scholarly journals Impact of the ice strength formulation on the performance of a sea ice thickness distribution model in the Arctic

2017 ◽  
Vol 122 (3) ◽  
pp. 2090-2107 ◽  
Author(s):  
Mischa Ungermann ◽  
L. Bruno Tremblay ◽  
Torge Martin ◽  
Martin Losch
Keyword(s):  
Sea Ice ◽  
Thickness Distribution ◽  
The Arctic ◽  
Distribution Model ◽  
Ice Thickness ◽  
Sea Ice Thickness ◽  
Ice Strength

scholarly journals A Multithickness Sea Ice Model Accounting for Sliding Friction

2006 ◽  
Vol 36 (9) ◽  
pp. 1719-1738 ◽  
Author(s):  
Alexander V. Wilchinsky ◽  
Daniel L. Feltham ◽  
Paul A. Miller
Keyword(s):  
Sea Ice ◽  
Sliding Friction ◽  
Kinematic Model ◽  
The Arctic ◽  
Ice Thickness ◽  
Sea Ice Thickness ◽  
Model Code ◽  
Ice Strength ◽  
Discrete Element Simulations ◽  
Ice Model

Abstract A multithickness sea ice model explicitly accounting for the ridging and sliding friction contributions to sea ice stress is developed. Both ridging and sliding contributions depend on the deformation type through functions adopted from the Ukita and Moritz kinematic model of floe interaction. In contrast to most previous work, the ice strength of a uniform ice sheet of constant ice thickness is taken to be proportional to the ice thickness raised to the 3/2 power, as is revealed in discrete element simulations by Hopkins. The new multithickness sea ice model for sea ice stress has been implemented into the Los Alamos “CICE” sea ice model code and is shown to improve agreement between model predictions and observed spatial distribution of sea ice thickness in the Arctic.

scholarly journals A combined approach of remote sensing and airborne electromagnetics to determine the volume of polynya sea ice in the Laptev Sea

2013 ◽  
Vol 7 (1) ◽  
pp. 441-473 ◽  
Author(s):  
L. Rabenstein ◽  
T. Krumpen ◽  
S. Hendricks ◽  
C. Koeberle ◽  
C. Haas ◽  
...  
Keyword(s):  
Sea Ice ◽  
Thickness Distribution ◽  
Growth Conditions ◽  
Ice Age ◽  
The Arctic ◽  
Ice Thickness ◽  
Laptev Sea ◽  
Volume Estimate ◽  
Sea Ice Thickness ◽  
Level Ice

Abstract. A combined interpretation of synthetic aperture radar (SAR) satellite images and helicopter electromagnetic (HEM) sea-ice thickness data has provided an estimate of sea-ice volume formed in Laptev Sea polynyas during the winter of 2007/08. The evolution of the surveyed sea-ice areas, which were formed between late December 2007 and middle April 2008, was tracked using a series of SAR images with a sampling interval of 2–3 days. Approximately 160 km of HEM data recorded in April 2008 provided sea-ice thicknesses along profiles that transected sea-ice varying in age from 1–116 days. For the volume estimates, thickness information along the HEM profiles was extrapolated to zones of the same age. The error of areal mean thickness information was estimated to be between 0.2 m for younger ice and up to 1.55 m for older ice, with the primary error source being the spatially limited HEM coverage. Our results have demonstrated that the modal thicknesses and mean thicknesses of level ice correlated with the sea-ice age, but that varying dynamic and thermodynamic sea-ice growth conditions resulted in a rather heterogeneous sea-ice thickness distribution on scales of tens of kilometers. Taking all uncertainties into account, total sea-ice area and volume produced within the entire surveyed area were 52 650 km2 and 93.6 ± 26.6 km3. The surveyed polynya contributed 2.0 ± 0.5% of the sea-ice produced throughout the Arctic during the 2007/08 winter. The SAR-HEM volume estimate compares well with the 112 km3 ice production calculated with a high resolution ocean sea-ice model. Measured modal and mean-level ice thicknesses correlate with calculated freezing-degree-day thicknesses with a factor of 0.87–0.89, which was too low to justify the assumption of homogeneous thermodynamic growth conditions in the area, or indicates a strong dynamic thickening of level ice by rafting of even thicker ice.

scholarly journals Variability and changes of Arctic sea ice thickness distribution under different AO/DA states

2011 ◽  
Vol 5 (1) ◽  
pp. 131-167
Author(s):  
A. Oikkonen ◽  
J. Haapala
Keyword(s):  
Sea Ice ◽  
Seasonal Variability ◽  
Large Scale ◽  
Thickness Distribution ◽  
Beaufort Sea ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Ice Thickness ◽  
Sea Ice Thickness ◽  
Ice Pack

Abstract. Changes of the mean sea ice thickness and concentration in the Arctic are well known. However, comparable little is known about the ice thickness distribution and the composition of ice pack in quantity. In this paper we determine the ice thickness distributions, mean and modal thicknesses, and their regional and seasonal variability in the Arctic under different large scale atmospheric circulation modes. We compare characteristics of the Arctic ice pack during the periods 1975–1987 and 1988–2000, which have a different distribution in the AO/DA space. The study is based on submarine measurements of sea ice draft. The prevalent feature is that the peak of sea ice thickness distributions has generally taken a narrower form and shifted toward thinner ice. Also, both mean and modal ice thickness have generally decreased. These noticeable changes result from a loss of thick, mostly deformed, ice. In the spring the loss of the volume of ice thicker than 5 m exceeds 35% in all regions except the Nansen Basin, and the reduction is as much as over 45% at the North Pole and in the Eastern Arctic. In the autumn the volume of thick, mostly deformed ice has decreased by more than 40% in the Canada Basin only, but the reduction is more than 30% also in the Beaufort Sea and in the Chukchi Sea. In the Beaufort Sea region the decrease of the modal draft has been so strong that the peak has shifted from multiyear ice to first-year type ice. Also, the regional and seasonal variability of the sea ice thickness has decreased, since the thinning has been the most pronounced in the regions with the thickest pack ice (the Western Arctic), and during the spring (0.6–0.8 m per decade).

scholarly journals Arctic sea ice drift-strength feedback modelled by NEMO-LIM3.6

2017 ◽  
Author(s):  
David Docquier ◽  
François Massonnet ◽  
Neil F. Tandon ◽  
Olivier Lecomte ◽  
Thierry Fichefet
Keyword(s):  
Sea Ice ◽  
Positive Feedback ◽  
Seasonal Cycle ◽  
The Arctic ◽  
Ice Thickness ◽  
Sea Ice Thickness ◽  
Drift Speed ◽  
Ice Drift ◽  
Sea Ice Drift ◽  
Ice Strength

Abstract. Sea ice cover and thickness have substantially decreased in the Arctic Ocean since the beginning of the satellite era. As a result, sea ice strength has been reduced, allowing more deformation and fracturing and leading to increased sea ice drift speed. The resulting increased sea ice export is thought to further lower sea ice concentration and thickness. We use the global ocean-sea ice NEMO-LIM3.6 model (Nucleus for European Modelling of the Ocean coupled to the Louvain-la-Neuve sea Ice Model), satellite and buoy observations, as well as reanalysis data over the period from 1979 to 2013 to study this positive feedback for the first time in such detail. Overall, the model agrees well with observations in terms of sea ice extent, concentration and thickness. Although the seasonal cycle of sea ice drift speed is reasonably well reproduced by the model, the recent positive trend in drift speed is weaker than observations in summer. NEMO-LIM3.6 is able to capture the relationships between sea ice drift speed, concentration and thickness in terms of seasonal cycle, with higher drift speed for both lower concentration and lower thickness, in agreement with observations. Sensitivity experiments are carried out by varying the initial ice strength and show that higher values of ice strength lead to lower sea ice thickness. We demonstrate that higher ice strength results in a more uniform sea ice thickness distribution, leading to lower heat conduction fluxes, which provide lower ice production, and thus lower ice thickness. This shows that the positive feedback between sea ice drift speed and strength is more than just dynamic, more complex than originally thought and that other processes are at play. The methodology proposed in this analysis provides a benchmark for a further model intercomparison related to the interactions between sea ice drift speed and strength.

The effects of assimilating a sub-grid scale sea ice thickness distribution in a new Arctic sea ice data assimilation system

2021 ◽  
Author(s):  
Nicholas Williams ◽  
Nicholas Byrne ◽  
Daniel Feltham ◽  
Peter Jan Van Leeuwen ◽  
Ross Bannister ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Sea Ice ◽  
Thickness Distribution ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Ice Thickness ◽  
Sea Ice Thickness ◽  
Arctic Sea ◽  
Data Assimilation System ◽  
Assimilation System

<div><span>A modified, standalone version of the Los Alamos Sea Ice Model (CICE) has been coupled to the Parallelized Data Assimilation Framework (PDAF) to produce a new Arctic sea ice data assimilation system CICE-PDAF, with routines for assimilating many types of recently developed sea ice observations. In this study we explore the effects of assimilating a sub-grid scale sea ice thickness distribution derived from Cryosat-2 Arctic sea ice estimates into CICE-PDAF. The true state of the sub-grid scale ice thickness distribution is not well established, and yet it plays a key role in large scale sea ice models and is vital to the dynamical and thermodynamical processes necessary to produce a good representation of the Arctic sea ice state. We examine how assimilating sub-grid scale sea ice thickness distributions can affect the evolution of the sea ice state in CICE-PDAF and better our understanding of the Arctic sea ice system.</span></div>

scholarly journals On the influence of sea-ice physics in multi-decadal ocean-ice hindcasts

2016 ◽  
Author(s):  
Petteri Uotila ◽  
Dorotea Iovino ◽  
Martin Vancoppenolle ◽  
Mikko Lensu ◽  
Clement Rousset
Keyword(s):  
Sea Ice ◽  
Thickness Distribution ◽  
The Arctic ◽  
Ice Thickness ◽  
Polar Regions ◽  
Sea Ice Thickness ◽  
Atmospheric Data ◽  
Single Category ◽  
Ice Model ◽  
Thermodynamic Processes

Abstract. A set of hindcast simulations with the new NEMO3.6 ocean-ice model in the ORCA1 grid and forced by the DFS5.2 atmospheric data was performed from 1958–2012. We focussed on simulations that differ only in their sea-ice component: the old standard version LIM2 and its successor LIM3. Main differences between these sea-ice models are the parameterisations of sub-grid-scale sea-ice thickness distribution, ice deformation, thermodynamic processes, and sea-ice salinity. Our main objective was to diagnose the ocean-ice sensitivity to the updated NEMO-LIM sea-ice physics. Results of such analysis have not been published for this new NEMO version. In the polar regions, NEMO-LIM3 compares better with observations, while NEMO-LIM2 deviates more, producing too much ice in the Arctic, for example. Differences between NEMO-LIM2 and NEMO-LIM3 do not change in simulations even when the freshwater adjustments are turned off. In the extra-polar regions, the oceanographic conditions of the two NEMO-LIM versions remain relatively similar, although they slowly drift apart over decades. A simplified NEMO-LIM3 configuration, having a virtual, single-category sea-ice thickness distribution, produced sea ice with a skill sufficient for ocean-ice hindcasts that target oceanographic studies. We conclude that NEMO3.6 is ready to be used as a stand-alone ocean-ice model and as a component of coupled atmosphere-ocean models.

scholarly journals Impact of the ice thickness distribution discretization on the sea ice concentration variability in the NEMO3.6–LIM3 global ocean–sea ice model

2020 ◽  
Vol 13 (10) ◽  
pp. 4773-4787
Author(s):  
Eduardo Moreno-Chamarro ◽  
Pablo Ortega ◽  
François Massonnet
Keyword(s):  
Sea Ice ◽  
Thickness Distribution ◽  
The Arctic ◽  
Global Ocean ◽  
Ice Thickness ◽  
Model Data ◽  
Atmospheric Variability ◽  
Sea Ice Concentration ◽  
Sea Ice Thickness ◽  
Ice Concentration

Abstract. This study assesses the impact of different sea ice thickness distribution (ITD) discretizations on the sea ice concentration (SIC) variability in ocean stand-alone NEMO3.6–LIM3 simulations. Three ITD discretizations with different numbers of sea ice thickness categories and boundaries are evaluated against three different satellite products (hereafter referred to as “data”). Typical model and data interannual SIC variability is characterized by K-means clustering both in the Arctic and Antarctica between 1979 and 2014. We focus on two seasons, winter (January–March) and summer (August–October), in which correlation coefficients across clusters in individual months are largest. In the Arctic, clusters are computed before and after detrending the series with a second-degree polynomial to separate interannual from longer-term variability. The analysis shows that, before detrending, winter clusters reflect the SIC response to large-scale atmospheric variability at both poles, while summer clusters capture the negative and positive trends in Arctic and Antarctic SIC, respectively. After detrending, Arctic clusters reflect the SIC response to interannual atmospheric variability predominantly. The cluster analysis is complemented with a model–data comparison of the sea ice extent and SIC anomaly patterns. The single-category discretization shows the worst model–data agreement in the Arctic summer before detrending, related to a misrepresentation of the long-term melting trend. Similarly, increasing the number of thin categories reduces model–data agreement in the Arctic, due to a poor representation of the summer melting trend and an overly large winter sea ice volume associated with a net increase in basal ice growth. In contrast, more thin categories improve model realism in Antarctica, and more thick ones improve it in central Arctic regions with very thick ice. In all the analyses we nonetheless identify no optimal discretization. Our results thus suggest that no clear benefit in the representation of SIC variability is obtained from increasing the number of sea ice thickness categories beyond the current standard with five categories in NEMO3.6–LIM3.

scholarly journals Comparing sea ice, hydrography and circulation between NEMO3.6 LIM3 and LIM2

2017 ◽  
Vol 10 (2) ◽  
pp. 1009-1031 ◽  
Author(s):  
Petteri Uotila ◽  
Doroteaciro Iovino ◽  
Martin Vancoppenolle ◽  
Mikko Lensu ◽  
Clement Rousset
Keyword(s):  
Sea Ice ◽  
Thickness Distribution ◽  
The Arctic ◽  
Ice Thickness ◽  
Polar Regions ◽  
Intermediate Water ◽  
Sea Ice Extent ◽  
Sea Ice Thickness ◽  
System Sensitivity ◽  
Ice Model

Abstract. A set of hindcast simulations with the new version 3.6 of the Nucleus for European Modelling of the Ocean (NEMO) ocean–ice model in the ORCA1 configuration and forced by the DRAKKAR Forcing Set version 5.2 (DFS5.2) atmospheric data was performed from 1958 to 2012. Simulations differed in their sea-ice component: the old standard version Louvain-la-Neuve Sea Ice Model (LIM2) and its successor LIM3. Main differences between these sea-ice models are the parameterisations of sub-grid-scale sea-ice thickness distribution, ice deformation, thermodynamic processes, and sea-ice salinity. Our main objective was to analyse the response of the ocean–ice system sensitivity to the change in sea-ice physics. Additional sensitivity simulations were carried out for the attribution of observed differences between the two main simulations.In the Arctic, NEMO-LIM3 compares better with observations by realistically reproducing the sea-ice extent decline during the last few decades due to its multi-category sea-ice thickness. In the Antarctic, NEMO-LIM3 more realistically simulates the seasonal evolution of sea-ice extent than NEMO-LIM2. In terms of oceanic properties, improvements are not as evident, although NEMO-LIM3 reproduces a more realistic hydrography in the Labrador Sea and in the Arctic Ocean, including a reduced cold temperature bias of the Arctic Intermediate Water at 250 m. In the extra-polar regions, the oceanographic conditions of the two NEMO-LIM versions remain relatively similar, although they slowly drift apart over decades. This drift is probably due to a stronger deep water formation around Antarctica in LIM3.

scholarly journals A combined approach of remote sensing and airborne electromagnetics to determine the volume of polynya sea ice in the Laptev Sea

2013 ◽  
Vol 7 (3) ◽  
pp. 947-959 ◽  
Author(s):  
L. Rabenstein ◽  
T. Krumpen ◽  
S. Hendricks ◽  
C. Koeberle ◽  
C. Haas ◽  
...  
Keyword(s):  
Sea Ice ◽  
Thickness Distribution ◽  
Growth Conditions ◽  
Ice Age ◽  
The Arctic ◽  
Ice Thickness ◽  
Laptev Sea ◽  
Volume Estimate ◽  
Sea Ice Thickness ◽  
Level Ice

Abstract. A combined interpretation of synthetic aperture radar (SAR) satellite images and helicopter electromagnetic (HEM) sea-ice thickness data has provided an estimate of sea-ice volume formed in Laptev Sea polynyas during the winter of 2007/08. The evolution of the surveyed sea-ice areas, which were formed between late December 2007 and middle April 2008, was tracked using a series of SAR images with a sampling interval of 2–3 days. Approximately 160 km of HEM data recorded in April 2008 provided sea-ice thicknesses along profiles that transected sea ice varying in age from 1 to 116 days. For the volume estimates, thickness information along the HEM profiles was extrapolated to zones of the same age. The error of areal mean thickness information was estimated to be between 0.2 m for younger ice and up to 1.55 m for older ice, with the primary error source being the spatially limited HEM coverage. Our results have demonstrated that the modal thicknesses and mean thicknesses of level ice correlated with the sea-ice age, but that varying dynamic and thermodynamic sea-ice growth conditions resulted in a rather heterogeneous sea-ice thickness distribution on scales of tens of kilometers. Taking all uncertainties into account, total sea-ice area and volume produced within the entire surveyed area were 52 650 km2 and 93.6 ± 26.6 km3. The surveyed polynya contributed 2.0 ± 0.5% of the sea-ice produced throughout the Arctic during the 2007/08 winter. The SAR-HEM volume estimate compares well with the 112 km3 ice production calculated with a~high-resolution ocean sea-ice model. Measured modal and mean-level ice thicknesses correlate with calculated freezing-degree-day thicknesses with a factor of 0.87–0.89, which was too low to justify the assumption of homogeneous thermodynamic growth conditions in the area, or indicates a strong dynamic thickening of level ice by rafting of even thicker ice.

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