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NASA NTRS1984

The sensitivity of a one-dimensional thermodynamic sea ice model to changes in cloudiness

A thermodynamic sea ice-lead model is used to assess the importance of cloud cover changes to modeled ice thickness. For regions of either permanent multiyear ice or seasonal sea ice, the cloud amount variations have relatively little impact. However, for regions where the presence of summer ice is variable from year to year, the predicted ice thickness is strongly dependent on cloud cover. In general, with a snow covered surface, decreased cloud leads to surface cooling while increased cloud gives rise to a surface warming. For a melting bare ice surface, the reverse occurs. The ice model response time is too long for interannual variations in cloud amount to explain interannual variations in ice thickness and extent. Nevertheless, the implication of the results is that numerical modeling of sea ice distribution requires accurate cloud data or cloud prediction and that trends in cloud cover may lead to significant perturbations in sea ice extent and thickness.

Shine, K. P.↗

NASA NTRS1985

Sensitivity of a thermodynamic sea ice model with leads to time step size

The characteristics of sea ice models, developed to study the physics of the growth and melt of ice at the ocean surface and the variations in ice extent, depend on the size of the time step. Thus, to study longer-term variations within a reasonable computer budget, a model with a scheme allowing longer time steps has been constructed. However, the results produced by the model can definitely depend on the length of the time step. The sensitivity of a model to time-step size can be reduced by appropriate approaches. The present investigation is concerned with experiments which use a formulation of a lead parameterization that can be considered as a first step toward the development of a lead parameterization suitable for a use in long-term climate studies.

Ledley, T. S.↗

NASA NTRS1992

Cryosphere and climate

This chapter will discuss two main issues related to the cryosphere and climate. One is the effect of sea ice and salinity gradients on ocean circulation, and in particular the possible role of sea ice transport on the ocean conveyer belt. The other is the effect of the cryosphere on climate, and in particular in high-latitude warming under increased CO2. In understanding the role of the cryosphere in both cases, it is useful to elucidate two types of toy sea ice models. Neither of these represents reality, but both are useful for illustrating the archetypal features of sea ice that control much of its large-scale behavior. The first model is a simple slab thermodynamic sea ice model as presented by Thorndike. In this model there are no dynamical effects and the thickness of ice is determined by surface heat budget and oceanic heat flux considerations, with the thickness of the ice critically affecting the effective conductivity whereby heat is transferred from the bottom ice boundary to the upper ice boundary. In this model all of the sea ice characteristics are controlled by the vertical heat fluxes from the atmosphere and ocean into the ice. The thickness is controlled by the ice's becoming an effective insulator as it thickens, thus reducing conductive heat loss to the atmosphere. A second model emphasizes the effects of dynamics. It considers the ice pack to be a collection of floes moving in response to synoptic wind fields and ocean currents. These motions create semipermanent leads (open areas) over which ice can grow rapidly.

Hibler, William D., III↗

NASA NTRS2011

Observations of Recent Arctic Sea Ice Volume Loss and Its Impact on Ocean-Atmosphere Energy Exchange and Ice Production

Using recently developed techniques we estimate snow and sea ice thickness distributions for the Arctic basin through the combination of freeboard data from the Ice, Cloud, and land Elevation Satellite (ICESat) and a snow depth model. These data are used with meteorological data and a thermodynamic sea ice model to calculate ocean-atmosphere heat exchange and ice volume production during the 2003-2008 fall and winter seasons. The calculated heat fluxes and ice growth rates are in agreement with previous observations over multiyear ice. In this study, we calculate heat fluxes and ice growth rates for the full distribution of ice thicknesses covering the Arctic basin and determine the impact of ice thickness change on the calculated values. Thinning of the sea ice is observed which greatly increases the 2005-2007 fall period ocean-atmosphere heat fluxes compared to those observed in 2003. Although there was also a decline in sea ice thickness for the winter periods, the winter time heat flux was found to be less impacted by the observed changes in ice thickness. A large increase in the net Arctic ocean-atmosphere heat output is also observed in the fall periods due to changes in the areal coverage of sea ice. The anomalously low sea ice coverage in 2007 led to a net ocean-atmosphere heat output approximately 3 times greater than was observed in previous years and suggests that sea ice losses are now playing a role in increasing surface air temperatures in the Arctic.

Kurtz, N. T.↗

NASA NTRS1992

The role of sea ice dynamics in global climate change

The topics covered include the following: general characteristics of sea ice drift; sea ice rheology; ice thickness distribution; sea ice thermodynamic models; equilibrium thermodynamic models; effect of internal brine pockets and snow cover; model simulations of Arctic Sea ice; and sensitivity of sea ice models to climate change.

Hibler, William D., III↗

NASA NTRS1984

Numerical Simulation of North Atlantic Sea Ice Variability, 1951 - 1980

A two-level dynamic-thermodynamic sea ice model is used to simulate the growth, drift and decay of sea ice in the Northern Hemisphere during a 30-year period, 1951 to 1980. The model is run with a daily timestep on a 222 km grid and is forced by interanually varying fields of geostrophic wind and temperature-derived thermodynamic fluxes. The objective is a quantitative description of large-scale sea ice variability in terms of the dynamic and thermodynamic processes responsible for the fluctuations, especially in the North Atlantic where sea ice represents a substantial input of fresh water. The fields of ice velocity and thickness contain strong seasonal as well as interannual variability. The mean drift pattern results in thicknesses of 4 to 5 m offshore of northern Canada and Greenland, while winter thicknesses of approximately 2 m are typical of Alaskan. Eurasian and East Greenland coastal waters. The 30-year mean fields are characterized by ecessive ice in the North Atlantic during winter and by a summer retreat that is more rapid than observed.

Walsh, J. E.↗

NASA NTRS1990

Multilayer sea ice in the Arctic - Model- and satellite-derived

The behavior of sea ice is a strong function of ice strength which, in the central Arctic, depends on the relative fractions of multiyear and first-year ice coverage. A dynamic-thermodynamic sea ice model has been configured to include both multiyear and first-year ice. The model has been run for a 7-year period, 1979-1985, for which a satellite microwave record of multiyear sea ice coverage is available. The simulated concentrations of multiyear ice are slightly higher than the satellite-derived concentrations, although the total coverage of simulated multiyear ice agrees well with the satellite-derived coverage. Both the simulated and the satellite-derived coverages in the early 1980s show large interannual variations that represent potentially large perturbations in the mass balance of Arctic pack ice. These fluctuations are generally consistent in the model and satellite data, and they are generally consistent with year-to-year differences in the large-scale wind forcing. In at least some cases the wintertime distribution of multiyear ice is influenced by the pattern of ice drift as far back as the previous summer. The late December coverage of multiyear ice in the Alaskan region appears to foreshadow summer ice conditions in the same region. The short-term response to an intense synoptic system is considerably larger in the satellite data than in the model results.

Walsh, John E.↗

NASA NTRS1988

Late Pleistocene variations in Antarctica sea ice. I - Effect of orbital isolation changes. II - Effect of interhemispheric deep-ocean heat exchange

A dynamic-thermodynamic sea-ice model is presently used to ascertain the effects of orbitally-induced insolation changes on Antarctic sea-ice cover; the results thus obtained are compared with modified CLIMAP reconstructions of sea-ice 18,000 years ago. The minor influence exerted by insolation on Pleistocene sea-ice distributions is attributable to a number of factors. In the second part of this investigation, variations in the production of warm North Atlantic Deep Water are proposed as a mechanism constituting the linkage between climate fluctuations in the Northern and Southern hemispheres during the Pleistocene; this hypothesis is tested by examining the sensitivity of the dynamic-thermodynamic model for Antarctic sea-ice changes in vertical ocean heat flux, and comparing the simulations with modified CLIMAP sea-ice maps for 18,000 years ago.

Crowley, Thomas J.↗

NASA NTRS1985

Sea ice - Multiyear cycles and white ice

The multiyear thickness cycles represent one of the interesting features of the sea ice studies performed by Semtner (1976) and Washington et al. (1976) with simple thermodynamic models of sea ice. In the present article, a description is given of results which show that the insulating effect of snow on the surface of the sea ice is important in producing these multiyear cycles given the physics included in the model. However, when the formation of white ice is included, the cycles almost disappear. White ice is the ice which forms at the snow-ice interface when the snow layer becomes thick enough to depress the ice below the water level. Water infiltrates the snow by coming through the ice at leads and generally freezes there, forming white ice.

Ledley, T. S.↗

NASA NTRS2006

Simulations of Sea-Ice Dynamics Using the Material-Point Method

In recent years, the availability of large volumes of recorded ice motion derived from high-resolution SAR data has provided an amazingly detailed look at the deformation of the ice cover. The deformation is dominated by the appearance of linear kinematic features that have been associated with the presence of leads. These remarkable data put us in a position to begin detailed evaluation of current coupled mechanical and thermodynamic models of sea ice. This presentation will describe the material point method (MPM) for solving these model equations. MPM is a numerical method for continuum mechanics that combines the best aspects of Lagrangian and Eulerian discretizations. The material points provide a Lagrangian description of the ice that models convection naturally. Thus, properties such as ice thickness and compactness are computed in a Lagrangian frame and do not suffer from errors associated with Eulerian advection schemes, such as artificial diffusion, dispersion, or oscillations near discontinuities. This desirable property is illustrated by solving transport of ice in uniform, rotational and convergent velocity fields. Moreover, the ice geometry is represented by unconnected material points rather than a grid. This representation facilitates modeling the large deformations observed in the Arctic, as well as localized deformation along leads, and admits a sharp representation of the ice edge. MPM also easily allows the use of any ice constitutive model. The versatility of MPM is demonstrated by using two constitutive models for simulations of wind-driven ice. The first model is a standard viscous-plastic model with two thickness categories. The MPM solution to the viscous-plastic model agrees with previously published results using finite elements. The second model is a new elastic-decohesive model that explicitly represents leads. The model includes a mechanism to initiate leads, and to predict their orientation and width. The elastic-decohesion model can provide similar overall deformation as the viscous-plastic model; however, explicit regions of opening and shear are predicted. Furthermore, the efficiency of MPM with the elastic-decohesive model is competitive with the current best methods for sea ice dynamics. Simulations will also be presented for an area of the Beaufort Sea, where predictions can be validated against satellite observations of the Arctic.

Sulsky, D.↗

NASA NTRS1997

Year-Round Pack Ice in the Weddell Sea, Antarctica: Response and Sensitivity to Atmospheric and Oceanic Forcing

Using a dynamic-thermodynamic numerical sea-ice model, external oceanic and atmospheric forcings on sea ice in the Weddell Sea are examined to identify physical processes associated with the seasonal cycle of pack ice, and to identify further the parameters that coupled models need to consider in predicting the response of the pack ice to climate and ocean-circulation changes. In agreement with earlier studies, the primary influence on the winter ice-edge maximum extent is air temperature. Ocean heat flux has more impact on the minimum-ice-edge extent and in reducing pack-ice thickness, especially in the eastern-Weddell Sea. Low relative humidity enhances ice growth in thin ice and open-water regions, producing a more realistic ice edge along the coastal areas of the western-Weddell Sea where dry continental air has an impact. The modeled extent of the Weddell summer pack is equally sensitive to ocean heat flux and atmospheric relative humidity variations with the more dynamic responses being from the atmosphere. Since the atmospheric regime in the eastern Weddell is dominated by marine intrusions from lower latitudes, with high humidity already, it is unlikely that either the moisture trans- port could be further raised or that it could be significantly lowered because of its distance from the continent (the lower humidity source). Ocean heat-transport variability is shown to lead to overall ice thinning in the model response and is a known feature of the actual system, as evidenced by the occurrence of the Weddell Polynya in the mid 1970s.

Geiger, Cathleen A.↗

NASA NTRS1980

Sea ice simulations based on fields generated by the GLAS GCM

The GLAS General Circulation Model (GCM) was applied to the four-month simulation of the thermodynamic part of the Parkinson-Washington sea ice model using atmospheric boundary conditions. The sea ice thickness and distribution were predicted for the Jan. 1-Apr. 30 period using the GCM-fields of solar and infrared radiation, specific humidity and air temperature at the surface, and snow accumulation; the sensible heat and evaporative surface fluxes were consistent with the ground temperatures produced by the ice model and the air temperatures determined by the atmospheric concept. It was concluded that the Parkinson-Washington sea ice model results in acceptable ice concentrations and thicknesses when used with GLAS GCM for the Jan.-Apr. period suggesting the feasibility of fully coupled ice-atmosphere simulations with these two approaches.

Parkinson, C. L.↗

NASA NTRS1983

Numerical simulation of the Weddell Sea pack ice

In order to determine the degree to which a coupled dynamic thermodynamic model can reproduce the seasonal cycle of the Antarctic Sea ice in the Weddell Sea, a series of two-year simulations of the Weddell Sea ice pack were carried out. The simulations employed Hibler's (1979) model and used a one-day time step on an 18 x 15 grid with a resolution of 222 km. Daily atmospheric data from 1979 were used to drive the simulations. The simulations yielded a seasonal cycle of ice with maximum and minimum extents close to that observed. Except for portions of the western Weddell, the advance of the ice is found to be primarily thermodynamic in nature, while the rapid decay depends critically on the presence of both leads and lateral ice advection. In early summer the ice motion causes a residual tongue of ice to extend eastward from the Antarctic Peninsula in agreement with observations. Mean ice thicknesses are consistent with observations, as are the mean drift rates of about 5 km/day.

Hibler, W. D., III↗

NASA NTRS2022

Effects of Increasing the Category Resolution of the Sea Ice Thickness Distribution in a Coupled Climate Model on Arctic and Antarctic Sea Ice Mean State

Many modern sea ice models used in global climate models represent the subgrid-scale heterogeneity in sea ice thickness with an ice thickness distribution (ITD), which improves model realism by representing the significant impact of the high spatial heterogeneity of sea ice thickness on thermodynamic and dynamic processes. Most models default to five thickness categories. However, little has been done to explore the effects of the resolution of this distribution (number of categories) on sea-ice feedbacks in a coupled model framework and resulting representation of the sea ice mean state. Here, we explore this using sensitivity experiments in CESM2 with the standard 5 ice thickness categories and 15 ice thickness categories. Increasing the resolution of the ITD in a run with preindustrial climate forcing results in substantially thicker Arctic sea ice year-round. Analyses show that this is a result of the ITD influence on ice strength. With 15 ITD categories, weaker ice occurs for the same average thickness, resulting in a higher fraction of ridged sea ice. In contrast, the higher resolution of thin ice categories results in enhanced heat conduction and bottom growth and leads to only somewhat increased winter Antarctic sea ice volume. The spatial resolution of the ICESat-2 satellite mission provides a new opportunity to compare model outputs with observations of seasonal evolution of the ITD in the Arctic (ICESat-2; 2018–2021). Comparisons highlight significant differences from the ITD modeled with both runs over this period, likely pointing to underlying issues contributing to the representation of average thickness.

Madison M. Smith↗

NASA NTRS2023

Importance of Atmospheric Feedbacks in Simulating the Seasonal Cycle of the Antarctic Sea Ice and Its Response to Perturbations

The seasonal cycle of the Antarctic sea ice extent is largely controlled by the evolution of the insolation received at the top of the atmosphere. However, sea ice processes and feedbacks with the ocean and the atmosphere can modulate this seasonal cycle. Here, the atmospheric feedbacks are quantified in a series of idealized sensitivity experiments performed with an eddy-permitting (1/4°) NEMO-LIM3 Southern Ocean configuration, including a representation of ice shelf cavities, in which the model was either driven by an atmospheric reanalysis or coupled to the COSMO-CLM 2 regional atmospheric model. In these experiments, sea ice thermodynamics and dynamics as well as the exchanges with the ocean and atmosphere are strongly perturbed. This perturbation is achieved by modifying snow and ice thermal conductivities, the vertical mixing in the ocean top layers, the effect of freshwater uptake/release upon sea ice growth/melt, ice dynamics and surface albedo. We show that the changes in surface heat fluxes are very different between the configurations driven by the reanalysis and those coupled to the atmosphere. Atmospheric feedbacks enhance the response of the modelled winter ice extent to any of the perturbed processes, and the enhancement is strongest when the albedo is modified. The response of sea ice volume and extent to changes in entrainment of subsurface warm waters to the ocean surface is also greatly amplified by the coupling with the atmosphere. By contrast, the atmospheric feedbacks can damp the impact of the perturbations affecting the heat conductivity through sea ice.

Atmospheric feedbacks↗

NASA NTRS2023

Modulation of the Seasonal Cycle of the Antarctic Sea Ice Extent By Sea Ice Processes and Feedbacks With the Ocean and the Atmosphere

The seasonal cycle of the Antarctic sea ice extent is strongly asymmetric, with a relatively slow increase after the summer minimum followed by a more rapid decrease after the winter maximum. This cycle is intimately linked to the seasonal cycle of the insolation received at the top of the atmosphere, but sea ice processes as well as the exchanges with the atmosphere and ocean may also play a role. To quantify these contributions, a series of idealized sensitivity experiments have been performed with an eddy-permitting (∘) NEMO-LIM3 (Nucleus for European Modelling of the Ocean–Louvain-la-Neuve sea ice model version 3) Southern Ocean configuration, including a representation of ice shelf cavities, in which the model was either driven by an atmospheric reanalysis or coupled to the COSMO-CLM2 regional atmospheric model. In those experiments, sea ice thermodynamics and dynamics as well as the exchanges with the ocean and atmosphere are strongly perturbed. This perturbation is achieved by modifying snow and ice thermal conductivities, the vertical mixing in the ocean top layers, the effect of freshwater uptake and release upon sea ice growth and melt, ice dynamics, and surface albedo. We find that the evolution of sea ice extent during the ice advance season is largely independent of the direct effect of the perturbation and appears thus mainly controlled by initial state in summer and subsequent insolation changes. In contrast, the melting rate varies strongly between the experiments during the retreat, in particular if the surface albedo or sea ice transport are modified, demonstrating a strong contribution of those elements to the evolution of ice coverage through spring and summer. As with the advance phase, the retreat is also influenced by conditions at the beginning of the melt season in September. Atmospheric feedbacks enhance the model winter ice extent response to any of the perturbed processes, and the enhancement is strongest when the albedo is modified. The response of sea ice volume and extent to changes in entrainment of subsurface warm waters to the ocean surface is also greatly amplified by the coupling with the atmosphere.

regional atmosphere ocean sea ice model↗

NASA NTRS1996

Surface Turbulent Fluxes Over Pack Ice Inferred from TOVS Observations

A one-dimensional, atmospheric boundary layer model is coupled to a thermodynamic ice model to estimate the surface turbulent fluxes over thick sea ice. The principal forcing parameters in this time-dependent model are the air temperature, humidity, and wind speed at a specified level (either at 2 m or at 850 mb) and the downwelling surface radiative fluxes. The free parameters. are the air temperature, humidity, and wind speed profiles below the specified level, the surface skin temperature, the ice temperature profile, and the surface turbulent fluxes. The goal is to determine how well we can estimate the turbulent surface heat and momentum fluxes using forcing parameters from atmospheric temperatures and radiative fluxes retrieved from the TIROS-N Operational Vertical Sounder (TOVS) data. Meteorological observations from the Lead Experiment (LeadEx, April 1992) ice camp are used to validate turbulent fluxes computed with the surface observations and the results are used to compare with estimates based on radio-sonde observations or with estimates based on TOVS data. We find that the TOVS-based estimates of the stress are significantly more accurate than those found with a constant geostrophic drag coefficient, with a root-mean-square error about half as large. This improvement is due to stratification effects included in the boundary layer model. The errors in the sensible heat flux estimates, however, are large compared to the small mean values observed during the field experiment.

Lindsay, R. W.↗

NASA NTRS2022

Constraining Arctic Climate Projections of Wintertime Warming With Surface Turbulent Flux Observations and Representation of Surface-Atmosphere Coupling

The drivers of rapid Arctic climate change—record sea ice loss, warming SSTs, and a lengthening of the sea ice melt season—compel us to understand how this complex system operates and use this knowledge to enhance Arctic predictability. Changing energy flows sparked by sea ice decline, spotlight atmosphere-surface coupling processes as central to Arctic system function and its climate change response. Despite this, the representation of surface turbulent flux parameterizations in models has not kept pace with our understanding. The large uncertainty in Arctic climate change projections, the central role of atmosphere-surface coupling, and the large discrepancy in model representation of surface turbulent fluxes indicates that these processes may serve as useful observational constraints on projected Arctic climate change. This possibility requires an evaluation of surface turbulent fluxes and their sensitivity to controlling factors (surface-air temperature and moisture differences, sea ice, and winds) within contemporary climate models (here Coupled Model Intercomparison Project 6). The influence of individual controlling factors and their interactions is diagnosed using a multi-linear regression approach. This evaluation is done for four sea ice loss regimes, determined from observational sea ice loss trends, to control for the confounding effects of natural variability between models and observations. The comparisons between satellite- and model-derived surface turbulent fluxes illustrate that while models capture the general sensitivity of surface turbulent fluxes to declining sea ice and to surface-air gradients of temperature and moisture, substantial mean state biases exist. Specifically, the central Arctic is too weak of a heat sink to the winter atmosphere compared to observations, with implications to the simulated atmospheric circulation variability and thermodynamic profiles. Models were found to be about 50% more efficient at turning an air-sea temperature gradient anomaly into a sensible heat flux anomaly relative to observations. Further, the influence of sea ice concentration on the sensible heat flux is underestimated in models compared to observations. The opposite is found for the latent heat flux variability in models; where the latent heat flux is too sensitive to a sea ice concentration anomaly. Lastly, the results suggest that present-day trends in sea ice retreat regions may serve as suitable observational constraints of projected Arctic warming.

turbulent fluxes↗