Jung, Thomas
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Jung, Thomas
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Jung, Thomas
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Item type:Publication, Natural Variability of Arctic and Antarctic Sea Ice : Insight From Pre-industrial CMIP5 Runs(2018-05-25); ; ; Understanding natural variability of Arctic and Antarctic sea ice is important for explaining and predicting observed sea ice variability. Motivated by this, I undertook this study that analyzes sea ice variability in pre-industrial control runs for a subset of Earth System Models (ESMs) and Climate Models (CMs) from the Coupled Model Intercomparison Project Phase 5 (CMIP5), and the Alfred Wegener Institute Climate Model (AWI-CM). I compare the general characteristics of simulated mean sea ice conditions in the Arctic and Antarctic for the selected models. I find that the main characteristics of Arctic sea ice are better simulated than that of Antarctic sea ice. None of the selected models were able to simulate all of the Antarctic sea ice characteristics properly.Inter-model spread of winter sea ice volume and summer sea ice extent in both hemispheres is large, with the spread exceeding the limits of natural variability. The drivers of the Arctic sea ice minimum in September and the Antarctic sea ice minimum in February are studied using composite analysis. In the Arctic, events of low sea ice extent in September are related to (1) Sea Ice Thickness (SIT) Memory (2) a negative Sea Level Pressure (SLP) and a positive Sea Surface Temperature (SST) anomaly in the Barents Sea in March, (3) the deepening of the Aleutian Low in March with imprints of ENSO and PDO, and (4) a positive SLP anomaly in the Beaufort Sea in July. I also find that events of low September sea ice extent minima tend to cluster in time. I suggest that in addition to low frequency climate variability, clustering of low September sea ice extent events depends on the memory of the Arctic sea ice system provided by SIT and ocean surface heat content. The occurrences of the aforementioned atmospheric patterns are random, in the sense that they are not necessarily taking place in the same years. An important characteristic of the events analyzed is an anomalous thin Arctic sea ice cover in winter that preconditions these late summer events. The anticyclonic SLP anomaly in the Beaufort Sea develops in summer, so if the sea ice cover is in a fragile and weak state, atmosphere-sea ice coupling will be even more efficient in reducing sea ice extent via Ekman convergence. In the Antarctic, events of low sea ice extent minimum in February are related to (1) a positive anomalous Southern Annular Mode (SAM) in winter that enhances sea ice divergence creating widespread negative anomalies in Sea Ice Concentration (SIC), (2) a negative anomalous SAM in summer and (3) a broad positive SST anomaly in the Southern Ocean associated with the negative SAM and SIC decline. Similar to the Arctic, events of low February sea ice extent minima tend to cluster in time, however with a lower likelihood of a February sea ice extent event to be followed by another. The memory of clustering in the Antarctic is provided by low frequency variability and the memory of the sea ice system that is predominately associated with ocean surface heat content anomalies. In both hemispheres, the reduction of sea ice extent and volume in years characterized by a low sea ice extent minimum, causes a strong negative net Short Wave Radiation (net SWR) anomaly in spring. This leads to enhanced sea ice melt via the positive sea ice-albedo feedback. From the composite analysis I suggest that the mechanism for producing low sea ice extent minima events in both hemispheres are similar. Such a mechanism involves the thinning of the sea ice cover in winter, enhanced sea ice albedo feedback in spring, and the efficient role of an anomalous anticyclonic SLP pattern in summer.doctoral thesis441 172 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Landfast ice in the Arctic: parameterization in numerical modeling and effects on the hydrography(2023-03-09); ; The Arctic amplification of climate change is strongly connected to the sea ice in the Arctic because of the sea ice albedo and insulation effects. This thesis presents numerical modeling studies on landfast ice and the kinetic energy dissipation within sea ice in the Arctic. Landfast ice is sea ice that is nearly immobile and attached to the coast. As an extension to the land, landfast ice provides a platform for tourism, transportation, and hunting for the local communities, as well as for oil and gas drilling and scientific observation. Although landfast ice plays an important role in the Arctic coastal regions, it is challenging to represent landfast ice in numerical sea ice models with a standard viscous-plastic (VP) rheology. In this thesis, I implement a lateral drag parameterization to improve the representation of the landfast ice in the sea ice model and study the kinetic energy dissipation by sea ice internal stress. This thesis has three scientific questions: (1) How can we improve the representation of landfast ice in the sea ice numerical model? (2) What is the influence on the Arctic Ocean hydrography with the presence of landfast ice cover in the sea ice model? (3) Does the kinetic energy dissipation depend on the details of the VP yield curves? With higher resolution, the heterogeneity of the sea ice cover increases and deformation localizes at distinct linear kinematic features. Does this change have an effect on the mechanical energy cycle? Firstly, coastal drag parameterization is implemented in the coarse sea ice model, as a function of coastline length, sea ice thickness, and sea ice drift velocity. The results show that the new parameterization improves the simulation of landfast ice in deep marginal seas of the Arctic. Furthermore, the combination of lateral and basal drag parameterization simulates realistic landfast ice distributions in the Arctic. Secondly, the landfast ice cover is switched on and off in the sea ice model to study the influence of the landfast ice on the Arctic hydrography. The results show that the presence of the landfast ice decreases the salinity in the upper ocean due to the reduced new ice formation releasing less salt in the water. Furthermore, the fresher upper ocean signal formed in the deep marginal sea is transported from the coast to the central Arctic, leading to a fresher upper ocean in the Makarov Basin. The salt budget analysis demonstrates that the salt is advected of the Arctic through the boundaries. Lastly, the kinetic energy dissipation with different yield curves and three model resolutions is evaluated. The standard ellipse, Mohr--Coulomb yield curve with elliptical plastic potential, Truncated Ellipse Method and Teardrop yield curves are employed in the 4.5 km sea ice model to compare the sea ice thickness, drift velocity, and kinetic energy dissipation differences. The results indicate that the simulations with yield curves with more shear strength lead to smaller sea ice drift and hence to smaller wind energy input and energy loss due to ocean drag. Moreover, the impact of the different yield curves on the net energy dissipation is small, but simulations with similar yield curves have similar kinetic energy dissipation within the ice. Finally, experiments with different model resolutions suggest that the higher the resolution of the simulation, the more deformation and dissipation are localized along shear lines. More localization leads to smaller mean drift, less kinetic energy input, and loss by ocean drag.doctoral thesis335 185 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Deep learning for temporal reconstruction of FESOM-derived sea surface temperature and 3D ocean variables(2025-08-27); ; ; In oceanography, the growing volume of data collection raises the challenge of efficient data storage and computational efficiency for ocean simulations. To address this, we adopted an interpolation-based approach for reducing data storage requirements while ensuring accurate reconstruction of sea surface temperature (SST) and 3D ocean variables, including temperature and horizontal velocities (u and v) derived from the Finite-volumE Sea ice–Ocean Model (FESOM2). Our research explores three distinct strategies: single-step interpolation, temporal-window interpolation, and multi-step interpolation. To achieve these goals within a supervised learning framework, we propose a hybrid CNN-BiLSTM deep learning model for both accurate interpolation and data storage optimization. This model extracts features from time-series data by combining the strengths of convolutional neural networks (CNNs) for capturing spatial patterns and bidirectional long short-term memory (BiLSTM) networks for capturing temporal dependencies in time-series data. Additionally, our approach uses a multi-input multi-output (MIMO) strategy to improve computational efficiency and prevent error accumulation, resulting in high prediction accuracy. By incorporating neighborhood information and preprocessing data to consider spatial and temporal dependencies, our approach effectively prepares the data for training. We use subsampling to reduce memory usage and introduce diverse, uncorrelated samples. The results show that our model outperforms traditional methods, including linear interpolation (LI) and linear regression (LR), achieving lower mean squared error (MSE) and higher correlation coefficients when reconstructing ocean variables. Single-step interpolation achieved a 75% improvement, temporal-window interpolation demonstrated an overall 46.80% improvement, and multi-step interpolation achieved an overall 59.51% improvement in predictive accuracy. Remarkably, the model predicts multiple time steps for 3D ocean fields without introducing artifacts, achieving this within a single model framework. After training on diverse datasets, the model generalizes well to unseen data without requiring additional computational resources, making it a scalable and sustainable solution for addressing the growing need for data storage efficiency in oceanographic research. To improve model performance, key techniques were applied, including overfitting prevention, balanced batching, multi-GPU training, adaptive learning rate schedules such as polynomial decay and cyclic learning, and fine-tuning. We also demonstrate the practical application of our model by computing ocean heat transport in zonal and meridional directions. The results confirm that our model predicts ocean heat content more accurately than traditional methods. However, the computation of ocean heat transport using mixed-sign velocity values presents challenges, despite individual velocity predictions being highly accurate. This work highlights the potential of advanced neural networks in reconstructing temperature and velocity data, accurately matching observed values, and enhancing our understanding of ocean heat dynamics.doctoral thesis45 50 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Modelling and parametrization of turbulent convective processes over leads in sea ice(2020-12-14); ; ; Im Nord- und Südpolarmeer ist das Klimasystem der Erde durch viele unterschiedliche Wechselwirkungsprozesse zwischen Atmosphäre, Ozean und Meereis geprägt. Die Meereisbedeckung spielt dabei durch ihren isolierenden Effekt und dem folglich minimierten Austausch zwischen Ozean und Atmosphäre eine wichtige Rolle. Nichtsdestotrotz, auch in der kalten Jahreszeit mit großflächiger Meereisbedeckung ist ein starker turbulenter Transport von Wärme und Feuchte zwischen dem relativ warmen Ozean hinein in die kalte Atmosphäre möglich, zum Beispiel durch längliche Öffnungen (Rinnen) im Meereis. Der konvektive Transport über Rinnen wird durch starke Temperaturunterschiede verursacht, was zu konvektiven Plumes mit verstärkter Turbulenz und einem starken Einfluss auf die Charakteristika der atmosphärischen Grenzschicht führt. Dieser Einfluss hängt wiederum von der Rinnengeometrie und den meteorologischen Bedingungen ab. Verständnis und Quantifizierung dieser eher kleinskaligen Prozesse sind entscheidend, um Modellergebnisse zu verbessern, was auch die Ergebnisse großskaliger (Klima-)Modelle betrifft. Diese Dissertation beinhaltet eine detaillierte Untersuchung der Strömung über Rinnen, vornehmlich mithilfe von kleinskaliger numerischer Modellierung. Durch die im Modell verwendete Gittergröße können konvektive Plumes aufgelöst werden, nicht jedoch einzelne turbulente Wirbel, was eine Parametrisierung turbulenter Flüsse sowie eine Validierung der zugehörigen Ergebnisse vonnöten macht. Hauptsächlich geht es in dieser Arbeit um die Herleitung einer verbesserten Parametrisierung der turbulenten Flüsse über Rinnen mit verschiedener Breite. Idealisierte und beobachtete Fälle werden unter Verwendung der neuen und bereits existierender Parametrisierungen simuliert und mithilfe von Referenzdaten evaluiert. Des weiteren wird eine vorläufige Studie durchgeführt, mit der mögliche Auswirkungen von kleinskaligen, rinnengenerierten atmosphärischen Prozessen auf größeren Skalen gezeigt werden.doctoral thesis738 289 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, The ocean mesoscale in a warming world: insights from multiscale modeling(2024-05-24); ; ; State-of-the-art climate models and computing infrastructure are now able to resolve mesoscale ocean eddy activity in many contexts. However, in computationally intensive model applications, such as the Coupled Model Intercomparison Project (CMIP) or simulations of the high latitudes, grid resolutions largely remain eddy-parameterizing due to resource constraints. These missing mesoscale processes are understood to be crucial drivers of ocean circulation and climate and may become still more relevant in the context of anthropogenic climate change. To overcome the computational limitations of traditional models, multiscale modeling strategies have been developed which can distribute grid resolution and resources based on resolution requirements and research goals. Here, several strategies for resolving the mesoscale using multiscale methods are described and the results of their implementation with the Finite volumE Sea ice Ocean Model (FESOM) are reported. In the first application, FESOM participates in CMIP6 with the strategy of concentrating computational resources on the major eddy-rich regions of the ocean. The resulting simulations are able to reproduce between 51 and 82% of observed eddy kinetic energy (EKE) in each region and project substantial climate change impacts on mesoscale activity for the first time at such a scale. The results include a poleward shift of eddy activity in most western boundary currents; EKE intensification in the Antarctic Circumpolar Current (ACC), Brazil and Malvinas Currents, and Kuroshio Current; EKE decline in the Gulf Stream; and intensification of Agulhas leakage. In a second application, FESOM is used to concentrate computational resources in the Southern Ocean and cost-reducing modeling strategies are used to enable fully eddy-resolving climate change projections with the regionally focused grid. The simulations faithfully reproduce EKE in the Southern Ocean and project intensified eddy activity in line with the CMIP6 analysis. The climate change signal is difficult to reliably discern from natural variability after 1 °C of warming, but becomes clear after 4 °C. Finally, the high-resolution Southern Ocean simulations are used to investigate high-latitude eddy activity where ice cover and low eddy size make observations and traditional modeling methods difficult. Detailed, near circumpolar mesoscale activity is detected and related to gyre circulation, the Antarctic Slope Current, and bathymetry. There is a strong seasonal cycle which suppresses winter eddy activity at the surface and selectively dampens cyclonic eddies. After prolonged anthropogenic warming, broad intensification of eddy activity occurs alongside regional decline, ACC eddy activity encroaches further into the high latitudes, and the seasonal cycle is diminished. Collectively, this work demonstrates the effectiveness of multiscale modeling in reducing the cost of resolving mesoscale ocean activity, facilitating the study of eddy activity and its interactions with the broader climate in previously unachievable contexts.doctoral thesis339 225 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Towards understanding of future Arctic Ocean using high-resolution FESOM2 model(2025-08-29); ; ; The Arctic Ocean is currently experiencing some of the most rapid, complex, and far-reaching climatic transformations on Earth. These changes are driven by intensified global warming and manifest through a combination of diminishing sea ice, altered ocean circulation, and shifting atmospheric interactions. Despite the Arctic's central role in regulating planetary climate feedbacks, most global climate models still lack the spatial resolution required to adequately represent mesoscale eddies. These eddies, which are typically on the scale of a few to tens of kilometres, are critical for capturing key processes such as lateral heat transport, vertical mixing, and the redistribution of tracers and momentum. Their influence is particularly pronounced in the Arctic, where steep gradients in temperature and salinity, along with seasonal sea-ice variability, create an environment highly susceptible to small-scale dynamical features. In this study, we apply a next-generation global sea ice–ocean model configured with kilometre-scale horizontal resolution, specifically optimized for high-latitude processes, to investigate how Arctic eddy activity responds under conditions of sustained warming. Our findings show that in a world that has warmed by 4 degrees Celsius, the average eddy kinetic energy increases significantly, approximately tripling relative to present-day levels. This robust increase is primarily attributed to stronger baroclinic instability, which arises due to intensified lateral density gradients and extensive sea-ice retreat. Beyond this energetic amplification, the simulations reveal notable structural changes in eddy distribution across depth layers. While the number of eddies in mid-to-deep waters decreases, those that remain tend to become larger in size, suggesting that energy is concentrated into fewer but more vigorous features. At the same time, the upper ocean experiences a sharp rise in the number and strength of near-surface eddies, driven by increased wind forcing and surface buoyancy fluxes in newly ice-free regions. Recognizing the essential role of mesoscale eddies in Arctic circulation and vertical heat exchange, we further examine how these evolving patterns affect sea-ice seasonality. Our analysis indicates that under accelerated warming, the probability of predominantly ice-free Arctic summers becomes considerably higher. A direct comparison between eddy-rich and eddy-present model configurations demonstrates that the higher-resolution configuration, which explicitly resolves mesoscale processes, produces a significantly extended open-water season by the end of the century. This extension is closely associated with enhanced upper-ocean vertical mixing, which results from elevated shear and weakened stratification linked to the intensification of near-surface eddies. Consequently, summer sea-ice melting begins earlier, while autumn freeze-up is delayed, revealing the high sensitivity of sea-ice regimes to fine-scale ocean dynamics. Taken together, these findings highlight the intricate and interconnected mechanisms by which the Arctic climate system responds to external forcing. From the substantial increase in eddy kinetic energy and the enlargement of deep eddy structures, to the intensification of surface eddy activity and the shift in sea-ice timing, our study underscores the importance of high-resolution ocean modeling in capturing these critical dynamics. In addition to its implications for sea-ice extent, enhanced eddy-driven mixing has broader consequences for marine heatwave development, nutrient cycling, and primary productivity, thereby influencing biodiversity and ecosystem resilience. Moreover, by shedding light on the interactions between mesoscale eddies and large-scale oceanic and atmospheric circulation patterns, our results provide an essential scientific basis for improving future projections of Arctic environmental change. To fully understand and predict the impacts of these evolving processes, we recommend a coordinated research effort that combines high-resolution modeling with comprehensive observational strategies. These should include advanced satellite measurements, expanded autonomous observing platforms, and targeted field campaigns designed to resolve fine-scale variability in ocean and ice dynamics. Such integrated approaches are vital for capturing the full spectrum of mesoscale influences on the Arctic system and for assessing their implications within the broader context of Earth system change.doctoral thesis61 60 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Sea-ice prediction across timescales and the role of model complexity(2021-01-12); ; ; In addition to observations and lab experiments, the scientific investigation of the Arctic and Antarctic sea ice is conducted through the employment of geophysical models. These models describe in a numerical framework the physical behavior of sea ice and its interactions with the atmosphere, ocean, and polar biogeochemical systems. Sea-ice models find application in the quantification of the past, present, and future sea-ice evolution, which becomes particularly relevant in the context of a warming climate system that causes the reduction of the Arctic sea ice cover. Because of the sea-ice decline, the navigation in the Arctic ocean increased substantially in the recent past, a trend that is expected to continue in the next decades and that requires the formulation of reliable sea-ice predictions at various timescales. Sea-ice predictions can be delivered by modern forecast systems that feature dynamical sea-ice models. The simulation of sea ice is at the center of this thesis: A coupled climate model with a simple sea-ice component is used to quantify potential impacts of a geoengineering approach termed "Arctic Ice Management"; the skill of current operational subseasonal-to-seasonal sea-ice forecasts, based on global models with a varying degree of sea-ice model complexity, is evaluated; and, lastly, an unstructured-grid ocean model is equipped with state-of-the-art sea-ice thermodynamics to study the impact of sea-ice model complexity on model performance. In chapter 2, I examine the potential of a geoengineering strategy to restore the Arctic sea ice and to mitigate the warming of the Arctic and global climate throughout the 21st century. The results, obtained with a fully coupled climate model, indicate that it is theoretically possible to delay the melting of the Arctic sea ice by ~60 years, but that this does not reduce global warming. In chapters 3 and 4, I assess the skill of global operational ensemble prediction systems in forecasting the evolution of the Arctic and Antarctic sea-ice edge position at subseasonal timescales. I find that some systems produce skillful forecasts more than 1.5 months ahead, but I also find evidence of substantial model biases and issues concerning data assimilation and model formulation. Chapter 5 deals with the impact of sea-ice model complexity on model performance. I present a new formulation of the FESOM2 sea-ice/ocean model with a revised description of the sea-ice thermodynamics, including various parameterizations of physical processes at the subgrid-scale. The model formulation grants substantial modularity in terms of sea-ice physics and resolution. The new system is used for assessing the impact of the sea-ice model complexity on the FESOM2 performance in different atmosphere-forced setups with a specific parameter-tuning approach and a special focus on sea-ice related variables. The results evidence that a more sophisticated model formulation is beneficial for the model representation of the sea-ice concentration and snow thickness, while less relevant for sea-ice thickness and drift. I also highlight a dependence of the model performance on the atmospheric forcing product used as boundary conditions. In the final part of this thesis, I formulate recommendations for future developments in the field of sea-ice modeling, with particular emphasis on FESOM2 and, more generally, on the modeling infrastructure under development at the Alfred Wegener Institute.doctoral thesis564 279 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Evaluation and application of Finite Element Sea Ice-Ocean Model (FESOM) for the Arctic-North Atlantic region in variable resolution global simulations(2016-05-30); ; ; The changes and variability of the Arctic-North Atlantic Oceans and the inter-exchange of water mass and heat is of crucial relevance for the global ocean and climate. In this work the Finite Element Sea-ice Ocean Model (FESOM) is used to simulate the global ocean with focus on the Arctic-North Atlantic region. FESOM is formulated on unstructured meshes and offers variable-resolution functionality which is diffcult to achieve in traditional structured-mesh models. With this powerful tool we are able to resolve the key areas with locally refined resolutions in global simulations. The performance of FESOM in the Arctic Ocean and North Atlantic on large time scales is first evaluated in a 240-yr hindcast experiment. The model can reproduce realistic Atlantic Meridional Overturning Circulation (AMOC) and realistic Arctic freshwater content variability and sea ice extent. A water-hosing experiment is conducted to study the model sensitivity to increased freshwater input from Greenland Ice Sheet (GrIS) melting in a 0.1Sv discharge rate scenario. The released freshwater from Greenland can penetrate into the Arctic Ocean, especially in the Eurasian Basin. The anomalous freshwater also leads to a reduction in the AMOC strength and changes in freshwater exchange between the two oceans. Simulations with different local resolutions of 24 km and 9 km in the Arctic Ocean and surrounding regions are carried out to study the influence of resolution on the simulated Arctic Ocean and Arctic-Subarctic fluxes. Both simulations can reasonably simulate the mean state and variability of sea ice condition, freshwater content in the Arctic Ocean, and the fluxes through the Arctic gateways when compared to observations and previous model studies. Although the high resolution (9 km) run tends to improve the representation of fluxes through the Arctic gateways and the salinity structure in the Arctic basin, higher meso-scale eddy resolving resolution is required to further improve the simulation. The driving mechanism of the interannual variability of Barents Sea sea ice is studied. We found that sea ice import into the Barents Sea drives the sea ice interannual variability. The amount of sea ice flux determines the thermodynamic growth rate in the Barents Sea. The increasing trend of Atlantic Water heat flux through the Barents Sea Opening leads to the decline of Barents Sea ice volume.doctoral thesis492 468 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Fracture Angles in Numerical Simulations of Sea Ice with Viscous-Plastic Rheologies(2020-09-04); ; Sea ice is an essential component of the climate system because it modulates the exchange of energy between the ocean and the atmosphere. Under stress from wind and ocean currents, sea ice deforms constantly. Sea ice deformation takes the shape of narrow lines, the Linear Kinematic Features (LKFs). LKFs influence the heat transfer, mass balance, and sea ice dynamics, so LKFs should be accurately represented in high-resolution climate models. Sea ice is commonly modeled using viscous-plastic (VP) rheologies defined by a yield curve and a flow rule. Recent work showed that VP sea ice models explicitly create LKFs but overestimate their intersection angles. This thesis aims to investigate the link between the angles of fracture in sea ice models and the parametrization of the sea ice internal stresses using idealized compression experiments. Three questions are addressed: Which parameters of the VP rheologies influence the fracture angle? Which theoretical framework explains this influence? Which rheologies should be used to simulate intersection angles at the observed range? With the commonly used standard VP rheology with an elliptical yield curve and a normal flow rule, the fracture angles are linked to the yield curve's elliptical shape. Because of this shape, this rheology cannot create sea ice fracture angles more acute than 30 degrees in uniaxial compression, even by changing the aspect of the ellipse. The classical coulombic theory predicts the angle of fracture accurately when adapted to the context of sea ice modeling. A new rheology with an elliptical yield curve and a non-normal flow rule shows that fracture angles are also sensitive to the orientation of the flow rule. Using this new rheology allows creating fracture angles as low as 22 degrees in uniaxial compression. A theory based on the angle of dilatancy and observations of granular materials predicts precisely the simulated angles. Alternative rheologies can create fracture angles lower than 30 degrees. With Mohr--Coulomb yield curves, fracture angles are well predicted by joining the concepts of coulombic friction and angle of dilatancy. Teardrop and Parabolic lens yield curves create small angles of fracture in uni-axial compression when used with small tensile strength. Using a more realistic sea ice cover with heterogeneity, failure under deformation takes the form of a network of fracture lines. The choice of rheology strongly influences the angle of fracture in this network. Two rheologies are suitable candidates to decrease the fracture angles in sea ice VP models. In conclusion, fracture angles in sea ice models are determined by the properties of the VP rheology and can be accurately predicted using fracture orientation theory. Changing the rheology can reduce the fracture angles in sea ice simulations. With the results presented in this thesis, new rheologies could be inferred from observations to represent sea ice fracture more realistically.doctoral thesis814 387