary
This paper uses sequential daily SAR images covering the Robeson Channel to quantitatively study kinematics of individual ice floes with exploration of wind influence and the evolution of the ice arch at the entry of the channel. Results show that drift of ice floes within the Robeson Channel and the arch are both significantly influenced by wind. The study highlights the advantage of using the high-resolution daily SAR coverage in monitoring sea ice cover in narrow water passages.
Guillian Van Achter, Leandro Ponsoni, François Massonnet, Thierry Fichefet, and Vincent Legat
The Cryosphere, 14, 3479–3486, https://doi.org/10.5194/tc-14-3479-2020, https://doi.org/10.5194/tc-14-3479-2020, 2020
Short summary
Short summary
We document the spatio-temporal internal variability of Arctic sea ice thickness and its changes under anthropogenic forcing, which is key to understanding, and eventually predicting, the evolution of sea ice in response to climate change.
The patterns of sea ice thickness variability remain more or less stable during pre-industrial, historical and future periods, despite non-stationarity on short timescales. These patterns start to change once Arctic summer ice-free events occur, after 2050.
Abigail Smith, Alexandra Jahn, and Muyin Wang
The Cryosphere, 14, 2977–2997, https://doi.org/10.5194/tc-14-2977-2020, https://doi.org/10.5194/tc-14-2977-2020, 2020
Short summary
Short summary
The annual cycle of Arctic sea ice can be used to gain more information about how climate model simulations of sea ice compare to observations. In some models, the September sea ice area agrees with observations for the wrong reasons because biases in the timing of seasonal transitions compensate for other unrealistic sea ice characteristics. This research was done to provide new process-based metrics of Arctic sea ice using satellite observations, the CESM Large Ensemble, and CMIP6 models.
Michael Kern, Robert Cullen, Bruno Berruti, Jerome Bouffard, Tania Casal, Mark R. Drinkwater, Antonio Gabriele, Arnaud Lecuyot, Michael Ludwig, Rolv Midthassel, Ignacio Navas Traver, Tommaso Parrinello, Gerhard Ressler, Erik Andersson, Cristina Martin-Puig, Ole Andersen, Annett Bartsch, Sinead Farrell, Sara Fleury, Simon Gascoin, Amandine Guillot, Angelika Humbert, Eero Rinne, Andrew Shepherd, Michiel R. van den Broeke, and John Yackel
The Cryosphere, 14, 2235–2251, https://doi.org/10.5194/tc-14-2235-2020, https://doi.org/10.5194/tc-14-2235-2020, 2020
Short summary
Short summary
The Copernicus Polar Ice and Snow Topography Altimeter will provide high-resolution sea ice thickness and land ice elevation measurements and the capability to determine the properties of snow cover on ice to serve operational products and services of direct relevance to the polar regions. This paper describes the mission objectives, identifies the key contributions the CRISTAL mission will make, and presents a concept – as far as it is already defined – for the mission payload.
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
Short summary
Short summary
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.
Sukun Cheng, Justin Stopa, Fabrice Ardhuin, and Hayley H. Shen
The Cryosphere, 14, 2053–2069, https://doi.org/10.5194/tc-14-2053-2020, https://doi.org/10.5194/tc-14-2053-2020, 2020
Short summary
Short summary
Wave states in ice in polar oceans are mostly studied near the ice edge. However, observations in the internal ice field, where ice morphology is very different from the ice edge, are rare. Recently derived wave data from satellite imagery are easier and cheaper than field studies and provide large coverage. This work presents a way of using these data to have a close view of some key features in the wave propagation over hundreds of kilometers and calibrate models for predicting wave decay.
Jutta E. Wollenburg, Morten Iversen, Christian Katlein, Thomas Krumpen, Marcel Nicolaus, Giulia Castellani, Ilka Peeken, and Hauke Flores
The Cryosphere, 14, 1795–1808, https://doi.org/10.5194/tc-14-1795-2020, https://doi.org/10.5194/tc-14-1795-2020, 2020
Short summary
Short summary
Based on an observed omnipresence of gypsum crystals, we concluded that their release from melting sea ice is a general feature in the Arctic Ocean. Individual gypsum crystals sank at more than 7000 m d−1, suggesting that they are an important ballast mineral. Previous observations found gypsum inside phytoplankton aggregates at 2000 m depth, supporting gypsum as an important driver for pelagic-benthic coupling in the ice-covered Arctic Ocean.
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
Short summary
Short summary
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.
Yinghui Liu, Jeffrey R. Key, Xuanji Wang, and Mark Tschudi
The Cryosphere, 14, 1325–1345, https://doi.org/10.5194/tc-14-1325-2020, https://doi.org/10.5194/tc-14-1325-2020, 2020
Short summary
Short summary
This study provides a consistent and accurate multi-decadal product of ice thickness and ice volume from 1984 to 2018 based on satellite-derived ice age. Sea ice volume trends from this dataset are stronger than the trends from other datasets. Changes in sea ice thickness contribute more to overall sea ice volume trends than changes in sea ice area do in all months.
Alice K. DuVivier, Patricia DeRepentigny, Marika M. Holland, Melinda Webster, Jennifer E. Kay, and Donald Perovich
The Cryosphere, 14, 1259–1271, https://doi.org/10.5194/tc-14-1259-2020, https://doi.org/10.5194/tc-14-1259-2020, 2020
Short summary
Short summary
In autumn 2019, a ship will be frozen into the Arctic sea ice for a year to study system changes. We analyze climate model data from a group of experiments and follow virtual sea ice floes throughout a year. The modeled sea ice conditions along possible tracks are highly variable. Observations that sample a wide range of sea ice conditions and represent the variety and diversity in possible conditions are necessary for improving climate model parameterizations over all types of sea ice.
Xiao-Yi Yang, Guihua Wang, and Noel Keenlyside
The Cryosphere, 14, 693–708, https://doi.org/10.5194/tc-14-693-2020, https://doi.org/10.5194/tc-14-693-2020, 2020
Short summary
Short summary
The post-2007 Arctic sea ice cover is characterized by a remarkable increase in annual cycle amplitude, which is attributed to multiyear variability in spring Bering sea ice extent. We demonstrated that changes of NPGO mode, by anomalous wind stress curl and Ekman pumping, trigger subsurface variability in the Bering basin. This accounts for the significant decadal oscillation of spring Bering sea ice after 2007. The study helps us to better understand the recent Arctic climate regime shift.
Adam W. Bateson, Daniel L. Feltham, David Schröder, Lucia Hosekova, Jeff K. Ridley, and Yevgeny Aksenov
The Cryosphere, 14, 403–428, https://doi.org/10.5194/tc-14-403-2020, https://doi.org/10.5194/tc-14-403-2020, 2020
Short summary
Short summary
The Arctic sea ice cover has been observed to be decreasing, particularly in summer. We use numerical models to gain insight into processes controlling its seasonal and decadal evolution. Sea ice is made of pieces of ice called floes. Previous models have set these floes to be the same size, which is not supported by observations. In this study we show that accounting for variable floe size reveals the importance of sea ice regions close to the open ocean in driving seasonal retreat of sea ice.
Alex West, Mat Collins, Ed Blockley, Jeff Ridley, and Alejandro Bodas-Salcedo
The Cryosphere, 13, 2001–2022, https://doi.org/10.5194/tc-13-2001-2019, https://doi.org/10.5194/tc-13-2001-2019, 2019
Short summary
Short summary
This study presents a framework for examining the causes of model errors in Arctic sea ice volume, using HadGEM2-ES as a case study. Simple models are used to estimate how much of the error in energy arriving at the ice surface is due to error in key Arctic climate variables. The method quantifies how each variable affects sea ice volume balance and shows that for HadGEM2-ES an annual mean low bias in ice thickness is likely due to errors in surface melt onset.
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
Short summary
Short summary
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.
John E. Walsh, J. Scott Stewart, and Florence Fetterer
The Cryosphere, 13, 1073–1088, https://doi.org/10.5194/tc-13-1073-2019, https://doi.org/10.5194/tc-13-1073-2019, 2019
Short summary
Short summary
Persistence-based statistical forecasts of a Beaufort Sea ice severity index as well as September pan-Arctic ice extent show significant statistical skill out to several seasons when the data include the trend. However, this apparent skill largely vanishes when the trends are removed from the data. This finding is consistent with the notion of a springtime “predictability barrier” that has been found in sea ice forecasts based on more sophisticated methods.
Leandro Ponsoni, François Massonnet, Thierry Fichefet, Matthieu Chevallier, and David Docquier
The Cryosphere, 13, 521–543, https://doi.org/10.5194/tc-13-521-2019, https://doi.org/10.5194/tc-13-521-2019, 2019
Short summary
Short summary
The Arctic is a main component of the Earth's climate system. It is fundamental to understand the behavior of Arctic sea ice coverage over time and in space due to many factors, e.g., shipping lanes, the travel and tourism industry, hunting and fishing activities, mineral resource extraction, and the potential impact on the weather in midlatitude regions. In this work we use observations and results from models to understand how variations in the sea ice thickness change over time and in space.
John R. Mioduszewski, Stephen Vavrus, Muyin Wang, Marika Holland, and Laura Landrum
The Cryosphere, 13, 113–124, https://doi.org/10.5194/tc-13-113-2019, https://doi.org/10.5194/tc-13-113-2019, 2019
Short summary
Short summary
Arctic sea ice is projected to thin substantially in every season by the end of the 21st century with a corresponding increase in its interannual variability as the rate of ice loss peaks. This typically occurs when the mean ice thickness falls between 0.2 and 0.6 m. The high variability in both growth and melt processes is the primary factor resulting in increased ice variability. This study emphasizes the importance of short-term variations in ice cover within the mean downward trend.
Marion Lebrun, Martin Vancoppenolle, Gurvan Madec, and François Massonnet
The Cryosphere, 13, 79–96, https://doi.org/10.5194/tc-13-79-2019, https://doi.org/10.5194/tc-13-79-2019, 2019
Short summary
Short summary
The present analysis shows that the increase in the Arctic ice-free season duration will be asymmetrical, with later autumn freeze-up contributing about twice as much as earlier spring retreat. This feature is robustly found in a hierarchy of climate models and is consistent with a simple mechanism: solar energy is absorbed more efficiently than it can be released in non-solar form and should emerge out of variability within the next few decades.
Abigail Smith and Alexandra Jahn
The Cryosphere, 13, 1–20, https://doi.org/10.5194/tc-13-1-2019, https://doi.org/10.5194/tc-13-1-2019, 2019
Short summary
Short summary
Here we assessed how natural climate variations and different definitions impact the diagnosed and projected Arctic sea ice melt season length using model simulations. Irrespective of the definition or natural variability, the sea ice melt season is projected to lengthen, potentially by as much as 4–5 months by 2100 under the business as usual scenario. We also find that different definitions have a bigger impact on melt onset, while natural variations have a bigger impact on freeze onset.
Yuanyuan Zhang, Xiao Cheng, Jiping Liu, and Fengming Hui
The Cryosphere, 12, 3747–3757, https://doi.org/10.5194/tc-12-3747-2018, https://doi.org/10.5194/tc-12-3747-2018, 2018
Aaron Letterly, Jeffrey Key, and Yinghui Liu
The Cryosphere, 12, 3373–3382, https://doi.org/10.5194/tc-12-3373-2018, https://doi.org/10.5194/tc-12-3373-2018, 2018
Short summary
Short summary
Significant reductions in Arctic sea ice and snow cover on Arctic land have led to increases in absorbed solar energy by the surface. Does one play a more important role in Arctic climate change? Using 34 years of satellite data we found that solar energy absorption increased by 10 % over the ocean, which was 3 times greater than over land. Therefore, the decreasing sea ice cover, not changes in terrestrial snow cover, has been the dominant feedback mechanism over the last few decades.
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
Short summary
Short summary
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.
Elena V. Shalina and Stein Sandven
The Cryosphere, 12, 1867–1886, https://doi.org/10.5194/tc-12-1867-2018, https://doi.org/10.5194/tc-12-1867-2018, 2018
Short summary
Short summary
In this paper we analyze snow data from Soviet airborne expeditions, Sever, which operated in late winter 1959-1986, in the Arctic and made snow measurements on the ice around plane landing sites. The snow measurements were made on the multiyear ice in the central Arctic and on the first-year ice in the Eurasian seas in the areas for which snow characteristics are poorly described in the literature. The main goal of this study is to produce an improved data set of snow depth on the sea ice.
Rebecca J. Rolph, Andrew R. Mahoney, John Walsh, and Philip A. Loring
The Cryosphere, 12, 1779–1790, https://doi.org/10.5194/tc-12-1779-2018, https://doi.org/10.5194/tc-12-1779-2018, 2018
Short summary
Short summary
Using thresholds of physical climate variables developed from community observations, together with two large-scale datasets, we have produced local indices directly relevant to the impacts of a reduced sea ice cover on Alaska coastal communities. We demonstrate how community observations can inform use of large-scale datasets to derive these locally relevant indices.
Xianmin Hu, Jingfan Sun, Ting On Chan, and Paul G. Myers
The Cryosphere, 12, 1233–1247, https://doi.org/10.5194/tc-12-1233-2018, https://doi.org/10.5194/tc-12-1233-2018, 2018
Short summary
Short summary
We evaluated the sea ice thickness simulation in the Canadian Arctic Archipelago region using 1/4 and 1/12 degree NEMO LIM2 configurations. Model resolution dose not play a significant role. Relatively smaller thermodynamic contribution in the winter season is found in the thick ice covered areas, with larger contributions in the thin ice covered regions. No significant trend in winter maximum ice volume is found in the northern CAA and Baffin Bay but a decline is simulated within Parry Channel.
Cited articles
Bovensmann, H., Bösch, H., Brunner, D., Ciais, P., Crisp, D., Dolman, H., Hayman, G., Houweling, S., and Lichtenberg, L.: Report for mission selection: CarbonSat – An earth explorer to observe greenhouse gases, Tech. rep., European Space Agency, Noordwijk, the Netherlands, Noordwijk, The Netherlands, http://nora.nerc.ac.uk/514012/ (last access: 30 July 2018), 2015.
Chevallier, M., Smith, G. C., Dupont, F., Lemieux, J.-F., Forget, G., Fujii, Y., Hernandez, F., Msadek, R., Peterson, K. A., Storto, A., Toyoda, T., Valdivieso, M., Vernieres, G., Zuo, H., Balmaseda, M., Chang, Y.-S., Ferry, N., Garric, G., Haines, K., Keeley, S., Kovach, R. M., Kuragano, T., Masina, S., Tang, Y., Tsujino, H., and Wang, X.: Intercomparison of the Arctic sea ice cover in global ocean–sea ice reanalyses from the ORA-IP project, Clim. Dynam., 49, 1107–1136, https://doi.org/10.1007/s00382-016-2985-y, 2017.
Crisp, D., Atlas, R., Breon, F.-M., Brown, L., Burrows, J., Ciais, P., Connor, B., Doney, S., Fung, I., Jacob, D., Miller, C., O'Brien, D., Pawson, S., Randerson, J., Rayner, P., Salawitch, R., Sander, S., Sen, B., Stephens, G., Tans, P., Toon, G., Wennberg, P., Wofsy, S., Yung, Y., Kuang, Z., Chudasama, B., Sprague, G., Weiss, B., Pollock, R., Kenyon, D., and Schroll, S.: The Orbiting Carbon Observatory (OCO) mission, Trace Constituents in the Troposphere and Lower Stratosphere, Adv. Space Res., 34, 700–709, https://doi.org/10.1016/j.asr.2003.08.062, 2004.
Day, J. J., Hawkins, E., and Tietsche, S.: Will Arctic sea ice thickness initialization improve seasonal forecast skill?, Geophys. Res. Lett., 41, 7566–7575, https://doi.org/10.1002/2014GL061694, 2014.
Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., Bechtold, P., Beljaars, A. C. M., van de Berg, L., Bidlot, J., Bormann, N., Delsol, C., Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., Healy, S. B., Hersbach, H., Hólm, E. V., Isaksen, L., Kållberg, P., Köhler, M., Matricardi, M., McNally, A. P., Monge-Sanz, B. M., Morcrette, J.-J., Park, B.-K., Peubey, C., de Rosnay, P., Tavolato, C., Thépaut, J.-N., and Vitart, F.: The ERA-Interim reanalysis: configuration and performance of the data assimilation system, Q. J. Roy. Meteor. Soc., 137, 553–597, https://doi.org/10.1002/qj.828, 2011.
Eastwood, S., Jenssen, M., Lavergne, T., Sorensen, A., and Tonboe: EUMETSAT Ocean and Sea Ice Satellite Application Facility, Global sea ice concentration reprocessing product (v1.2), Product user manual, Technical Report, Norwegian and Danish Meteorological Institutes, Oslo, Norway and Copenhagen, Denmark, 14, 2079–2087, 2015.
Eicken, H.: Arctic sea ice needs better forecasts, Nature, 497, 431–433, https://doi.org/10.1038/497431a, 2013.
Feng, L., Palmer, P. I., Bösch, H., and Dance, S.: Estimating surface CO2 fluxes from space-borne CO2 dry air mole fraction observations using an ensemble Kalman Filter, Atmos. Chem. Phys., 9, 2619–2633, https://doi.org/10.5194/acp-9-2619-2009, 2009.
Gent, P. and McWilliams, J.: Isopycnal mixing in ocean circulation models, J. Phys. Oceanogr., 20, 150–155, https://doi.org/10.1175/1520-0485(1990)020<0150:IMIOCM>2.0.CO;2, 1990.
Gent, P., Willebrand, J., McDougall, T., and McWilliams, J.: Parameterizing eddy-induced tracer transport in ocean circulation models, J. Phys. Oceanogr., 25, 463–474, https://doi.org/10.1016/j.ocemod.2010.08.002, 1995.
Giorgetta, M. A., Jungclaus, J., Reick, C. H., Legutke, S., Bader, J., Böttinger, M., Brovkin, V., Crueger, T., Esch, M., Fieg, K., Glushak, K., Gayler, V., Haak, H., Hollweg, H.-D., Ilyina, T., Kinne, S., Kornblueh, L., Matei, D., Mauritsen, T., Mikolajewicz, U., Mueller, W., Notz, D., Pithan, F., Raddatz, T., Rast, S., Redler, R., Roeckner, E., Schmidt, H., Schnur, R., Segschneider, J., Six, K. D., Stockhause, M., Timmreck, C., Wegner, J., Widmann, H., Wieners, K.-H., Claussen, M., Marotzke, J., and Stevens, B.: Climate and carbon cycle changes from 1850 to 2100 in MPI-ESM simulations for the Coupled Model Intercomparison Project phase 5, J. Adv. Model. Earth Sy., 5, 572–597, https://doi.org/10.1002/jame.20038, 2013.
Griffies, S. M.: The Gent-McWilliams skew flux, J. Phys. Oceanogr., 28, 831–841, https://doi.org/10.1175/1520-0485(1998)028<0831:TGMSF>2.0.CO;2, 1998.
Guerrier, D. and Horley, F.: Archimedes: Archimedes' Principle and the Law of Flotation, Discovering with the Scientists Series, Blond & Briggs, available at: https://books.google.de/books?id=FOa_AAAACAAJ (last access: 30 July 2018), 1970.
Haak, H., Jungclaus, J., Mikolajewicz, U., and Latif, M.: Formation and propagation of great salinity anomalies, Geophys. Res. Lett., 30, 1473, https://doi.org/10.1029/2003GL017065, 2003.
Haas, C., Beckers, J., King, J., Silis, A., Stroeve, J., Wilkinson, J., Notenboom, B., Schweiger, A., and Hendricks, S.: Ice and Snow Thickness Variability and Change in the High Arctic Ocean Observed by In Situ Measurements, Geophys. Res. Lett., 44, 10462–10469, https://doi.org/10.1002/2017GL075434, 2017.
Hardt, M. and Scherbaum, F.: The Design of Optimum Networks for Aftershock Recordings, Geophys. J. Int., 117, 716–726, https://doi.org/10.1111/j.1365-246X.1994.tb02464.x, 1994.
Hendricks, S., Ricker, R., and Helm, V.: User Guide – AWI CryoSat-2 Sea Ice Thickness Data Product (v1.2), 2016.
Hibler, W.: A dynamic thermodynamic sea ice model, J. Geophys. Res., 9, 815–846, https://doi.org/10.1175/1520-0485(1979)009<0815:ADTSIM>2.0.CO;2, 1979.
Houweling, S., Breon, F.-M., Aben, I., Rödenbeck, C., Gloor, M., Heimann, M., and Ciais, P.: Inverse modeling of CO2 sources and sinks using satellite data: a synthetic inter-comparison of measurement techniques and their performance as a function of space and time, Atmos. Chem. Phys., 4, 523–538, https://doi.org/10.5194/acp-4-523-2004, 2004.
Hungershoefer, K., Breon, F.-M., Peylin, P., Chevallier, F., Rayner, P., Klonecki, A., Houweling, S., and Marshall, J.: Evaluation of various observing systems for the global monitoring of CO2 surface fluxes, Atmos. Chem. Phys., 10, 10503–10520, https://doi.org/10.5194/acp-10-10503-2010, 2010.
Ilyina, T., Six, K. D., Segschneider, J., Maier-Reimer, E., Li, H., and Núñez-Riboni, I.: Global ocean biogeochemistry model HAMOCC: Model architecture and performance as component of the MPI-Earth system model in different CMIP5 experimental realizations, J. Adv. Model. Earth Sy., 5, 287–315, https://doi.org/10.1029/2012MS000178, 2013.
Jungclaus, J., Giorgetta, M., Reick, C., Legutke, S., Brovkin, V., Crueger, T., Esch, M., Fieg, K., Fischer, N., Glushak, K., Gayler, V., Haak, H., Hollweg, H., Kinne, S., Kornblueh, L., Matei, D., Mauritsen, T., Mikolajewicz, U., Müller, W., Notz, D., Pohlmann, T., Raddatz, T., Rast, S., Roeckner, E., Salzmann, M., Schmidt, H., Schnur, R., Segschneider, J., Six, K., Stockhause, M., Wegner, J., Widmann, H., Wieners, K., Claussen, M., Marotzke, J., and Stevens, B.: CMIP5 simulations of the Max Planck Institute for Meteorology (MPI-M) based on the MPI-ESM-P model: The 1pctCO2 experiment, served by ESGF, WDCC at DKRZ, https://doi.org/10.1594/WDCC/CMIP5.MXEPc1, 2012.
Jungclaus, J. H., Keenlyside, N., Botzet, M., Haak, H., Luo, J.-J., Latif, M., Marotzke, J., Mikolajewicz, U., and Roeckner, E.: Ocean Circulation and Tropical Variability in the Coupled Model ECHAM5/MPI-OM, J. Clim., 19, 3952–3972, https://doi.org/10.1175/JCLI3827.1, 2006.
Jungclaus, J. H., Fischer, N., Haak, H., Lohmann, K., Marotzke, J., Matei, D., Mikolajewicz, U., Notz, D., and von Storch, J.: Characteristics of the ocean simulations in MPIOM, the ocean component of the MPI-Earth system model, J. Adv. Model. Earth Sy., 5, 422–446, https://doi.org/10.1002/jame.20023, 2013.
Kadygrov, N., Maksyutov, S., Eguchi, N., Aoki, T., Nakazawa, T., Yokota, T., and Inoue, G.: Role of simulated GOSAT total column CO2 observations in surface CO2 flux uncertainty reduction, J. Geophys. Res.-Atmos., 114, D21208, https://doi.org/10.1029/2008JD011597, 2009.
Kaminski, T.: Prior and posterior uncertainties of sea ice volume and snow volume, Zenodo, 10.5281/zenodo.1308857, last access: 30 July 2018.
Kaminski, T. and Mathieu, P.-P.: Reviews and syntheses: Flying the satellite into your model: on the role of observation operators in constraining models of the Earth system and the carbon cycle, Biogeosciences, 14, 2343–2357, https://doi.org/10.5194/bg-14-2343-2017, 2017.
Kaminski, T. and Rayner, P. J.: Reviews and syntheses: guiding the evolution of the observing system for the carbon cycle through quantitative network design, Biogeosciences, 14, 4755–4766, https://doi.org/10.5194/bg-14-4755-2017, 2017.
Kaminski, T., Rayner, P., Heimann, M., and Enting, I.: On aggregation errors in atmospheric transport inversions, J. Geophys. Res., 106, 4703, https://doi.org/10.1029/2000JD900581, 2001.
Kaminski, T., Scholze, M., and Houweling, S.: Quantifying the Benefit of A-SCOPE Data for Reducing Uncertainties in Terrestrial Carbon Fluxes in CCDAS, Tellus B, 62, 784–796, https://doi.org/10.1111/j.1600-0889.2010.00483.x, 2010.
Kaminski, T., Knorr, W., Scholze, M., Gobron, N., Pinty, B., Giering, R., and Mathieu, P.-P.: Consistent assimilation of MERIS FAPAR and atmospheric CO2 into a terrestrial vegetation model and interactive mission benefit analysis, Biogeosciences, 9, 3173–3184, https://doi.org/10.5194/bg-9-3173-2012, 2012a.
Kaminski, T., Rayner, P. J., Voßbeck, M., Scholze, M., and Koffi, E.: Observing the continental-scale carbon balance: assessment of sampling complementarity and redundancy in a terrestrial assimilation system by means of quantitative network design, Atmos. Chem. Phys., 12, 7867–7879, https://doi.org/10.5194/acp-12-7867-2012, 2012b.
Kaminski, T., Kauker, F., Eicken, H., and Karcher, M.: Exploring the utility of quantitative network design in evaluating Arctic sea ice thickness sampling strategies, The Cryosphere, 9, 1721–1733, https://doi.org/10.5194/tc-9-1721-2015, 2015.
Kaminski, T., Kauker, F., Toudal Pedersen, L., Voßbeck, M., Haak, H., Niederdrenk, L., Hendricks, S., Ricker, R., Karcher, M., Eicken, H., and Gråbak, O.: Arctic Mission Benefit Analysis: Impact of Sea Ice Thickness, Freeboard, and Snow Depth Products on Sea Ice Forecast Performance, The Cryosphere Discuss., https://doi.org/10.5194/tc-2017-249, in review, 2017.
Kauker, F., Kaminski, T., Ricker, R., Toudal-Pedersen, L., Dybkjaer, G., Melsheimer, C., Eastwood, S., Sumata, H., Karcher, M., and Gerdes, R.: Seasonal sea ice predictions for the Arctic based on assimilation of remotely sensed observations, The Cryosphere Discuss., 9, 5521–5554, https://doi.org/10.5194/tcd-9-5521-2015, 2015.
Kurtz, N. and Farrell, S.: Large-scale surveys of snow depth on Arctic sea ice from Operation IceBridge, Geophys. Res. Lett., 38, 10462–10469, https://doi.org/10.1029/2011GL049216, 2011.
Kwok, R. and Cunningham, G. F.: ICESat over Arctic sea ice: Estimation of snow depth and ice thickness, J. Geophys. Res.-Ocean., 113, C08010, https://doi.org/10.1029/2008JC004753, 2008.
Lindsay, R. and Schweiger, A.: Arctic sea ice thickness loss determined using subsurface, aircraft, and satellite observations, The Cryosphere, 9, 269–283, https://doi.org/10.5194/tc-9-269-2015, 2015.
Lisaeter, K. A., Evensen, G., and Laxon, S.: Assimilating synthetic CryoSat sea ice thickness in a coupled ice-ocean model, J. Geophys. Res.-Ocean., 112, C07023, https://doi.org/10.1029/2006JC003786, 2007.
Mikolajewicz, U., Sein, D., Jacob, D., Königk, T., Podzun, R., and Semmler, T.: Simulating Arctic sea ice variability with a coupled regional atmosphere-ocean-sea ice model, Meteorol. Z., 14, 793–800, https://doi.org/10.1127/0941-2948/2005/0083, 2015.
Müller, W. A., Baehr, J., Haak, H., Jungclaus, J. H., Kröger, J., Matei, D., Notz, D., Pohlmann, H., von Storch, J. S., and Marotzke, J.: Forecast skill of multi-year seasonal means in the decadal prediction system of the Max Planck Institute for Meteorology, Geophys. Res. Lett., 39, L22707, https://doi.org/10.1029/2012GL053326, 2012.
Niederdrenk, A.: The Arctic hydrologic cycle and its variability in a regional coupled climate model, PhD Thesis, Unversity Hamburg, 1–186, 2013.
Niederdrenk, A. L., Sein, D. V., and Mikolajewicz, U.: Interannual variability of the Arctic freshwater cycle in the second half of the twentieth century in a regionally coupled climate model, Clim. Dynam., 47, 3883–3900, https://doi.org/10.1007/s00382-016-3047-1, 2016.
NOAA: Data Announcement 88-MGG-02, Digital relief of the Surface of the Earth, NOAA, National Geophysical Data Center, Boulder, Colorado, 1988.
Notz, D., Haumann, F. A., Haak, H., Jungclaus, J. H., and Marotzke, J.: Arctic sea-ice evolution as modeled by Max Planck Institute for Meteorology's Earth system model, J. Adv. Model. Earth Sy., 5, 173–194, https://doi.org/10.1002/jame.20016, 2013.
Pacanowski, R. and Philander, S.: Parameterization of vertical mixing in numerical-models of tropical oceans, J. Phys. Oceanogr., 11, 1443–1451, https://doi.org/10.1175/1520-0485(1981)011<1443:POVMIN>2.0.CO;2, 1981.
Patra, P. K., Maksyutov, S., Sasano, Y., Nakajima, H., Inoue, G., and Nakazawa, T.: An evaluation of CO2 observations with Solar Occultation FTS for Inclined-Orbit Satellite sensor for surface source inversion, J. Geophys. Res.-Atmos., 108, 4759, https://doi.org/10.1029/2003JD003661, 2003.
Rayner, P., Michalak, A. M., and Chevallier, F.: Fundamentals of Data Assimilation, Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2016-148, 2016.
Rayner, P. J. and O'Brien, D. M.: The utility of remotely sensed CO2 concentration data in surface source inversions, Geophys. Res. Let., 28, 175–178, https://doi.org/10.1029/2000GL011912, 2001.
Rayner, P. J., Enting, I. G., and Trudinger, C. M.: Optimizing the CO2 Observing Network for Constraining Sources and Sinks, Tellus B, 48, 433–444, 1996.
Rayner, P. J., Utembe, S. R., and Crowell, S.: Constraining regional greenhouse gas emissions using geostationary concentration measurements: a theoretical study, Atmos. Meas. Tech., 7, 3285–3293, https://doi.org/10.5194/amt-7-3285-2014, 2014.
Redi, M. H.: Oceanic isopycnal mixing by coordinate rotation, J. Phys. Oceanogr., 12, 1154–1158, https://doi.org/10.1175/1520-0485(1982)012<1154:OIMBCR>2.0.CO;2, 1982.
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.
Röske, F.: An atlas of surface fluxes based on the ECMWF reanalysis – A climatological data set to force global ocean general circulation models, Tech. Rep. 323, Max-Planck-Inst. Meteorol., Hamburg, Germany, 2001.
Semtner, A.: A Model for the Thermodynamic Growth of Sea Ice in Numerical Investigastions of Climate, J. Phys. Oceanogr., 6, 379–389, https://doi.org/10.1175/1520-0485(1976)006<0379:AMFTTG>2.0.CO;2, 1976.
Steele, M., Morley, R., and W. Ermold, W.: PHC: A global ocean hydrography with a high quality Arctic Ocean, J. Clim., 14, 2079–2087, https://doi.org/10.1175/1520-0442(2001)014<2079:PAGOHW>2.0.CO;2, 2001.
Stocker, T., Qin, D., Plattner, G.-K., Tignor, M., Allen, S., Boschung, J., Nauels, A., Xia, Y., Bex, V., and Midgley, P.: Climate Change 2013: The Physical Science Basis, Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Stocker, T. F., Qin, D., Plattner, G.-K., Tignor, M., Allen, S. K., Boschung, J., Nauels, A., Xia, Y., Bex, V., and Midgley, P. M., Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 1535 pp., https://doi.org/10.1017/CBO9781107415324, 2013.
Tarantola, A.: Inverse Problem Theory and methods for model parameter estimation, SIAM, Philadelphia, https://doi.org/10.1137/1.9780898717921, 2005.
Trampert, J. and Snieder, R.: Model Estimations Biased by Truncated Expansions: Possible Artifacts in Seismic Tomography, Science, 271, 1257–1260, https://doi.org/10.1126/science.271.5253.1257, 1996.
Warren, S., Rigor, I., Untersteiner, N., Radionov, V., Bryaz-gin, N., Aleksandrov, Y., and Colony, R.: Snow depth on Arctic sea ice, J. Clim., 12, 1814–1829, https://doi.org/10.1175/1520-0442(1999)012<1814:SDOASI>2.0.CO;2, 1999.
Xie, J., Counillon, F., Bertino, L., Tian-Kunze, X., and Kaleschke, L.: Benefits of assimilating thin sea ice thickness from SMOS into the TOPAZ system, The Cryosphere, 10, 2745–2761, https://doi.org/10.5194/tc-10-2745-2016, 2016.
Yang, Q., Losa, S. N., Losch, M., Tian-Kunze, X., Nerger, L., Liu, J., Kaleschke, L., and Zhang, Z.: Assimilating SMOS sea ice thickness into a coupled ice-ocean model using a local SEIK filter, J. Geophys. Res.-Ocean., 119, 6680–6692, https://doi.org/10.1002/2014JC009963, 2014.
Short summary
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.
We present mathematically rigorous assessments of the observation impact (added value) of...
