Possible dynamic and thermal causes for the recent decrease in sea ice in the Arctic Basin

2003 ◽  
Vol 108 (C7) ◽  
Author(s):  
Alexander P. Makshtas
Keyword(s):  
Sea Ice ◽  
Arctic Basin ◽  
The Arctic

scholarly journals Retrieval of Snow Depth over Arctic Sea Ice Using a Deep Neural Network

2019 ◽  
Vol 11 (23) ◽  
pp. 2864 ◽  
Author(s):  
Jiping Liu ◽  
Yuanyuan Zhang ◽  
Xiao Cheng ◽  
Yongyun Hu
Keyword(s):  
Neural Network ◽  
Sea Ice ◽  
Snow Depth ◽  
Deep Neural Network ◽  
Arctic Basin ◽  
Temporal Variations ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Sea Ice Thickness ◽  
Arctic Sea

The accurate knowledge of spatial and temporal variations of snow depth over sea ice in the Arctic basin is important for understanding the Arctic energy budget and retrieving sea ice thickness from satellite altimetry. In this study, we develop and validate a new method for retrieving snow depth over Arctic sea ice from brightness temperatures at different frequencies measured by passive microwave radiometers. We construct an ensemble-based deep neural network and use snow depth measured by sea ice mass balance buoys to train the network. First, the accuracy of the retrieved snow depth is validated with observations. The results show the derived snow depth is in good agreement with the observations, in terms of correlation, bias, root mean square error, and probability distribution. Our ensemble-based deep neural network can be used to extend the snow depth retrieval from first-year sea ice (FYI) to multi-year sea ice (MYI), as well as during the melting period. Second, the consistency and discrepancy of snow depth in the Arctic basin between our retrieval using the ensemble-based deep neural network and two other available retrievals using the empirical regression are examined. The results suggest that our snow depth retrieval outperforms these data sets.

scholarly journals On the effect of rheology on seasonal sea-ice simulations

1991 ◽  
Vol 15 ◽  
pp. 17-25 ◽  
Author(s):  
Chi F. Ip ◽  
William D. Hibler ◽  
Gregory M. Flato
Keyword(s):  
Shear Stress ◽  
Sea Ice ◽  
Correlation Coefficients ◽  
Arctic Basin ◽  
The Arctic ◽  
Flow Rule ◽  
Average Model ◽  
Ice Drift ◽  
Cavitating Fluid

A generalized numerical model which allows for a variety of non-linear rheologies is developed for the seasonal simulation of sea-ice circulation and thickness. The model is used to investigate the effects (such as the role of shear stress and the existence of a flow rule) of different rheologies on the ice-drift pattern and build-up in the Arctic Basin. Differences in local drift seem to be closely related to the amount of allowable shear stress. Similarities are found between the elliptical and square cases and between the Mohr-Coulomb and cavitating fluid cases. Comparisons between observed and simulated buoy drift are made for several buoy tracks in the Arctic Basin. Correlation coefficients to the observed buoy drift range from 0.83 for the cavitating fluid to 0.86 for the square rheology. The average ratio of buoy-drift distance to average model-drift distance for several buoys is 1.15 (square), 1.18 (elliptical), 1.30 (Mohr-Coulomb) and 1.40 (cavitating fluid).

scholarly journals Genesis and Decay of Mesoscale Baroclinic Eddies in the Seasonally Ice-Covered Interior Arctic Ocean

2021 ◽  
Vol 51 (1) ◽  
pp. 115-129
Author(s):  
Gianluca Meneghello ◽  
John Marshall ◽  
Camille Lique ◽  
Pål Erik Isachsen ◽  
Edward Doddridge ◽  
...  
Keyword(s):  
Sea Ice ◽  
Arctic Ocean ◽  
Seasonal Cycle ◽  
Climate Models ◽  
Baroclinic Instability ◽  
Temporal Distribution ◽  
Arctic Basin ◽  
Ocean Model ◽  
The Arctic ◽  
Origin And Evolution

AbstractObservations of ocean currents in the Arctic interior show a curious, and hitherto unexplained, vertical and temporal distribution of mesoscale activity. A marked seasonal cycle is found close to the surface: strong eddy activity during summer, observed from both satellites and moorings, is followed by very quiet winters. In contrast, subsurface eddies persist all year long within the deeper halocline and below. Informed by baroclinic instability analysis, we explore the origin and evolution of mesoscale eddies in the seasonally ice-covered interior Arctic Ocean. We find that the surface seasonal cycle is controlled by friction with sea ice, dissipating existing eddies and preventing the growth of new ones. In contrast, subsurface eddies, enabled by interior potential vorticity gradients and shielded by a strong stratification at a depth of approximately 50 m, can grow independently of the presence of sea ice. A high-resolution pan-Arctic ocean model confirms that the interior Arctic basin is baroclinically unstable all year long at depth. We address possible implications for the transport of water masses between the margins and the interior of the Arctic basin, and for climate models’ ability to capture the fundamental difference in mesoscale activity between ice-covered and ice-free regions.

scholarly journals A Model Simulation of 20 Years of Northern Hemisphere Sea-Ice Fluctuations

1984 ◽  
Vol 5 ◽  
pp. 170-176 ◽  
Author(s):  
John E. Walsh ◽  
William D. Hibler ◽  
Becky Ross
Keyword(s):  
Sea Ice ◽  
Northern Hemisphere ◽  
Model Simulation ◽  
Thickness Distribution ◽  
Arctic Basin ◽  
The Arctic ◽  
Data Set ◽  
Ice Dynamics ◽  
Thermodynamic Computations ◽  
Covered Area

A dynamic-thermodynamic sea-ice model (Hibler 1979) is used to simulate northern hemisphere sea ice for a 20-year period, 1961 to 1980. The model is driven by daily atmospheric grids of sea-level pressure (geo-strophic wind) and by temperatures derived from the Russian surface temperature data set. Among the modifications to earlier formulations are the inclusion of snow cover and a multilevel ice-thickness distribution in the thermodynamic computations.The time series of the simulated anomalies show relatively large amounts of ice during the early 1960s and middle 1970s, and relatively small amounts during the late 1960s and early 1970s. The fluctuations of ice mass, both in the entire domain and in individual regions, are more persistent than are the fluctuations of ice-covered area. The ice dynamics tend to introduce more high-frequency variability into the regional (and total) amounts of ice mass. The simulated annual ice export from the Arctic Basin into the East Greenland Sea varies interannually by factors of 3 to 4.

scholarly journals Modeling M2 tidal variability in Arctic Sea-ice drift and deformation

2006 ◽  
Vol 44 ◽  
pp. 418-428 ◽  
Author(s):  
W.D. Hibler ◽  
A. Roberts ◽  
P. Heil ◽  
A.Y. Proshutinsky ◽  
H.L. Simmons ◽  
...  
Keyword(s):  
Sea Ice ◽  
Arctic Basin ◽  
Ocean Model ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Ocean Coupling ◽  
Ice Drift ◽  
Arctic Sea ◽  
Sea Ice Drift ◽  
Tidal Variability

AbstractSemi-diurnal oscillations are a ubiquitous feature of polar Sea-ice motion. Over much of the Arctic basin, inertial and Semi-diurnal tidal variability have Similar frequencies So that periodicity alone is inadequate to determine the Source of oscillations. We investigate the relative roles of tidal and inertial variability in Arctic Sea ice using a barotropic ice–ocean model with Sea ice embedded in an upper boundary layer. Results from this model are compared with ‘levitated’ ice–ocean coupling used in many models. In levitated models the mechanical buoyancy effect of Sea ice is neglected So that convergence of ice, for example, does not affect the oceanic Ekman flux. We use rotary Spectral analysis to compare Simulated and observed results. This helps to interpret the rotation Sense of Sea-ice drift and deformation at the Semi-diurnal period and is a useful discriminator between tidal and inertial effects. Results indicate that the levitated model generates an artificial inertial resonance in the presence of tidal and wind forcing, contrary to the embedded Sea-ice model. We conclude that Sea-ice mechanics can cause the rotational response of ice motion to change Sign even in the presence of Strong and opposing local tidal forcing when a physically consistent dynamic ice–ocean coupling is employed.

scholarly journals Arctic sea ice thickness loss determined using subsurface, aircraft, and satellite observations

2015 ◽  
Vol 9 (1) ◽  
pp. 269-283 ◽  
Author(s):  
R. Lindsay ◽  
A. Schweiger
Keyword(s):  
Sea Ice ◽  
Large Scale ◽  
Spatial Scales ◽  
Arctic Basin ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Ice Thickness ◽  
Spatial And Temporal Variability ◽  
Sampling Errors ◽  
Sea Ice Thickness

Abstract. Sea ice thickness is a fundamental climate state variable that provides an integrated measure of changes in the high-latitude energy balance. However, observations of mean ice thickness have been sparse in time and space, making the construction of observation-based time series difficult. Moreover, different groups use a variety of methods and processing procedures to measure ice thickness, and each observational source likely has different and poorly characterized measurement and sampling errors. Observational sources used in this study include upward-looking sonars mounted on submarines or moorings, electromagnetic sensors on helicopters or aircraft, and lidar or radar altimeters on airplanes or satellites. Here we use a curve-fitting approach to determine the large-scale spatial and temporal variability of the ice thickness as well as the mean differences between the observation systems, using over 3000 estimates of the ice thickness. The thickness estimates are measured over spatial scales of approximately 50 km or time scales of 1 month, and the primary time period analyzed is 2000–2012 when the modern mix of observations is available. Good agreement is found between five of the systems, within 0.15 m, while systematic differences of up to 0.5 m are found for three others compared to the five. The trend in annual mean ice thickness over the Arctic Basin is −0.58 ± 0.07 m decade−1 over the period 2000–2012. Applying our method to the period 1975–2012 for the central Arctic Basin where we have sufficient data (the SCICEX box), we find that the annual mean ice thickness has decreased from 3.59 m in 1975 to 1.25 m in 2012, a 65% reduction. This is nearly double the 36% decline reported by an earlier study. These results provide additional direct observational evidence of substantial sea ice losses found in model analyses.

scholarly journals sea-ice arching and multiple flow States of Arctic pack ice

2006 ◽  
Vol 44 ◽  
pp. 339-344 ◽  
Author(s):  
W.D. Hibler ◽  
J.K. Hutchings ◽  
C.F. Ip
Keyword(s):  
Sea Ice ◽  
Initial Conditions ◽  
Arctic Basin ◽  
The Arctic ◽  
Wind Fields ◽  
Narrow Channels ◽  
Pack Ice ◽  
General Parameter ◽  
Flow Through ◽  
Flow States

AbstractFlow of ice through narrow channels is Significantly affected by the amount of Shear Strength in plastic rheologies used in Sea-ice models as well as in reality. When thermodynamics is added to this problem, the capability of multiple flow States for the Same forcing through narrow passages arises. To understand this problem and examine the potential for Seasonal Stoppage of flow through passages constraining the Arctic basin outflow, the effect of Sea-ice rheology on idealized flow through narrow passages is first analyzed. This ideal analysis is then combined with thermodynamic effects and fluctuating wind fields in an Arctic basin dynamic–thermodynamic Sea-ice model with multiple outlet passages. The results demonstrate that the capability for multiple flow States existing through passages depends on the initial conditions and general ‘climate’ State, and yield insight into the general parameter range over which the Seasonal Stoppage might irreversibly Shift to an unconstrained outflow regime.

Relationship between sea ice freeboard and draft in the Arctic Basin, and implications for ice thickness monitoring

1992 ◽  
Vol 97 (C12) ◽  
pp. 20325 ◽  
Author(s):  
P. Wadhams ◽  
W. B. Tucker ◽  
W. B. Krabill ◽  
R. N. Swift ◽  
J. C. Comiso ◽  
...  
Keyword(s):  
Sea Ice ◽  
Arctic Basin ◽  
The Arctic ◽  
Ice Thickness

scholarly journals Impact of a Reduced Arctic Sea Ice Cover on Ocean and Atmospheric Properties

2012 ◽  
Vol 25 (1) ◽  
pp. 307-319 ◽  
Author(s):  
Jan Sedláček ◽  
Reto Knutti ◽  
Olivia Martius ◽  
Urs Beyerle
Keyword(s):  
Sea Ice ◽  
North Atlantic ◽  
Arctic Basin ◽  
Ice Cover ◽  
Arctic Sea Ice ◽  
Storm Tracks ◽  
The Arctic ◽  
The North ◽  
Arctic Sea ◽  
The North Atlantic

Abstract The Arctic sea ice cover declined over the last few decades and reached a record minimum in 2007, with a slight recovery thereafter. Inspired by this the authors investigate the response of atmospheric and oceanic properties to a 1-yr period of reduced sea ice cover. Two ensembles of equilibrium and transient simulations are produced with the Community Climate System Model. A sea ice change is induced through an albedo change of 1 yr. The sea ice area and thickness recover in both ensembles after 3 and 5 yr, respectively. The sea ice anomaly leads to changes in ocean temperature and salinity to a depth of about 200 m in the Arctic Basin. Further, the salinity and temperature changes in the surface layer trigger a “Great Salinity Anomaly” in the North Atlantic that takes roughly 8 yr to travel across the North Atlantic back to high latitudes. In the atmosphere the changes induced by the sea ice anomaly do not last as long as in the ocean. The response in the transient and equilibrium simulations, while similar overall, differs in specific regional and temporal details. The surface air temperature increases over the Arctic Basin and the anomaly extends through the whole atmospheric column, changing the geopotential height fields and thus the storm tracks. The patterns of warming and thus the position of the geopotential height changes vary in the two ensembles. While the equilibrium simulation shifts the storm tracks to the south over the eastern North Atlantic and Europe, the transient simulation shifts the storm tracks south over the western North Atlantic and North America. The authors propose that the overall reduction in sea ice cover is important for producing ocean anomalies; however, for atmospheric anomalies the regional location of the sea ice anomalies is more important. While observed trends in Arctic sea ice are large and exceed those simulated by comprehensive climate models, there is little evidence based on this particular model that the seasonal loss of sea ice (e.g., as occurred in 2007) would constitute a threshold after which the Arctic would exhibit nonlinear, irreversible, or strongly accelerated sea ice loss. Caution should be exerted when extrapolating short-term trends to future sea ice behavior.

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