Articles | Volume 9, issue 2
https://doi.org/10.5194/gmd-9-523-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-9-523-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Model description paper
| 
08 Feb 2016
Model description paper |
| 08 Feb 2016
Simulating the thermal regime and thaw processes of ice-rich permafrost ground with the land-surface model CryoGrid 3
S. Westermann
CORRESPONDING AUTHOR
Department of Geosciences, University of Oslo, P.O. Box 1047, Blindern, 0316 Oslo, Norway
M. Langer
Alfred Wegener Institute Helmholtz Center for Polar and Marine Research, Telegrafenberg A43, 14473 Potsdam, Germany
CNRS, LGGE (UMR5183), 38041 Grenoble, France
Université Grenoble Alpes, LGGE (UMR5183), 38041 Grenoble, France
Department of Geography, Humboldt-University, Unter den Linden 6, 10099 Berlin, Germany
J. Boike
Alfred Wegener Institute Helmholtz Center for Polar and Marine Research, Telegrafenberg A43, 14473 Potsdam, Germany
M. Heikenfeld
Alfred Wegener Institute Helmholtz Center for Polar and Marine Research, Telegrafenberg A43, 14473 Potsdam, Germany
M. Peter
Department of Geosciences, University of Oslo, P.O. Box 1047, Blindern, 0316 Oslo, Norway
Alfred Wegener Institute Helmholtz Center for Polar and Marine Research, Telegrafenberg A43, 14473 Potsdam, Germany
B. Etzelmüller
Department of Geosciences, University of Oslo, P.O. Box 1047, Blindern, 0316 Oslo, Norway
G. Krinner
CNRS, LGGE (UMR5183), 38041 Grenoble, France
Université Grenoble Alpes, LGGE (UMR5183), 38041 Grenoble, France
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Sarah E. Chadburn, Eleanor J. Burke, Angela V. Gallego-Sala, Noah D. Smith, M. Syndonia Bret-Harte, Dan J. Charman, Julia Drewer, Colin W. Edgar, Eugenie S. Euskirchen, Krzysztof Fortuniak, Yao Gao, Mahdi Nakhavali, Włodzimierz Pawlak, Edward A. G. Schuur, and Sebastian Westermann
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Bernd Etzelmüller, Justyna Czekirda, Florence Magnin, Pierre-Allain Duvillard, Ludovic Ravanel, Emanuelle Malet, Andreas Aspaas, Lene Kristensen, Ingrid Skrede, Gudrun D. Majala, Benjamin Jacobs, Johannes Leinauer, Christian Hauck, Christin Hilbich, Martina Böhme, Reginald Hermanns, Harald Ø. Eriksen, Tom Rune Lauknes, Michael Krautblatter, and Sebastian Westermann
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Léo C. P. Martin, Jan Nitzbon, Johanna Scheer, Kjetil S. Aas, Trond Eiken, Moritz Langer, Simon Filhol, Bernd Etzelmüller, and Sebastian Westermann
The Cryosphere, 15, 3423–3442, https://doi.org/10.5194/tc-15-3423-2021, https://doi.org/10.5194/tc-15-3423-2021, 2021
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Juditha Undine Schmidt, Bernd Etzelmüller, Thomas Vikhamar Schuler, Florence Magnin, Julia Boike, Moritz Langer, and Sebastian Westermann
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Thomas Schneider von Deimling, Hanna Lee, Thomas Ingeman-Nielsen, Sebastian Westermann, Vladimir Romanovsky, Scott Lamoureux, Donald A. Walker, Sarah Chadburn, Erin Trochim, Lei Cai, Jan Nitzbon, Stephan Jacobi, and Moritz Langer
The Cryosphere, 15, 2451–2471, https://doi.org/10.5194/tc-15-2451-2021, https://doi.org/10.5194/tc-15-2451-2021, 2021
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Jan Nitzbon, Moritz Langer, Léo C. P. Martin, Sebastian Westermann, Thomas Schneider von Deimling, and Julia Boike
The Cryosphere, 15, 1399–1422, https://doi.org/10.5194/tc-15-1399-2021, https://doi.org/10.5194/tc-15-1399-2021, 2021
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Lei Cai, Hanna Lee, Kjetil Schanke Aas, and Sebastian Westermann
The Cryosphere, 14, 4611–4626, https://doi.org/10.5194/tc-14-4611-2020, https://doi.org/10.5194/tc-14-4611-2020, 2020
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A sub-grid representation of excess ground ice in the Community Land Model (CLM) is developed as novel progress in modeling permafrost thaw and its impacts under the warming climate. The modeled permafrost degradation with sub-grid excess ice follows the pathway that continuous permafrost transforms into discontinuous permafrost before it disappears, including surface subsidence and talik formation, which are highly permafrost-relevant landscape changes excluded from most land models.
Jaroslav Obu, Sebastian Westermann, Gonçalo Vieira, Andrey Abramov, Megan Ruby Balks, Annett Bartsch, Filip Hrbáček, Andreas Kääb, and Miguel Ramos
The Cryosphere, 14, 497–519, https://doi.org/10.5194/tc-14-497-2020, https://doi.org/10.5194/tc-14-497-2020, 2020
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Little is known about permafrost in the Antarctic outside of the few research stations. We used a simple equilibrium permafrost model to estimate permafrost temperatures in the whole Antarctic. The lowest permafrost temperature on Earth is −36 °C in the Queen Elizabeth Range in the Transantarctic Mountains. Temperatures are commonly between −23 and −18 °C in mountainous areas rising above the Antarctic Ice Sheet, between −14 and −8 °C in coastal areas, and up to 0 °C on the Antarctic Peninsula.
Joel Fiddes, Kristoffer Aalstad, and Sebastian Westermann
Hydrol. Earth Syst. Sci., 23, 4717–4736, https://doi.org/10.5194/hess-23-4717-2019, https://doi.org/10.5194/hess-23-4717-2019, 2019
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In this paper we address one of the big challenges in snow hydrology, namely the accurate simulation of the seasonal snowpack in ungauged regions. We do this by assimilating satellite observations of snow cover into a modelling framework. Importantly (and a novelty of the paper), we include a clustering approach that permits highly efficient ensemble simulations. Efficiency gains and dependency on purely global datasets, means that this method can be applied over large areas anywhere on Earth.
Florence Magnin, Bernd Etzelmüller, Sebastian Westermann, Ketil Isaksen, Paula Hilger, and Reginald L. Hermanns
Earth Surf. Dynam., 7, 1019–1040, https://doi.org/10.5194/esurf-7-1019-2019, https://doi.org/10.5194/esurf-7-1019-2019, 2019
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This study proposes the first permafrost (i.e. ground with temperature permanently < 0 °C) map covering the steep rock slopes of Norway. It was created by using rock temperature data collected at the near surface of 25 rock walls spread across the country between 2010 and 2018. The map shows that permafrost mostly exists above 1300–1400 m a.s.l. in southern Norway and close to sea level in northern Norway. The results have strong potential for the study of rock wall sliding and failure.
Lei Cai, Hanna Lee, Sebastian Westermann, and Kjetil Schanke Aas
The Cryosphere Discuss., https://doi.org/10.5194/tc-2019-230, https://doi.org/10.5194/tc-2019-230, 2019
Preprint withdrawn
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We develop a sub-grid representation of excess ground ice in the Community Land Model (CLM) by adding three landunits to the original CLM sub-grid hierarchy, in order to prescribe three different excess ice conditions in one grid cell. Single-grid simulations verify the potential of the model development on better projecting excess ice melt in a warming climate. Global simulations recommend the proper way of applying the model development with the existing excess ice dataset.
Jan Nitzbon, Moritz Langer, Sebastian Westermann, Léo Martin, Kjetil Schanke Aas, and Julia Boike
The Cryosphere, 13, 1089–1123, https://doi.org/10.5194/tc-13-1089-2019, https://doi.org/10.5194/tc-13-1089-2019, 2019
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We studied the stability of ice wedges (massive bodies of ground ice in permafrost) under recent climatic conditions in the Lena River delta of northern Siberia. For this we used a novel modelling approach that takes into account lateral transport of heat, water, and snow and the subsidence of the ground surface due to melting of ground ice. We found that wetter conditions have a destabilizing effect on the ice wedges and associated our simulation results with observations from the study area.
Kjetil S. Aas, Léo Martin, Jan Nitzbon, Moritz Langer, Julia Boike, Hanna Lee, Terje K. Berntsen, and Sebastian Westermann
The Cryosphere, 13, 591–609, https://doi.org/10.5194/tc-13-591-2019, https://doi.org/10.5194/tc-13-591-2019, 2019
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Many permafrost landscapes contain large amounts of excess ground ice, which gives rise to small-scale elevation differences. This results in lateral fluxes of snow, water, and heat, which we investigate and show how it can be accounted for in large-scale models. Using a novel model technique which can account for these differences, we are able to model both the current state of permafrost and how these landscapes change as permafrost thaws, in a way that could not previously be achieved.
Julia Boike, Inge Juszak, Stephan Lange, Sarah Chadburn, Eleanor Burke, Pier Paul Overduin, Kurt Roth, Olaf Ippisch, Niko Bornemann, Lielle Stern, Isabelle Gouttevin, Ernst Hauber, and Sebastian Westermann
Earth Syst. Sci. Data, 10, 355–390, https://doi.org/10.5194/essd-10-355-2018, https://doi.org/10.5194/essd-10-355-2018, 2018
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A 20-year data record from the Bayelva site at Ny-Ålesund, Svalbard, is presented on meteorology, energy balance components, surface and subsurface observations. This paper presents the data set, instrumentation, calibration, processing and data quality control. The data show that mean annual, summer and winter soil temperature data from shallow to deeper depths have been warming over the period of record, indicating the degradation and loss of permafrost at this site.
Kristoffer Aalstad, Sebastian Westermann, Thomas Vikhamar Schuler, Julia Boike, and Laurent Bertino
The Cryosphere, 12, 247–270, https://doi.org/10.5194/tc-12-247-2018, https://doi.org/10.5194/tc-12-247-2018, 2018
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We demonstrate how snow cover data from satellites can be used to constrain estimates of snow distributions at sites in the Arctic. In this effort, we make use of data assimilation to combine the information contained in the snow cover data with a simple snow model. By comparing our snow distribution estimates to independent observations, we find that this method performs favorably. Being modular, this method could be applied to other areas as a component of a larger reanalysis system.
Sarah E. Chadburn, Gerhard Krinner, Philipp Porada, Annett Bartsch, Christian Beer, Luca Belelli Marchesini, Julia Boike, Altug Ekici, Bo Elberling, Thomas Friborg, Gustaf Hugelius, Margareta Johansson, Peter Kuhry, Lars Kutzbach, Moritz Langer, Magnus Lund, Frans-Jan W. Parmentier, Shushi Peng, Ko Van Huissteden, Tao Wang, Sebastian Westermann, Dan Zhu, and Eleanor J. Burke
Biogeosciences, 14, 5143–5169, https://doi.org/10.5194/bg-14-5143-2017, https://doi.org/10.5194/bg-14-5143-2017, 2017
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Earth system models (ESMs) are our main tools for understanding future climate. The Arctic is important for the future carbon cycle, particularly due to the large carbon stocks in permafrost. We evaluated the performance of the land component of three major ESMs at Arctic tundra sites, focusing on the fluxes and stocks of carbon.
We show that the next steps for model improvement are to better represent vegetation dynamics, to include mosses and to improve below-ground carbon cycle processes.
Sebastian Westermann, Maria Peter, Moritz Langer, Georg Schwamborn, Lutz Schirrmeister, Bernd Etzelmüller, and Julia Boike
The Cryosphere, 11, 1441–1463, https://doi.org/10.5194/tc-11-1441-2017, https://doi.org/10.5194/tc-11-1441-2017, 2017
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We demonstrate a remote-sensing-based scheme estimating the evolution of ground temperature and active layer thickness by means of a ground thermal model. A comparison to in situ observations from the Lena River delta in Siberia indicates that the model is generally capable of reproducing the annual temperature regime and seasonal thawing of the ground. The approach could hence be a first step towards remote detection of ground thermal conditions in permafrost areas.
Amund F. Borge, Sebastian Westermann, Ingvild Solheim, and Bernd Etzelmüller
The Cryosphere, 11, 1–16, https://doi.org/10.5194/tc-11-1-2017, https://doi.org/10.5194/tc-11-1-2017, 2017
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Palsas and peat plateaus are permafrost landforms in subarctic mires which constitute sensitive ecosystems with strong significance for vegetation, wildlife, hydrology and carbon cycle. We have systematically mapped the occurrence of palsas and peat plateaus in northern Norway by interpretation of aerial images from the 1950s until today. The results show that about half of the area of palsas and peat plateaus has disappeared due to lateral erosion and melting of ground ice in the last 50 years.
Kjersti Gisnås, Sebastian Westermann, Thomas Vikhamar Schuler, Kjetil Melvold, and Bernd Etzelmüller
The Cryosphere, 10, 1201–1215, https://doi.org/10.5194/tc-10-1201-2016, https://doi.org/10.5194/tc-10-1201-2016, 2016
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In wind exposed areas snow redistribution results in large spatial variability in ground temperatures. In these areas, the ground temperature of a grid cell must be determined based on the distribution, and not the average, of snow depths. We employ distribution functions of snow in a regional permafrost model, showing highly improved representation of ground temperatures. By including snow distributions, we find the permafrost area to be nearly twice as large as what is modelled without.
S. Westermann, T. I. Østby, K. Gisnås, T. V. Schuler, and B. Etzelmüller
The Cryosphere, 9, 1303–1319, https://doi.org/10.5194/tc-9-1303-2015, https://doi.org/10.5194/tc-9-1303-2015, 2015
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We use remotely sensed land surface temperature and land cover in conjunction with air temperature and snowfall from a reanalysis product as input for a simple permafrost model. The scheme is applied to the permafrost regions bordering the North Atlantic. A comparison with ground temperatures in boreholes suggests a modeling accuracy of 2 to 2.5 °C.
S. Westermann, B. Elberling, S. Højlund Pedersen, M. Stendel, B. U. Hansen, and G. E. Liston
The Cryosphere, 9, 719–735, https://doi.org/10.5194/tc-9-719-2015, https://doi.org/10.5194/tc-9-719-2015, 2015
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The development of ground temperatures in permafrost areas is influenced by many factors varying on different spatial and temporal scales. We present numerical simulations of ground temperatures for the Zackenberg valley in NE Greenland, which take into account the spatial variability of snow depths, surface and ground properties at a scale of 10m. The ensemble of the model grid cells suggests a spatial variability of annual average ground temperatures of up to 5°C.
M. Langer, S. Westermann, K. Walter Anthony, K. Wischnewski, and J. Boike
Biogeosciences, 12, 977–990, https://doi.org/10.5194/bg-12-977-2015, https://doi.org/10.5194/bg-12-977-2015, 2015
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Methane production rates of Arctic ponds during the freezing period within a typical tundra landscape in northern Siberia are presented. Production rates were inferred by inverse modeling based on measured methane concentrations in the ice cover. Results revealed marked differences in early winter methane production among ponds showing different stages of shore degradation. This suggests that shore erosion can increase methane production of Arctic ponds by 2 to 3 orders of magnitude.
J. Lüers, S. Westermann, K. Piel, and J. Boike
Biogeosciences, 11, 6307–6322, https://doi.org/10.5194/bg-11-6307-2014, https://doi.org/10.5194/bg-11-6307-2014, 2014
K. Gisnås, S. Westermann, T. V. Schuler, T. Litherland, K. Isaksen, J. Boike, and B. Etzelmüller
The Cryosphere, 8, 2063–2074, https://doi.org/10.5194/tc-8-2063-2014, https://doi.org/10.5194/tc-8-2063-2014, 2014
S. Westermann, T. V. Schuler, K. Gisnås, and B. Etzelmüller
The Cryosphere, 7, 719–739, https://doi.org/10.5194/tc-7-719-2013, https://doi.org/10.5194/tc-7-719-2013, 2013
Alexandru Onaca, Flavius Sirbu, Valentin Poncos, Christin Hilbich, Tazio Strozzi, Petru Urdea, Răzvan Popescu, Oana Berzescu, Bernd Etzelmüller, Alfred Vespremeanu-Stroe, Mirela Vasile, Delia Teleagă, Dan Birtaș, Iosif Lopătiță, Simon Filhol, Alexandru Hegyi, and Florina Ardelean
EGUsphere, https://doi.org/10.5194/egusphere-2024-3262, https://doi.org/10.5194/egusphere-2024-3262, 2025
This preprint is open for discussion and under review for Earth Surface Dynamics (ESurf).
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This study establishes a methodology for the study of slow-moving rock glaciers in marginal permafrost and provides the basic knowledge for understanding rock glaciers in south east Europe. By using a combination of different methods (remote sensing, geophysical survey, thermal measurements), we found out that, on the transitional rock glaciers, low ground ice content (i.e. below 20 %) produces horizontal displacements of up to 3 cm per year.
Lotte Wendt, Line Rouyet, Hanne H. Christiansen, Tom Rune Lauknes, and Sebastian Westermann
EGUsphere, https://doi.org/10.5194/egusphere-2024-2972, https://doi.org/10.5194/egusphere-2024-2972, 2024
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In permafrost environments, the ground surface moves due to the formation and melt of ice in the ground. This study compares ground surface displacements measured from satellite images against field data of ground ice contents. We find good agreement between the detected seasonal subsidence and observed ground ice melt. Our results show the potential of satellite remote sensing for mapping ground ice variability, but also indicate that ice in excess of the pore space must be considered.
Robin Benjamin Zweigel, Avirmed Dashtseren, Khurelbaatar Temuujin, Anarmaa Sharkhuu, Clare Webster, Hanna Lee, and Sebastian Westermann
Biogeosciences, 21, 5059–5077, https://doi.org/10.5194/bg-21-5059-2024, https://doi.org/10.5194/bg-21-5059-2024, 2024
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Intense grazing at grassland sites removes vegetation, reduces the snow cover, and inhibits litter layers from forming. Grazed sites generally have a larger annual ground surface temperature amplitude than ungrazed sites, but the net effect depends on effects in the transitional seasons. Our results also suggest that seasonal use of pastures can reduce ground temperatures, which can be a strategy to protect currently degrading grassland permafrost.
Sigrid Trier Kjær, Sebastian Westermann, Nora Nedkvitne, and Peter Dörsch
Biogeosciences, 21, 4723–4737, https://doi.org/10.5194/bg-21-4723-2024, https://doi.org/10.5194/bg-21-4723-2024, 2024
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Permafrost peatlands are thawing due to climate change, releasing large quantities of carbon that degrades upon thawing and is released as CO2, CH4 or dissolved organic carbon (DOC). We incubated thawed Norwegian permafrost peat plateaus and thermokarst pond sediment found next to permafrost for up to 350 d to measure carbon loss. CO2 production was initially the highest, whereas CH4 production increased over time. The largest carbon loss was measured at the top of the peat plateau core as DOC.
Juditha Aga, Livia Piermattei, Luc Girod, Kristoffer Aalstad, Trond Eiken, Andreas Kääb, and Sebastian Westermann
Earth Surf. Dynam., 12, 1049–1070, https://doi.org/10.5194/esurf-12-1049-2024, https://doi.org/10.5194/esurf-12-1049-2024, 2024
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Coastal rock cliffs on Svalbard are considered to be fairly stable; however, long-term trends in coastal-retreat rates remain unknown. This study examines changes in the coastline position along Brøggerhalvøya, Svalbard, using aerial images from 1970, 1990, 2010, and 2021. Our analysis shows that coastal-retreat rates accelerate during the period 2010–2021, which coincides with increasing storminess and retreating sea ice.
G. Alexander Sokolowsky, Sean W. Freeman, William K. Jones, Julia Kukulies, Fabian Senf, Peter J. Marinescu, Max Heikenfeld, Kelcy N. Brunner, Eric C. Bruning, Scott M. Collis, Robert C. Jackson, Gabrielle R. Leung, Nils Pfeifer, Bhupendra A. Raut, Stephen M. Saleeby, Philip Stier, and Susan C. van den Heever
Geosci. Model Dev., 17, 5309–5330, https://doi.org/10.5194/gmd-17-5309-2024, https://doi.org/10.5194/gmd-17-5309-2024, 2024
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Building on previous analysis tools developed for atmospheric science, the original release of the Tracking and Object-Based Analysis (tobac) Python package, v1.2, was open-source, modular, and insensitive to the type of gridded input data. Here, we present the latest version of tobac, v1.5, which substantially improves scientific capabilities and computational efficiency from the previous version. These enhancements permit new uses for tobac in atmospheric science and potentially other fields.
Marco Mazzolini, Kristoffer Aalstad, Esteban Alonso-González, Sebastian Westermann, and Désirée Treichler
EGUsphere, https://doi.org/10.5194/egusphere-2024-1404, https://doi.org/10.5194/egusphere-2024-1404, 2024
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In this work, we use the satellite laser altimeter ICESat-2 to retrieve snow depth in areas where snow amounts are still poorly estimated despite the high societal importance. We explore how to update snow models with these observations through algorithms that spatially propagate the information beyond the narrow satellite profiles. The positive results show the potential of this approach for improving snow simulations, both in terms of average snow depth and spatial distribution.
Moritz Langer, Jan Nitzbon, Brian Groenke, Lisa-Marie Assmann, Thomas Schneider von Deimling, Simone Maria Stuenzi, and Sebastian Westermann
The Cryosphere, 18, 363–385, https://doi.org/10.5194/tc-18-363-2024, https://doi.org/10.5194/tc-18-363-2024, 2024
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Using a model that can simulate the evolution of Arctic permafrost over centuries to millennia, we find that post-industrialization permafrost warming has three "hotspots" in NE Canada, N Alaska, and W Siberia. The extent of near-surface permafrost has decreased substantially since 1850, with the largest area losses occurring in the last 50 years. The simulations also show that volcanic eruptions have in some cases counteracted the loss of near-surface permafrost for a few decades.
Bernd Etzelmüller, Ketil Isaksen, Justyna Czekirda, Sebastian Westermann, Christin Hilbich, and Christian Hauck
The Cryosphere, 17, 5477–5497, https://doi.org/10.5194/tc-17-5477-2023, https://doi.org/10.5194/tc-17-5477-2023, 2023
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Permafrost (permanently frozen ground) is widespread in the mountains of Norway and Iceland. Several boreholes were drilled after 1999 for long-term permafrost monitoring. We document a strong warming of permafrost, including the development of unfrozen bodies in the permafrost. Warming and degradation of mountain permafrost may lead to more natural hazards.
Esteban Alonso-González, Kristoffer Aalstad, Norbert Pirk, Marco Mazzolini, Désirée Treichler, Paul Leclercq, Sebastian Westermann, Juan Ignacio López-Moreno, and Simon Gascoin
Hydrol. Earth Syst. Sci., 27, 4637–4659, https://doi.org/10.5194/hess-27-4637-2023, https://doi.org/10.5194/hess-27-4637-2023, 2023
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Here we explore how to improve hyper-resolution (5 m) distributed snowpack simulations using sparse observations, which do not provide information from all the areas of the simulation domain. We propose a new way of propagating information throughout the simulations adapted to the hyper-resolution, which could also be used to improve simulations of other nature. The method has been implemented in an open-source data assimilation tool that is readily accessible to everyone.
Anatoly O. Sinitsyn, Sara Bazin, Rasmus Benestad, Bernd Etzelmüller, Ketil Isaksen, Hanne Kvitsand, Julia Lutz, Andrea L. Popp, Lena Rubensdotter, and Sebastian Westermann
EGUsphere, https://doi.org/10.5194/egusphere-2023-2950, https://doi.org/10.5194/egusphere-2023-2950, 2023
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This study looked at under the ground on Svalbard, an archipelago close to the North Pole. We found something very surprising – there is water under the all year around frozen soil. This was not known before. This water could be used for drinking if we manage it carefully. This is important because getting clean drinking water is very difficult in Svalbard, and other Arctic places. Also, because the climate is getting warmer, there might be even more water underground in the future.
Léo C. P. Martin, Sebastian Westermann, Michele Magni, Fanny Brun, Joel Fiddes, Yanbin Lei, Philip Kraaijenbrink, Tamara Mathys, Moritz Langer, Simon Allen, and Walter W. Immerzeel
Hydrol. Earth Syst. Sci., 27, 4409–4436, https://doi.org/10.5194/hess-27-4409-2023, https://doi.org/10.5194/hess-27-4409-2023, 2023
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Across the Tibetan Plateau, many large lakes have been changing level during the last decades as a response to climate change. In high-mountain environments, water fluxes from the land to the lakes are linked to the ground temperature of the land and to the energy fluxes between the ground and the atmosphere, which are modified by climate change. With a numerical model, we test how these water and energy fluxes have changed over the last decades and how they influence the lake level variations.
Juditha Aga, Julia Boike, Moritz Langer, Thomas Ingeman-Nielsen, and Sebastian Westermann
The Cryosphere, 17, 4179–4206, https://doi.org/10.5194/tc-17-4179-2023, https://doi.org/10.5194/tc-17-4179-2023, 2023
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This study presents a new model scheme for simulating ice segregation and thaw consolidation in permafrost environments, depending on ground properties and climatic forcing. It is embedded in the CryoGrid community model, a land surface model for the terrestrial cryosphere. We describe the model physics and functionalities, followed by a model validation and a sensitivity study of controlling factors.
Matan Ben-Asher, Florence Magnin, Sebastian Westermann, Josué Bock, Emmanuel Malet, Johan Berthet, Ludovic Ravanel, and Philip Deline
Earth Surf. Dynam., 11, 899–915, https://doi.org/10.5194/esurf-11-899-2023, https://doi.org/10.5194/esurf-11-899-2023, 2023
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Quantitative knowledge of water availability on high mountain rock slopes is very limited. We use a numerical model and field measurements to estimate the water balance at a steep rock wall site. We show that snowmelt is the main source of water at elevations >3600 m and that snowpack hydrology and sublimation are key factors. The new information presented here can be used to improve the understanding of thermal, hydrogeological, and mechanical processes on steep mountain rock slopes.
Brian Groenke, Moritz Langer, Jan Nitzbon, Sebastian Westermann, Guillermo Gallego, and Julia Boike
The Cryosphere, 17, 3505–3533, https://doi.org/10.5194/tc-17-3505-2023, https://doi.org/10.5194/tc-17-3505-2023, 2023
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It is now well known from long-term temperature measurements that Arctic permafrost, i.e., ground that remains continuously frozen for at least 2 years, is warming in response to climate change. Temperature, however, only tells half of the story. In this study, we use computer modeling to better understand how the thawing and freezing of water in the ground affects the way permafrost responds to climate change and what temperature trends can and cannot tell us about how permafrost is changing.
Louise Steffensen Schmidt, Thomas Vikhamar Schuler, Erin Emily Thomas, and Sebastian Westermann
The Cryosphere, 17, 2941–2963, https://doi.org/10.5194/tc-17-2941-2023, https://doi.org/10.5194/tc-17-2941-2023, 2023
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Here, we present high-resolution simulations of glacier mass balance (the gain and loss of ice over a year) and runoff on Svalbard from 1991–2022, one of the fastest warming regions in the Arctic. The simulations are created using the CryoGrid community model. We find a small overall loss of mass over the simulation period of −0.08 m yr−1 but with no statistically significant trend. The average runoff was found to be 41 Gt yr−1, with a significant increasing trend of 6.3 Gt per decade.
Justyna Czekirda, Bernd Etzelmüller, Sebastian Westermann, Ketil Isaksen, and Florence Magnin
The Cryosphere, 17, 2725–2754, https://doi.org/10.5194/tc-17-2725-2023, https://doi.org/10.5194/tc-17-2725-2023, 2023
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We assess spatio-temporal permafrost variations in selected rock walls in Norway over the last 120 years. Ground temperature is modelled using the two-dimensional ground heat flux model CryoGrid 2D along nine profiles. Permafrost probably occurs at most sites. All simulations show increasing ground temperature from the 1980s. Our simulations show that rock wall permafrost with a temperature of −1 °C at 20 m depth could thaw at this depth within 50 years.
Norbert Pirk, Kristoffer Aalstad, Yeliz A. Yilmaz, Astrid Vatne, Andrea L. Popp, Peter Horvath, Anders Bryn, Ane Victoria Vollsnes, Sebastian Westermann, Terje Koren Berntsen, Frode Stordal, and Lena Merete Tallaksen
Biogeosciences, 20, 2031–2047, https://doi.org/10.5194/bg-20-2031-2023, https://doi.org/10.5194/bg-20-2031-2023, 2023
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We measured the land–atmosphere exchange of CO2 and water vapor in alpine Norway over 3 years. The extremely snow-rich conditions in 2020 reduced the total annual evapotranspiration to 50 % and reduced the growing-season carbon assimilation to turn the ecosystem from a moderate annual carbon sink to an even stronger source. Our analysis suggests that snow cover anomalies are driving the most consequential short-term responses in this ecosystem’s functioning.
Sebastian Westermann, Thomas Ingeman-Nielsen, Johanna Scheer, Kristoffer Aalstad, Juditha Aga, Nitin Chaudhary, Bernd Etzelmüller, Simon Filhol, Andreas Kääb, Cas Renette, Louise Steffensen Schmidt, Thomas Vikhamar Schuler, Robin B. Zweigel, Léo Martin, Sarah Morard, Matan Ben-Asher, Michael Angelopoulos, Julia Boike, Brian Groenke, Frederieke Miesner, Jan Nitzbon, Paul Overduin, Simone M. Stuenzi, and Moritz Langer
Geosci. Model Dev., 16, 2607–2647, https://doi.org/10.5194/gmd-16-2607-2023, https://doi.org/10.5194/gmd-16-2607-2023, 2023
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The CryoGrid community model is a new tool for simulating ground temperatures and the water and ice balance in cold regions. It is a modular design, which makes it possible to test different schemes to simulate, for example, permafrost ground in an efficient way. The model contains tools to simulate frozen and unfrozen ground, snow, glaciers, and other massive ice bodies, as well as water bodies.
Cas Renette, Kristoffer Aalstad, Juditha Aga, Robin Benjamin Zweigel, Bernd Etzelmüller, Karianne Staalesen Lilleøren, Ketil Isaksen, and Sebastian Westermann
Earth Surf. Dynam., 11, 33–50, https://doi.org/10.5194/esurf-11-33-2023, https://doi.org/10.5194/esurf-11-33-2023, 2023
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One of the reasons for lower ground temperatures in coarse, blocky terrain is a low or varying soil moisture content, which most permafrost modelling studies did not take into account. We used the CryoGrid community model to successfully simulate this effect and found markedly lower temperatures in well-drained, blocky deposits compared to other set-ups. The inclusion of this drainage effect is another step towards a better model representation of blocky mountain terrain in permafrost regions.
Norbert Pirk, Kristoffer Aalstad, Sebastian Westermann, Astrid Vatne, Alouette van Hove, Lena Merete Tallaksen, Massimo Cassiani, and Gabriel Katul
Atmos. Meas. Tech., 15, 7293–7314, https://doi.org/10.5194/amt-15-7293-2022, https://doi.org/10.5194/amt-15-7293-2022, 2022
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In this study, we show how sparse and noisy drone measurements can be combined with an ensemble of turbulence-resolving wind simulations to estimate uncertainty-aware surface energy exchange. We demonstrate the feasibility of this drone data assimilation framework in a series of synthetic and real-world experiments. This new framework can, in future, be applied to estimate energy and gas exchange in heterogeneous landscapes more representatively than conventional methods.
Karianne S. Lilleøren, Bernd Etzelmüller, Line Rouyet, Trond Eiken, Gaute Slinde, and Christin Hilbich
Earth Surf. Dynam., 10, 975–996, https://doi.org/10.5194/esurf-10-975-2022, https://doi.org/10.5194/esurf-10-975-2022, 2022
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In northern Norway we have observed several rock glaciers at sea level. Rock glaciers are landforms that only form under the influence of permafrost, which is frozen ground. Our investigations show that the rock glaciers are probably not active under the current climate but most likely were active in the recent past. This shows how the Arctic now changes due to climate changes and also how similar areas in currently colder climates will change in the future.
Juri Palmtag, Jaroslav Obu, Peter Kuhry, Andreas Richter, Matthias B. Siewert, Niels Weiss, Sebastian Westermann, and Gustaf Hugelius
Earth Syst. Sci. Data, 14, 4095–4110, https://doi.org/10.5194/essd-14-4095-2022, https://doi.org/10.5194/essd-14-4095-2022, 2022
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The northern permafrost region covers 22 % of the Northern Hemisphere and holds almost twice as much carbon as the atmosphere. This paper presents data from 651 soil pedons encompassing more than 6500 samples from 16 different study areas across the northern permafrost region. We use this dataset together with ESA's global land cover dataset to estimate soil organic carbon and total nitrogen storage up to 300 cm soil depth, with estimated values of 813 Pg for carbon and 55 Pg for nitrogen.
Aldo Bertone, Chloé Barboux, Xavier Bodin, Tobias Bolch, Francesco Brardinoni, Rafael Caduff, Hanne H. Christiansen, Margaret M. Darrow, Reynald Delaloye, Bernd Etzelmüller, Ole Humlum, Christophe Lambiel, Karianne S. Lilleøren, Volkmar Mair, Gabriel Pellegrinon, Line Rouyet, Lucas Ruiz, and Tazio Strozzi
The Cryosphere, 16, 2769–2792, https://doi.org/10.5194/tc-16-2769-2022, https://doi.org/10.5194/tc-16-2769-2022, 2022
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We present the guidelines developed by the IPA Action Group and within the ESA Permafrost CCI project to include InSAR-based kinematic information in rock glacier inventories. Nine operators applied these guidelines to 11 regions worldwide; more than 3600 rock glaciers are classified according to their kinematics. We test and demonstrate the feasibility of applying common rules to produce homogeneous kinematic inventories at global scale, useful for hydrological and climate change purposes.
Noah D. Smith, Eleanor J. Burke, Kjetil Schanke Aas, Inge H. J. Althuizen, Julia Boike, Casper Tai Christiansen, Bernd Etzelmüller, Thomas Friborg, Hanna Lee, Heather Rumbold, Rachael H. Turton, Sebastian Westermann, and Sarah E. Chadburn
Geosci. Model Dev., 15, 3603–3639, https://doi.org/10.5194/gmd-15-3603-2022, https://doi.org/10.5194/gmd-15-3603-2022, 2022
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The Arctic has large areas of small mounds that are caused by ice lifting up the soil. Snow blown by wind gathers in hollows next to these mounds, insulating them in winter. The hollows tend to be wetter, and thus the soil absorbs more heat in summer. The warm wet soil in the hollows decomposes, releasing methane. We have made a model of this, and we have tested how it behaves and whether it looks like sites in Scandinavia and Siberia. Sometimes we get more methane than a model without mounds.
Sarah E. Chadburn, Eleanor J. Burke, Angela V. Gallego-Sala, Noah D. Smith, M. Syndonia Bret-Harte, Dan J. Charman, Julia Drewer, Colin W. Edgar, Eugenie S. Euskirchen, Krzysztof Fortuniak, Yao Gao, Mahdi Nakhavali, Włodzimierz Pawlak, Edward A. G. Schuur, and Sebastian Westermann
Geosci. Model Dev., 15, 1633–1657, https://doi.org/10.5194/gmd-15-1633-2022, https://doi.org/10.5194/gmd-15-1633-2022, 2022
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We present a new method to include peatlands in an Earth system model (ESM). Peatlands store huge amounts of carbon that accumulates very slowly but that can be rapidly destabilised, emitting greenhouse gases. Our model captures the dynamic nature of peat by simulating the change in surface height and physical properties of the soil as carbon is added or decomposed. Thus, we model, for the first time in an ESM, peat dynamics and its threshold behaviours that can lead to destabilisation.
Bernd Etzelmüller, Justyna Czekirda, Florence Magnin, Pierre-Allain Duvillard, Ludovic Ravanel, Emanuelle Malet, Andreas Aspaas, Lene Kristensen, Ingrid Skrede, Gudrun D. Majala, Benjamin Jacobs, Johannes Leinauer, Christian Hauck, Christin Hilbich, Martina Böhme, Reginald Hermanns, Harald Ø. Eriksen, Tom Rune Lauknes, Michael Krautblatter, and Sebastian Westermann
Earth Surf. Dynam., 10, 97–129, https://doi.org/10.5194/esurf-10-97-2022, https://doi.org/10.5194/esurf-10-97-2022, 2022
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This paper is a multi-authored study documenting the possible existence of permafrost in permanently monitored rockslides in Norway for the first time by combining a multitude of field data, including geophysical surveys in rock walls. The paper discusses the possible role of thermal regime and rockslide movement, and it evaluates the possible impact of atmospheric warming on rockslide dynamics in Norwegian mountains.
Léo C. P. Martin, Jan Nitzbon, Johanna Scheer, Kjetil S. Aas, Trond Eiken, Moritz Langer, Simon Filhol, Bernd Etzelmüller, and Sebastian Westermann
The Cryosphere, 15, 3423–3442, https://doi.org/10.5194/tc-15-3423-2021, https://doi.org/10.5194/tc-15-3423-2021, 2021
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It is important to understand how permafrost landscapes respond to climate changes because their thaw can contribute to global warming. We investigate how a common permafrost morphology degrades using both field observations of the surface elevation and numerical modeling. We show that numerical models accounting for topographic changes related to permafrost degradation can reproduce the observed changes in nature and help us understand how parameters such as snow influence this phenomenon.
Juditha Undine Schmidt, Bernd Etzelmüller, Thomas Vikhamar Schuler, Florence Magnin, Julia Boike, Moritz Langer, and Sebastian Westermann
The Cryosphere, 15, 2491–2509, https://doi.org/10.5194/tc-15-2491-2021, https://doi.org/10.5194/tc-15-2491-2021, 2021
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This study presents rock surface temperatures (RSTs) of steep high-Arctic rock walls on Svalbard from 2016 to 2020. The field data show that coastal cliffs are characterized by warmer RSTs than inland locations during winter seasons. By running model simulations, we analyze factors leading to that effect, calculate the surface energy balance and simulate different future scenarios. Both field data and model results can contribute to a further understanding of RST in high-Arctic rock walls.
Thomas Schneider von Deimling, Hanna Lee, Thomas Ingeman-Nielsen, Sebastian Westermann, Vladimir Romanovsky, Scott Lamoureux, Donald A. Walker, Sarah Chadburn, Erin Trochim, Lei Cai, Jan Nitzbon, Stephan Jacobi, and Moritz Langer
The Cryosphere, 15, 2451–2471, https://doi.org/10.5194/tc-15-2451-2021, https://doi.org/10.5194/tc-15-2451-2021, 2021
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Climate warming puts infrastructure built on permafrost at risk of failure. There is a growing need for appropriate model-based risk assessments. Here we present a modelling study and show an exemplary case of how a gravel road in a cold permafrost environment in Alaska might suffer from degrading permafrost under a scenario of intense climate warming. We use this case study to discuss the broader-scale applicability of our model for simulating future Arctic infrastructure failure.
Jan Nitzbon, Moritz Langer, Léo C. P. Martin, Sebastian Westermann, Thomas Schneider von Deimling, and Julia Boike
The Cryosphere, 15, 1399–1422, https://doi.org/10.5194/tc-15-1399-2021, https://doi.org/10.5194/tc-15-1399-2021, 2021
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We used a numerical model to investigate how small-scale landscape heterogeneities affect permafrost thaw under climate-warming scenarios. Our results show that representing small-scale heterogeneities in the model can decide whether a landscape is water-logged or well-drained in the future. This in turn affects how fast permafrost thaws under warming. Our research emphasizes the importance of considering small-scale processes in model assessments of permafrost thaw under climate change.
Simone Maria Stuenzi, Julia Boike, William Cable, Ulrike Herzschuh, Stefan Kruse, Luidmila A. Pestryakova, Thomas Schneider von Deimling, Sebastian Westermann, Evgenii S. Zakharov, and Moritz Langer
Biogeosciences, 18, 343–365, https://doi.org/10.5194/bg-18-343-2021, https://doi.org/10.5194/bg-18-343-2021, 2021
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Boreal forests in eastern Siberia are an essential component of global climate patterns. We use a physically based model and field measurements to study the interactions between forests, permanently frozen ground and the atmosphere. We find that forests exert a strong control on the thermal state of permafrost through changing snow cover dynamics and altering the surface energy balance, through absorbing most of the incoming solar radiation and suppressing below-canopy turbulent fluxes.
Lei Cai, Hanna Lee, Kjetil Schanke Aas, and Sebastian Westermann
The Cryosphere, 14, 4611–4626, https://doi.org/10.5194/tc-14-4611-2020, https://doi.org/10.5194/tc-14-4611-2020, 2020
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A sub-grid representation of excess ground ice in the Community Land Model (CLM) is developed as novel progress in modeling permafrost thaw and its impacts under the warming climate. The modeled permafrost degradation with sub-grid excess ice follows the pathway that continuous permafrost transforms into discontinuous permafrost before it disappears, including surface subsidence and talik formation, which are highly permafrost-relevant landscape changes excluded from most land models.
Jaroslav Obu, Sebastian Westermann, Gonçalo Vieira, Andrey Abramov, Megan Ruby Balks, Annett Bartsch, Filip Hrbáček, Andreas Kääb, and Miguel Ramos
The Cryosphere, 14, 497–519, https://doi.org/10.5194/tc-14-497-2020, https://doi.org/10.5194/tc-14-497-2020, 2020
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Little is known about permafrost in the Antarctic outside of the few research stations. We used a simple equilibrium permafrost model to estimate permafrost temperatures in the whole Antarctic. The lowest permafrost temperature on Earth is −36 °C in the Queen Elizabeth Range in the Transantarctic Mountains. Temperatures are commonly between −23 and −18 °C in mountainous areas rising above the Antarctic Ice Sheet, between −14 and −8 °C in coastal areas, and up to 0 °C on the Antarctic Peninsula.
Joel Fiddes, Kristoffer Aalstad, and Sebastian Westermann
Hydrol. Earth Syst. Sci., 23, 4717–4736, https://doi.org/10.5194/hess-23-4717-2019, https://doi.org/10.5194/hess-23-4717-2019, 2019
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In this paper we address one of the big challenges in snow hydrology, namely the accurate simulation of the seasonal snowpack in ungauged regions. We do this by assimilating satellite observations of snow cover into a modelling framework. Importantly (and a novelty of the paper), we include a clustering approach that permits highly efficient ensemble simulations. Efficiency gains and dependency on purely global datasets, means that this method can be applied over large areas anywhere on Earth.
Florence Magnin, Bernd Etzelmüller, Sebastian Westermann, Ketil Isaksen, Paula Hilger, and Reginald L. Hermanns
Earth Surf. Dynam., 7, 1019–1040, https://doi.org/10.5194/esurf-7-1019-2019, https://doi.org/10.5194/esurf-7-1019-2019, 2019
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This study proposes the first permafrost (i.e. ground with temperature permanently < 0 °C) map covering the steep rock slopes of Norway. It was created by using rock temperature data collected at the near surface of 25 rock walls spread across the country between 2010 and 2018. The map shows that permafrost mostly exists above 1300–1400 m a.s.l. in southern Norway and close to sea level in northern Norway. The results have strong potential for the study of rock wall sliding and failure.
Max Heikenfeld, Peter J. Marinescu, Matthew Christensen, Duncan Watson-Parris, Fabian Senf, Susan C. van den Heever, and Philip Stier
Geosci. Model Dev., 12, 4551–4570, https://doi.org/10.5194/gmd-12-4551-2019, https://doi.org/10.5194/gmd-12-4551-2019, 2019
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We present tobac (Tracking and Object-Based Analysis of Clouds), a newly developed framework for tracking and analysing clouds in different types of datasets. It provides a flexible new way to include the evolution of individual clouds in a wide range of analyses. It is developed as a community project to provide a common basis for the inclusion of existing tracking algorithms and the development of new analyses that involve tracking clouds and other features in geoscientific research.
Lei Cai, Hanna Lee, Sebastian Westermann, and Kjetil Schanke Aas
The Cryosphere Discuss., https://doi.org/10.5194/tc-2019-230, https://doi.org/10.5194/tc-2019-230, 2019
Preprint withdrawn
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We develop a sub-grid representation of excess ground ice in the Community Land Model (CLM) by adding three landunits to the original CLM sub-grid hierarchy, in order to prescribe three different excess ice conditions in one grid cell. Single-grid simulations verify the potential of the model development on better projecting excess ice melt in a warming climate. Global simulations recommend the proper way of applying the model development with the existing excess ice dataset.
Jan Nitzbon, Moritz Langer, Sebastian Westermann, Léo Martin, Kjetil Schanke Aas, and Julia Boike
The Cryosphere, 13, 1089–1123, https://doi.org/10.5194/tc-13-1089-2019, https://doi.org/10.5194/tc-13-1089-2019, 2019
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We studied the stability of ice wedges (massive bodies of ground ice in permafrost) under recent climatic conditions in the Lena River delta of northern Siberia. For this we used a novel modelling approach that takes into account lateral transport of heat, water, and snow and the subsidence of the ground surface due to melting of ground ice. We found that wetter conditions have a destabilizing effect on the ice wedges and associated our simulation results with observations from the study area.
Max Heikenfeld, Bethan White, Laurent Labbouz, and Philip Stier
Atmos. Chem. Phys., 19, 2601–2627, https://doi.org/10.5194/acp-19-2601-2019, https://doi.org/10.5194/acp-19-2601-2019, 2019
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Aerosols can affect the evolution of deep convective clouds by controlling the cloud droplet number concentration. We perform a detailed analysis of the pathways of such aerosol perturbations through the cloud microphysics in numerical model simulations. By focussing on individually tracked convective cells, we can reveal consistent changes to individual process rates, such as a lifting of freezing and riming, but also major differences between the three different microphysics schemes used.
Kjetil S. Aas, Léo Martin, Jan Nitzbon, Moritz Langer, Julia Boike, Hanna Lee, Terje K. Berntsen, and Sebastian Westermann
The Cryosphere, 13, 591–609, https://doi.org/10.5194/tc-13-591-2019, https://doi.org/10.5194/tc-13-591-2019, 2019
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Many permafrost landscapes contain large amounts of excess ground ice, which gives rise to small-scale elevation differences. This results in lateral fluxes of snow, water, and heat, which we investigate and show how it can be accounted for in large-scale models. Using a novel model technique which can account for these differences, we are able to model both the current state of permafrost and how these landscapes change as permafrost thaws, in a way that could not previously be achieved.
Julia Boike, Inge Juszak, Stephan Lange, Sarah Chadburn, Eleanor Burke, Pier Paul Overduin, Kurt Roth, Olaf Ippisch, Niko Bornemann, Lielle Stern, Isabelle Gouttevin, Ernst Hauber, and Sebastian Westermann
Earth Syst. Sci. Data, 10, 355–390, https://doi.org/10.5194/essd-10-355-2018, https://doi.org/10.5194/essd-10-355-2018, 2018
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A 20-year data record from the Bayelva site at Ny-Ålesund, Svalbard, is presented on meteorology, energy balance components, surface and subsurface observations. This paper presents the data set, instrumentation, calibration, processing and data quality control. The data show that mean annual, summer and winter soil temperature data from shallow to deeper depths have been warming over the period of record, indicating the degradation and loss of permafrost at this site.
Kristoffer Aalstad, Sebastian Westermann, Thomas Vikhamar Schuler, Julia Boike, and Laurent Bertino
The Cryosphere, 12, 247–270, https://doi.org/10.5194/tc-12-247-2018, https://doi.org/10.5194/tc-12-247-2018, 2018
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We demonstrate how snow cover data from satellites can be used to constrain estimates of snow distributions at sites in the Arctic. In this effort, we make use of data assimilation to combine the information contained in the snow cover data with a simple snow model. By comparing our snow distribution estimates to independent observations, we find that this method performs favorably. Being modular, this method could be applied to other areas as a component of a larger reanalysis system.
Sarah E. Chadburn, Gerhard Krinner, Philipp Porada, Annett Bartsch, Christian Beer, Luca Belelli Marchesini, Julia Boike, Altug Ekici, Bo Elberling, Thomas Friborg, Gustaf Hugelius, Margareta Johansson, Peter Kuhry, Lars Kutzbach, Moritz Langer, Magnus Lund, Frans-Jan W. Parmentier, Shushi Peng, Ko Van Huissteden, Tao Wang, Sebastian Westermann, Dan Zhu, and Eleanor J. Burke
Biogeosciences, 14, 5143–5169, https://doi.org/10.5194/bg-14-5143-2017, https://doi.org/10.5194/bg-14-5143-2017, 2017
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Earth system models (ESMs) are our main tools for understanding future climate. The Arctic is important for the future carbon cycle, particularly due to the large carbon stocks in permafrost. We evaluated the performance of the land component of three major ESMs at Arctic tundra sites, focusing on the fluxes and stocks of carbon.
We show that the next steps for model improvement are to better represent vegetation dynamics, to include mosses and to improve below-ground carbon cycle processes.
Sebastian Westermann, Maria Peter, Moritz Langer, Georg Schwamborn, Lutz Schirrmeister, Bernd Etzelmüller, and Julia Boike
The Cryosphere, 11, 1441–1463, https://doi.org/10.5194/tc-11-1441-2017, https://doi.org/10.5194/tc-11-1441-2017, 2017
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We demonstrate a remote-sensing-based scheme estimating the evolution of ground temperature and active layer thickness by means of a ground thermal model. A comparison to in situ observations from the Lena River delta in Siberia indicates that the model is generally capable of reproducing the annual temperature regime and seasonal thawing of the ground. The approach could hence be a first step towards remote detection of ground thermal conditions in permafrost areas.
Luc Girod, Christopher Nuth, Andreas Kääb, Bernd Etzelmüller, and Jack Kohler
The Cryosphere, 11, 827–840, https://doi.org/10.5194/tc-11-827-2017, https://doi.org/10.5194/tc-11-827-2017, 2017
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While gathering data on a changing environment is often a costly and complicated endeavour, it is also the backbone of all research. What if one could measure elevation change by just strapping a camera and a hiking GPS under an helicopter or a small airplane used for transportation and gather data on the ground bellow the flight path? In this article, we present a way to do exactly that and show an example survey where it helped compute the volume of ice lost by a glacier in Svalbard.
Amund F. Borge, Sebastian Westermann, Ingvild Solheim, and Bernd Etzelmüller
The Cryosphere, 11, 1–16, https://doi.org/10.5194/tc-11-1-2017, https://doi.org/10.5194/tc-11-1-2017, 2017
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Palsas and peat plateaus are permafrost landforms in subarctic mires which constitute sensitive ecosystems with strong significance for vegetation, wildlife, hydrology and carbon cycle. We have systematically mapped the occurrence of palsas and peat plateaus in northern Norway by interpretation of aerial images from the 1950s until today. The results show that about half of the area of palsas and peat plateaus has disappeared due to lateral erosion and melting of ground ice in the last 50 years.
Wenli Wang, Annette Rinke, John C. Moore, Duoying Ji, Xuefeng Cui, Shushi Peng, David M. Lawrence, A. David McGuire, Eleanor J. Burke, Xiaodong Chen, Bertrand Decharme, Charles Koven, Andrew MacDougall, Kazuyuki Saito, Wenxin Zhang, Ramdane Alkama, Theodore J. Bohn, Philippe Ciais, Christine Delire, Isabelle Gouttevin, Tomohiro Hajima, Gerhard Krinner, Dennis P. Lettenmaier, Paul A. Miller, Benjamin Smith, Tetsuo Sueyoshi, and Artem B. Sherstiukov
The Cryosphere, 10, 1721–1737, https://doi.org/10.5194/tc-10-1721-2016, https://doi.org/10.5194/tc-10-1721-2016, 2016
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The winter snow insulation is a key process for air–soil temperature coupling and is relevant for permafrost simulations. Differences in simulated air–soil temperature relationships and their modulation by climate conditions are found to be related to the snow model physics. Generally, models with better performance apply multilayer snow schemes.
Kjersti Gisnås, Sebastian Westermann, Thomas Vikhamar Schuler, Kjetil Melvold, and Bernd Etzelmüller
The Cryosphere, 10, 1201–1215, https://doi.org/10.5194/tc-10-1201-2016, https://doi.org/10.5194/tc-10-1201-2016, 2016
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In wind exposed areas snow redistribution results in large spatial variability in ground temperatures. In these areas, the ground temperature of a grid cell must be determined based on the distribution, and not the average, of snow depths. We employ distribution functions of snow in a regional permafrost model, showing highly improved representation of ground temperatures. By including snow distributions, we find the permafrost area to be nearly twice as large as what is modelled without.
S. E. Chadburn, E. J. Burke, R. L. H. Essery, J. Boike, M. Langer, M. Heikenfeld, P. M. Cox, and P. Friedlingstein
The Cryosphere, 9, 1505–1521, https://doi.org/10.5194/tc-9-1505-2015, https://doi.org/10.5194/tc-9-1505-2015, 2015
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In this paper we use a global land-surface model to study the dynamics of Arctic permafrost. We examine the impact of new and improved processes in the model, namely soil depth and resolution, organic soils, moss and the representation of snow. These improvements make the simulated soil temperatures and thaw depth significantly more realistic. Simulations under future climate scenarios show that permafrost thaws more slowly in the new model version, but still a large amount is lost by 2100.
S. Westermann, T. I. Østby, K. Gisnås, T. V. Schuler, and B. Etzelmüller
The Cryosphere, 9, 1303–1319, https://doi.org/10.5194/tc-9-1303-2015, https://doi.org/10.5194/tc-9-1303-2015, 2015
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We use remotely sensed land surface temperature and land cover in conjunction with air temperature and snowfall from a reanalysis product as input for a simple permafrost model. The scheme is applied to the permafrost regions bordering the North Atlantic. A comparison with ground temperatures in boreholes suggests a modeling accuracy of 2 to 2.5 °C.
S. Chadburn, E. Burke, R. Essery, J. Boike, M. Langer, M. Heikenfeld, P. Cox, and P. Friedlingstein
Geosci. Model Dev., 8, 1493–1508, https://doi.org/10.5194/gmd-8-1493-2015, https://doi.org/10.5194/gmd-8-1493-2015, 2015
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Permafrost, ground that is frozen for 2 or more years, is found extensively in the Arctic. It stores large quantities of carbon, which may be released under climate warming, so it is important to include it in climate models. Here we improve the representation of permafrost in a climate model land-surface scheme, both in the numerical representation of soil and snow, and by adding the effects of organic soils and moss. Site simulations show significantly improved soil temperature and thaw depth.
S. Westermann, B. Elberling, S. Højlund Pedersen, M. Stendel, B. U. Hansen, and G. E. Liston
The Cryosphere, 9, 719–735, https://doi.org/10.5194/tc-9-719-2015, https://doi.org/10.5194/tc-9-719-2015, 2015
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The development of ground temperatures in permafrost areas is influenced by many factors varying on different spatial and temporal scales. We present numerical simulations of ground temperatures for the Zackenberg valley in NE Greenland, which take into account the spatial variability of snow depths, surface and ground properties at a scale of 10m. The ensemble of the model grid cells suggests a spatial variability of annual average ground temperatures of up to 5°C.
M. Langer, S. Westermann, K. Walter Anthony, K. Wischnewski, and J. Boike
Biogeosciences, 12, 977–990, https://doi.org/10.5194/bg-12-977-2015, https://doi.org/10.5194/bg-12-977-2015, 2015
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Methane production rates of Arctic ponds during the freezing period within a typical tundra landscape in northern Siberia are presented. Production rates were inferred by inverse modeling based on measured methane concentrations in the ice cover. Results revealed marked differences in early winter methane production among ponds showing different stages of shore degradation. This suggests that shore erosion can increase methane production of Arctic ponds by 2 to 3 orders of magnitude.
J. Lüers, S. Westermann, K. Piel, and J. Boike
Biogeosciences, 11, 6307–6322, https://doi.org/10.5194/bg-11-6307-2014, https://doi.org/10.5194/bg-11-6307-2014, 2014
K. Gisnås, S. Westermann, T. V. Schuler, T. Litherland, K. Isaksen, J. Boike, and B. Etzelmüller
The Cryosphere, 8, 2063–2074, https://doi.org/10.5194/tc-8-2063-2014, https://doi.org/10.5194/tc-8-2063-2014, 2014
S. Westermann, T. V. Schuler, K. Gisnås, and B. Etzelmüller
The Cryosphere, 7, 719–739, https://doi.org/10.5194/tc-7-719-2013, https://doi.org/10.5194/tc-7-719-2013, 2013
Related subject area
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Simon Horton, Florian Herla, and Pascal Haegeli
Geosci. Model Dev., 18, 193–209, https://doi.org/10.5194/gmd-18-193-2025, https://doi.org/10.5194/gmd-18-193-2025, 2025
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We present a method for avalanche forecasters to analyze patterns in snowpack model simulations. It uses fuzzy clustering to group small regions into larger forecast areas based on snow characteristics, locations, and temporal history. Tested in the Columbia Mountains in two winter seasons, it closely matched real forecast regions regions and identified major avalanche hazard patterns. This approach simplifies complex model outputs, helping forecasters make informed decisions.
Adrien Michel, Johannes Aschauer, Tobias Jonas, Stefanie Gubler, Sven Kotlarski, and Christoph Marty
Geosci. Model Dev., 17, 8969–8988, https://doi.org/10.5194/gmd-17-8969-2024, https://doi.org/10.5194/gmd-17-8969-2024, 2024
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We present a method to correct snow cover maps (represented in terms of snow water equivalent) to match better-quality maps. The correction can then be extended backwards and forwards in time for periods when better-quality maps are not available. The method is fast and gives good results. It is then applied to obtain a climatology of the snow cover in Switzerland over the past 60 years at a resolution of 1 d and 1 km. This is the first time that such a dataset has been produced.
Ghislain Picard and Quentin Libois
Geosci. Model Dev., 17, 8927–8953, https://doi.org/10.5194/gmd-17-8927-2024, https://doi.org/10.5194/gmd-17-8927-2024, 2024
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The Two-streAm Radiative TransfEr in Snow (TARTES) is a radiative transfer model to compute snow albedo in the solar domain and the profiles of light and energy absorption in a multi-layered snowpack whose physical properties are user defined. It uniquely considers snow grain shape flexibly, based on recent insights showing that snow does not behave as a collection of ice spheres but instead as a random medium. TARTES is user-friendly yet performs comparably to more complex models.
Yoshihiro Nakayama, Alena Malyarenko, Hong Zhang, Ou Wang, Matthis Auger, Yafei Nie, Ian Fenty, Matthew Mazloff, Armin Köhl, and Dimitris Menemenlis
Geosci. Model Dev., 17, 8613–8638, https://doi.org/10.5194/gmd-17-8613-2024, https://doi.org/10.5194/gmd-17-8613-2024, 2024
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Global- and basin-scale ocean reanalyses are becoming easily accessible. However, such ocean reanalyses are optimized for their entire model domains and their ability to simulate the Southern Ocean requires evaluation. We conduct intercomparison analyses of Massachusetts Institute of Technology General Circulation Model (MITgcm)-based ocean reanalyses. They generally perform well for the open ocean, but open-ocean temporal variability and Antarctic continental shelves require improvements.
Diego Monteiro, Cécile Caillaud, Matthieu Lafaysse, Adrien Napoly, Mathieu Fructus, Antoinette Alias, and Samuel Morin
Geosci. Model Dev., 17, 7645–7677, https://doi.org/10.5194/gmd-17-7645-2024, https://doi.org/10.5194/gmd-17-7645-2024, 2024
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Modeling snow cover in climate and weather forecasting models is a challenge even for high-resolution models. Recent simulations with CNRM-AROME have shown difficulties when representing snow in the European Alps. Using remote sensing data and in situ observations, we evaluate modifications of the land surface configuration in order to improve it. We propose a new surface configuration, enabling a more realistic simulation of snow cover, relevant for climate and weather forecasting applications.
Alessandro Maissen, Frank Techel, and Michele Volpi
Geosci. Model Dev., 17, 7569–7593, https://doi.org/10.5194/gmd-17-7569-2024, https://doi.org/10.5194/gmd-17-7569-2024, 2024
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By harnessing AI models, this work enables processing large amounts of data, including weather conditions, snowpack characteristics, and historical avalanche data, to predict human-like avalanche forecasts in Switzerland. Our proposed model can significantly assist avalanche forecasters in their decision-making process, thereby facilitating more efficient and accurate predictions crucial for ensuring safety in Switzerland's avalanche-prone regions.
Enrico Zorzetto, Sergey Malyshev, Paul Ginoux, and Elena Shevliakova
Geosci. Model Dev., 17, 7219–7244, https://doi.org/10.5194/gmd-17-7219-2024, https://doi.org/10.5194/gmd-17-7219-2024, 2024
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We describe a new snow scheme developed for use in global climate models, which simulates the interactions of snowpack with vegetation, atmosphere, and soil. We test the new snow model over a set of sites where in situ observations are available. We find that when compared to a simpler snow model, this model improves predictions of seasonal snow and of soil temperature under the snowpack, important variables for simulating both the hydrological cycle and the global climate system.
Therese Rieckh, Andreas Born, Alexander Robinson, Robert Law, and Gerrit Gülle
Geosci. Model Dev., 17, 6987–7000, https://doi.org/10.5194/gmd-17-6987-2024, https://doi.org/10.5194/gmd-17-6987-2024, 2024
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We present the open-source model ELSA, which simulates the internal age structure of large ice sheets. It creates layers of snow accumulation at fixed times during the simulation, which are used to model the internal stratification of the ice sheet. Together with reconstructed isochrones from radiostratigraphy data, ELSA can be used to assess ice sheet models and to improve their parameterization. ELSA can be used coupled to an ice sheet model or forced with its output.
Fu Zhao, Xi Liang, Zhongxiang Tian, Ming Li, Na Liu, and Chengyan Liu
Geosci. Model Dev., 17, 6867–6886, https://doi.org/10.5194/gmd-17-6867-2024, https://doi.org/10.5194/gmd-17-6867-2024, 2024
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In this work, we introduce a newly developed Antarctic sea ice forecasting system, namely the Southern Ocean Ice Prediction System (SOIPS). The system is based on a regional sea ice‒ocean‒ice shelf coupled model and can assimilate sea ice concentration observations. By assessing the system's performance in sea ice forecasts, we find that the system can provide reliable Antarctic sea ice forecasts for the next 7 d and has the potential to guide ship navigation in the Antarctic sea ice zone.
Chenhui Ning, Shiming Xu, Yan Zhang, Xuantong Wang, Zhihao Fan, and Jiping Liu
Geosci. Model Dev., 17, 6847–6866, https://doi.org/10.5194/gmd-17-6847-2024, https://doi.org/10.5194/gmd-17-6847-2024, 2024
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Sea ice models are mainly based on non-moving structured grids, which is different from buoy measurements that follow the ice drift. To facilitate Lagrangian analysis, we introduce online tracking of sea ice in Community Ice CodE (CICE). We validate the sea ice tracking with buoys and evaluate the sea ice deformation in high-resolution simulations, which show multi-fractal characteristics. The source code is openly available and can be used in various scientific and operational applications.
Ulrich Strasser, Michael Warscher, Erwin Rottler, and Florian Hanzer
Geosci. Model Dev., 17, 6775–6797, https://doi.org/10.5194/gmd-17-6775-2024, https://doi.org/10.5194/gmd-17-6775-2024, 2024
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openAMUNDSEN is a fully distributed open-source snow-hydrological model for mountain catchments. It includes process representations of an empirical, semi-empirical, and physical nature. It uses temperature, precipitation, humidity, radiation, and wind speed as forcing data and is computationally efficient, of a modular nature, and easily extendible. The Python code is available on GitHub (https://github.com/openamundsen/openamundsen), including documentation (https://doc.openamundsen.org).
Matthias Rauter and Julia Kowalski
Geosci. Model Dev., 17, 6545–6569, https://doi.org/10.5194/gmd-17-6545-2024, https://doi.org/10.5194/gmd-17-6545-2024, 2024
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Snow avalanches can form large powder clouds that substantially exceed the velocity and reach of the dense core. Only a few complex models exist to simulate this phenomenon, and the respective hazard is hard to predict. This work provides a novel flow model that focuses on simple relations while still encapsulating the significant behaviour. The model is applied to reconstruct two catastrophic powder snow avalanche events in Austria.
Till Andreas Soya Rasmussen, Jacob Poulsen, Mads Hvid Ribergaard, Ruchira Sasanka, Anthony P. Craig, Elizabeth C. Hunke, and Stefan Rethmeier
Geosci. Model Dev., 17, 6529–6544, https://doi.org/10.5194/gmd-17-6529-2024, https://doi.org/10.5194/gmd-17-6529-2024, 2024
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Earth system models (ESMs) today strive for better quality based on improved resolutions and improved physics. A limiting factor is the supercomputers at hand and how best to utilize them. This study focuses on the refactorization of one part of a sea ice model (CICE), namely the dynamics. It shows that the performance can be significantly improved, which means that one can either run the same simulations much cheaper or advance the system according to what is needed.
Anton Korosov, Yue Ying, and Einar Olason
EGUsphere, https://doi.org/10.5194/egusphere-2024-2527, https://doi.org/10.5194/egusphere-2024-2527, 2024
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We have developed a new method to improve the accuracy of sea ice models, which predict how ice moves and deforms due to wind and ocean currents. Traditional models use parameters that are often poorly defined. The new approach uses machine learning to fine-tune these parameters by comparing simulated ice drift with satellite data. The method identifies optimal settings for the model by analysing patterns in ice deformation. This results in more accurate simulations of sea ice drift forecasting.
Iain Wheel, Douglas I. Benn, Anna J. Crawford, Joe Todd, and Thomas Zwinger
Geosci. Model Dev., 17, 5759–5777, https://doi.org/10.5194/gmd-17-5759-2024, https://doi.org/10.5194/gmd-17-5759-2024, 2024
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Calving, the detachment of large icebergs from glaciers, is one of the largest uncertainties in future sea level rise projections. This process is poorly understood, and there is an absence of detailed models capable of simulating calving. A new 3D calving model has been developed to better understand calving at glaciers where detailed modelling was previously limited. Importantly, the new model is very flexible. By allowing for unrestricted calving geometries, it can be applied at any location.
Jan Svoboda, Marc Ruesch, David Liechti, Corinne Jones, Michele Volpi, Michael Zehnder, and Jürg Schweizer
EGUsphere, https://doi.org/10.5194/egusphere-2024-1752, https://doi.org/10.5194/egusphere-2024-1752, 2024
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Accurately measuring snow height is key for modeling approaches in climate sciences, snow hydrology and avalanche forecasting. Erroneous snow height measurements often occur when the snow height is low or changes, for instance, during a snowfall in the summer. We prepare a new benchmark dataset with annotated snow height data and demonstrate how to improve the measurement quality using modern deep learning approaches. Our approach can be easily implemented into a data pipeline for snow modeling.
Jim Marschalek, Edward Gasson, Tina van de Flierdt, Claus-Dieter Hillenbrand, Martin Siegert, and Liam Holder
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-104, https://doi.org/10.5194/gmd-2024-104, 2024
Revised manuscript accepted for GMD
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Ice sheet models can help predict how Antarctica's ice sheets respond to environmental change, and such models benefit from comparison to geological data. Here, we use an ice sheet model output, plus other data, to predict the erosion of debris and trace its transport to where it is deposited on the ocean floor. This allows the results of ice sheet modelling to be directly and quantitively compared to real-world data, helping to reduce uncertainty regarding Antarctic sea level contribution.
Xia Wang, Tao Che, Xueyin Ruan, Shanna Yue, Jing Wang, Chun Zhao, and Lei Geng
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-37, https://doi.org/10.5194/gmd-2024-37, 2024
Revised manuscript accepted for GMD
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We employed the WRF-Chem model to parameterize atmospheric nitrate deposition in snow and evaluated its performance in simulating snow cover, snow depth, and concentrations of black carbon (BC), dust, and nitrate using new observations from Northern China. The results generally exhibit reasonable agreement with field observations in northern China, demonstrating the model's capability to simulate snow properties, including concentrations of reservoir species.
Kévin Fourteau, Julien Brondex, Fanny Brun, and Marie Dumont
Geosci. Model Dev., 17, 1903–1929, https://doi.org/10.5194/gmd-17-1903-2024, https://doi.org/10.5194/gmd-17-1903-2024, 2024
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In this paper, we provide a novel numerical implementation for solving the energy exchanges at the surface of snow and ice. By combining the strong points of previous models, our solution leads to more accurate and robust simulations of the energy exchanges, surface temperature, and melt while preserving a reasonable computation time.
Matthieu Baron, Ange Haddjeri, Matthieu Lafaysse, Louis Le Toumelin, Vincent Vionnet, and Mathieu Fructus
Geosci. Model Dev., 17, 1297–1326, https://doi.org/10.5194/gmd-17-1297-2024, https://doi.org/10.5194/gmd-17-1297-2024, 2024
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Increasing the spatial resolution of numerical systems simulating snowpack evolution in mountain areas requires representing small-scale processes such as wind-induced snow transport. We present SnowPappus, a simple scheme coupled with the Crocus snow model to compute blowing-snow fluxes and redistribute snow among grid points at 250 m resolution. In terms of numerical cost, it is suitable for large-scale applications. We present point-scale evaluations of fluxes and snow transport occurrence.
Lizz Ultee, Alexander A. Robel, and Stefano Castruccio
Geosci. Model Dev., 17, 1041–1057, https://doi.org/10.5194/gmd-17-1041-2024, https://doi.org/10.5194/gmd-17-1041-2024, 2024
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The surface mass balance (SMB) of an ice sheet describes the net gain or loss of mass from ice sheets (such as those in Greenland and Antarctica) through interaction with the atmosphere. We developed a statistical method to generate a wide range of SMB fields that reflect the best understanding of SMB processes. Efficiently sampling the variability of SMB will help us understand sources of uncertainty in ice sheet model projections.
Anjali Sandip, Ludovic Räss, and Mathieu Morlighem
Geosci. Model Dev., 17, 899–909, https://doi.org/10.5194/gmd-17-899-2024, https://doi.org/10.5194/gmd-17-899-2024, 2024
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We solve momentum balance for unstructured meshes to predict ice flow for real glaciers using a pseudo-transient method on graphics processing units (GPUs) and compare it to a standard central processing unit (CPU) implementation. We justify the GPU implementation by applying the price-to-performance metric for up to million-grid-point spatial resolutions. This study represents a first step toward leveraging GPU processing power, enabling more accurate polar ice discharge predictions.
Julien Brondex, Kévin Fourteau, Marie Dumont, Pascal Hagenmuller, Neige Calonne, François Tuzet, and Henning Löwe
Geosci. Model Dev., 16, 7075–7106, https://doi.org/10.5194/gmd-16-7075-2023, https://doi.org/10.5194/gmd-16-7075-2023, 2023
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Vapor diffusion is one of the main processes governing snowpack evolution, and it must be accounted for in models. Recent attempts to represent vapor diffusion in numerical models have faced several difficulties regarding computational cost and mass and energy conservation. Here, we develop our own finite-element software to explore numerical approaches and enable us to overcome these difficulties. We illustrate the capability of these approaches on established numerical benchmarks.
Matthias Tonnel, Anna Wirbel, Felix Oesterle, and Jan-Thomas Fischer
Geosci. Model Dev., 16, 7013–7035, https://doi.org/10.5194/gmd-16-7013-2023, https://doi.org/10.5194/gmd-16-7013-2023, 2023
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Avaframe - the open avalanche framework - provides open-source tools to simulate and investigate snow avalanches. It is utilized for multiple purposes, the two main applications being hazard mapping and scientific research of snow processes. We present the theory, conversion to a computer model, and testing for one of the core modules used for simulations of a particular type of avalanche, the so-called dense-flow avalanches. Tests check and confirm the applicability of the utilized method.
Jordi Bolibar, Facundo Sapienza, Fabien Maussion, Redouane Lguensat, Bert Wouters, and Fernando Pérez
Geosci. Model Dev., 16, 6671–6687, https://doi.org/10.5194/gmd-16-6671-2023, https://doi.org/10.5194/gmd-16-6671-2023, 2023
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We developed a new modelling framework combining numerical methods with machine learning. Using this approach, we focused on understanding how ice moves within glaciers, and we successfully learnt a prescribed law describing ice movement for 17 glaciers worldwide as a proof of concept. Our framework has the potential to discover important laws governing glacier processes, aiding our understanding of glacier physics and their contribution to water resources and sea-level rise.
Prateek Gantayat, Alison F. Banwell, Amber A. Leeson, James M. Lea, Dorthe Petersen, Noel Gourmelen, and Xavier Fettweis
Geosci. Model Dev., 16, 5803–5823, https://doi.org/10.5194/gmd-16-5803-2023, https://doi.org/10.5194/gmd-16-5803-2023, 2023
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We developed a new supraglacial hydrology model for the Greenland Ice Sheet. This model simulates surface meltwater routing, meltwater drainage, supraglacial lake (SGL) overflow, and formation of lake ice. The model was able to reproduce 80 % of observed lake locations and provides a good match between the observed and modelled temporal evolution of SGLs.
Kevin Hank, Lev Tarasov, and Elisa Mantelli
Geosci. Model Dev., 16, 5627–5652, https://doi.org/10.5194/gmd-16-5627-2023, https://doi.org/10.5194/gmd-16-5627-2023, 2023
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Physically meaningful modeling of geophysical system instabilities is numerically challenging, given the potential effects of purely numerical artifacts. Here we explore the sensitivity of ice stream surge activation to numerical and physical model aspects. We find that surge characteristics exhibit a resolution dependency but converge at higher horizontal grid resolutions and are significantly affected by the incorporation of bed thermal and sub-glacial hydrology models.
Yannic Fischler, Thomas Kleiner, Christian Bischof, Jeremie Schmiedel, Roiy Sayag, Raban Emunds, Lennart Frederik Oestreich, and Angelika Humbert
Geosci. Model Dev., 16, 5305–5322, https://doi.org/10.5194/gmd-16-5305-2023, https://doi.org/10.5194/gmd-16-5305-2023, 2023
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Water underneath ice sheets affects the motion of glaciers. This study presents a newly developed code, CUAS-MPI, that simulates subglacial hydrology. It is designed for supercomputers and is hence a parallelized code. We measure the performance of this code for simulations of the entire Greenland Ice Sheet and find that the code works efficiently. Moreover, we validated the code to ensure the correctness of the solution. CUAS-MPI opens new possibilities for simulations of ice sheet hydrology.
Julia Kaltenborn, Amy R. Macfarlane, Viviane Clay, and Martin Schneebeli
Geosci. Model Dev., 16, 4521–4550, https://doi.org/10.5194/gmd-16-4521-2023, https://doi.org/10.5194/gmd-16-4521-2023, 2023
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Snow layer segmentation and snow grain classification are essential diagnostic tasks for cryospheric applications. A SnowMicroPen (SMP) can be used to that end; however, the manual classification of its profiles becomes infeasible for large datasets. Here, we evaluate how well machine learning models automate this task. Of the 14 models trained on the MOSAiC SMP dataset, the long short-term memory model performed the best. The findings presented here facilitate and accelerate SMP data analysis.
Johannes Aschauer, Adrien Michel, Tobias Jonas, and Christoph Marty
Geosci. Model Dev., 16, 4063–4081, https://doi.org/10.5194/gmd-16-4063-2023, https://doi.org/10.5194/gmd-16-4063-2023, 2023
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Snow water equivalent is the mass of water stored in a snowpack. Based on exponential settling functions, the empirical snow density model SWE2HS is presented to convert time series of daily snow water equivalent into snow depth. The model has been calibrated with data from Switzerland and validated with independent data from the European Alps. A reference implementation of SWE2HS is available as a Python package.
Eric Keenan, Nander Wever, Jan T. M. Lenaerts, and Brooke Medley
Geosci. Model Dev., 16, 3203–3219, https://doi.org/10.5194/gmd-16-3203-2023, https://doi.org/10.5194/gmd-16-3203-2023, 2023
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Ice sheets gain mass via snowfall. However, snowfall is redistributed by the wind, resulting in accumulation differences of up to a factor of 5 over distances as short as 5 km. These differences complicate estimates of ice sheet contribution to sea level rise. For this reason, we have developed a new model for estimating wind-driven snow redistribution on ice sheets. We show that, over Pine Island Glacier in West Antarctica, the model improves estimates of snow accumulation variability.
Sebastian Westermann, Thomas Ingeman-Nielsen, Johanna Scheer, Kristoffer Aalstad, Juditha Aga, Nitin Chaudhary, Bernd Etzelmüller, Simon Filhol, Andreas Kääb, Cas Renette, Louise Steffensen Schmidt, Thomas Vikhamar Schuler, Robin B. Zweigel, Léo Martin, Sarah Morard, Matan Ben-Asher, Michael Angelopoulos, Julia Boike, Brian Groenke, Frederieke Miesner, Jan Nitzbon, Paul Overduin, Simone M. Stuenzi, and Moritz Langer
Geosci. Model Dev., 16, 2607–2647, https://doi.org/10.5194/gmd-16-2607-2023, https://doi.org/10.5194/gmd-16-2607-2023, 2023
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The CryoGrid community model is a new tool for simulating ground temperatures and the water and ice balance in cold regions. It is a modular design, which makes it possible to test different schemes to simulate, for example, permafrost ground in an efficient way. The model contains tools to simulate frozen and unfrozen ground, snow, glaciers, and other massive ice bodies, as well as water bodies.
Alex S. Gardner, Nicole-Jeanne Schlegel, and Eric Larour
Geosci. Model Dev., 16, 2277–2302, https://doi.org/10.5194/gmd-16-2277-2023, https://doi.org/10.5194/gmd-16-2277-2023, 2023
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This is the first description of the open-source Glacier Energy and Mass Balance (GEMB) model. GEMB models the ice sheet and glacier surface–atmospheric energy and mass exchange, as well as the firn state. The model is evaluated against the current state of the art and in situ observations and is shown to perform well.
Yafei Nie, Chengkun Li, Martin Vancoppenolle, Bin Cheng, Fabio Boeira Dias, Xianqing Lv, and Petteri Uotila
Geosci. Model Dev., 16, 1395–1425, https://doi.org/10.5194/gmd-16-1395-2023, https://doi.org/10.5194/gmd-16-1395-2023, 2023
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State-of-the-art Earth system models simulate the observed sea ice extent relatively well, but this is often due to errors in the dynamic and other processes in the simulated sea ice changes cancelling each other out. We assessed the sensitivity of these processes simulated by the coupled ocean–sea ice model NEMO4.0-SI3 to 18 parameters. The performance of the model in simulating sea ice change processes was ultimately improved by adjusting the three identified key parameters.
Varun Sharma, Franziska Gerber, and Michael Lehning
Geosci. Model Dev., 16, 719–749, https://doi.org/10.5194/gmd-16-719-2023, https://doi.org/10.5194/gmd-16-719-2023, 2023
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Most current generation climate and weather models have a relatively simplistic description of snow and snow–atmosphere interaction. One reason for this is the belief that including an advanced snow model would make the simulations too computationally demanding. In this study, we bring together two state-of-the-art models for atmosphere (WRF) and snow cover (SNOWPACK) and highlight both the feasibility and necessity of such coupled models to explore underexplored phenomena in the cryosphere.
Anne M. Felden, Daniel F. Martin, and Esmond G. Ng
Geosci. Model Dev., 16, 407–425, https://doi.org/10.5194/gmd-16-407-2023, https://doi.org/10.5194/gmd-16-407-2023, 2023
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We present and validate a novel subglacial hydrology model, SUHMO, based on an adaptive mesh refinement framework. We propose the addition of a pseudo-diffusion to recover the wall melting in channels. Computational performance analysis demonstrates the efficiency of adaptive mesh refinement on large-scale hydrologic problems. The adaptive mesh refinement approach will eventually enable better ice bed boundary conditions for ice sheet simulations at a reasonable computational cost.
Dalei Hao, Gautam Bisht, Karl Rittger, Edward Bair, Cenlin He, Huilin Huang, Cheng Dang, Timbo Stillinger, Yu Gu, Hailong Wang, Yun Qian, and L. Ruby Leung
Geosci. Model Dev., 16, 75–94, https://doi.org/10.5194/gmd-16-75-2023, https://doi.org/10.5194/gmd-16-75-2023, 2023
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Snow with the highest albedo of land surface plays a vital role in Earth’s surface energy budget and water cycle. This study accounts for the impacts of snow grain shape and mixing state of light-absorbing particles with snow on snow albedo in the E3SM land model. The findings advance our understanding of the role of snow grain shape and mixing state of LAP–snow in land surface processes and offer guidance for improving snow simulations and radiative forcing estimates in Earth system models.
Esteban Alonso-González, Kristoffer Aalstad, Mohamed Wassim Baba, Jesús Revuelto, Juan Ignacio López-Moreno, Joel Fiddes, Richard Essery, and Simon Gascoin
Geosci. Model Dev., 15, 9127–9155, https://doi.org/10.5194/gmd-15-9127-2022, https://doi.org/10.5194/gmd-15-9127-2022, 2022
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Snow cover plays an important role in many processes, but its monitoring is a challenging task. The alternative is usually to simulate the snowpack, and to improve these simulations one of the most promising options is to fuse simulations with available observations (data assimilation). In this paper we present MuSA, a data assimilation tool which facilitates the implementation of snow monitoring initiatives, allowing the assimilation of a wide variety of remotely sensed snow cover information.
Vincent Verjans, Alexander A. Robel, Helene Seroussi, Lizz Ultee, and Andrew F. Thompson
Geosci. Model Dev., 15, 8269–8293, https://doi.org/10.5194/gmd-15-8269-2022, https://doi.org/10.5194/gmd-15-8269-2022, 2022
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We describe the development of the first large-scale ice sheet model that accounts for stochasticity in a range of processes. Stochasticity allows the impacts of inherently uncertain processes on ice sheets to be represented. This includes climatic uncertainty, as the climate is inherently chaotic. Furthermore, stochastic capabilities also encompass poorly constrained glaciological processes that display strong variability at fine spatiotemporal scales. We present the model and test experiments.
Max Brils, Peter Kuipers Munneke, Willem Jan van de Berg, and Michiel van den Broeke
Geosci. Model Dev., 15, 7121–7138, https://doi.org/10.5194/gmd-15-7121-2022, https://doi.org/10.5194/gmd-15-7121-2022, 2022
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Firn covers the Greenland ice sheet (GrIS) and can temporarily prevent mass loss. Here, we present the latest version of our firn model, IMAU-FDM, with an application to the GrIS. We improved the density of fallen snow, the firn densification rate and the firn's thermal conductivity. This leads to a higher air content and 10 m temperatures. Furthermore we investigate three case studies and find that the updated model shows greater variability and an increased sensitivity in surface elevation.
Océane Hames, Mahdi Jafari, David Nicholas Wagner, Ian Raphael, David Clemens-Sewall, Chris Polashenski, Matthew D. Shupe, Martin Schneebeli, and Michael Lehning
Geosci. Model Dev., 15, 6429–6449, https://doi.org/10.5194/gmd-15-6429-2022, https://doi.org/10.5194/gmd-15-6429-2022, 2022
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This paper presents an Eulerian–Lagrangian snow transport model implemented in the fluid dynamics software OpenFOAM, which we call snowBedFoam 1.0. We apply this model to reproduce snow deposition on a piece of ridged Arctic sea ice, which was produced during the MOSAiC expedition through scan measurements. The model appears to successfully reproduce the enhanced snow accumulation and deposition patterns, although some quantitative uncertainties were shown.
Constantijn J. Berends, Heiko Goelzer, Thomas J. Reerink, Lennert B. Stap, and Roderik S. W. van de Wal
Geosci. Model Dev., 15, 5667–5688, https://doi.org/10.5194/gmd-15-5667-2022, https://doi.org/10.5194/gmd-15-5667-2022, 2022
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The rate at which marine ice sheets such as the West Antarctic ice sheet will retreat in a warming climate and ocean is still uncertain. Numerical ice-sheet models, which solve the physical equations that describe the way glaciers and ice sheets deform and flow, have been substantially improved in recent years. Here we present the results of several years of work on IMAU-ICE, an ice-sheet model of intermediate complexity, which can be used to study ice sheets of both the past and the future.
Abby C. Lute, John Abatzoglou, and Timothy Link
Geosci. Model Dev., 15, 5045–5071, https://doi.org/10.5194/gmd-15-5045-2022, https://doi.org/10.5194/gmd-15-5045-2022, 2022
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We developed a snow model that can be used to quantify snowpack over large areas with a high degree of spatial detail. We ran the model over the western United States, creating a snow and climate dataset for three time periods. Compared to observations of snowpack, the model captured the key aspects of snow across time and space. The model and dataset will be useful in understanding historical and future changes in snowpack, with relevance to water resources, agriculture, and ecosystems.
Francesco Avanzi, Simone Gabellani, Fabio Delogu, Francesco Silvestro, Edoardo Cremonese, Umberto Morra di Cella, Sara Ratto, and Hervé Stevenin
Geosci. Model Dev., 15, 4853–4879, https://doi.org/10.5194/gmd-15-4853-2022, https://doi.org/10.5194/gmd-15-4853-2022, 2022
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Knowing in real time how much snow and glacier ice has accumulated across the landscape has significant implications for water-resource management and flood control. This paper presents a computer model – S3M – allowing scientists and decision makers to predict snow and ice accumulation during winter and the subsequent melt during spring and summer. S3M has been employed for real-world flood forecasting since the early 2000s but is here being made open source for the first time.
Adrian K. Turner, William H. Lipscomb, Elizabeth C. Hunke, Douglas W. Jacobsen, Nicole Jeffery, Darren Engwirda, Todd D. Ringler, and Jonathan D. Wolfe
Geosci. Model Dev., 15, 3721–3751, https://doi.org/10.5194/gmd-15-3721-2022, https://doi.org/10.5194/gmd-15-3721-2022, 2022
Short summary
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We present the dynamical core of the MPAS-Seaice model, which uses a mesh consisting of a Voronoi tessellation with polygonal cells. Such a mesh allows variable mesh resolution in different parts of the domain and the focusing of computational resources in regions of interest. We describe the velocity solver and tracer transport schemes used and examine errors generated by the model in both idealized and realistic test cases and examine the computational efficiency of the model.
Noah D. Smith, Eleanor J. Burke, Kjetil Schanke Aas, Inge H. J. Althuizen, Julia Boike, Casper Tai Christiansen, Bernd Etzelmüller, Thomas Friborg, Hanna Lee, Heather Rumbold, Rachael H. Turton, Sebastian Westermann, and Sarah E. Chadburn
Geosci. Model Dev., 15, 3603–3639, https://doi.org/10.5194/gmd-15-3603-2022, https://doi.org/10.5194/gmd-15-3603-2022, 2022
Short summary
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The Arctic has large areas of small mounds that are caused by ice lifting up the soil. Snow blown by wind gathers in hollows next to these mounds, insulating them in winter. The hollows tend to be wetter, and thus the soil absorbs more heat in summer. The warm wet soil in the hollows decomposes, releasing methane. We have made a model of this, and we have tested how it behaves and whether it looks like sites in Scandinavia and Siberia. Sometimes we get more methane than a model without mounds.
Adrian K. Turner, Kara J. Peterson, and Dan Bolintineanu
Geosci. Model Dev., 15, 1953–1970, https://doi.org/10.5194/gmd-15-1953-2022, https://doi.org/10.5194/gmd-15-1953-2022, 2022
Short summary
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We developed a technique to remap sea ice tracer quantities between circular discrete element distributions. This is needed for a global discrete element method sea ice model being developed jointly by Los Alamos National Laboratory and Sandia National Laboratories that has the potential to better utilize newer supercomputers with graphics processing units and better represent sea ice dynamics. This new remapping technique ameliorates the effect of element distortion created by sea ice ridging.
Zhen Yin, Chen Zuo, Emma J. MacKie, and Jef Caers
Geosci. Model Dev., 15, 1477–1497, https://doi.org/10.5194/gmd-15-1477-2022, https://doi.org/10.5194/gmd-15-1477-2022, 2022
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We provide a multiple-point geostatistics approach to probabilistically learn from training images to fill large-scale irregular geophysical data gaps. With a repository of global topographic training images, our approach models high-resolution basal topography and quantifies the geospatial uncertainty. It generated high-resolution topographic realizations to investigate the impact of basal topographic uncertainty on critical subglacial hydrological flow patterns associated with ice velocity.
Yu Yan, Wei Gu, Andrea M. U. Gierisch, Yingjun Xu, and Petteri Uotila
Geosci. Model Dev., 15, 1269–1288, https://doi.org/10.5194/gmd-15-1269-2022, https://doi.org/10.5194/gmd-15-1269-2022, 2022
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In this study, we developed NEMO-Bohai, an ocean–ice model for the Bohai Sea, China. This study presented the scientific design and technical choices of the parameterizations for the NEMO-Bohai model. The model was calibrated and evaluated with in situ and satellite observations of ocean and sea ice. NEMO-Bohai is intended to be a valuable tool for long-term ocean and ice simulations and climate change studies.
Chao-Yuan Yang, Jiping Liu, and Dake Chen
Geosci. Model Dev., 15, 1155–1176, https://doi.org/10.5194/gmd-15-1155-2022, https://doi.org/10.5194/gmd-15-1155-2022, 2022
Short summary
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We present an improved coupled modeling system for Arctic sea ice prediction. We perform Arctic sea ice prediction experiments with improved/updated physical parameterizations, which show better skill in predicting sea ice state as well as atmospheric and oceanic state in the Arctic compared with its predecessor. The improved model also shows extended predictive skill of Arctic sea ice after the summer season. This provides an added value of this prediction system for decision-making.
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Short summary
Thawing of permafrost is governed by a complex interplay of different processes, of which only conductive heat transfer is taken into account in most model studies. We present a new land-surface scheme designed for permafrost applications, CryoGrid 3, which constitutes a flexible platform to explore new parameterizations for a range of permafrost processes.
Thawing of permafrost is governed by a complex interplay of different processes, of which only...
