An Observationally Based Evaluation of Subgrid Scale Ice Thickness Distributions Simulated in a Large‐Scale Sea Ice‐Ocean Model of the Arctic Ocean

Ungermann, Mischa; Lösch, Martin

doi:10.1029/2018jc014022

Cited by 9 publications

(10 citation statements)

References 62 publications

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“…Most commonly this conversion is done by assigning all ice in one grid cell to the category with the same ice thickness. Then, some years of spin-up time are used to redistribute the ice into different categories (Ungermann and Losch, 2018). Due to the high-resolution in our simulation a multiyear spin-up is not affordable.…”

Section: Model Configurationsmentioning

confidence: 99%

Feature-based comparison of sea-ice deformation in lead-resolving sea-ice simulations

Hutter¹,

Lösch²

2019

Preprint

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Abstract. The sea-ice modelling community progresses towards Pan-Arctic simulations that explicitly resolve leads in the simulated sea-ice cover. Evaluating these simulations against observations poses new challenges. A new feature-based evaluation of simulated deformation fields is introduced and the results are compared to a scaling analysis of sea ice deformation. Leads and pressure ridges – here combined into Linear Kinematic Features (LKF) – are detected and tracked automatically from deformation and drift data. LKFs in two Pan-Arctic sea-ice simulations with a horizontal grid spacing of 2 km are compared with an LKF data-set derived from the RADARSAT Geophysical Processor System (RGPS). One simulation uses a 5-class Ice Thickness Distribution (ITD). The simulated sea-ice deformation follows a multi-fractal spatial and temporal scaling as observed from RGPS. The heavy-tailed distribution of LKF lengths and the scale invariance of LKF curvature, which points to the self-similar nature of sea-ice deformation fields, is reproduced by the model. Interannual and seasonal variations of the number of LKFs, LKF densities, and LKF orientations in the ITD simulation are found to be consistent with RGPS observations. The lifetimes and growth rates follow a distribution with an exponential tail. The model overestimates the intersection angle of LKFs, which is attributed to the model's viscous-plastic rheology with an elliptical yield curve. In conclusion, the new feature-based analysis of LKF statistics is found to be useful for a comprehensive evaluation of simulated deformation features, which is required before the simulated features can be used with confidence in the context of climate studies. As such it complements the commonly used scaling analysis and provides new useful information for comparing deformation statistics. The ITD simulation is shown to reproduce LKFs sufficiently well to be used for studying the effect of directly resolved leads in climate simulations. The feature-based analysis of LKFs also identifies specific model deficits that may be address by specific parameterizations, for example, a damage parameter, a grounding scheme, and a Mohr-Coulombic yield curve.

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Section: Model Configurationsmentioning

confidence: 99%

Feature-based comparison of sea-ice deformation in lead-resolving sea-ice simulations

Hutter¹,

Lösch²

2019

Preprint

Self Cite

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“…Our observations provide insights into two key aspects in modeling sea ice dynamics, namely the mean dynamic thickness change and the effect of deformation on the shape of the ITD whose accurate representation in models is subject of present research (e.g. Lipscomb et al, 2007;Ungermann and Losch, 2018).…”

Section: Magnitude Of Deformation Shapes Itdmentioning

confidence: 94%

“…Hence, we suggest to chose the parameter as a function of the deformation rate. Since Ungermann and Losch (2018) showed in a sensitivity study with the MITgcm that is an important parameter in shaping the modeled ITD, we expect this to improve the fit between modeled and observed ITDs.…”

Section: Magnitude Of Deformation Shapes Itdmentioning

confidence: 95%

Linking sea ice deformation to ice thickness redistribution using high-resolution satellite and airborne observations

Albedyll

Haas

Dierking

2020

Preprint

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Abstract. An unusual, large polynya opened and then closed by freezing and convergence north of the coast of Greenland in late winter 2018. The closing corresponded to a natural, but well-constrained, full-scale ice deformation experiment. We have observed the closing of and deformation within the polynya with satellite synthetic-aperture radar (SAR) imagery, and measured the accumulated effects of dynamic and thermodynamic ice growth 5 with an airborne electromagnetic (AEM) ice thickness survey one month after the closing began. During that time strong ice convergence decreased the area of the former polynya by a factor of 2.5. The AEM survey showed mean and modal thicknesses of the one-month old ice of 1.96 ± 1.5 m and 0.95 m, respectively.We show that this is in close agreement with the modeled thermodynamic growth and with the dynamic thickening expected from the polynya area decrease during that time. In addition,we found characteristic differences in the shapes of ice thickness distributions in different regions of the closing polynya. These closely corresponded to different deformation histories of the surveyed ice that were derived from the high-resolution SAR imagery by drift tracking along Lagrangian backward trajectories. Results show a linear proportionality between convergence and thickness change that agrees well with ice thickness redistribution theory. In addition, the e-folding of the tails of the different ice thickness distributions is proportional to the magnitude of the total deformation experienced by the ice. Lastly, we developed a simple volume-conserving model to derive dynamic ice thickness change from high-resolution SAR deformation tracking. The model has a spatial resolution of 1.4 km and reconstructs thickness profiles in reasonable agreement with the AEM observations. The computed ice thickness distribution resembles main characteristics like mode, e-folding, and width of the observed distribution. This demonstrates that high-resolution SAR deformation observations are capable of producing realistic ice thickness distributions. The MYI surrounding the polynya had a mean and modal total thickness (snow + ice) of 2.1 ± 1.4 m and 2.0 m, respectively. The similar first- and multi-year ice mean thicknesses elude to the large amount of deformation experienced by the closing polynya.

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“…Hence, we suggest choosing the parameter µ as a function of the deformation rate. Since Ungermann and Losch (2018) showed in a sensitivity study with the MITgcm that µ is an important parameter in shaping the modeled ITD, we expect this to improve the fit between modeled and observed ITDs.…”

Section: The Magnitude Of Deformation Shapes the Itdmentioning

confidence: 95%

“…Our observations provide insights into two key aspects in modeling sea ice dynamics, namely, the mean dynamic thickness change and the effect of deformation on the shape of the ITD, whose accurate representation in models is the subject of current research (e.g., Lipscomb et al, 2007;Ungermann and Losch, 2018).…”

Section: The Magnitude Of Deformation Shapes the Itdmentioning

confidence: 97%

Linking sea ice deformation to ice thickness redistribution using high-resolution satellite and airborne observations

2021

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Abstract. An unusual, large, latent-heat polynya opened and then closed by freezing and convergence north of Greenland's coast in late winter 2018. The closing presented a natural but well-constrained full-scale ice deformation experiment. We observed the closing of and deformation within the polynya with satellite synthetic-aperture radar (SAR) imagery and measured the accumulated effects of dynamic and thermodynamic ice growth with an airborne electromagnetic (AEM) ice thickness survey 1 month after the closing began. During that time, strong ice convergence decreased the area of the refrozen polynya by a factor of 2.5. The AEM survey showed mean and modal thicknesses of the 1-month-old ice of 1.96 ± 1.5 m and 1.1 m, respectively. We show that this is in close agreement with modeled thermodynamic growth and with the dynamic thickening expected from the polynya area decrease during that time. We found significant differences in the shapes of ice thickness distributions (ITDs) in different regions of the refrozen polynya. These closely corresponded to different deformation histories of the surveyed ice that we reconstructed from Lagrangian ice drift trajectories in reverse chronological order. We constructed the ice drift trajectories from regularly gridded, high-resolution drift fields calculated from SAR imagery and extracted deformation derived from the drift fields along the trajectories. Results show a linear proportionality between convergence and thickness change that agrees well with the ice thickness redistribution theory. We found a proportionality between the e folding of the ITDs' tails and the total deformation experienced by the ice. Lastly, we developed a simple, volume-conserving model to derive dynamic ice thickness change from the combination of Lagrangian trajectories and high-resolution SAR drift and deformation fields. The model has a spatial resolution of 1.4 km and reconstructs thickness profiles in reasonable agreement with the AEM observations. The modeled ITD resembles the main characteristics of the observed ITD, including mode, e folding, and full width at half maximum. Thus, we demonstrate that high-resolution SAR deformation observations are capable of producing realistic ice thickness distributions.

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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

Cited by 9 publications

References 62 publications

Feature-based comparison of sea-ice deformation in lead-resolving sea-ice simulations

Feature-based comparison of sea-ice deformation in lead-resolving sea-ice simulations

Linking sea ice deformation to ice thickness redistribution using high-resolution satellite and airborne observations

Linking sea ice deformation to ice thickness redistribution using high-resolution satellite and airborne observations

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