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 Variability and changes of Arctic sea ice draft distribution – submarine sonar measurements revisited

2011 ◽  
Vol 5 (4) ◽  
pp. 917-929 ◽  
Author(s):  
A. Oikkonen ◽  
J. Haapala
Keyword(s):  
Sea Ice ◽  
Seasonal Variability ◽  
Large Scale ◽  
Thickness Distribution ◽  
Quantitative Information ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Ice Thickness ◽  
First Year ◽  
Pack Ice

Abstract. Changes in the mean sea ice thickness and concentration in the Arctic are well known. However, quantitative information about changes in the ice thickness distribution and the composition of the pack ice is lacking. In this paper we determine the ice draft distributions, mean and modal thicknesses, and their regional and seasonal variability in the Arctic for the time period 1975–2000. We compare characteristics of the Arctic pack ice for the years 1975–1987 and 1988–2000. These periods represent different large-scale atmospheric circulation modes and sea ice circulation patterns, most evident in clearly weaker Beaufort Gyre and stronger as well as westward shifted Transpolar Drift during the later period. The comparison of these two periods reveals that the peak of sea ice draft distributions has narrowed and shifted toward thinner ice, with reductions in both mean and modal ice draft. These noticeable changes are attributed to the loss of thick, mostly deformed ice. Springtime, loss of ice volume with draft greater than 5 m exceeds 35 % in all regions except the Nansen Basin, with as much as 45 % or more at the North Pole and in the Eastern Arctic. Autumn volume reduction, mostly of deformed ice, exceeds 40 % in the Canada Basin only, but is above 30 % also in the Beaufort and Chukchi Seas. During the later period, the volume of ice category consisting thin, mostly level first-year ice, is clearly larger than during the former period, especially in the spring. In the Beaufort Sea region, changes in the composition of ice cover have resulted in a shift of modal draft from level multiyear ice draft range to values of level first-year ice. The regional and seasonal variability of sea ice draft has decreased, since the thinning has been most pronounced in 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 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.

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 The effect of sea-ice parameterizations on the simulation of the Arctic ice pack

1997 ◽  
Vol 25 ◽  
pp. 12-16 ◽  
Author(s):  
Stephen J. Vavrus
Keyword(s):  
Heat Exchange ◽  
Sea Ice ◽  
Mixed Layer ◽  
Large Scale ◽  
Thickness Distribution ◽  
Heat Content ◽  
The Arctic ◽  
Ice Thickness ◽  
Ice Dynamics ◽  
Ice Pack

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.

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

2014 ◽  
Vol 8 (4) ◽  
pp. 4545-4580 ◽  
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 ◽  
Sea Ice Thickness ◽  
Observation Systems

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 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 biases. Observational sources 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 evaluate the systematic differences between eight different observation systems in the Arctic Basin. The approach determines 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 2000–2013 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 2000–2013, while the annual mean ice thickness for the central Arctic Basin alone (the SCICEX Box) has decreased from 3.45 m in 1975 to 1.11 m in 2013, a 68% reduction. This is nearly double the 36% decline reported by an earlier study. These results provide additional direct observational confirmation of substantial sea ice losses found in model analyses.

scholarly journals The effect of sea-ice parameterizations on the simulation of the Arctic ice pack

1997 ◽  
Vol 25 ◽  
pp. 12-16 ◽  
Author(s):  
Stephen J. Vavrus
Keyword(s):  
Heat Exchange ◽  
Sea Ice ◽  
Mixed Layer ◽  
Large Scale ◽  
Thickness Distribution ◽  
Heat Content ◽  
The Arctic ◽  
Ice Thickness ◽  
Ice Dynamics ◽  
Ice Pack

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.

scholarly journals Near Real Time Arctic sea ice thickness and volume from CryoSat-2

2016 ◽  
Author(s):  
R. L. Tilling ◽  
A. Ridout ◽  
A. Shepherd
Keyword(s):  
Sea Ice ◽  
Real Time ◽  
Arctic Sea Ice ◽  
Arctic Climate ◽  
The Arctic ◽  
Ice Thickness ◽  
Satellite Orbits ◽  
Sea Ice Thickness ◽  
Arctic Sea ◽  
Arctic Sea Ice Thickness

Abstract. Timely observations of sea ice thickness help us to understand Arctic climate, and can support maritime activities in the Polar Regions. Although it is possible to calculate Arctic sea ice thickness using measurements acquired by CryoSat-2, the latency of the final release dataset is typically one month, due to the time required to determine precise satellite orbits. We use a new fast delivery CryoSat-2 dataset based on preliminary orbits to compute Arctic sea ice thickness in near real time (NRT), and analyse this data for one sea ice growth season from October 2014 to April 2015. We show that this NRT sea ice thickness product is of comparable accuracy to that produced using the final release CryoSat-2 data, with an average thickness difference of 5 cm, demonstrating that the satellite orbit is not a critical factor in determining sea ice freeboard. In addition, the CryoSat-2 fast delivery product also provides measurements of Arctic sea ice thickness within three days of acquisition by the satellite, and a measurement is delivered, on average, within 10, 7 and 6 km of each location in the Arctic every 2, 14 and 28 days respectively. The CryoSat-2 NRT sea ice thickness dataset provides an additional constraint for seasonal predictions of Arctic climate change, and will allow industries such as tourism and transport to navigate the polar oceans with safety and care.

scholarly journals New insight from CryoSat-2 sea ice thickness for sea ice modelling

2018 ◽  
Author(s):  
David Schröder ◽  
Danny L. Feltham ◽  
Michel Tsamados ◽  
Andy Ridout ◽  
Rachel Tilling
Keyword(s):  
Sea Ice ◽  
Thickness Distribution ◽  
Arctic Sea Ice ◽  
Ice Thickness ◽  
Atmospheric Conditions ◽  
Sea Ice Concentration ◽  
Sea Ice Thickness ◽  
Ice Growth ◽  
Melt Pond ◽  
The Impact

Abstract. Estimates of Arctic sea ice thickness are available from the CryoSat-2 (CS2) radar altimetry mission during ice growth seasons since 2010. We derive the sub-grid scale ice thickness distribution (ITD) with respect to 5 ice thickness categories used in a sea ice component (CICE) of climate simulations. This allows us to initialize the ITD in stand-alone simulations with CICE and to verify the simulated cycle of ice thickness. We find that a default CICE simulation strongly underestimates ice thickness, despite reproducing the inter-annual variability of summer sea ice extent. We can identify the underestimation of winter ice growth as being responsible and show that increasing the ice conductive flux for lower temperatures (bubbly brine scheme) and accounting for the loss of drifting snow results in the simulated sea ice growth being more realistic. Sensitivity studies provide insight into the impact of initial and atmospheric conditions and, thus, on the role of positive and negative feedback processes. During summer, atmospheric conditions are responsible for 50 % of September sea ice thickness variability through the positive sea ice and melt pond albedo feedback. However, atmospheric winter conditions have little impact on winter ice growth due to the dominating negative conductive feedback process: the thinner the ice and snow in autumn, the stronger the ice growth in winter. We conclude that the fate of Arctic summer sea ice is largely controlled by atmospheric conditions during the melting season rather than by winter temperature. Our optimal model configuration does not only improve the simulated sea ice thickness, but also summer sea ice concentration, melt pond fraction, and length of the melt season. It is the first time CS2 sea ice thickness data have been applied successfully to improve sea ice model physics.

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