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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

LANL Institutional Computing Report: Towards a digital twin of Arctic sea ice

Our goal is to develop a digital twin of Arctic sea ice that combines high-resolution predictive modeling with observational products. This effort will provide an optimized model for use in seasonal to sub-seasonal forecasting and a tool for policymakers to better anticipate, plan for, and mitigate the national security impacts of rapidly changing Arctic conditions. The modeling component uses the Discrete Element Model for Sea Ice (DEMSI), which uses discrete elements to represent the sea ice with an explicit representation of forces between them.

58 GEOSCIENCES↗
DOE OSTI2022

Arctic sea ice albedo: Spectral composition, spatial heterogeneity, and temporal evolution observed during the MOSAiC drift

The magnitude, spectral composition, and variability of the Arctic sea ice surface albedo are key to understanding and numerically simulating Earth’s shortwave energy budget. Spectral and broadband albedos of Arctic sea ice were spatially and temporally sampled by on-ice observers along individual survey lines throughout the sunlit season (April–September, 2020) during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition. The seasonal evolution of albedo for the MOSAiC year was constructed from spatially averaged broadband albedo values for each line. Specific locations were identified as representative of individual ice surface types, including accumulated dry snow, melting snow, bare and melting ice, melting and refreezing ponded ice, and sediment-laden ice. The area-averaged seasonal progression of total albedo recorded during MOSAiC showed remarkable similarity to that recorded 22 years prior on multiyear sea ice during the Surface Heat Budget of the Arctic Ocean (SHEBA) expedition. In accord with these and other previous field efforts, the spectral albedo of relatively thick, snow-free, melting sea ice shows invariance across location, decade, and ice type. In particular, the albedo of snow-free, melting seasonal ice was indistinguishable from that of snow-free, melting second-year ice, suggesting that the highly scattering surface layer that forms on sea ice during the summer is robust and stabilizing. In contrast, the albedo of ponded ice was observed to be highly variable at visible wavelengths. Notable temporal changes in albedo were documented during melt and freeze onset, formation and deepening of melt ponds, and during melt evolution of sediment-laden ice. While model simulations show considerable agreement with the observed seasonal albedo progression, disparities suggest the need to improve how the albedo of both ponded ice and thin, melting ice are simulated.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Impact of Ural Blocking on Early Winter Climate Variability Under Different Barents‐Kara Sea Ice Conditions

Abstract Ural blocking (UB) is a prominent mode of variability of the Northern Hemisphere atmospheric circulation, particularly in fall. It can persist for several days and exert a lagged influence on the wintertime NH circulation, providing predictability at the subseasonal time scale. Using two atmospheric models, we explore how the early winter atmospheric circulation responds to a 2‐week persistent UB anomaly imposed in early November. Experiments are carried out with two different configurations of Barents‐Kara (BK) sea‐ice concentration to examine whether it plays a role in how UB impacts atmospheric variability. In both models, the UB anomaly is followed by a weakening of the stratospheric polar vortex and a negative phase of the North Atlantic Oscillation (NAO), which lasts up to 2 months after the forcing is released. Interestingly, the response is more persistent under low BK sea‐ice conditions, that is, BK sea ice modulates the atmospheric response to UB. Additional experiments with prescribed sea ice concentration anomalies alone suggest that BK sea ice exerts a limited influence on early winter NH atmospheric variability. The response to UB involves a weakening of the polar vortex that persists longer under low BK sea ice, which explains the more persistent response in that configuration. Our study highlights that UB variability in November is a robust precursor for early winter NAO/polar stratosphere anomalies, and this may be more relevant in the context of declining Arctic sea‐ice extent. Provided that climate models accurately capture this teleconnection, it has the potential to improve subseasonal predictions of the NH wintertime climate.

Meteorology & Atmospheric Sciences↗
DOE OSTI2022

Modeling the small-scale deposition of snow onto structured Arctic sea ice during a MOSAiC storm using snowBedFoam 1.0.

The remoteness and extreme conditions of the Arctic make it a very difficult environment to investigate. In these polar regions covered by sea ice, the wind is relatively strong due to the absence of obstructions and redistributes a large part of the deposited snow mass, which complicates estimates for precipitation hardly distinguishable from blowing or drifting snow. Moreover, the snow mass balance in the sea ice system is still poorly understood, notably due to the complex structure of its surface. Quantitatively assessing the snow distribution on sea ice and its connection to the sea ice surface features is an important step to remove the snow mass balance uncertainties (i.e., snow transport contribution) in the Arctic environment. In this work we introduce snowBedFoam 1.0., a physics-based snow transport model implemented in the open-source fluid dynamics software OpenFOAM. We combine the numerical simulations with terrestrial laser scan observations of surface dynamics to simulate snow deposition in a MOSAiC (Multidisciplinary Drifting Observatory for the Study of Arctic Climate) sea ice domain with a complicated structure typical for pressure ridges. The results demonstrate that a large fraction of snow accumulates in their vicinity, which compares favorably against scanner measurements. However, the approximations imposed by the numerical framework, together with potential measurement errors (precipitation), give rise to quantitative inaccuracies, which should be addressed in future work. The modeling of snow distribution on sea ice should help to better constrain precipitation estimates and more generally assess and predict snow and ice dynamics in the Arctic.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Separating the Influences of Low-Latitude Warming and Sea Ice Loss on Northern Hemisphere Climate Change

Abstract Analyzing a multimodel ensemble of coupled climate model simulations forced with Arctic sea ice loss using a two-parameter pattern-scaling technique to remove the cross-coupling between low- and high-latitude responses, the sensitivity to high-latitude sea ice loss is isolated and contrasted to the sensitivity to low-latitude warming. Despite some differences in experimental design, the Northern Hemisphere near-surface atmospheric sensitivity to sea ice loss is found to be robust across models in the cold season; however, a larger intermodel spread is found at the surface in boreal summer, and in the free tropospheric circulation. In contrast, the sensitivity to low-latitude warming is most robust in the free troposphere and in the warm season, with more intermodel spread in the surface ocean and surface heat flux over the Northern Hemisphere. The robust signals associated with sea ice loss include upward turbulent and longwave heat fluxes where sea ice is lost, warming and freshening of the Arctic Ocean, warming of the eastern North Pacific Ocean relative to the western North Pacific with upward turbulent heat fluxes in the Kuroshio Extension, and salinification of the shallow shelf seas of the Arctic Ocean alongside freshening in the subpolar North Atlantic Ocean. In contrast, the robust signals associated with low-latitude warming include intensified ocean warming and upward latent heat fluxes near the western boundary currents, freshening of the Pacific Ocean, salinification of the North Atlantic, and downward sensible and longwave fluxes over the ocean.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Sea ice breakup and freeze-up indicators for users of the Arctic coastal environment

Abstract. The timing of sea ice retreat and advance in Arctic coastal waters varies substantially from year to year. Various activities, ranging from marine transport to the use of sea ice as a platform for industrial activity or winter travel, are affected by variations in the timing of breakup and freeze-up, resulting in a need for indicators to document the regional and temporal variations in coastal areas. The primary objective of this study is to use locally based metrics to construct indicators of breakup and freeze-up in the Arctic and subarctic coastal environment. The indicators developed here are based on daily sea ice concentrations derived from satellite passive-microwave measurements. The “day of year” indicators are designed to optimize value for users while building on past studies characterizing breakup and freeze-up dates in the open pack ice. Relative to indicators for broader adjacent seas, the coastal indicators generally show later breakup at sites known to have landfast ice. The coastal indicators also show earlier freeze-up at some sites in comparison with freeze-up for broader offshore regions, likely tied to earlier freezing of shallow-water regions and areas affected by freshwater input from nearby streams and rivers. A factor analysis performed to synthesize the local indicator variations shows that the local breakup and freeze-up indicators have greater spatial variability than corresponding metrics based on regional ice coverage. However, the trends towards earlier breakup and later freeze-up are unmistakable over the post-1979 period in the synthesized metrics of coastal breakup and freeze-up and the corresponding regional ice coverage. The findings imply that locally defined indicators can serve as key links between pan-Arctic or global indicators such as sea ice extent or volume and local uses of sea ice, with the potential to inform community-scale adaptation and response.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Partitioning uncertainty in projections of Arctic sea ice

Abstract Improved knowledge of the contributing sources of uncertainty in projections of Arctic sea ice over the 21st century is essential for evaluating impacts of a changing Arctic environment. Here, we consider the role of internal variability, model structure and emissions scenario in projections of Arctic sea-ice area (SIA) by using six single model initial-condition large ensembles and a suite of models participating in Phase 5 of the Coupled Model Intercomparison Project. For projections of September Arctic SIA change, internal variability accounts for as much as 40%–60% of the total uncertainty in the next decade, while emissions scenario dominates uncertainty toward the end of the century. Model structure accounts for 60%–70% of the total uncertainty by mid-century and declines to 30% at the end of the 21st century in the summer months. For projections of wintertime Arctic SIA change, internal variability contributes as much as 50%–60% of the total uncertainty in the next decade and impacts total uncertainty at longer lead times when compared to the summertime. In winter, there exists a considerable scenario dependence of model uncertainty with relatively larger model uncertainty under strong forcing compared to weak forcing. At regional scales, the contribution of internal variability can vary widely and strongly depends on the calendar month and region. For wintertime SIA change in the Greenland-Iceland-Norwegian and Barents Seas, internal variability contributes 60%–70% to the total uncertainty over the coming decades and remains important much longer than in other regions. We further find that the relative contribution of internal variability to total uncertainty is state-dependent and increases as sea ice volume declines. These results demonstrate that internal variability is a significant source of uncertainty in projections of Arctic sea ice.

Bonan, David B. (ORCID:0000000338676009)↗
DOE OSTI2019

Emergent Relationships Among Sea Ice, Longwave Radiation, and the Beaufort High Circulation Exposed Through Parameter Uncertainty Analysis

Using a perturbed parameter ensemble of a coupled climate model, emerging relationships are identified between sea ice area, net surface longwave radiation, and the atmospheric circulation over the Beaufort gyre. There is a strong positive correlation between sea ice area and the net longwave radiation over the ocean-ice surface during the melting season and a negative correlation during the freezing season. The mechanisms responsible for the longwave radiation balance at the surface are mainly driven by sea ice variations in the freezing season and by clouds in the melting season. A strong positive (negative) correlation is also found between the fall (summer) total sea ice area in the Arctic and the sea level pressure over the Beaufort High region. It is argued that as sea ice coverage is lost, static stability losses are severe in fall, resulting in enhanced evaporation, vertical motions, and weakening of the general large-scale anticyclonic circulation of the Beaufort High.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Investigating Future Arctic Sea Ice Loss and Near–Surface Wind Speed Changes Related to Surface Roughness Using the Community Earth System Model

The Arctic is undergoing a pronounced and rapid transformation in response to changing greenhouse gasses, including reduction in sea ice extent and thickness. There are also projected increases in near-surface Arctic wind. This study addresses how the winds trends may be driven by changing surface roughness and/or stability in different Arctic regions and seasons, something that has not yet been thoroughly investigated. We analyze 50 experiments from the Community Earth System Model Version 2 (CESM2) Large Ensemble and five experiments using CESM2 with an artificially decreased sea ice roughness to match that of the open ocean. We find that with a smoother surface there are higher mean wind speeds and slower mean ice speeds in the autumn, winter, and spring. The artificially reduced surface roughness also strongly impacts the wind speed trends in autumn and winter, and we find that atmospheric stability changes are also important contributors to driving wind trends in both experiments. In contrast to the clear impacts on winds, the sea ice mean state and trends are statistically indistinguishable, suggesting that near-surface winds are not major drivers of Arctic sea ice loss. Two major results of this work are: (a) the near-surface wind trends are driven by changes in both surface roughness and near-surface atmospheric stability that are themselves changing from sea ice loss, and (b) the sea ice mean state and trends are driven by the overall warming trend due to increasing greenhouse gas emissions and not significantly impacted by coupled feedbacks with the surface winds.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Modeling Sea Ice Effects for Wave Energy Resource Assessments

Wave-generated power has potential as a valuable coastal resource, but the wave climate needs to be mapped for feasibility before wave energy converters are installed. Numerical models are used for wave resource assessments to quantify the amount of available power and its seasonality. Alaska is the U.S. state with the longest coastline and has extensive wave resources, but it is affected by seasonal sea ice that dampens the wave energy and the full extent of this dampening is unknown. To accurately characterize the wave resource in regions that experience seasonal sea ice, coastal wave models must account for these effects. The aim of this study is to determine how the dampening effects of sea ice change wave energy resource assessments in the nearshore. Here, we show that by combining high-resolution sea ice imagery with a sea ice/wave dampening parameterization in an unstructured grid, the Simulating Waves Nearshore (SWAN) model improves wave height predictions and demonstrates the extent to which wave power decreases when sea ice is present. The sea ice parametrization decreases the bias and root mean square errors of wave height comparisons with two wave buoys and predicts a decrease in the wave power of up to 100 kW/m in areas around Prince William Sound, Alaska. The magnitude of the improvement of the model/buoy comparison depends on the coefficients used to parameterize the wave–ice interaction.

16 TIDAL AND WAVE POWER↗
DOE OSTI2021

Sea Ice Collision Risk Assessment for Tidal Turbine Siting in Cook Inlet, Alaska

Cook Inlet has great potential for tidal stream energy development. However, the presence of drifting sea ice could create hazardous collision risks for tidal turbine farms. Before turbines can be installed in Cook Inlet, sites must be surveyed to determine how often sea ice is present, how fast it will be moved by the current, and where the trajectories of drifting sea ice will be concentrated. In this study, we use remotely sensed data to characterize the seasonal sea ice conditions in Cook Inlet, a hydrodynamic model to map the water velocities, and a particle trajectory tracking model to calculate collision risks. The resulting sea ice coverage and collision risk maps will enable tidal energy developers to choose the best locations for the deployment of tidal turbines and other offshore platforms in Cook Inlet.

16 TIDAL AND WAVE POWER↗
DOE OSTI2026

Large Eddy Simulations of the Atmospheric Boundary Layer Over Satellite‐Sensed Sea Ice Maps

Surface heterogeneity in the marginal ice zone (MIZ) causes multiscale secondary atmospheric circulations that are challenging to model or observe. The absence or inadequate representation of these circulations in ocean‐atmosphere exchange schemes in climate models is partially responsible for the underestimation of Arctic sea ice loss. Observationally, such circulations obfuscate the interpretation of polar atmospheric chemistry measurements, among others. To address this open challenge, large‐eddy simulations are conducted over real‐world satellite‐sensed sea ice maps with an ice‐sea temperature contrast, as well as over idealizations of these maps that alter the ice pattern but conserve its fraction, showing that the ice fraction of a surface is not sufficient to predict the surface heat flux. In a second suite of simulations, three other heterogeneity metrics (representing the surface fragmentation, patch edge tortuosity, and patch size variability) are introduced to complement the ice fraction in describing the surface. Simulations varying these parameters suggest that they also significantly impact surface‐air interactions. A roughness contrast is then added to the surface temperature contrast, indicating that the contribution of roughness changes to the resulting atmospheric circulations is less pronounced than that of thermal heterogeneity. Based on these results, we illustrate, using a multi‐linear regression on these map features, that MIZ surface parameterizations in Earth Systems Models can be improved if they account for these various characteristics of the sea‐ice patterns.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Changes in sea ice concentration explain half of the winter warming of the Arctic surface

Arctic winter warming is stronger than in summer, but its driving mechanisms remain debated, particularly the roles of local processes, like sea-ice loss, versus remote factors, like atmospheric heat transport. Here we introduce a novel decomposition framework that characterizes Arctic warming as a function of historical atmospheric circulation, sea ice concentration, and carbon dioxide changes using observational and reanalysis data. We show that sea ice changes explain about 55% of the winter Arctic near-surface temperature trend during 1959–2015, after removing the effects directly connected to atmospheric circulation. Dynamically induced warming accounts for about 20% at surface and up to 80% in mid-troposphere. The remaining ~25% is attributed to the increase in carbon dioxide, though it also indirectly affects sea-ice loss and circulation-related warming. These findings highlight the dominant role of sea ice loss and change in atmospheric dynamics in affecting the historical Arctic winter warming.

Arctic Sea Ice change↗
DOE OSTI2025

Arctic sea-ice loss drives a strong regional atmospheric response over the North Pacific and North Atlantic on decadal scales

Previous studies have suggested that Arctic sea-ice loss can have a profound influence on atmospheric circulation far away from the Arctic. However, there is little scientific consensus on the features of these remote responses, with the opposite impacts reported. Here we present a multi-model analysis of the decadal climate response to Arctic sea-ice loss using state-of-the-art energy conserving methodologies to isolate the impacts of sea-ice decline. We observe weakening of the Aleutian Low and development of a geopotential ridge in the North Pacific, associated with drier winter conditions over the southwest United States. Over the Atlantic, a negative NAO-like response drives wetter winter conditions across the western Mediterranean. These decadal-scale impacts substantially differ from reported centennial-scale responses to Arctic sea-ice loss simulated using non-energy conserving methodologies. Factors such as the timescale of the response and methodologies used to isolate the impacts of disappearing sea-ice cover should be carefully considered when consolidating scientific understanding on the future impacts of changing Arctic.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Overview of the MOSAiC expedition: Snow and sea ice

Year-round observations of the physical snow and ice properties and processes that govern the ice pack evolution and its interaction with the atmosphere and the ocean were conducted during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition of the research vessel Polarstern in the Arctic Ocean from October 2019 to September 2020. This work was embedded into the interdisciplinary design of the 5 MOSAiC teams, studying the atmosphere, the sea ice, the ocean, the ecosystem, and biogeochemical processes. The overall aim of the snow and sea ice observations during MOSAiC was to characterize the physical properties of the snow and ice cover comprehensively in the central Arctic over an entire annual cycle. This objective was achieved by detailed observations of physical properties and of energy and mass balance of snow and ice. By studying snow and sea ice dynamics over nested spatial scales from centimeters to tens of kilometers, the variability across scales can be considered. On-ice observations of in situ and remote sensing properties of the different surface types over all seasons will help to improve numerical process and climate models and to establish and validate novel satellite remote sensing methods; the linkages to accompanying airborne measurements, satellite observations, and results of numerical models are discussed. We found large spatial variabilities of snow metamorphism and thermal regimes impacting sea ice growth. We conclude that the highly variable snow cover needs to be considered in more detail (in observations, remote sensing, and models) to better understand snow-related feedback processes. The ice pack revealed rapid transformations and motions along the drift in all seasons. The number of coupled ice–ocean interface processes observed in detail are expected to guide upcoming research with respect to the changing Arctic sea ice.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

The two radiative states of the Arctic atmosphere and their impacts on the surface energy budget of sea ice

The surface energy budget (SEB) is a central regulator of Arctic climate and sea ice evolution, yet its processes remain poorly constrained due to sparse observations and complex, coupled surface-atmosphere interactions. This study leverages year-long measurements from the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) to provide the most comprehensive assessment to date of the central Arctic SEB and its modulation by atmospheric variability. Ship- and ice-based observations from October 2019 to September 2020 were used to directly measure or tightly constrain each term of the SEB, leading to exceptional energetic closure with the seasonal snow and ice mass balance. The analysis reveals strong seasonal transitions in atmosphere-surface energy transfer that are modulated by the atmospheric state and constrained by the ability of the surface temperature to respond. Classification of the atmosphere into its two dominant radiative states—the semi-transparent (ST) and opaque (OP)—highlights the central role of synoptic-scale variability in clouds. The ST atmospheric state dominated the long winter ice growth season, with limited cloudiness supporting persistent surface radiative cooling and ice growth. The OP state, associated with liquid-containing or thick ice clouds, became dominant in spring, with the combination of increased solar heating and cloud surface longwave warming driving ice and snow melt. Eddy covariance versus bulk approaches for deriving surface turbulent heat fluxes provide vastly different perspectives on the role of turbulence in modulating the SEB. These results establish a high-quality benchmark dataset for Arctic SEB studies and demonstrate how the balance of atmospheric radiative states exerts a first-order control on the annual evolution of the sea ice. The findings have broad implications for advancing observing technologies, understanding Arctic amplification, improving climate models, and predicting future sea ice change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Broadband radiometric measurements from GPS satellites reveal summertime Arctic Ocean Albedo decreases more rapidly than sea ice recedes

Abstract New measurements from the Arctic ± 40 days around the summer solstice show reflected sunlight from north of 80°N decreases 20–35%. Arctic sea ice coverage decreases 7–9% over this same time period (as reported by the NSIDC) implying Arctic sea ice albedo decreases in addition to the sea ice receding. Similar Antarctic measurements provide a baseline to which Arctic measurements are compared. The Antarctic reflected sunlight south of 80°S is up to 30% larger than the Arctic reflectance and is symmetric around the solstice implying constant Antarctic reflectivity. Arctic reflected sunlight 20 days after solstice is > 100W/m 2 less than Antarctic reflected sunlight. For perspective, this is enough heat to melt > 1 mm/hour of ice. This finding should be compared with climate models and in reanalysis data sets to further quantify sea ice albedo’s role in Arctic Amplification. The measurements were made with previously unpublished pixelated radiometers on Global Positioning System satellites from 2014 to 2019. The GPS orbits give each radiometer instantaneous and continuous views of 37% of the Earth, two daily full views of the Arctic and Antarctic. Furthermore, the GPS constellation gives full-time full-Earth coverage that may provide data that complements existing limited field of view instruments that provide a less synoptic Earth view.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

The Vertical Structure of Turbulence Kinetic Energy Near the Arctic Sea‐Ice Surface

Atmospheric turbulence over the Arctic sea-ice surface has been understudied due to the lack of observational data. In this study, we focus on the turbulence kinetic energy (TKE) over sea ice and distinguish its two different vertical structures, the “Surface” type and the “Elevated” type, using observations during the Multidisciplinary drifting Observatory for the Study of Arctic Climate expedition (MOSAiC). The “Surface” type has the maximum TKE near the surface (at 2 m), while the “Elevated” type has the maximum TKE at a higher level (6 m). The TKE budget analysis indicates that the “Elevated” type is caused by the increased shear production of TKE at 6 m. In addition, spectral analysis reveals that the contribution to TKE by horizontal large eddies is enhanced in the “Elevated” type. Finally, how the vertical structure of TKE affects the parameterization of turbulent momentum flux is discussed.

54 ENVIRONMENTAL SCIENCES↗