Simulated Sea Ice Research Articles

A generalized stress correction scheme for the Maxwell elasto-brittle rheology: impact on the fracture angles and deformations

Abstract. The Maxwell elasto-brittle (MEB) rheology uses a damage parameterization to represent the brittle fracture of sea ice without involving plastic laws to constrain the sea ice deformations. The conventional MEB damage parameterization is based on a correction of super-critical stresses that binds the simulated stress to the yield criterion but leads to a growth of errors in the stress field. A generalized damage parameterization is developed to reduce this error growth and to investigate the influence of the super-critical stress correction scheme on the simulated sea ice fractures, deformations and orientation of linear kinematic features (LKFs). A decohesive stress tensor is used to correct the super-critical stresses towards different points on the yield curve. The sensitivity of the simulated sea ice fractures and deformations to the decohesive stress tensor is investigated in uniaxial compression experiments. Results show that the decohesive stress tensor influences the growth of residual errors associated with the correction of super-critical stresses, the orientation of the lines of fracture and the short-term deformation associated with the damage, but it does not influence the long-term post-fracture sea ice deformations. We show that when ice fractures, divergence first occurs while the elastic response is dominant, and convergence develops post-fracture in the long term when the viscous response dominates – contrary to laboratory experiments of granular flow and satellite imagery in the Arctic. The post-fracture deformations are shown to be dissociated from the fracture process itself, an important difference with classical viscous plastic (VP) models in which large deformations are governed by associative plastic laws. Using the generalized damage parameterization together with a stress correction path normal to the yield curve reduces the growth of errors sufficiently for the production of longer-term simulations, with the added benefit of bringing the simulated LKF intersection half-angles closer to observations (from 40–50 to 35–45∘, compared to 15–25∘ in observations).

Sea water frozen crystalisation impacted by flow and heterogeneous nucleation: PFM-LBM coupled modeling, simulation and experiments

This study presents a novel phase field method (PFM) - lattice Boltzmann method (LBM) coupled model that describes the ice crystal growth in sea water freezing. Sea water frozen crystalisation impacted by flow and heterogeneous nucleation was numerically and experimentally investigated. The PFM-LBM model was established to conduct simulation. A microscope observation experimental system was built to conduct verification. The results show that flow of sea water effectively promotes the diffusion of discharged salt and the growth of ice crystals, and reduces the probability of dendrite closure. In the directional competitive growth of ice crystals, the salt content trapped in the ice crystals decreased by 17.4% at 0.025 m/s and 21.9% at 0.05 m/s, while the existence of heterogeneous particles resulted in a narrower the brine channel and higher ice crystal growth rate, of which the ice crystal area increased by 10.8% and the trapped salt content in the ice crystals decreased by 14.8%. The study provides both a methodology of numerically simulate sea ice crystallisation which includes the phase change, solute migration, heat transfer and flow, and a feasible controlling approach to improve desalination efficiency of sea water frozen crystallisation.

Simulating sea ice drift in the Southern Ocean incorporating real wind data using the LSFEM

AbstractThe viscous‐plastic sea ice model of [2] describes the motion of sea ice on large scales. The numerical model of the sea ice drift considers velocities and stresses and is coupled with the field quantities ice thickness and ice concentration, which are modeled by transient advection equations. Here, the viscosity in sense of a non‐Newtonian fluid depends on velocity gradients, as well as on ice concentration and ice thickness. This leads to a strong nonlinearity of the constitutive model.In [8], we discussed the hurdles of large scale sea ice models and possible solutions of an implementation within a least‐squares finite element method (LSFEM). Previous studies on sea ice model implementations have shown that the LSFEM is a promising solution to the numerically difficult problem, cf. [9] and [7]. In this work, another essential aspect of sea ice research comes into play: embedding real data into the numerical solution is an important field of research in sea ice and ocean modeling. Here, we show a 2D boundary value problem for simulating sea ice drift in the Southern Ocean incorporating real wind data from the ERA‐5 project [1].

Mechanisms of Regional Winter Sea-Ice Variability in a Warming Arctic

AbstractThe Arctic winter sea ice cover is in retreat overlaid by large internal variability. Changes to sea ice are driven by exchange of heat, momentum, and freshwater within and between the ocean and the atmosphere. Using a combination of observations and output from the Community Earth System Model Large Ensemble, we analyze and contrast present and future drivers of the regional winter sea ice cover. Consistent with observations and previous studies, we find that for the recent decades ocean heat transport though the Barents Sea and Bering Strait is a major source of sea ice variability in the Atlantic and Pacific sectors of the Arctic, respectively. Future projections show a gradually expanding footprint of Pacific and Atlantic inflows highlighting the importance of future Atlantification and Pacification of the Arctic Ocean. While the dominant hemispheric modes of winter atmospheric circulation are only weakly connected to the sea ice, we find distinct local atmospheric circulation patterns associated with present and future regional sea ice variability in the Atlantic and Pacific sectors, consistent with heat and moisture transport from lower latitudes. Even if the total freshwater input from rivers is projected to increase substantially, its influence on simulated sea ice is small in the context of internal variability.

Effects of the atmospheric forcing resolution on simulated sea ice and polynyas off Adélie Land, East Antarctica

Coastal polynyas of the Southern Ocean play a central role in the ventilation of the deep ocean and affect the stability of ice shelves. It appears crucial to incorporate them into climate models, but it is unclear how to adequately simulate them. In particular, there is no consensus on the atmospheric forcing resolution needed to appropriately model the sea ice in coastal Antarctica. A high resolution might be required to represent the local winds such as katabatic winds which are key drivers of coastal polynyas. To fill in this gap, we have tested the sensitivity of sea ice and air-sea-ice interactions to the resolution of the atmospheric forcing in a high-resolution ocean–sea ice model. A set of regional atmospheric simulations at horizontal resolutions of 20, 10, and 5 km are performed with an atmospheric regional model and used to force three ocean–sea ice simulations in the Adélie Land sector, East Antarctica. Due to the better representation of topography with a refined grid, the offshore component of coastal winds becomes stronger at increased resolution. The wind intensification is particularly strong down valleys channelizing the katabatic flow, with increase in wind speed ranging between 1 and 3 m/s. Under a higher resolution forcing, polynyas open more frequently and are wider. This fosters the growth rate of sea ice in polynyas, while landfast ice and pack ice are weakly affected. In polynyas, the production of sea ice is increased by up to 30% at 5 km resolution compared to 20 km resolution. Polynyas downstream of the katabatic wind pathway are more affected than the ones driven by easterly winds, highlighting the importance of the local wind conditions. Brine rejection associated with these higher sea ice production rates affects the salinity budget of the ocean and enhances both the volume and density of the dense Shelf Water produced off Adélie Land. These results underpin the need to better account for local coastal winds and polynyas in ocean and climate models.

SITool (v1.0) – a new evaluation tool for large-scale sea ice simulations: application to CMIP6 OMIP

Abstract. The Sea Ice Evaluation Tool (SITool) described in this paper is a performance metrics and diagnostics tool developed to evaluate the skill of Arctic and Antarctic model reconstructions of sea ice concentration, extent, edge location, drift, thickness, and snow depth. It is a Python-based software and consists of well-documented functions used to derive various sea ice metrics and diagnostics. Here, SITool version 1.0 (v1.0) is introduced and documented, and is then used to evaluate the performance of global sea ice reconstructions from nine models that provided sea ice output under the experimental protocols of the Coupled Model Intercomparison Project phase 6 (CMIP6) Ocean Model Intercomparison Project with two different atmospheric forcing datasets: the Coordinated Ocean-ice Reference Experiments version 2 (CORE-II) and the updated Japanese 55-year atmospheric reanalysis (JRA55-do). Two sets of observational references for the sea ice concentration, thickness, snow depth, and ice drift are systematically used to reflect the impact of observational uncertainty on model performance. Based on available model outputs and observational references, the ice concentration, extent, and edge location during 1980–2007, as well as the ice thickness, snow depth, and ice drift during 2003–2007 are evaluated. In general, model biases are larger than observational uncertainties, and model performance is primarily consistent compared to different observational references. By changing the atmospheric forcing from CORE-II to JRA55-do reanalysis data, the overall performance (mean state, interannual variability, and trend) of the simulated sea ice areal properties in both hemispheres, as well as the mean ice thickness simulation in the Antarctic, the mean snow depth, and ice drift simulations in both hemispheres are improved. The simulated sea ice areal properties are also improved in the model with higher spatial resolution. For the cross-metric analysis, there is no link between the performance in one variable and the performance in another. SITool is an open-access version-controlled software that can run on a wide range of CMIP6-compliant sea ice outputs. The current version of SITool (v1.0) is primarily developed to evaluate atmosphere-forced simulations and it could be eventually extended to fully coupled models.

Antarctic winter sea-ice seasonal simulation with a coupled model: Evaluation of mean features and biases

Antarctic winter sea-ice seasonal simulation with a coupled model: Evaluation of mean features and biases

Sensitivity of Arctic sea ice to melt pond processes and atmospheric forcing: A model study

Melt ponds are pools of meltwater forming principally on Arctic sea ice during the melt season. The albedo of melt ponds is a key component of the surface energy balance. For this reason, various melt pond schemes have been developed for climate models. These schemes require assumptions on the physical processes governing melt ponds as well as a knowledge of the atmospheric state, which are not perfectly known. In this study, we investigate the effects of the sources of uncertainty from the prescribed atmospheric surface state, the melt pond scheme definition and the refreezing formulation of melt ponds on the simulated Arctic sea ice and melt pond properties with the NEMO-LIM3 ocean–sea ice general circulation model. We find that the simulated melt pond state is largely controlled by the freezing point of melt ponds. The representation of melt ponds is in better agreement with observations when using the freezing point of −0.15°C compared to the value of −2.00°C, in our model set-up. All the simulations feature positive trends in melt pond area fraction over the past decades. However, only 3 out of 8 simulations have significant positive trends in melt pond volume per sea ice area. This suggests an influence of the sea ice state for melt ponds over the last 30 years. Overall, we find that the simulated sea ice state, and in particular sea ice volume, is more affected by changes in the prescribed atmospheric forcing than by changes in the prescribed melt pond scheme or refreezing formulation. Including explicit melt pond schemes in large-scale sea-ice models offer the possibility to improve the representation of the surface energy balance in climate general circulation models. Our results underline that, in parallel to these efforts in model developments, improved estimates of surface atmospheric conditions will be required to achieve more realistic sea ice states.

Influence of Arctic sea-ice loss on the Greenland ice sheet climate

The Arctic is the region on Earth that is warming the fastest. At the same time, Arctic sea ice is reducing while the Greenland ice sheet (GrIS) is losing mass at an accelerated pace. Here, we study the seasonal impact of reduced Arctic sea ice on GrIS surface mass balance (SMB), using the Community Earth System Model version 2.1 (CESM2), which features an advanced, interactive calculation of SMB. Addressing the impact of sea-ice reductions on the GrIS SMB from observations is difficult due to the short observational records. Also, signals detected using transient climate simulations may be aliases of other forcings. Here, we analyze dedicated simulations from the Polar Amplification Model Intercomparison Project with reduced Arctic sea ice and compare them with preindustrial sea ice simulations while keeping all other forcings constant. In response to reduced sea ice, the GrIS SMB increases in winter due to increased precipitation, driven by the more humid atmosphere and increasing cyclones. In summer, surface melt increases due to a warmer, more humid atmosphere providing increased energy transfer to the surface through the sensible and latent heat fluxes, which triggers the melt-albedo feedback. Further, warming occurs throughout the entire troposphere over Baffin Bay. This deep warming results in regional enhancement of the 500 hPa geopotential heights over the Baffin Bay and Greenland, increasing blocking and heat advection over the GrIS’ surface. This anomalous circulation pattern has been linked to recent increases in the surface melt of the GrIS.

Modeling turbulent heat fluxes over Arctic sea ice using a maximum-entropy-production approach

Recently, an algorithm of surface turbulent heat fluxes over snow/sea ice has been developed based on the theory of maximum entropy production (MEP), which is fundamentally different from the bulk flux algorithm (BF) that has been used in sea ice models for a few decades. In this study, we first assess how well the MEP algorithm captures the observed variations of turbulent heat fluxes over Arctic sea ice. It is found that the calculated heat fluxes by the MEP method are in good agreement with in-situ observations after considering the absorption of incoming radiation in a snow/ice surface layer with infinitesimal depth. We then investigate the effects of two different schemes (MEP vs. BF) in the sea ice model of CICE6 on simulated turbulent heat fluxes and sea ice processes in the Arctic Basin. Our results show that the two different schemes give quite different representations of seasonal variations of heat fluxes, particularly for sensible heat fluxes in summer. The heat fluxes simulated by the MEP produce weak cooling effect on the ice surface in summer, whereas the BF generates a warming effect. As a result, compared to the BF, the MEP leads to a reduced seasonal cycle of Arctic sea ice mass flux by modulating snow-to-ice conversion, basal ice growth, surface ice melt and basal ice melt.

The prediction data analyzed in "CAPS v1.0: An improved regional coupled modeling system for Arctic sea ice and climate simulation and prediction"

The prediction data analyzed in "CAPS v1.0: An improved regional coupled modeling system for Arctic sea ice and climate simulation and prediction"

Intercomparison of Arctic sea ice simulation in ROMS-CICE and ROMS-Budgell

Accurate representation of the complex ocean-sea ice interaction is still an ongoing effort. In this study, we have coupled the Community Ice Code (CICE) model and Regional Ocean Modeling System (ROMS) to develop a high-resolution regional coupled ocean-sea ice model for polar regions. This setup allows us to investigate the interaction between ocean and sea ice in detail. The Coupled-Ocean-Atmosphere-Wave-Sediment-Transport (COAWST) modeling system is the core of this coupled model. Currently, the ROMS model in COAWST uses the Budgell sea ice model, embedded as a sub-module in it but introducing a more comprehensive sea ice model (CICE) may provide a better treatment of sea ice. Here, we present our preliminary results based on the coupled ROMS-CICE and ROMS-Budgell simulation over the Arctic Ocean. Our results show that both CICE and Budgell models perform better in simulating sea ice concentration during winter than during summer. Compared to the satellite observations, sea ice concentrations from the CICE model in most subregions have higher correlations and smaller centered root mean square errors, showing higher simulation skills. The sea ice thickness biases are larger in the Budgell model in the early months of the year, whereas in the CICE model they are larger after October. Both CICE and Budgell models overestimate the sea ice extent and sea ice volume in summer, and their performances differ in the subregions.

DASSO: a data assimilation system for the Southern Ocean that utilizes both sea-ice concentration and thickness observations

AbstractTo improve Antarctic sea-ice simulations and estimations, an ensemble-based Data Assimilation System for the Southern Ocean (DASSO) was developed based on a regional sea ice–ocean coupled model, which assimilates sea-ice thickness (SIT) together with sea-ice concentration (SIC) derived from satellites. To validate the performance of DASSO, experiments were conducted from 15 April to 14 October 2016. Generally, assimilating SIC and SIT can suppress the overestimation of sea ice in the model-free run. Besides considering uncertainties in the operational atmospheric forcing data, a covariance inflation procedure in data assimilation further improves the simulation of Antarctic sea ice, especially SIT. The results demonstrate the effectiveness of assimilating sea-ice observations in reconstructing the state of Antarctic sea ice, but also highlight the necessity of more reasonable error estimation for the background as well as the observation.

Robust Inter‐Hemispheric Asymmetry in the Response to Symmetric Volcanic Forcing in Model Large Ensembles

AbstractThe climate response to volcanic eruptions in the twentieth century is difficult to separate from the influence of anthropogenic greenhouse gas forcing and internal variability. Here, we make use of recently available large ensembles of Earth‐system model simulations to better understand the forced climate response to contemporary volcanic eruptions. While the Pinatubo eruption in June 1991 resulted in approximately symmetric forcing between the Northern and Southern Hemispheres, the ensemble‐mean simulated temperature and sea ice responses it produces are asymmetric. The strongest cooling and sea ice expansion occur in the Arctic, while the responses in the Antarctic are weak. The damped high‐latitude Southern Hemisphere response to volcanic forcing is analogous to the fast response to increased greenhouse gas concentrations, despite the differing physical nature of the forcing. We find that Arctic cooling in response to a Pinatubo‐scale eruption may not occur due to the high internal variability in that region

An Assessment of the Antarctic Sea Ice Mass Budget Simulation in CMIP6 Historical Experiment

The sea ice formation and dissipation processes are complicated and involve many factors and mechanisms, from the basal growth/melting, the frazil ice formation, the snow ice processes to the dynamic process, etc. The contribution of different factors to the sea ice extent among different models over the Antarctic region has not been systematically evaluated. In this study, we evaluate and quantify the uncertainties of different contributors to the Antarctic Sea ice mass budget among 15 models from the Coupled Model Intercomparison Project Phase 6 (CMIP6). Results show that the simulated total Antarctic Sea ice mass budget is primarily adjusted by the basal growth/melting terms, the frazil ice formation term and the snow-ice term, whereas the top melting terms, the lateral melting terms, the dynamic process and the evaporation process play secondary roles. In addition, while recent studies indicated that the contributors of the Arctic Sea ice formation/dissipation processes show strong coherency among different CMIP models, our results revealed a significant model diversity over the Antarctic region, indicating that the uncertainties of the sea ice formation and dissipation are still considerable in these state-of-the-art climate models. The largest uncertainties appear in the snow ice formation, the basal melting and the top melting terms, whose spread among different models is of the same order of magnitude as the multi-model mean. In some models, large positive bias in the snow ice terms may neutralize the strong negative bias of the basal/top melting terms, resulting in a similar value of the total Antarctic Sea ice area compared with other models, yet with an inaccurate physical process. The uncertainties in these Antarctic Sea ice formation/dissipation terms highlight the importance of further improving the sea ice dynamical and parameterization processes in the state-of-the-art models.

Effects of Wave-Induced Sea Ice Break-Up and Mixing in a High-Resolution Coupled Ice-Ocean Model

Arctic sea ice plays a vital role in modulating the global climate. In the most recent decades, the rapid decline of the Arctic summer sea ice cover has exposed increasing areas of ice-free ocean, with sufficient fetch for waves to develop. This has highlighted the complex and not well-understood nature of wave-ice interactions, requiring modeling effort. Here, we introduce two independent parameterizations in a high-resolution coupled ice-ocean model to investigate the effects of wave-induced sea ice break-up (through albedo change) and mixing on the Arctic sea ice simulation. Our results show that wave-induced sea ice break-up leads to increases in sea ice concentration and thickness in the Bering Sea, the Baffin Sea and the Barents Sea during the ice growth season, but accelerates the sea ice melt in the Chukchi Sea and the East Siberian Sea in summer. Further, wave-induced mixing can decelerate the sea ice formation in winter and the sea ice melt in summer by exchanging the heat fluxes between the surface and subsurface layer. As our baseline model underestimates sea ice cover in winter and produces more sea ice in summer, wave-induced sea ice break-up plays a positive role in improving the sea ice simulation. This study provides two independent parameterizations to directly include the wave effects into the sea ice models, with important implications for the future sea ice model development.

Seismic behaviour analysis of a wind turbine tower affected by sea ice based on a simplified model

Ice-structure interaction threatens the safety of the offshore structure; however, dynamic seismic action even renders this process more sophisticated. This research constructed a simplified calculation model for the wind turbine tower, ice, and water under seismic loading, which could avoid solving the complex non-linear equations. Then, the seismic behaviour of the structure, i.e. wind turbine tower, in the presence and absence of influences of the sea ice was investigated, and we found the remarkable effect of sea ice upon the wind turbine tower when its mass is within a range; the wind turbine tower is found to have reduced capacity in energy dissipation, and thickness of tower walls or stiffening ribs is supposed to be enlarged for making the structure more ductile. Affected by the sea ice, the shear force and bending moment of the tower showed significant increases, and more attention needs to be paid to the tower bottom and action position of the sea ice. According to the dynamic similarity principle, finally paraffin was used to simulate sea ice, and shaking-table tests were performed for simulating dynamic ice-structure-water interactions. Results of shaking-table tests verified the rationality of our proposed simplified model.

Discrete Element Analysis of High-Pressure Zones of Sea Ice on Vertical Structures

In cold regions, ice pressure poses a serious threat to the safe operation of ship hulls and fixed offshore platforms. In this study, a discrete element method (DEM) with bonded particles was adapted to simulate the generation and distribution of local ice pressures during the interaction between level ice and vertical structures. The strength and failure mode of simulated sea ice under uniaxial compression were consistent with the experimental results, which verifies the accuracy of the discrete element parameters. The crushing process of sea ice acting on the vertical structure simulated by the DEM was compared with the field test. The distribution of ice pressure on the contact surface was calculated, and it was found that the local ice pressure was much greater than the global ice pressure. The high-pressure zones in sea ice are mainly caused by its simultaneous destruction, and these zones are primarily distributed near the midline of the contact area of sea ice and the structure. The contact area and loading rate are the two main factors affecting the high-pressure zones. The maximum local and global ice pressures decrease with an increase in the contact area. The influence of the loading rate on the local ice pressure is caused by the change in the sea ice failure mode. When the loading rate is low, ductile failure of sea ice occurs, and the ice pressure increases with the increase in the loading rate. When the loading rate is high, brittle failure of sea ice occurs, and the ice pressure decreases with an increase in the loading rate. This DEM study of sea ice can reasonably predict the distribution of high-pressure zones on marine structures and provide a reference for the anti-ice performance design of marine structures.

Assimilation of Satellite-Retrieved Sea Ice Concentration and Prospects for September Predictions of Arctic Sea Ice

AbstractThe current GFDL seasonal prediction system achieved retrospective sea ice extent (SIE) skill without direct sea ice data assimilation. Here we develop sea ice data assimilation, shown to be a key source of skill for seasonal sea ice predictions, in GFDL’s next-generation prediction system, the Seamless System for Prediction and Earth System Research (SPEAR). Satellite sea ice concentration (SIC) observations are assimilated into the GFDL Sea Ice Simulator version 2 (SIS2) using the ensemble adjustment Kalman filter (EAKF). Sea ice physics is perturbed to form an ensemble of ice–ocean members with atmospheric forcing from the JRA-55 reanalysis. Assimilation is performed every 5 days from 1982 to 2017 and the evaluation is conducted at pan-Arctic and regional scales over the same period. To mitigate an assimilation overshoot problem and improve the analysis, sea surface temperatures (SSTs) are restored to the daily Optimum Interpolation Sea Surface Temperature version 2 (OISSTv2). The combination of SIC assimilation and SST restoring reduces analysis errors to the observational error level (~10%) from up to 3 times larger than this (~30%) in the free-running model. Sensitivity experiments show that the choice of assimilation localization half-width (190 km) is near optimal and that SIC analysis errors can be further reduced slightly either by reducing the observational error or by increasing the assimilation frequency from every 5 days to daily. A lagged-correlation analysis suggests substantial prediction skill improvements from SIC initialization at lead times of less than 2 months.

Observed Antarctic sea ice expansion reproduced in a climate model after correcting biases in sea ice drift velocity

The Antarctic sea ice area expanded significantly during 1979–2015. This is at odds with state-of-the-art climate models, which typically simulate a receding Antarctic sea ice cover in response to increasing greenhouse forcing. Here, we investigate the hypothesis that this discrepancy between models and observations occurs due to simulation biases in the sea ice drift velocity. As a control we use the Community Earth System Model (CESM) Large Ensemble, which has 40 realizations of past and future climate change that all undergo Antarctic sea ice retreat during recent decades. We modify CESM to replace the simulated sea ice velocity field with a satellite-derived estimate of the observed sea ice motion, and we simulate 3 realizations of recent climate change. We find that the Antarctic sea ice expands in all 3 of these realizations, with the simulated spatial structure of the expansion bearing resemblance to observations. The results suggest that the reason CESM has failed to capture the observed Antarctic sea ice expansion is due to simulation biases in the sea ice drift velocity, implying that an improved representation of sea ice motion is crucial for more accurate sea ice projections.