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

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.

1984 ◽  
Vol 5 ◽  
pp. 170-176 ◽  
Author(s):  
John E. Walsh ◽  
William D. Hibler ◽  
Becky Ross

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.


2021 ◽  
Author(s):  
Frédéric Dupont ◽  
Dany Dumont ◽  
Jean-François Lemieux ◽  
Elie Dumas-Lefebvre ◽  
Alain Caya

Abstract. In some coastal regions of the Arctic Ocean, as well as in shallow seasonally ice-covered seas, grounded ice ridges contribute to stabilizing and maintaining a landfast ice cover. Recently, a grounding scheme representing this effect on sea ice dynamics was introduced and tested in a coupled ice-ocean model. This grounding scheme, based on a parameterization of ridged keel thickness linearly correlated to the mean thickness, improves the simulation of landfast ice in many regions such as in the East Siberian Sea, the Laptev Sea and along the coast of Alaska. Nevertheless, this parameterization is based solely on the mean properties of sea ice. Here, we extend the parameterization by taking into account subgridscale ice thickness distribution and bathymetry distributions, which are generally non-normal, and by computing the maximum seabed stress as a joint probability interaction between the ice and the seabed. The probabilistic approach shows a reasonably good agreement with observations and with the previously proposed grounding scheme while potentially offering more physical insights in the formation of landfast ice.


Elem Sci Anth ◽  
2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Tricia A. Stadnyk ◽  
A. Tefs ◽  
M. Broesky ◽  
S. J. Déry ◽  
P. G. Myers ◽  
...  

The pan-Arctic domain is undergoing some of Earth’s most rapid and significant changes resulting from anthropogenic and climate-induced alteration of freshwater distribution. Changes in terrestrial freshwater discharge entering the Arctic Basin from pan-Arctic watersheds significantly impact oceanic circulation and sea ice dynamics. Historical streamflow records in high-latitude basins are often discontinuous (seasonal or with large temporal gaps) or sparse (poor spatial coverage), however, making trends from observed records difficult to quantify. Our objectives were to generate a more continuous 90-year record (1981–2070) of spatially distributed freshwater flux for the Arctic Basin (all Arctic draining rivers, including the Yukon), suitable for forcing ocean models, and to analyze the changing simulated trends in freshwater discharge across the domain. We established these data as valid during the historical period (1971–2015) and then used projected futures (preserving uncertainty by running a coupled climate-hydrologic ensemble) to analyze long-term (2021–2070) trends for major Arctic draining rivers. When compared to historic trends reported in the literature, we find that trends are projected to nearly double by 2070, with river discharge to the Arctic Basin increasing by 22% (on average) by 2070. We also find a significant trend toward earlier onset of spring freshet and a general flattening of the average annual hydrograph, with a trend toward decreasing seasonality of Arctic freshwater discharge with climate change and regulation combined. The coupled climate-hydrologic ensemble was then used to force an ocean circulation model to simulate freshwater content and thermohaline circulation. This research provides the marine research community with a daily time series of historic and projected freshwater discharge suitable for forcing sea ice and ocean models. Although important, this work is only a first step in mapping the impacts of climate change on the pan-Arctic region.


1997 ◽  
Vol 25 ◽  
pp. 12-16 ◽  
Author(s):  
Stephen J. Vavrus

A one-dimensional (1-D), thermodynamic sea-ice model with parameterized ice dynamics is coupled to a mixed-layer ocean model and driven with prescribed atmospheric forcings for the central Arctic. The model is used to calculate the sensitivity of the ice pack to various parameterizations that have traditionally been neglected or considered only implicitly in large-scale sea-ice models. The model includes melt ponds, leads (with summertime stratification), an ice-export term, a stability-dependent air–sea heat-exchange coefficient, a prognostic ocean–ice heat exchange, a crude ice-thickness distribution, and a sophisticated albedo parameterization.The ice pack is sensitive to the partitioning of solar energy between lateral melting and mixed-layer warming, with the most realistic simulations occurring when the heat is nearly evenly divided between these two processes. Conversely, ice thickness and coverage are fairly insensitive to the amount of lateral mixing within the upper ocean, vertical mixing within leads, and to the partitioning of mixed-layer heat content between warming the water and melting the ice bottom. The ice concentration during summer is strongly dependent on the assumed ice-thickness distribution: the amount of open water during summer is less than half the size of the empirically based distribution used here, compared with one in which ice floes are distributed uniformly across a range of thicknesses.


1990 ◽  
Vol 14 ◽  
pp. 338-339
Author(s):  
W.D. Hibler ◽  
Peter Ranelli

The seasonal cycle of sea ice, especially the ice margin location in the East Greenland region, is significantly affected by ocean circulation. The ocean circulation in turn can be altered by ice dynamics which cause large amounts of ice to be transported to the ice margin to be melted, thus stratifying the ocean there. By responding to wind changes, the ice dynamics can also create rapid melting or freezing events which can destabilize the ocean.In an earlier study, Hibler and Bryan (1987) carried out a diagnostic simulation of the Arctic ice-ocean system in which a coupled ice-ocean circulation model was integrated for about five years beginning with mean annual estimates by Levitus (1982) of the observed temperature and salinity fields. As a consequence of this short integration, the mean baroclinic circulation of the ocean deviated little from the initial fields, although seasonal and local effects due to the interactive models were simulated. One particularly interesting result of this study was the presence of fluctuations of oceanic heat flux at the ice margin, which appeared to coincide with strong wind events occurring over a few days which induced periods of freezing.With this diagnostic model, good results for the location of the ice margin were obtained. However, a global budget analysis indicated that the net northward heat transport through the Faero–Shetland passage was not adequate to balance the heat loss to the atmosphere sustained by the ocean in the fifth year. Moreover, a 20-year simulation without diagnostic terms showed a degraduation of the baroclinic fields in the Arctic Basin possibly due to the very weak wind stress used for this particular years's wind forcing, or perhaps due to excessive damping in the ocean due to computational requirements imposed by the coarse grid.As a first step in the development of a higher-resolution fully interactive prognostic model, we have modified this model and carried out two prognostic simulations of the Arctic ice ocean system by employing 50-year integrations. The ocean model used for this study is essentially that of Hibler and Bryan (1987). However, the boundary conditions, atmospheric forcing, and ice model have been changed. In particular, a much more robust wind forcing was obtained by replacing the monthly mean wind fields with a 30-year means in order to obtain a seasonal forcing closer to climatology. With regard to the ice rheology, a cavitating fluid model in spherical coordinates which fully conserves ice mass and air sea heat exchanges was employed. The idea here is to attenuate less of the stress into the ocean so that even though the circulation is somewhat sluggish due to large viscous damping, a reasonable current field for the Arctic Basin might be obtained.Two types of prognostic circulation experiments were carried out with this model using different southern boundary conditions. In one case, a diagnostic relaxation near the boundary as used by Hibler and Bryan (1987) was employed. In this case, heat mass and salt transports through the southern boundary are essentially simulated. In the second case, the net burotropic flow through the Faero-Shetland passage and Denmark Strait were specified with the baroclinic transports partially specified by diagnostic relaxation terms. The results from both these models are analyzed with special attention to the ice edge location and the character of the baroclinic fields in the Arctic Basin.


1997 ◽  
Vol 25 ◽  
pp. 12-16 ◽  
Author(s):  
Stephen J. Vavrus

A one-dimensional (1-D), thermodynamic sea-ice model with parameterized ice dynamics is coupled to a mixed-layer ocean model and driven with prescribed atmospheric forcings for the central Arctic. The model is used to calculate the sensitivity of the ice pack to various parameterizations that have traditionally been neglected or considered only implicitly in large-scale sea-ice models. The model includes melt ponds, leads (with summertime stratification), an ice-export term, a stability-dependent air–sea heat-exchange coefficient, a prognostic ocean–ice heat exchange, a crude ice-thickness distribution, and a sophisticated albedo parameterization.The ice pack is sensitive to the partitioning of solar energy between lateral melting and mixed-layer warming, with the most realistic simulations occurring when the heat is nearly evenly divided between these two processes. Conversely, ice thickness and coverage are fairly insensitive to the amount of lateral mixing within the upper ocean, vertical mixing within leads, and to the partitioning of mixed-layer heat content between warming the water and melting the ice bottom. The ice concentration during summer is strongly dependent on the assumed ice-thickness distribution: the amount of open water during summer is less than half the size of the empirically based distribution used here, compared with one in which ice floes are distributed uniformly across a range of thicknesses.


1990 ◽  
Vol 14 ◽  
pp. 338-339
Author(s):  
W.D. Hibler ◽  
Peter Ranelli

The seasonal cycle of sea ice, especially the ice margin location in the East Greenland region, is significantly affected by ocean circulation. The ocean circulation in turn can be altered by ice dynamics which cause large amounts of ice to be transported to the ice margin to be melted, thus stratifying the ocean there. By responding to wind changes, the ice dynamics can also create rapid melting or freezing events which can destabilize the ocean. In an earlier study, Hibler and Bryan (1987) carried out a diagnostic simulation of the Arctic ice-ocean system in which a coupled ice-ocean circulation model was integrated for about five years beginning with mean annual estimates by Levitus (1982) of the observed temperature and salinity fields. As a consequence of this short integration, the mean baroclinic circulation of the ocean deviated little from the initial fields, although seasonal and local effects due to the interactive models were simulated. One particularly interesting result of this study was the presence of fluctuations of oceanic heat flux at the ice margin, which appeared to coincide with strong wind events occurring over a few days which induced periods of freezing. With this diagnostic model, good results for the location of the ice margin were obtained. However, a global budget analysis indicated that the net northward heat transport through the Faero–Shetland passage was not adequate to balance the heat loss to the atmosphere sustained by the ocean in the fifth year. Moreover, a 20-year simulation without diagnostic terms showed a degraduation of the baroclinic fields in the Arctic Basin possibly due to the very weak wind stress used for this particular years's wind forcing, or perhaps due to excessive damping in the ocean due to computational requirements imposed by the coarse grid. As a first step in the development of a higher-resolution fully interactive prognostic model, we have modified this model and carried out two prognostic simulations of the Arctic ice ocean system by employing 50-year integrations. The ocean model used for this study is essentially that of Hibler and Bryan (1987). However, the boundary conditions, atmospheric forcing, and ice model have been changed. In particular, a much more robust wind forcing was obtained by replacing the monthly mean wind fields with a 30-year means in order to obtain a seasonal forcing closer to climatology. With regard to the ice rheology, a cavitating fluid model in spherical coordinates which fully conserves ice mass and air sea heat exchanges was employed. The idea here is to attenuate less of the stress into the ocean so that even though the circulation is somewhat sluggish due to large viscous damping, a reasonable current field for the Arctic Basin might be obtained. Two types of prognostic circulation experiments were carried out with this model using different southern boundary conditions. In one case, a diagnostic relaxation near the boundary as used by Hibler and Bryan (1987) was employed. In this case, heat mass and salt transports through the southern boundary are essentially simulated. In the second case, the net burotropic flow through the Faero-Shetland passage and Denmark Strait were specified with the baroclinic transports partially specified by diagnostic relaxation terms. The results from both these models are analyzed with special attention to the ice edge location and the character of the baroclinic fields in the Arctic Basin.


2019 ◽  
Vol 11 (23) ◽  
pp. 2864 ◽  
Author(s):  
Jiping Liu ◽  
Yuanyuan Zhang ◽  
Xiao Cheng ◽  
Yongyun Hu

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.


2017 ◽  
Vol 14 (12) ◽  
pp. 3129-3155 ◽  
Author(s):  
Hakase Hayashida ◽  
Nadja Steiner ◽  
Adam Monahan ◽  
Virginie Galindo ◽  
Martine Lizotte ◽  
...  

Abstract. Sea ice represents an additional oceanic source of the climatically active gas dimethyl sulfide (DMS) for the Arctic atmosphere. To what extent this source contributes to the dynamics of summertime Arctic clouds is, however, not known due to scarcity of field measurements. In this study, we developed a coupled sea ice–ocean ecosystem–sulfur cycle model to investigate the potential impact of bottom-ice DMS and its precursor dimethylsulfoniopropionate (DMSP) on the oceanic production and emissions of DMS in the Arctic. The results of the 1-D model simulation were compared with field data collected during May and June of 2010 in Resolute Passage. Our results reproduced the accumulation of DMS and DMSP in the bottom ice during the development of an ice algal bloom. The release of these sulfur species took place predominantly during the earlier phase of the melt period, resulting in an increase of DMS and DMSP in the underlying water column prior to the onset of an under-ice phytoplankton bloom. Production and removal rates of processes considered in the model are analyzed to identify the processes dominating the budgets of DMS and DMSP both in the bottom ice and the underlying water column. When openings in the ice were taken into account, the simulated sea–air DMS flux during the melt period was dominated by episodic spikes of up to 8.1 µmol m−2 d−1. Further model simulations were conducted to assess the effects of the incorporation of sea-ice biogeochemistry on DMS production and emissions, as well as the sensitivity of our results to changes of uncertain model parameters of the sea-ice sulfur cycle. The results highlight the importance of taking into account both the sea-ice sulfur cycle and ecosystem in the flux estimates of oceanic DMS near the ice margins and identify key uncertainties in processes and rates that should be better constrained by new observations.


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