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  • 1
    Online Resource
    Online Resource
    Numerical experiments for the appropiate representative volume element size selection on thin texturized metals under mechanical loads (2012)
    Bremen : Zentrum für Technomathematik, Universität Bremen
    Details Availability
    Keywords: Forschungsbericht
    Type of Medium: Online Resource
    Pages: 1 Online-Ressource (18 Seiten, 677 kB) , Illustrationen
    Series Statement: Berichte aus der Technomathematik Report 12-04
    URL: http://www.math.uni-bremen.de/zetem/cms/media.php/262/Zetembericht_1204_Montalvo.pdf
    URL: https://edocs.tib.eu/files/e01fn17/738390542.pdf
    Language: English
    Note: Literaturverzeichnis: Seite 16-17 , Systemvoraussetzungen: Acrobat reader.
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    GEOMAR CATALOGUE
    Link to Library Catalog
    get availability status
  • 2
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    Data files for simulation of sub-grid ice thickness distributions in an Arctic configuration of the MITgcm (2018)
    PANGAEA
    In:  Supplement to: Ungermann, Mischa; Losch, Martin (2018): An Observationally Based Evaluation of Subgrid Scale Ice Thickness Distributions Simulated in a Large-Scale Sea Ice-Ocean Model of the Arctic Ocean. Journal of Geophysical Research: Oceans, 123(11), 8052-8067, https://doi.org/10.1029/2018JC014022
    Details
    Publication Date: 2023-01-13
    Description: A key parameterization in sea ice models describes the sub-grid scale ice thickness distribution. Based on only a few observations, the ice thickness distribution model was shown to be consistent with field data and to improve the simulation's large scale properties. The available submarine and airborne observations enable to evaluate in greater detail the ability of a pan-Arctic sea ice - ocean model with an ice thickness distribution parameterization to reproduce observed thickness distributions in different regions and seasons. Many observations are reproduced accurately. Some cases of poorly simulated modes and tails of the distributions are tentatively attributed to simplified thermodynamics and inaccurate deformation fields. Variability on decadal timescales, however, is generally underestimated. Thickness distributions in individual grid cells of the model show similar differences between regions and seasons as observed regional mean distributions, but the modeled grid-scale variability is lower than observed. Simulated modal thicknesses of first-year ice are only insufficiently different from those of multi-year ice. The modal thickness proves to be a useful metric for quantifying model biases in both dynamics and thermodynamics. In addition to improving basin-wide mean variables, the ice thickness distribution parameterization provides reliable and valuable additional sub-grid scale data. At the same time the low climate sensitivity of the parameterization may affect longer simulations with strong climate change aspects. Archived are the data files necessary to run the simulation. The simulation was performed with the MITgcm (version checkpoint 66a), simulation geometry and boundary conditions were taken from [Nguyen et al., 2011, doi:10.1029/2010JC006573]
    Keywords: Arctic; pan-Arctic
    Type: Dataset
    Format: application/zip, 5.5 kBytes
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    DATA PANGAEA
  • 3
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    Sea ice thickness distribution (ITD) Model for the Arctic, links to NetCDF files
    PANGAEA
    In:  Supplement to: Ungermann, Mischa; Tremblay, L Bruno; Martin, Torge; Losch, Martin (2017): Impact of the Ice Strength Formulation on the Performance of a Sea Ice Thickness Distribution Model in the Arctic. Journal of Geophysical Research: Oceans, 122(3), 2090-2107, https://doi.org/10.1002/2016JC012128
    Details
    Publication Date: 2023-05-12
    Description: The impact of a subgrid-scale ice thickness distribution (ITD) and two standard ice strength formulations on simulated Arctic sea ice climate is investigated. To this end different model configurations with and without an ITD were tuned by minimizing the weighted mean error between the simulated and observed sea ice concentration, thickness and drift speed with an semi-automatic parameter optimization routine. The standard ITD and ice strength parameterization lead to larger errors when compared to the simple single-category model with an ice strength parameterization based on the mean ice thickness. Interestingly, the simpler ice strength formulation, which depends linearly on the mean ice thickness, also reduces the model-observation error when using an ITD. For the ice strength parameterization that makes use of the ITD, the effective ice strength depends strongly on the number of thickness categories, so that introducing more categories can lead to overall thicker ice that is more easily deformed.
    Keywords: Arctic; File content; File format; File name; File size; pan-Arctic; Uniform resource locator/link to file
    Type: Dataset
    Format: text/tab-separated-values, 30 data points
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    DATA PANGAEA
  • 4
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    Impact of the ice strength formulation on the performance of a sea ice thickness distribution model in the Arctic (2017)
    AGU (American Geophysical Union) | Wiley
    In:  Journal of Geophysical Research: Oceans, 122 (3). pp. 2090-2107.
    Details
    Publication Date: 2020-02-06
    Description: The impact of a subgrid-scale ice thickness distribution (ITD) and two standard ice strength formulations on simulated Arctic sea ice climate is investigated. To this end, different model configurations with and without an ITD were tuned by minimizing the weighted mean error between the simulated and observed sea ice concentration, thickness, and drift speed with an semiautomatic parameter optimization routine. The standard ITD and ice strength parameterization lead to larger errors when compared to the simple single-category model with an ice strength parameterization based on the mean ice thickness. Interestingly, the simpler ice strength formulation, which depends linearly on the mean ice thickness, also reduces the model-observation error when using an ITD. For the ice strength parameterization that makes use of the ITD, the effective ice strength depends strongly on the number of thickness categories, so that introducing more categories can lead to overall thicker ice that is more easily deformed.
    Type: Article , PeerReviewed
    Format: text
    DOI: 10.1002/2016JC012128
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    OceanRep: Article in a Scientific Journal - peer-reviewed
  • 5
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    An Observationally Based Evaluation of Subgrid Scale Ice Thickness Distributions Simulated in a Large-Scale Sea Ice-Ocean Model of the Arctic Ocean (2018)
    In:  EPIC3Journal of Geophysical Research: Oceans, 123, pp. 1-16, ISSN: 2169-9275
    Details
    Publication Date: 2018-11-19
    Description: A key parameterization in sea ice models describes the subgrid scale ice thickness distribution. Based on only a few observations, the ice thickness distribution model was shown to be consistent with field data and to improve the simulation’s large-scale properties. The available submarine and airborne observations enable to evaluate in greater detail the ability of a pan-Arctic sea ice-ocean model with an ice thickness distribution parameterization to reproduce observed thickness distributions in different regions and seasons. Many observations are reproduced accurately. Some cases of poorly simulated modes and tails of the distributions are tentatively attributed to simplified thermodynamics and inaccurate deformation fields. Variability on decadal timescales, however, is generally underestimated. Thickness distributions in individual grid cells of the model show similar differences between regions and seasons as observed regional mean distributions, but the modeled grid-scale variability is lower than observed. Simulated modal thicknesses of first-year ice are only insufficiently different from those of multiyear ice. The modal thickness proves to be a useful metric for quantifying model biases in both dynamics and thermodynamics. In addition to improving basin-wide mean variables, the ice thickness distribution parameterization provides reliable and valuable additional subgrid scale data. At the same time the low climate sensitivity of the parameterization may affect longer simulations with strong climate change aspects.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , isiRev
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    PAPER (OA)
  • 6
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    Impact of the Ice Strength Formulation on the Performance of a Sea Ice Thickness Distribution Model in the Arctic (2017)
    AMER GEOPHYSICAL UNION
    In:  EPIC3Journal of Geophysical Research: Oceans, AMER GEOPHYSICAL UNION, 122(3), pp. 2090-2107, ISSN: 2169-9275
    Details
    Publication Date: 2019-07-17
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , isiRev
    Format: application/pdf
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    PAPER (OA)
  • 7
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    The impact of an ITD parameterisation on the quality of model results (2015)
    In:  EPIC3FAMOS Workshop, 2015-11-03-2015-11-06
    Details
    Publication Date: 2016-10-31
    Description: An ice thickness distribution (ITD) parameterisation is by now part of most sea-ice models. Yet although it is based on a more physical reasoning, the gain for current models by its use is still unclear. By measuring the misfit to satellite observations for concentration, thickness and drift in a cost function we arrive at a measure of the obtained change in quality of model results. In this respect the sea ice component of the MITgcm is compared with and without an activated ITD parameterisation.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Conference , notRev
    Format: application/pdf
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    PAPER (OA)
  • 8
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    Investigating Arctic Sea Ice properties with an adjoint model (2014)
    In:  EPIC3Arctic Change 2014, Ottawa, Canada, 2014-12-08-2014-12-08
    Details
    Publication Date: 2017-01-27
    Description: In spite of its comparatively small volume sea ice plays a major part in the Arctic climate system, because the interactions with the ocean and the atmosphere lead to many feedbacks in the coupled system. Unfortunately, these interesting properties are also one reason why modeling sea ice is still not mature. Many physical processes, most prominently maybe the formation and evolution of leads, are still only poorly represented in numerical models. The cause of those misrepresentations is often very hard to pinpoint because many factors play a role. One possibility to address this problem is an adjoint model. Such a numerical tool takes one objective function out of the huge output of a climate model and calculates the gradients and thereby the sensitivities to all variables that are modeled. In a first step one property of the sea ice model such as the ice transport through a strait in a certain time span or the minimal summer sea ice extent is defined. The result of the adjoint model then gives directly the influence of all modeled variables of the ocean, sea ice and the atmospheric forcing on this property, resolved in space and time. This level of detail is in no way feasible to arrive at via traditional sensitivity analysis by parameter perturbation. With this information we want to investigate the role of different components of current sea-ice-ocean-models in the simulation results. For this we will focus for one part on the sensitivities of modeled sea ice distribution to the boundary, initial and forcing conditions prescribed to the model. The results can be used to inform future choices for additional measurements to improve model output. The other focus will be on the modeling framework itself, and the influence the rheology and the different physical parameterisations used in the sea ice models have on those calculated sensitivities.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Conference , notRev
    Format: application/pdf
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  • 9
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    Modelling Arctic Sea Ice: On the Relationship between Ice Thickness Distributions and the Ice Strength (2017)
    In:  EPIC3
    Details
    Publication Date: 2020-03-27
    Description: The effects of anthropogenic climate change are most drastic in the Arctic. This amplification of climate change signals is strongly connected to the sea ice in the Arctic Ocean. This thesis presents an analysis of the sea ice cover in numerical ocean – sea ice models with a focus on two different parameter- izations: an active ice thickness distribution and an ice strength parameter- ization that is based on this additional thickness information. The research questions are: (1) can the parameterizations improve the reproduction of Arctic-wide sea ice observations? (2) Do the parameterizations actually re- produce physically observed behavior? (3) How can the parameterizations and their use in basin-scale models be improved further? In a first step, model quality is assessed by a quantitative measure of the reproduction of satellite observations of sea ice concentration, thickness and drift. Including a full ice thickness distribution in each grid cell instead of only two ice categories clearly improves the model results. At the same time, a strength parameterization based on a two-category approach produces better model results than a multi-category strength parameterization. In a next step, the two parameterizations are evaluated in more detail. The ice thickness distribution parameterization reproduces local observations in the Arctic to a large degree and simulates faithfully regional and seasonal differences found in observed distributions. The poor performance of the multi-category ice strength parameterization is explained by the physical assumptions that were made in its original derivation and that do not agree with the current understanding of the ice cover. In conclusion, using an ice thickness distribution improves model performance, but a multi-category parameterization of the ice strength should be avoided. In future work, a new ice strength parameterization could be derived from the physical properties of the ice pack that are demonstrated in this work.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Thesis , notRev
    Format: application/pdf
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  • 10
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    Sea-ice drag as a function of deformation and ice cover: Effects on simulated sea ice and ocean circulation in the Arctic (2018)
    Elsevier BV
    In:  EPIC3Ocean Modelling, Elsevier BV, 128, pp. 48-66, ISSN: 1463-5003
    Details
    Publication Date: 2023-06-12
    Description: Many state-of-the-art coupled sea ice-ocean models use atmospheric and oceanic drag coefficients that are at best a function of the atmospheric stability but otherwise constant in time and space. Constant drag coefficients might lead to an incorrect representation of the ice-air and ice-ocean momentum exchange, since observations of turbulent fluxes imply high variability of drag coefficients. We compare three model runs, two with constant drag coefficients and one with drag coefficients varying as function of sea-ice characteristics. The computed drag coefficients range between 0.88 ×10−3 and 4.68 ×10−3 for the atmosphere, and between 1.28 ×10−3 and 13.68 ×10−3 for the ocean. They fall in the range of observed drag coefficients and illustrate the interplay of ice deformation and ice concentration in different seasons and regions. The introduction of variable drag coefficients improves the realism of the model simulation. In addition, using the average values of the variable drag coefficients improves simulations with constant drag coefficients. When drag coefficients depend on sea-ice characteristics, the average sea-ice drift speed in the Arctic basin increases from 6.22 cm s−1 to 6.64 cm s−1. This leads to a reduction of ice thickness in the entire Arctic and particularly in the Lincoln Sea with a mean value decreasing from 7.86 m to 6.62 m. Variable drag coefficients lead also to a deeper mixed layer in summer and to changes in surface salinity. Surface temperatures in the ocean are also affected by variable drag coefficients with differences of up to 0.06 °C in the East Siberian Sea. Small effects are visible in the ocean interior
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , peerRev
    Format: application/pdf
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