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Geoscientific Model Development
An interactive open-access journal of the European Geosciences Union
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- About
- Editorial board
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IF 5.240
5.768CiteScore
8.9SNIP 1.713
SJR 3.18
index 71h5-index 51
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Volume 10, issue 8
Geosci. Model Dev., 10, 3105–3123, 2017
https://doi.org/10.5194/gmd-10-3105-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-10-3105-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
Special issue: Nucleus for European Modelling of the Ocean - NEMO
Geosci. Model Dev., 10, 3105–3123, 2017
https://doi.org/10.5194/gmd-10-3105-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-10-3105-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
Development and technical paper 22 Aug 2017
Development and technical paper | 22 Aug 2017
Sea-ice evaluation of NEMO-Nordic 1.0: a NEMO–LIM3.6-based ocean–sea-ice model setup for the North Sea and Baltic Sea
Per Pemberton et al.
Related authors
Robinson Hordoir, Lars Axell, Anders Höglund, Christian Dieterich, Filippa Fransner, Matthias Gröger, Ye Liu, Per Pemberton, Semjon Schimanke, Helen Andersson, Patrik Ljungemyr, Petter Nygren, Saeed Falahat, Adam Nord, Anette Jönsson, Iréne Lake, Kristofer Döös, Magnus Hieronymus, Heiner Dietze, Ulrike Löptien, Ivan Kuznetsov, Antti Westerlund, Laura Tuomi, and Jari Haapala
Geosci. Model Dev., 12, 363–386, https://doi.org/10.5194/gmd-12-363-2019, https://doi.org/10.5194/gmd-12-363-2019, 2019
Short summary
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Nemo-Nordic is a regional ocean model based on a community code (NEMO). It covers the Baltic and the North Sea area and is used as a forecast model by the Swedish Meteorological and Hydrological Institute. It is also used as a research tool by scientists of several countries to study, for example, the effects of climate change on the Baltic and North seas. Using such a model permits us to understand key processes in this coastal ecosystem and how such processes will change in a future climate.
Thomas Krumpen, Florent Birrien, Frank Kauker, Thomas Rackow, Luisa von Albedyll, Michael Angelopoulos, H. Jakob Belter, Vladimir Bessonov, Ellen Damm, Klaus Dethloff, Jari Haapala, Christian Haas, Carolynn Harris, Stefan Hendricks, Jens Hoelemann, Mario Hoppmann, Lars Kaleschke, Michael Karcher, Nikolai Kolabutin, Ruibo Lei, Josefine Lenz, Anne Morgenstern, Marcel Nicolaus, Uwe Nixdorf, Tomash Petrovsky, Benjamin Rabe, Lasse Rabenstein, Markus Rex, Robert Ricker, Jan Rohde, Egor Shimanchuk, Suman Singha, Vasily Smolyanitsky, Vladimir Sokolov, Tim Stanton, Anna Timofeeva, Michel Tsamados, and Daniel Watkins
The Cryosphere, 14, 2173–2187, https://doi.org/10.5194/tc-14-2173-2020, https://doi.org/10.5194/tc-14-2173-2020, 2020
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In October 2019 the research vessel Polarstern was moored to an ice floe in order to travel with it on the 1-year-long MOSAiC journey through the Arctic. Here we provide historical context of the floe's evolution and initial state for upcoming studies. We show that the ice encountered on site was exceptionally thin and was formed on the shallow Siberian shelf. The analyses presented provide the initial state for the analysis and interpretation of upcoming biogeochemical and ecological studies.
Britta Munkes, Ulrike Löptien, and Heiner Dietze
Biogeosciences Discuss., https://doi.org/10.5194/bg-2020-151, https://doi.org/10.5194/bg-2020-151, 2020
Preprint under review for BG
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Cyanobacteria blooms can strongly aggravate eutrophication problems of water bodies. Their controls are, however, not comprehensively understood which impedes effective management and protection plans. Here we review the current understanding of cyanobacteria blooms. Juxtapositioning respective field and laboratory studies with state-of-the-art mathematical models reveal substantial uncertainty associated to nutrient demands, grazing and death of cyanobacteria.
Ulrike Löptien and Heiner Dietze
Biogeosciences Discuss., https://doi.org/10.5194/bg-2020-96, https://doi.org/10.5194/bg-2020-96, 2020
Manuscript not accepted for further review
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Nitrogen fixation, conducted by specific microorganisms, makes molecular nitrogen available for marine biota. By this means this process exerts major control on the growth of algae in the ocean. This study compares two contemporary paradigms, anticipating the ecological niche of N-fixing organisms in an Earth System Model. We illustrate respective uncertainties in climate projections and suggest specific observations to advance the reliable representation of nitrogen fixation in numerical models.
Murat Gunduz, Emin Özsoy, and Robinson Hordoir
Geosci. Model Dev., 13, 121–138, https://doi.org/10.5194/gmd-13-121-2020, https://doi.org/10.5194/gmd-13-121-2020, 2020
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The Bosphorus exchange is of critical importance for hydrodynamics and hydroclimatology of the Black Sea. In this study, we report on the development of a medium-resolution circulation model of the Black Sea, making use of surface atmospheric forcing with high space and time resolution, climatic river fluxes and strait exchange, enabled by adding elementary details of strait and coastal topography and seasonal hydrology specified in an artificial box on the Marmara Sea side.
Heiner Dietze, Ulrike Löptien, and Julia Getzlaff
Geosci. Model Dev., 13, 71–97, https://doi.org/10.5194/gmd-13-71-2020, https://doi.org/10.5194/gmd-13-71-2020, 2020
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We present a new near-global coupled biogeochemical ocean-circulation model configuration of the Southern Ocean. The configuration features both a relatively equilibrated oceanic carbon inventory and an explicit representation of mesoscale eddies. In this paper, we document the model configuration and showcase its potential to tackle research questions such as the Southern Ocean carbon uptake dynamics on decadal timescales.
Filippa Fransner, Agneta Fransson, Christoph Humborg, Erik Gustafsson, Letizia Tedesco, Robinson Hordoir, and Jonas Nycander
Biogeosciences, 16, 863–879, https://doi.org/10.5194/bg-16-863-2019, https://doi.org/10.5194/bg-16-863-2019, 2019
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Although rivers carry large amounts of organic material to the oceans, little is known about what fate it meets when it reaches the sea. In this study we are investigating the fate of the carbon in this organic matter by the use of a numerical model in combination with ship measurements from the northern Baltic Sea. Our results suggests that there is substantial remineralization taking place, transforming the organic carbon into CO2, which is released to the atmosphere.
Robinson Hordoir, Lars Axell, Anders Höglund, Christian Dieterich, Filippa Fransner, Matthias Gröger, Ye Liu, Per Pemberton, Semjon Schimanke, Helen Andersson, Patrik Ljungemyr, Petter Nygren, Saeed Falahat, Adam Nord, Anette Jönsson, Iréne Lake, Kristofer Döös, Magnus Hieronymus, Heiner Dietze, Ulrike Löptien, Ivan Kuznetsov, Antti Westerlund, Laura Tuomi, and Jari Haapala
Geosci. Model Dev., 12, 363–386, https://doi.org/10.5194/gmd-12-363-2019, https://doi.org/10.5194/gmd-12-363-2019, 2019
Short summary
Short summary
Nemo-Nordic is a regional ocean model based on a community code (NEMO). It covers the Baltic and the North Sea area and is used as a forecast model by the Swedish Meteorological and Hydrological Institute. It is also used as a research tool by scientists of several countries to study, for example, the effects of climate change on the Baltic and North seas. Using such a model permits us to understand key processes in this coastal ecosystem and how such processes will change in a future climate.
Iina Ronkainen, Jonni Lehtiranta, Mikko Lensu, Eero Rinne, Jari Haapala, and Christian Haas
The Cryosphere, 12, 3459–3476, https://doi.org/10.5194/tc-12-3459-2018, https://doi.org/10.5194/tc-12-3459-2018, 2018
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We quantify the sea ice thickness variability in the Bay of Bothnia using various observational data sets. For the first time we use helicopter and shipborne electromagnetic soundings to study changes in drift ice of the Bay of Bothnia. Our results show that the interannual variability of ice thickness is larger in the drift ice zone than in the fast ice zone. Furthermore, the mean thickness of heavily ridged ice near the coast can be several times larger than that of fast ice.
Volkmar Sauerland, Ulrike Löptien, Claudine Leonhard, Andreas Oschlies, and Anand Srivastav
Geosci. Model Dev., 11, 1181–1198, https://doi.org/10.5194/gmd-11-1181-2018, https://doi.org/10.5194/gmd-11-1181-2018, 2018
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We present a concept to prove that a parametric model is well calibrated, i.e., that changes of its free parameters cannot lead to a much better model–data misfit anymore. The intention is motivated by the fact that calibrating global biogeochemical ocean models is important for assessment and inter-model comparison but computationally expensive.
Sofia Saraiva, H. E. Markus Meier, Helén Andersson, Anders Höglund, Christian Dieterich, Robinson Hordoir, and Kari Eilola
Earth Syst. Dynam. Discuss., https://doi.org/10.5194/esd-2018-16, https://doi.org/10.5194/esd-2018-16, 2018
Revised manuscript not accepted
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Uncertainties are estimated in Baltic Sea climate projections by performing scenarios combining 4 Global Climate Models, 2 future gas emissions (RCP4.5, RCP8.5) and 3 nutrient load scenarios. Results on primary production, nitrogen fixation, and hypoxic areas show that uncertainties caused by the nutrients loads are greater than uncertainties due to GCMs and RCPs. In all scenarios, nutrient load abatement strategy, Baltic Sea Action Plan, will lead to an improvement in the environmental state.
Markus Schartau, Philip Wallhead, John Hemmings, Ulrike Löptien, Iris Kriest, Shubham Krishna, Ben A. Ward, Thomas Slawig, and Andreas Oschlies
Biogeosciences, 14, 1647–1701, https://doi.org/10.5194/bg-14-1647-2017, https://doi.org/10.5194/bg-14-1647-2017, 2017
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Plankton models have become an integral part in marine ecosystem and biogeochemical research. These models differ in complexity and in their number of parameters. How values are assigned to parameters is essential. An overview of major methodologies of parameter estimation is provided. Aspects of parameter identification in the literature are diverse. Individual findings could be better synthesized if notation and expertise of the different scientific communities would be reasonably merged.
Heiner Dietze, Julia Getzlaff, and Ulrike Löptien
Biogeosciences, 14, 1561–1576, https://doi.org/10.5194/bg-14-1561-2017, https://doi.org/10.5194/bg-14-1561-2017, 2017
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The Southern Ocean is a sink for anthropogenic carbon. Projections of how this sink will evolve in an ever-warming climate are based on coupled ocean-circulation–biogeochemical models. This study compares uncertainties of simulated oceanic carbon uptake associated to physical (eddy) parameterizations with those associated wtih (unconstrained) supply of bioavailable iron supply to the surface ocean.
Heiner Dietze and Ulrike Löptien
Ocean Sci., 12, 977–986, https://doi.org/10.5194/os-12-977-2016, https://doi.org/10.5194/os-12-977-2016, 2016
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Winds blowing over the ocean drive ocean currents. The oceanic response to winds is, in turn, influenced by ocean currents. Theoretical considerations suggest that the latter effect is especially pronounced in the Baltic Sea. The study presented here puts theses theoretical considerations in a high-resolution ocean circulation model of the Baltic Sea to the test.
U. Löptien and H. Dietze
Ocean Sci., 11, 573–590, https://doi.org/10.5194/os-11-573-2015, https://doi.org/10.5194/os-11-573-2015, 2015
Short summary
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Marine biogeochemical ocean models are embedded into earth system models - which are, to an increasing degree, applied to project the fate of our warming world. These biogeochemical models generally depend on poorly constrained model parameters. In this study we investigate the the demands on observations for an objective estimation of such parameters. A major result is that even modest noise (10%) inherent to observations can hinder the assignment of reasonable parameters.
U. Löptien and L. Axell
The Cryosphere, 8, 2409–2418, https://doi.org/10.5194/tc-8-2409-2014, https://doi.org/10.5194/tc-8-2409-2014, 2014
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The Baltic Sea is a seasonally ice-covered marginal sea in central northern Europe. In wintertime, on-time shipping depends crucially on sea ice forecasts. Among the forecasting tools heavily applied are numerical models, which suffer from a lack of calibration data because relevant ice properties are difficult (and costly) to monitor. We developed an innovative and inexpensive approach, by using ship speed observations obtained by the automatic identification system (AIS) to asses such models.
U. Löptien and H. Dietze
Earth Syst. Sci. Data, 6, 367–374, https://doi.org/10.5194/essd-6-367-2014, https://doi.org/10.5194/essd-6-367-2014, 2014
H. Dietze, U. Löptien, and K. Getzlaff
Geosci. Model Dev., 7, 1713–1731, https://doi.org/10.5194/gmd-7-1713-2014, https://doi.org/10.5194/gmd-7-1713-2014, 2014
Related subject area
Cryosphere
Description and validation of the ice-sheet model Yelmo (version 1.0)
Evaluating integrated surface/subsurface permafrost thermal hydrology models in ATS (v0.88) against observations from a polygonal tundra site
SICOPOLIS-AD v1: an open-source adjoint modeling framework for ice sheet simulation enabled by the algorithmic differentiation tool OpenAD
On the calculation of normalized viscous–plastic sea ice stresses
Modelling thermomechanical ice deformation using an implicit pseudo-transient method (FastICE v1.0) based on graphical processing units (GPUs)
Version 1 of a sea ice module for the physics-based, detailed, multi-layer SNOWPACK model
A module to convert spectral to narrowband snow albedo for use in climate models: SNOWBAL v1.2
Simulating the Early Holocene demise of the Laurentide Ice Sheet with BISICLES (public trunk revision 3298)
On the discretization of the ice thickness distribution in the NEMO3.6-LIM3 global ocean–sea ice model
Scientific workflows applied to the coupling of a continuum (Elmer v8.3) and a discrete element (HiDEM v1.0) ice dynamic model
A rapidly converging initialisation method to simulate the present-day Greenland ice sheet using the GRISLI ice sheet model (version 1.3)
Assessment of sub-shelf melting parameterisations using the ocean–ice-sheet coupled model NEMO(v3.6)–Elmer/Ice(v8.3)
CSIB v1 (Canadian Sea-ice Biogeochemistry): a sea-ice biogeochemical model for the NEMO community ocean modelling framework
LIVVkit 2.1: automated and extensible ice sheet model validation
ATAT 1.1, the Automated Timing Accordance Tool for comparing ice-sheet model output with geochronological data
The Open Global Glacier Model (OGGM) v1.1
Description and evaluation of the Community Ice Sheet Model (CISM) v2.1
Implementation and performance of adaptive mesh refinement in the Ice Sheet System Model (ISSM v4.14)
A continuum model (PSUMEL1) of ice mélange and its role during retreat of the Antarctic Ice Sheet
ESM-SnowMIP: assessing snow models and quantifying snow-related climate feedbacks
The GRISLI ice sheet model (version 2.0): calibration and validation for multi-millennial changes of the Antarctic ice sheet
CVPM 1.1: a flexible heat-transfer modeling system for permafrost
Dynamically coupling full Stokes and shallow shelf approximation for marine ice sheet flow using Elmer/Ice (v8.3)
The NASA Eulerian Snow on Sea Ice Model (NESOSIM) v1.0: initial model development and analysis
MPAS-Albany Land Ice (MALI): a variable-resolution ice sheet model for Earth system modeling using Voronoi grids
BrAHMs V1.0: a fast, physically based subglacial hydrology model for continental-scale application
SHAKTI: Subglacial Hydrology and Kinetic, Transient Interactions v1.0
SMRT: an active–passive microwave radiative transfer model for snow with multiple microstructure and scattering formulations (v1.0)
PIC v1.3: comprehensive R package for computing permafrost indices with daily weather observations and atmospheric forcing over the Qinghai–Tibet Plateau
Numerical experiments on vapor diffusion in polar snow and firn and its impact on isotopes using the multi-layer energy balance model Crocus in SURFEX v8.0
Implementation of higher-order vertical finite elements in ISSM v4.13 for improved ice sheet flow modeling over paleoclimate timescales
Intercomparison of Antarctic ice-shelf, ocean, and sea-ice interactions simulated by MetROMS-iceshelf and FESOM 1.4
The sea ice model component of HadGEM3-GC3.1
A JavaScript API for the Ice Sheet System Model (ISSM) 4.11: towards an online interactive model for the cryosphere community
Implementation of a physically based water percolation routine in the Crocus/SURFEX (V7.3) snowpack model
Evaluating the performance of coupled snow–soil models in SURFEXv8 to simulate the permafrost thermal regime at a high Arctic site
A vertical representation of soil carbon in the JULES land surface scheme (vn4.3_permafrost) with a focus on permafrost regions
An ice sheet model validation framework for the Greenland ice sheet
Optimal numerical solvers for transient simulations of ice flow using the Ice Sheet System Model (ISSM versions 4.2.5 and 4.11)
An approach to computing discrete adjoints for MPI-parallelized models applied to Ice Sheet System Model 4.11
The CMIP6 Sea-Ice Model Intercomparison Project (SIMIP): understanding sea ice through climate-model simulations
Comparison of adjoint and nudging methods to initialise ice sheet model basal conditions
Experimental design for three interrelated marine ice sheet and ocean model intercomparison projects: MISMIP v. 3 (MISMIP +), ISOMIP v. 2 (ISOMIP +) and MISOMIP v. 1 (MISOMIP1)
Performance and applicability of a 2.5-D ice-flow model in the vicinity of a dome
An optimized treatment for algorithmic differentiation of an important glaciological fixed-point problem
Large ensemble modeling of the last deglacial retreat of the West Antarctic Ice Sheet: comparison of simple and advanced statistical techniques
ICESHEET 1.0: a program to produce paleo-ice sheet reconstructions with minimal assumptions
Discrete-Element bonded-particle Sea Ice model DESIgn, version 1.3a – model description and implementation
The location of the thermodynamic atmosphere–ice interface in fully coupled models – a case study using JULES and CICE
Simulating the thermal regime and thaw processes of ice-rich permafrost ground with the land-surface model CryoGrid 3
Alexander Robinson, Jorge Alvarez-Solas, Marisa Montoya, Heiko Goelzer, Ralf Greve, and Catherine Ritz
Geosci. Model Dev., 13, 2805–2823, https://doi.org/10.5194/gmd-13-2805-2020, https://doi.org/10.5194/gmd-13-2805-2020, 2020
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Here we describe Yelmo v1.0, an intuitive and state-of-the-art hybrid ice sheet model. The model design and physics are described, and benchmark simulations are provided to validate its performance. Yelmo is a versatile ice sheet model that can be applied to a wide variety of problems.
Ahmad Jan, Ethan T. Coon, and Scott L. Painter
Geosci. Model Dev., 13, 2259–2276, https://doi.org/10.5194/gmd-13-2259-2020, https://doi.org/10.5194/gmd-13-2259-2020, 2020
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Computer simulations are important tools for understanding the response of Arctic permafrost to a warming climate. To build confidence in an emerging class of permafrost simulators, we evaluated the Advanced Terrestrial Simulator against field observations from a frozen tundra site near Utqiaġvik (formerly Barrow), Alaska. The 3-year simulations agree well with observations of snow depth, summer water table, soil temperature at multiple locations, and spatially averaged evaporation.
Liz C. Logan, Sri Hari Krishna Narayanan, Ralf Greve, and Patrick Heimbach
Geosci. Model Dev., 13, 1845–1864, https://doi.org/10.5194/gmd-13-1845-2020, https://doi.org/10.5194/gmd-13-1845-2020, 2020
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A new capability has been developed for the ice sheet model SICOPOLIS (SImulation COde for POLythermal Ice Sheets) that enables the generation of derivative code, such as tangent linear or adjoint models, by means of algorithmic differentiation. It relies on the source transformation algorithmic (AD) differentiation tool OpenAD. The reverse mode of AD provides the adjoint model, SICOPOLIS-AD, which may be applied for comprehensive sensitivity analyses as well as gradient-based optimization.
Jean-François Lemieux and Frédéric Dupont
Geosci. Model Dev., 13, 1763–1769, https://doi.org/10.5194/gmd-13-1763-2020, https://doi.org/10.5194/gmd-13-1763-2020, 2020
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Sea ice dynamics plays an important role in shaping the sea cover in polar regions. Winds and ocean currents exert large stresses on the sea ice cover. This can lead to the formation of long cracks and ridges, which strongly impact the exchange of heat, momentum and moisture between the atmosphere and the ocean. It is therefore crucial for a sea ice model to be able to represent these features. This article describes how internal sea ice stresses should be diagnosed from model simulations.
Ludovic Räss, Aleksandar Licul, Frédéric Herman, Yury Y. Podladchikov, and Jenny Suckale
Geosci. Model Dev., 13, 955–976, https://doi.org/10.5194/gmd-13-955-2020, https://doi.org/10.5194/gmd-13-955-2020, 2020
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Accurate predictions of future sea level rise require numerical models that predict rapidly deforming ice. Localised ice deformation can be captured numerically only with high temporal and spatial resolution. This paper’s goal is to propose a parallel FastICE solver for modelling ice deformation. Our model is particularly useful for improving our process-based understanding of localised ice deformation. Our solver reaches a parallel efficiency of 99 % on GPU-based supercomputers.
Nander Wever, Leonard Rossmann, Nina Maaß, Katherine C. Leonard, Lars Kaleschke, Marcel Nicolaus, and Michael Lehning
Geosci. Model Dev., 13, 99–119, https://doi.org/10.5194/gmd-13-99-2020, https://doi.org/10.5194/gmd-13-99-2020, 2020
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Sea ice is an important component of the global climate system. The presence of a snow layer covering sea ice can impact ice mass and energy budgets. The detailed, physics-based, multi-layer snow model SNOWPACK was modified to simulate the snow–sea-ice system, providing simulations of the snow microstructure, water percolation and flooding, and superimposed ice formation. The model is applied to in situ measurements from snow and ice mass-balance buoys installed in the Antarctic Weddell Sea.
Christiaan T. van Dalum, Willem Jan van de Berg, Quentin Libois, Ghislain Picard, and Michiel R. van den Broeke
Geosci. Model Dev., 12, 5157–5175, https://doi.org/10.5194/gmd-12-5157-2019, https://doi.org/10.5194/gmd-12-5157-2019, 2019
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Climate models are often limited to relatively simple snow albedo schemes. Therefore, we have developed the SNOWBAL module to couple a climate model with a physically based wavelength dependent snow albedo model. Using SNOWBAL v1.2 to couple the snow albedo model TARTES with the regional climate model RACMO2 indicates a potential performance gain for the Greenland ice sheet.
Ilkka S. O. Matero, Lauren J. Gregoire, and Ruza F. Ivanovic
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2019-304, https://doi.org/10.5194/gmd-2019-304, 2019
Revised manuscript accepted for GMD
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Eight thousand years ago, the N. hemisphere cooled by several degrees for a century, due to the collapse of an ice sheet in N. America that released large amounts of meltwater to the North Atlantic and slowed down its circulation. We numerically model the ice sheet to understand its evolution during this event. Our results match data thanks to good ice dynamics, but depend mostly on surface melt and snowfall. Further work will help us understand how past and future ice melt affects climate.
François Massonnet, Antoine Barthélemy, Koffi Worou, Thierry Fichefet, Martin Vancoppenolle, Clément Rousset, and Eduardo Moreno-Chamarro
Geosci. Model Dev., 12, 3745–3758, https://doi.org/10.5194/gmd-12-3745-2019, https://doi.org/10.5194/gmd-12-3745-2019, 2019
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Sea ice thickness varies considerably on spatial scales of several meters. However, contemporary climate models cannot resolve such scales yet. This is why sea ice models used in climate models include an ice thickness distribution (ITD) to account for this unresolved variability. Here, we explore with the ocean–sea ice model NEMO3.6-LIM3 the sensitivity of simulated mean Arctic and Antarctic sea ice states to the way the ITD is discretized.
Shahbaz Memon, Dorothée Vallot, Thomas Zwinger, Jan Åström, Helmut Neukirchen, Morris Riedel, and Matthias Book
Geosci. Model Dev., 12, 3001–3015, https://doi.org/10.5194/gmd-12-3001-2019, https://doi.org/10.5194/gmd-12-3001-2019, 2019
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Scientific workflows enable complex scientific computational scenarios, which include data intensive scenarios, parametric executions, and interactive simulations. In this article, we applied the UNICORE workflow management system to automate a formerly hard-coded coupling of a glacier flow model and a calving model, which contain many tasks and dependencies, ranging from pre-processing and data management to repetitive executions on heterogeneous high-performance computing (HPC) resources.
Sébastien Le clec'h, Aurélien Quiquet, Sylvie Charbit, Christophe Dumas, Masa Kageyama, and Catherine Ritz
Geosci. Model Dev., 12, 2481–2499, https://doi.org/10.5194/gmd-12-2481-2019, https://doi.org/10.5194/gmd-12-2481-2019, 2019
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To provide reliable projections of the ice-sheet contribution to future sea-level rise, ice sheet models must be able to simulate the observed ice sheet present-day state. Using a low computational iterative minimisation procedure, based on the adjustment of the basal drag coefficient, we rapidly minimise the errors between the simulated and the observed Greenland ice thickness and ice velocity, and we succeed in stabilising the simulated Greenland ice sheet state under present-day conditions.
Lionel Favier, Nicolas C. Jourdain, Adrian Jenkins, Nacho Merino, Gaël Durand, Olivier Gagliardini, Fabien Gillet-Chaulet, and Pierre Mathiot
Geosci. Model Dev., 12, 2255–2283, https://doi.org/10.5194/gmd-12-2255-2019, https://doi.org/10.5194/gmd-12-2255-2019, 2019
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The melting at the base of floating ice shelves is the main driver of the Antarctic ice sheet current retreat. Here, we use an ideal set-up to assess a wide range of melting parameterisations depending on oceanic properties with regard to a new ocean–ice-sheet coupled model, published here for the first time. A parameterisation that depends quadratically on thermal forcing in both a local and a non-local way yields the best results and needs to be further assessed with more realistic set-ups.
Hakase Hayashida, James R. Christian, Amber M. Holdsworth, Xianmin Hu, Adam H. Monahan, Eric Mortenson, Paul G. Myers, Olivier G. J. Riche, Tessa Sou, and Nadja S. Steiner
Geosci. Model Dev., 12, 1965–1990, https://doi.org/10.5194/gmd-12-1965-2019, https://doi.org/10.5194/gmd-12-1965-2019, 2019
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Ice algae, the primary producer in sea ice, play a fundamental role in shaping marine ecosystems and biogeochemical cycling of key elements in polar regions. In this study, we developed a process-based numerical model component representing sea-ice biogeochemistry for a sea ice–ocean coupled general circulation model. The model developed can be used to simulate the projected changes in sea-ice ecosystems and biogeochemistry in response to on-going rapid decline of the Arctic.
Katherine J. Evans, Joseph H. Kennedy, Dan Lu, Mary M. Forrester, Stephen Price, Jeremy Fyke, Andrew R. Bennett, Matthew J. Hoffman, Irina Tezaur, Charles S. Zender, and Miren Vizcaíno
Geosci. Model Dev., 12, 1067–1086, https://doi.org/10.5194/gmd-12-1067-2019, https://doi.org/10.5194/gmd-12-1067-2019, 2019
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A robust validation of ice sheet models is presented using LIVVkit, version 2.1. It targets ice sheet and coupled Earth system models, and handles datasets and operations that require high-performance computing and storage. We apply LIVVkit to a Greenland ice sheet simulation to show the degree to which it captures the surface mass balance. LIVVkit identifies a positive bias due to insufficient melting compared to observations that is focused largely around Greenland's southwest region.
Jeremy C. Ely, Chris D. Clark, David Small, and Richard C. A. Hindmarsh
Geosci. Model Dev., 12, 933–953, https://doi.org/10.5194/gmd-12-933-2019, https://doi.org/10.5194/gmd-12-933-2019, 2019
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During the last 2.6 million years, the Earth's climate has cycled between cold glacials and warm interglacials, causing the growth and retreat of ice sheets. These ice sheets can be independently reconstructed using numerical models or from dated evidence that they leave behind (e.g. sediments, boulders). Here, we present a tool for comparing numerical model simulations with dated ice-sheet material. We demonstrate the utility of this tool by applying it to the last British–Irish ice sheet.
Fabien Maussion, Anton Butenko, Nicolas Champollion, Matthias Dusch, Julia Eis, Kévin Fourteau, Philipp Gregor, Alexander H. Jarosch, Johannes Landmann, Felix Oesterle, Beatriz Recinos, Timo Rothenpieler, Anouk Vlug, Christian T. Wild, and Ben Marzeion
Geosci. Model Dev., 12, 909–931, https://doi.org/10.5194/gmd-12-909-2019, https://doi.org/10.5194/gmd-12-909-2019, 2019
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Mountain glaciers are one of the few remaining subsystems of the global climate system for which no globally applicable community-driven model exists. Here we present the Open Global Glacier Model (OGGM; www.oggm.org), developed to provide a modular and open-source numerical model framework for simulating past and future change of any glacier in the world.
William H. Lipscomb, Stephen F. Price, Matthew J. Hoffman, Gunter R. Leguy, Andrew R. Bennett, Sarah L. Bradley, Katherine J. Evans, Jeremy G. Fyke, Joseph H. Kennedy, Mauro Perego, Douglas M. Ranken, William J. Sacks, Andrew G. Salinger, Lauren J. Vargo, and Patrick H. Worley
Geosci. Model Dev., 12, 387–424, https://doi.org/10.5194/gmd-12-387-2019, https://doi.org/10.5194/gmd-12-387-2019, 2019
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This paper describes the Community Ice Sheet Model (CISM) version 2.1. CISM solves equations for ice flow, heat conduction, surface melting, and other processes such as basal sliding and iceberg calving. It can be used for ice-sheet-only simulations or as the ice sheet component of the Community Earth System Model. Model solutions have been verified for standard test problems. CISM can efficiently simulate the whole Greenland ice sheet, with results that are broadly consistent with observations.
Thiago Dias dos Santos, Mathieu Morlighem, Hélène Seroussi, Philippe Remy Bernard Devloo, and Jefferson Cardia Simões
Geosci. Model Dev., 12, 215–232, https://doi.org/10.5194/gmd-12-215-2019, https://doi.org/10.5194/gmd-12-215-2019, 2019
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The reduction of numerical errors in ice sheet modeling increases the results' accuracy reliability. We improve numerical accuracy by better capturing grounding line dynamics, while maintaining a low computational cost. We implement an adaptive mesh refinement (AMR) technique in the Ice Sheet System Model and compare AMR simulations with uniformly refined meshes. Our results show that the computational time with AMR is significantly shorter than for uniformly refined meshes for a given accuracy.
David Pollard, Robert M. DeConto, and Richard B. Alley
Geosci. Model Dev., 11, 5149–5172, https://doi.org/10.5194/gmd-11-5149-2018, https://doi.org/10.5194/gmd-11-5149-2018, 2018
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Around the margins of ice sheets in contact with the ocean, calving of icebergs can generate large amounts of floating ice debris called "mélange". In major Greenland fjords, mélange significantly slows down ice flow from upstream. Our study applies numerical models to past and possible future episodes of rapid Antarctic Ice Sheet retreat. We find that, due to larger spatial scales, Antarctic mélange does not significantly impede flow or slow ice retreat and associated sea level rise.
Gerhard Krinner, Chris Derksen, Richard Essery, Mark Flanner, Stefan Hagemann, Martyn Clark, Alex Hall, Helmut Rott, Claire Brutel-Vuilmet, Hyungjun Kim, Cécile B. Ménard, Lawrence Mudryk, Chad Thackeray, Libo Wang, Gabriele Arduini, Gianpaolo Balsamo, Paul Bartlett, Julia Boike, Aaron Boone, Frédérique Chéruy, Jeanne Colin, Matthias Cuntz, Yongjiu Dai, Bertrand Decharme, Jeff Derry, Agnès Ducharne, Emanuel Dutra, Xing Fang, Charles Fierz, Josephine Ghattas, Yeugeniy Gusev, Vanessa Haverd, Anna Kontu, Matthieu Lafaysse, Rachel Law, Dave Lawrence, Weiping Li, Thomas Marke, Danny Marks, Martin Ménégoz, Olga Nasonova, Tomoko Nitta, Masashi Niwano, John Pomeroy, Mark S. Raleigh, Gerd Schaedler, Vladimir Semenov, Tanya G. Smirnova, Tobias Stacke, Ulrich Strasser, Sean Svenson, Dmitry Turkov, Tao Wang, Nander Wever, Hua Yuan, Wenyan Zhou, and Dan Zhu
Geosci. Model Dev., 11, 5027–5049, https://doi.org/10.5194/gmd-11-5027-2018, https://doi.org/10.5194/gmd-11-5027-2018, 2018
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This paper provides an overview of a coordinated international experiment to determine the strengths and weaknesses in how climate models treat snow. The models will be assessed at point locations using high-quality reference measurements and globally using satellite-derived datasets. How well climate models simulate snow-related processes is important because changing snow cover is an important part of the global climate system and provides an important freshwater resource for human use.
Aurélien Quiquet, Christophe Dumas, Catherine Ritz, Vincent Peyaud, and Didier M. Roche
Geosci. Model Dev., 11, 5003–5025, https://doi.org/10.5194/gmd-11-5003-2018, https://doi.org/10.5194/gmd-11-5003-2018, 2018
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This paper presents the GRISLI (Grenoble ice sheet and land ice) model in its newest revision. We present the recent model improvements from its original version (Ritz et al., 2001), together with a discussion of the model performance in reproducing the present-day Antarctic ice sheet geometry and the grounding line advances and retreats during the last 400 000 years. We show that GRISLI is a computationally cheap model, able to reproduce the large-scale behaviour of ice sheets.
Gary D. Clow
Geosci. Model Dev., 11, 4889–4908, https://doi.org/10.5194/gmd-11-4889-2018, https://doi.org/10.5194/gmd-11-4889-2018, 2018
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CVPM is a modular heat-transfer modeling system designed for scientific and engineering studies in permafrost terrain, and as an educational tool. CVPM implements the heat-transfer equations in both Cartesian and cylindrical coordinates. To accommodate a diversity of geologic settings, a variety of materials can be specified within the model domain. CVPM can be used over a broad range of depth, temperature, porosity, water saturation, and solute conditions on either Earth or Mars.
Eef C. H. van Dongen, Nina Kirchner, Martin B. van Gijzen, Roderik S. W. van de Wal, Thomas Zwinger, Gong Cheng, Per Lötstedt, and Lina von Sydow
Geosci. Model Dev., 11, 4563–4576, https://doi.org/10.5194/gmd-11-4563-2018, https://doi.org/10.5194/gmd-11-4563-2018, 2018
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Ice flow forced by gravity is governed by the full Stokes (FS) equations, which are computationally expensive to solve. Therefore, approximations to the FS equations are used, especially when modeling an ice sheet on long time spans. Here, we report a combination of an approximation with the FS equations that allows simulating the dynamics of ice sheets over long time spans without introducing artifacts caused by application of approximations in parts of the domain where they are not valid.
Alek A. Petty, Melinda Webster, Linette Boisvert, and Thorsten Markus
Geosci. Model Dev., 11, 4577–4602, https://doi.org/10.5194/gmd-11-4577-2018, https://doi.org/10.5194/gmd-11-4577-2018, 2018
Matthew J. Hoffman, Mauro Perego, Stephen F. Price, William H. Lipscomb, Tong Zhang, Douglas Jacobsen, Irina Tezaur, Andrew G. Salinger, Raymond Tuminaro, and Luca Bertagna
Geosci. Model Dev., 11, 3747–3780, https://doi.org/10.5194/gmd-11-3747-2018, https://doi.org/10.5194/gmd-11-3747-2018, 2018
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MPAS-Albany Land Ice (MALI) is a new variable-resolution land ice model that uses unstructured grids on a plane or sphere. MALI is built for Earth system modeling on high-performance computing platforms using existing software libraries. MALI simulates the evolution of ice thickness, velocity, and temperature, and it includes schemes for simulating iceberg calving and the flow of water beneath ice sheets and its effect on ice sliding. The model is demonstrated for the Antarctic ice sheet.
Mark Kavanagh and Lev Tarasov
Geosci. Model Dev., 11, 3497–3513, https://doi.org/10.5194/gmd-11-3497-2018, https://doi.org/10.5194/gmd-11-3497-2018, 2018
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We present and validate BrAHMs (BAsal Hydrology Model): a new
physically based basal hydrology model, which captures the two main
types of subglacial drainage systems (high-pressure distributed systems and
low-pressure channelized systems). BrAHMs is designed for continental
glacial cycle scale contexts, for which computational speed is
essential. This speed is accomplished, in part, by numerical methods
novel to basal hydrology contexts.
Aleah Sommers, Harihar Rajaram, and Mathieu Morlighem
Geosci. Model Dev., 11, 2955–2974, https://doi.org/10.5194/gmd-11-2955-2018, https://doi.org/10.5194/gmd-11-2955-2018, 2018
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Meltwater drainage beneath glaciers and ice sheets influences how fast they move and is complicated and constantly changing. Most models distinguish between
fastand
slowdrainage with different equations for each system. The SHAKTI model allows for the ice–water drainage arrangement to transition naturally between different types of flow. This model can be used to understand how drainage affects glacier speeds and the associated ice loss to further inform predictions of sea level rise.
Ghislain Picard, Melody Sandells, and Henning Löwe
Geosci. Model Dev., 11, 2763–2788, https://doi.org/10.5194/gmd-11-2763-2018, https://doi.org/10.5194/gmd-11-2763-2018, 2018
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The Snow Microwave Radiative Transfer (SMRT) is a novel model developed to calculate how microwaves are scattered and emitted by snow. The model is built from separate, interconnecting modules to make it easy to compare different aspects of the theory. SMRT is the first model to allow a choice of how to represent the microstructure of the snow, which is extremely important, and has been used to unite multiple previous studies. This model will ultimately be used to observe snow from space.
Lihui Luo, Zhongqiong Zhang, Wei Ma, Shuhua Yi, and Yanli Zhuang
Geosci. Model Dev., 11, 2475–2491, https://doi.org/10.5194/gmd-11-2475-2018, https://doi.org/10.5194/gmd-11-2475-2018, 2018
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Based on the current situation of permafrost modeling in the Qinghai–Tibet Plateau (QTP), a software PIC was developed to evaluate the temporal–spatial change trends of permafrost, which allows us to automatically compute permafrost indices with daily weather and atmospheric forcing datasets. The main features include computing, visualization, and statistics. The software will serve engineering applications and can be used to assess the impact of climate change on permafrost over the QTP.
Alexandra Touzeau, Amaëlle Landais, Samuel Morin, Laurent Arnaud, and Ghislain Picard
Geosci. Model Dev., 11, 2393–2418, https://doi.org/10.5194/gmd-11-2393-2018, https://doi.org/10.5194/gmd-11-2393-2018, 2018
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We introduced a new module of water vapor diffusion into the snowpack model Crocus. Vapor transport locally modifies the density of snow layers, possibly influencing compaction. It also affects the original isotopic signature of snow layers. We also introduced water isotopes (𝛿18O) in the model. Over 10 years, the modeled attenuation of isotopic variations due to vapor diffusion is 7–18 % lower than the observations. Thus, other processes are required to explain the total attenuation.
Joshua K. Cuzzone, Mathieu Morlighem, Eric Larour, Nicole Schlegel, and Helene Seroussi
Geosci. Model Dev., 11, 1683–1694, https://doi.org/10.5194/gmd-11-1683-2018, https://doi.org/10.5194/gmd-11-1683-2018, 2018
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This paper details the implementation of higher-order vertical finite elements in the Ice Sheet System Model (ISSM). When using higher-order vertical finite elements, fewer vertical layers are needed to accurately capture the thermal structure in an ice sheet versus a conventional linear vertical interpolation, therefore greatly improving model runtime speeds, particularly in higher-order stress balance ice sheet models. The implications for paleoclimate ice sheet simulations are discussed.
Kaitlin A. Naughten, Katrin J. Meissner, Benjamin K. Galton-Fenzi, Matthew H. England, Ralph Timmermann, Hartmut H. Hellmer, Tore Hattermann, and Jens B. Debernard
Geosci. Model Dev., 11, 1257–1292, https://doi.org/10.5194/gmd-11-1257-2018, https://doi.org/10.5194/gmd-11-1257-2018, 2018
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MetROMS and FESOM are two ocean/sea-ice models which resolve Antarctic ice-shelf cavities and consider thermodynamics at the ice-shelf base. We simulate the period 1992–2016 with both models, and with two options for resolution in FESOM, and compare output from the three simulations. Ice-shelf melt rates, sub-ice-shelf circulation, continental shelf water masses, and sea-ice processes are compared and evaluated against available observations.
Jeff K. Ridley, Edward W. Blockley, Ann B. Keen, Jamie G. L. Rae, Alex E. West, and David Schroeder
Geosci. Model Dev., 11, 713–723, https://doi.org/10.5194/gmd-11-713-2018, https://doi.org/10.5194/gmd-11-713-2018, 2018
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The sea ice component of the Met Office coupled climate model, HadGEM3-GC3.1, is presented and evaluated. We determine that the mean state of the sea ice is well reproduced for the Arctic; however, a warm sea surface temperature bias over the Southern Ocean results in a low Antarctic sea ice cover.
Eric Larour, Daniel Cheng, Gilberto Perez, Justin Quinn, Mathieu Morlighem, Bao Duong, Lan Nguyen, Kit Petrie, Silva Harounian, Daria Halkides, and Wayne Hayes
Geosci. Model Dev., 10, 4393–4403, https://doi.org/10.5194/gmd-10-4393-2017, https://doi.org/10.5194/gmd-10-4393-2017, 2017
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This work presents a new way of carrying out simulations using the C++ based Ice Sheet System Model (ISSM) within a web page. This allows for a new generation of websites that can rely on the entire code of a climate model, without compromising or simplifying the physics implemented in such a model. We believe this approach will enable better education/outreach websites as well as improve access to complex climate models without compromising their integrity.
Christopher J. L. D'Amboise, Karsten Müller, Laurent Oxarango, Samuel Morin, and Thomas V. Schuler
Geosci. Model Dev., 10, 3547–3566, https://doi.org/10.5194/gmd-10-3547-2017, https://doi.org/10.5194/gmd-10-3547-2017, 2017
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We present a new water percolation routine added to the Crocus model. The new routine is physically based, describing motion of water through a layered snowpack considering capillary-driven and gravity flow. We tested the routine on two data sets. Wet-snow layers were able to reach higher saturations than the empirical routine. Meaningful applicability is limited until new and better parameterizations of water retention are developed, and feedbacks are adjusted to handle higher saturations.
Mathieu Barrere, Florent Domine, Bertrand Decharme, Samuel Morin, Vincent Vionnet, and Matthieu Lafaysse
Geosci. Model Dev., 10, 3461–3479, https://doi.org/10.5194/gmd-10-3461-2017, https://doi.org/10.5194/gmd-10-3461-2017, 2017
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Global warming projections still suffer from a limited representation of the permafrost–carbon feedback. This study assesses the capacity of snow-soil coupled models to simulate the permafrost thermal regime at Bylot Island, a high Arctic site. Significant flaws are found in the description of Arctic snow properties, resulting in erroneous heat transfers between the soil and the snow in simulations. Improved snow schemes are needed to accurately predict the future of permafrost.
Eleanor J. Burke, Sarah E. Chadburn, and Altug Ekici
Geosci. Model Dev., 10, 959–975, https://doi.org/10.5194/gmd-10-959-2017, https://doi.org/10.5194/gmd-10-959-2017, 2017
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There is a large amount of relatively inert organic carbon locked into permafrost soils. In a warming climate the permafrost will thaw and this organic carbon will become vulnerable to decomposition. This process is not typically included within Earth system models (ESMs). This paper describes the development of a vertically resolved soil organic carbon decomposition model which, in the future, can be included within the UKESM to quantify the response of the climate to permafrost carbon loss.
Stephen F. Price, Matthew J. Hoffman, Jennifer A. Bonin, Ian M. Howat, Thomas Neumann, Jack Saba, Irina Tezaur, Jeffrey Guerber, Don P. Chambers, Katherine J. Evans, Joseph H. Kennedy, Jan Lenaerts, William H. Lipscomb, Mauro Perego, Andrew G. Salinger, Raymond S. Tuminaro, Michiel R. van den Broeke, and Sophie M. J. Nowicki
Geosci. Model Dev., 10, 255–270, https://doi.org/10.5194/gmd-10-255-2017, https://doi.org/10.5194/gmd-10-255-2017, 2017
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We introduce the Cryospheric Model Comparison Tool (CmCt) and propose qualitative and quantitative metrics for evaluating ice sheet model simulations against observations. Greenland simulations using the Community Ice Sheet Model are compared to gravimetry and altimetry observations from 2003 to 2013. We show that the CmCt can be used to score simulations of increasing complexity relative to observations of dynamic change in Greenland over the past decade.
Feras Habbal, Eric Larour, Mathieu Morlighem, Helene Seroussi, Christopher P. Borstad, and Eric Rignot
Geosci. Model Dev., 10, 155–168, https://doi.org/10.5194/gmd-10-155-2017, https://doi.org/10.5194/gmd-10-155-2017, 2017
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This work presents the results from testing a suite of numerical solvers on a standard ice sheet benchmark test. We note the relevance of this test to practical simulations and identify the fastest solvers for the transient simulation. The highlighted solvers show significant speed-ups in relation to the default solver (~1.5–100 times faster) and enable a new capability for solving massive, high-resolution models that are critical for improving projections of ice sheets and sea-level change.
Eric Larour, Jean Utke, Anton Bovin, Mathieu Morlighem, and Gilberto Perez
Geosci. Model Dev., 9, 3907–3918, https://doi.org/10.5194/gmd-9-3907-2016, https://doi.org/10.5194/gmd-9-3907-2016, 2016
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We present an approach to derive the adjoint state of the C++ coded Ice Sheet System Model. The approach enables data assimilation of observations to improve projections of polar ice sheet mass balance and contribution to sea-level rise. It is applicable to other Earth science frameworks relying on C++ and parallel computing, is non-intrusive, and enables computation of transient adjoints for any type of physics, hence providing insights into the sensitivities of any model to its inputs.
Dirk Notz, Alexandra Jahn, Marika Holland, Elizabeth Hunke, François Massonnet, Julienne Stroeve, Bruno Tremblay, and Martin Vancoppenolle
Geosci. Model Dev., 9, 3427–3446, https://doi.org/10.5194/gmd-9-3427-2016, https://doi.org/10.5194/gmd-9-3427-2016, 2016
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The large-scale evolution of sea ice is both an indicator and a driver of climate changes. Hence, a realistic simulation of sea ice is key for a realistic simulation of the climate system of our planet. To assess and to improve the realism of sea-ice simulations, we present here a new protocol for climate-model output that allows for an in-depth analysis of the simulated evolution of sea ice.
Cyrille Mosbeux, Fabien Gillet-Chaulet, and Olivier Gagliardini
Geosci. Model Dev., 9, 2549–2562, https://doi.org/10.5194/gmd-9-2549-2016, https://doi.org/10.5194/gmd-9-2549-2016, 2016
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Model projections of ice sheet contribution to 21st century sea level rise are greatly affected by initial conditions. Solutions have been developed to infer the friction of the ice on its bedrock using observed surface velocities. A drawback of these methods is that remaining uncertainties, especially in the bedrock elevation, lead to non-physical ice flux divergence anomalies. Here, we compare two different solutions able to infer both bedrock friction and elevation with good performance.
Xylar S. Asay-Davis, Stephen L. Cornford, Gaël Durand, Benjamin K. Galton-Fenzi, Rupert M. Gladstone, G. Hilmar Gudmundsson, Tore Hattermann, David M. Holland, Denise Holland, Paul R. Holland, Daniel F. Martin, Pierre Mathiot, Frank Pattyn, and Hélène Seroussi
Geosci. Model Dev., 9, 2471–2497, https://doi.org/10.5194/gmd-9-2471-2016, https://doi.org/10.5194/gmd-9-2471-2016, 2016
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Coupled ice sheet–ocean models capable of simulating moving grounding lines are just becoming available. Such models have a broad range of potential applications in studying the dynamics of ice sheets and glaciers, including assessing their contributions to sea level change. Here we describe the idealized experiments that make up three interrelated Model Intercomparison Projects (MIPs) for marine ice sheet models and regional ocean circulation models incorporating ice shelf cavities.
Olivier Passalacqua, Olivier Gagliardini, Frédéric Parrenin, Joe Todd, Fabien Gillet-Chaulet, and Catherine Ritz
Geosci. Model Dev., 9, 2301–2313, https://doi.org/10.5194/gmd-9-2301-2016, https://doi.org/10.5194/gmd-9-2301-2016, 2016
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In ice-flow modelling, computing in 3-D requires a lot of resources, but 2-D models lack physical likelihood when the flow is diverging. That is why 2-D models accounting for the divergence, so-called 2.5-D models, are an interesting trade-off. However, the applicability of these 2.5-D models has never been systematically examined. We show that these models are ineffective in the case of highly diverging flows, but also for varying temperature, which was not suspected.
Daniel N. Goldberg, Sri Hari Krishna Narayanan, Laurent Hascoet, and Jean Utke
Geosci. Model Dev., 9, 1891–1904, https://doi.org/10.5194/gmd-9-1891-2016, https://doi.org/10.5194/gmd-9-1891-2016, 2016
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Geophysical adjoint models are powerful tools, allowing sensitivity studies that are not possible otherwise, and enabling optimized fit of models to observing data sets. The complexity involved requires the use of algorithmic differentiation (AD) software, but AD adjoint calculation for ice models can be slow, with prohibitive memory requirements. In this paper, we present a method to improve the performance of ice model adjoint generation, in terms of timing, memory load, and accuracy.
David Pollard, Won Chang, Murali Haran, Patrick Applegate, and Robert DeConto
Geosci. Model Dev., 9, 1697–1723, https://doi.org/10.5194/gmd-9-1697-2016, https://doi.org/10.5194/gmd-9-1697-2016, 2016
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Computer modeling of variations of the Antarctic Ice Sheet help to
understand the ice sheet's sensitivity to climate change. We apply
a numerical model to its retreat over the last 20 000 years, from its
maximum glacial extent to modern. An ensemble of 625 simulations is performed
with systematic combinations of uncertain model parameter values. Results are
analyzed using (1) simple averaging, and (2) advanced statistical techniques,
and reasonable agreement is found between the two.
Evan J. Gowan, Paul Tregoning, Anthony Purcell, James Lea, Oscar J. Fransner, Riko Noormets, and J. A. Dowdeswell
Geosci. Model Dev., 9, 1673–1682, https://doi.org/10.5194/gmd-9-1673-2016, https://doi.org/10.5194/gmd-9-1673-2016, 2016
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We present a program that can create paleo-ice sheet reconstructions, using an assumed basal shear stress, margin location and basal topography as input. This allows for the quick determination of relatively realistic past ice sheet configurations without reliance on highly uncertain factors such as climate and ice dynamics. This is ideal for modelling Earth deformation due to the loading of ice sheets. The subsequent ice sheet configurations can be used as an input for climate modelling.
Agnieszka Herman
Geosci. Model Dev., 9, 1219–1241, https://doi.org/10.5194/gmd-9-1219-2016, https://doi.org/10.5194/gmd-9-1219-2016, 2016
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Recent developments in observational and modeling techniques allow us to analyze sea ice with increasingly higher resolution. Instead of a continuous ice cover we observe a complex, constantly changing medium composed of interacting floes. Understanding these aspects of sea ice behavior requires new modeling methods, like the Discrete-Element Sea Ice model (DESIgn) in which sea ice is treated as an assemblage of grains that freeze together or break apart in response to wind and ocean currents.
Alex E. West, Alison J. McLaren, Helene T. Hewitt, and Martin J. Best
Geosci. Model Dev., 9, 1125–1141, https://doi.org/10.5194/gmd-9-1125-2016, https://doi.org/10.5194/gmd-9-1125-2016, 2016
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This study compares two methods of coupling a sea ice model to an atmospheric model in a series of idealized one-dimensional experiments. The JULES method calculates surface variables in the atmosphere; the CICE method calculates surface variables in the sea ice. It is found that simulations of all variables are more accurate in the JULES method, likely because of the shorter time step of the atmosphere.
S. Westermann, M. Langer, J. Boike, M. Heikenfeld, M. Peter, B. Etzelmüller, and G. Krinner
Geosci. Model Dev., 9, 523–546, https://doi.org/10.5194/gmd-9-523-2016, https://doi.org/10.5194/gmd-9-523-2016, 2016
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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.
Cited articles
Alenius, P., Nekrasov, A., and Myrberg, K.: Variability of the baroclinic Rossby radius in the Gulf of Finland, Cont. Shelf Res., 23, 563–573, https://doi.org/10.1016/S0278-4343(03)00004-9, 2003.
Beckmann, A. and Döscher, R.: A Method for Improved Representation of Dense Water Spreading over Topography in Geopotential-Coordinate Models, J. Phys. Oceanogr., 27, 581–591, https://doi.org/10.1175/1520-0485(1997)027<0581:AMFIRO>2.0.CO;2, 1997.
Berg, P., Döscher, R., and Koenigk, T.: Impacts of using spectral nudging on regional climate model RCA4 simulations of the Arctic, Geosci. Model Dev., 6, 849–859, https://doi.org/10.5194/gmd-6-849-2013, 2013.
Bitz, C. M., Holland, M. M., Weaver, A. J., and Eby, M.: Simulating the ice-thickness distribution in a coupled climate model, J. Geophys. Res.-Oceans, 106, 2441–2463, https://doi.org/10.1029/1999JC000113, 2001.
Bouillon, S., Maqueda, M. A. M., Legat, V., and Fichefet, T.: An elastic–viscous–plastic sea ice model formulated on Arakawa B and C grids, Ocean Model., 27, 174–184, https://doi.org/10.1016/j.ocemod.2009.01.004, 2009.
Dietze, H., Löptien, U., and Getzlaff, K.: MOMBA 1.1 – a high-resolution Baltic Sea configuration of GFDL's Modular Ocean Model, Geosci. Model Dev., 7, 1713–1731, https://doi.org/10.5194/gmd-7-1713-2014, 2014.
Eilola, K., Mårtensson, S., and Meier, H. E. M.: Modeling the impact of reduced sea ice cover in future climate on the Baltic Sea biogeochemistry, Geophys. Res. Lett., 40, 149–154, https://doi.org/10.1029/2012GL054375, 2013.
Funkquist, L. and Eckhard Kleine, E.: HIROMB An introduction to HIROMB, an operational baroclinic model for the Baltic Sea, Report Oceanography No 37, SMHI, available at: http://www.smhi.se/publikationer (last access: 16 August 2017), 2007.
Goerlandt, F., Montewka, J., Zhang, W., and Kujala, P.: An analysis of ship escort and convoy operations in ice conditions, Safety Sci., 95 195–209, https://doi.org/10.1016/j.ssci.2016.01.004, 2016.
Gröger, M., Dieterich, C., Meier, H. E. M., and Schimanke, S.: Thermal air–sea coupling in hindcast simulations for the North Sea and Baltic Sea on the NW European shelf, Tellus A, 67, 26911, https://doi.org/10.1029/2004JC002378, 2015.
Haapala, J., Markus Meier, H. E., and Rinne, J.: Numerical Investigations of Future Ice Conditions in the Baltic Sea, AMBIO, 30, 237–244, https://doi.org/10.1579/0044-7447-30.4.237, 2001.
Haas, C.: Airborne EM sea-ice thickness profiling over brackish Baltic sea water, in: 17th International Symposium on Ice, Saint Petersburg, Russia, 1–17, 2004.
HELCOM: Recommendation 25/7 on Safety of winter navigation in the Baltic Sea Area, Baltic Marine Environment Protection Commission (Helsinki Commission), available at: http://www.helcom.fi/ (last access: 16 August 2017), 2004.
HELCOM: Ensuring safe shipping in the Baltic, Baltic Marine Environment Protection Commission (Helsinki Commission), available at: http://www.helcom.fi/ (last access: 16 August 2017), 2009.
Hordoir, R. and Meier, H. E. M.: Effect of climate change on the thermal stratification of the baltic sea: a sensitivity experiment, Clim. Dynam., 38, 1703–1713, https://doi.org/10.1007/s00382-011-1036-y, 2011.
Hordoir, R., Dieterich, C., Basu, C., Dietze, H., and Meier, H. E. M.: Freshwater outflow of the Baltic Sea and transport in the Norwegian current: A statistical correlation analysis based on a numerical experiment, Cont. Shelf Res., 64, 1–9, https://doi.org/10.1016/j.csr.2013.05.006, 2013.
Hordoir, R., Axell, L., Löptien, U., Dietze, H., and Kuznetsov, I.: Influence of sea level rise on the dynamics of salt inflows in the Baltic Sea, J. Geophys. Res., 120, 6653–6668, https://doi.org/10.1002/2014JC010642, 2015.
Hordoir, R., et al.: A NEMO based ocean model for Baltic & North Seas, research and operational applications, in preparation, 2017.
Hunke, E. and Holland, M. M.: Global atmospheric forcing data for Arctic ice-ocean modeling, J. Geophys. Res., 112, C04S14, https://doi.org/10.1029/2006JC003640, 2007.
Jones, C. G., Willén, U., Ullerstig, A., and Hansson, U.: The Rossby Centre Regional Atmospheric Climate Model Part I: Model Climatology and Performance for the Present Climate over Europe, AMBIO, 33, 199–210, https://doi.org/10.1579/0044-7447-33.4.199, 2004.
Lemieux, J.-F., Tremblay, L. B., Dupont, F., Plante, M., Smith, G. C., and Dumont, D.: A basal stress parameterization for modeling landfast ice, J. Geophys. Res., 120, 3157–3173, https://doi.org/10.1002/2014JC010678, 2015.
Leppäranta, M. and Hakala, R.: The structure and strength of first-year ice ridges in the Baltic Sea, Cold Reg. Sci. Technol., 20, 295–311, https://doi.org/10.1016/0165-232X(92)90036-T, 1992.
Leppäranta, M. and Myrberg, K.: Physical oceanography of the Baltic Sea, Springer Science and Business Media, 2009.
Leppäranta, M., Sun, Y., and Haapala, J.: Comparisons of Sea-Ice Velocity Fields from ERS-1 SAR and a dynamic model, J. Glaciol., 44, 248–262, https://doi.org/10.1017/S0022143000002598, 1998.
Loewe, P.: Surface temperatures of the North Sea in 1996, Ocean Dynam., 48, 175–184, 1996.
Löptien, U. and Axell, L.: Ice and AIS: ship speed data and sea ice forecasts in the Baltic Sea, The Cryosphere, 8, 2409–2418, https://doi.org/10.5194/tc-8-2409-2014, 2014.
Löptien, U. and Dietze, H.: Sea ice in the Baltic Sea – revisiting BASIS ice, a historical data set covering the period 1960/1961–1978/1979, Earth Syst. Sci. Data, 6, 367–374, https://doi.org/10.5194/essd-6-367-2014, 2014 (data available at: https://doi.org/10.1594/PANGAEA.832353), last access: 16 August 2017.
Löptien, U. and Meier, H. E. M.: The influence of increasing water turbidity on the sea surface temperature in the Baltic Sea: A model sensitivity study, J. Marine Syst., 88, 323–331, https://doi.org/10.1016/j.jmarsys.2011.06.001, 2011.
Löptien, U., Mårtensson, S., Meier, H. E. M., and Höglund, A.: Long-term characteristics of simulated ice deformation in the Baltic Sea (1962-2007), J. Geophys. Res., 118, 801–815, https://doi.org/10.1002/jgrc.20089, 2013.
Madec, G.: NEMO ocean engine, Note du Pole de modélisation No 27, Institut Pierre-Simon Laplace (IPSL), available at: www.nemo-ocean.eu (last access: 16 August 2017), 2016.
Meier, H. E. M.: Baltic Sea climate in the late twenty-first century: a dynamical downscaling approach using two global models and two emission scenarios, Clim. Dynam., 27, 39–68, https://doi.org/10.1007/s00382-006-0124-x, 2006.
Meier, H. E. M., Döscher, R., and Faxen, T.: A multiprocessor coupled ice-ocean model for the Baltic Sea: Application to salt inflow, J. Geophys. Res., 108, 3273, https://doi.org/10.1029/2000JC000521, 2003.
Meier, H. E. M., Döscher, R., and Halkka, A.: Simulated distributions of Baltic Sea-ice in warming climate and consequences for the winter habitat of the Baltic ringed seal, AMBIO, 33, 249–256, 2004.
Meier, H. E. M., Höglund, A., Döscher, R., Andersson, H., Löptien, U., and Kjellström, E.: Quality assessment of atmospheric surface fields over the Baltic Sea from an ensemble of regional climate model simulations with respect to ocean dynamics, Oceanologia, 53, 193–227, https://doi.org/10.5697/oc.53-1-TI.193, 2011.
Meier, H. E. M., Hordoir, R., Andersson, H. C., Dieterich, C., Eilola, K., Gustafsson, B. G., Höglund, A., and Schimanke, S.: Modeling the combined impact of changing climate and changing nutrient loads on the Baltic Sea environment in an ensemble of transient simulations for 1961–2099, Clim. Dynam., 39, 2421–2441, https://doi.org/10.1007/s00382-012-1339-7, 2012.
Montewka, J., Goerlandt, F., Kujala, P., and Lensu, M.: Towards probabilistic models for the prediction of a ship performance in dynamic ice, Cold Reg. Sci. Technol., 112, 14–28, https://doi.org/10.1016/j.coldregions.2014.12.009, 2015.
Olason, E.: A dynamical model of Kara Sea land-fast ice, J. Geophys. Res., 121, 3141–3158, https://doi.org/10.1002/2016JC011638, 2016.
Osinski, R., Rak, D., Walczowski, W., and Piechura, J.: Baroclinic Rossby radius of deformation in the southern Baltic Sea, Oceanologia, 52, 417–429, 2010.
Parmerter, R. R.: A model of simple rafting in sea ice, J. Geophys. Res., 80, 1948–1952, https://doi.org/10.1029/JC080i015p01948, 1975.
Rousset, C., Vancoppenolle, M., Madec, G., Fichefet, T., Flavoni, S., Barthélemy, A., Benshila, R., Chanut, J., Levy, C., Masson, S., and Vivier, F.: The Louvain-La-Neuve sea ice model LIM3.6: global and regional capabilities, Geosci. Model Dev., 8, 2991–3005, https://doi.org/10.5194/gmd-8-2991-2015, 2015.
Samuelsson, P., Jones, C. G., Willén, U., Ullerstig, A., Gollvik, S., Hansson, U., Jansson, C., Kjellström, E., Nikulin, G., and Wyser, K.: The Rossby Centre Regional Climate model RCA3: model description and performance, Tellus A, 63, 4–23, https://doi.org/10.1111/j.1600-0870.2010.00478.x, 2010.
Seinä, A. and Paluso, E.: The classification of the maximum annual extent of ice cover in the Baltic Sea 1720–1995, Report series of the Finnish Institute of Marine Research No 20, Finnish Institute of Marine Research, 1996.
Thorndike, A. S., Rothrock, D. A., Maykut, G. A., and Colony, R.: The thickness distribution of sea ice, J. Geophys. Res., 80, 4501–4513, https://doi.org/10.1029/JC080i033p04501, 1975.
Umlauf, L. and Burchard, H.: Second-order turbulence closure models for geophysical boundary layers. A review of recent work, Cont. Shelf Res., 25, 795–827, https://doi.org/10.1016/j.csr.2004.08.004, 2005.
Uppala, S. M., Kållberg, P. W., Simmons, A. J., Andrae, U., Bechtold, V. D. C., Fiorino, M., Gibson, J. K., Haseler, J., Hernandez, A., Kelly, G. A., Li, X., Onogi, K., Saarinen, S., Sokka, N., Allan, R. P., Andersson, E., Arpe, K., Balmaseda, M. A., Beljaars, A. C. M., Berg, L. V. D., Bidlot, J., Bormann, N., Caires, S., Chevallier, F., Dethof, A., Dragosavac, M., Fisher, M., Fuentes, M., Hagemann, S., Hólm, E., Hoskins, B. J., Isaksen, L., Janssen, P. A. E. M., Jenne, R., Mcnally, A. P., Mahfouf, J. F., Morcrette, J. J., Rayner, N. A., Saunders, R. W., Simon, P., Sterl, A., Trenberth, K. E., Untch, A., Vasiljevic, D., Viterbo, P., and Woollen, J.: The ERA-40 re-analysis, Q. J. Roy. Meteor. Soc., 131, 2961–3012, https://doi.org/10.1256/qj.04.176, 2006.
Valdez Banda, O., Goerlandt, F., Montewka, J., and Kujala, P.: A risk analysis of winter navigation in Finnish sea areas, Accident Anal. Prev., 79, 100–116, 2015.
Vancoppenolle, M., Fichefet, T., Goosse, H., Bouillon, S., Madec, G., and Maqueda, M. A. M.: Simulating the mass balance and salinity of Arctic and Antarctic sea ice. 1. Model description and validation, Ocean Model., 27, 33–53, https://doi.org/10.1016/j.ocemod.2008.10.005, 2009.
Vihma, T. and Haapala, J.: Geophysics of sea ice in the Baltic Sea: A review, Prog. Oceanogr., 80, 129–148, https://doi.org/10.1016/j.pocean.2009.02.002, 2009.
Weeks, W. F.: On sea ice, Universiy of Alaska Press, Fairbanks, 1st Edn., 664 pp., 2010.
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Short summary
The Baltic Sea is seasonally ice covered with intense wintertime ship traffic and a sensitive ecosystem. Understanding the sea-ice pack is important for climate effect studies and forecasting. A NEMO-LIM3.6-based model setup for the North Sea/Baltic Sea is introduced, including a method for ice in the coastal zone. We evaluate different sea-ice parameters and overall find that the model agrees well with the observation though deformed ice is more challenging to capture.
The Baltic Sea is seasonally ice covered with intense wintertime ship traffic and a sensitive...
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