scholarly journals The Response of the Sea Ice Edge to Atmospheric and Oceanic Jet Formation

2014 ◽  
Vol 44 (9) ◽  
pp. 2292-2316 ◽  
Author(s):  
Harold D. B. S. Heorton ◽  
Daniel L. Feltham ◽  
Julian C. R. Hunt
Keyword(s):  
Surface Roughness ◽  
Sea Ice ◽  
Climate Model ◽  
Sharp Change ◽  
Jet Formation ◽  
Ice Drift ◽  
Sea Ice Drift ◽  
Ice Edge ◽  
Sea Ice Edge ◽  
The Impact

Abstract The sea ice edge presents a region of many feedback processes between the atmosphere, ocean, and sea ice (Maslowski et al.). Here the authors focus on the impact of on-ice atmospheric and oceanic flows at the sea ice edge. Mesoscale jet formation due to the Coriolis effect is well understood over sharp changes in surface roughness such as coastlines (Hunt et al.). This sharp change in surface roughness is experienced by the atmosphere and ocean encountering a compacted sea ice edge. This paper presents a study of a dynamic sea ice edge responding to prescribed atmospheric and oceanic jet formation. An idealized analytical model of sea ice drift is developed and compared to a sea ice climate model [the Los Alamos Sea Ice Model (CICE)] run on an idealized domain. The response of the CICE model to jet formation is tested at various resolutions. It is found that the formation of atmospheric jets at the sea ice edge increases the wind speed parallel to the sea ice edge and results in the formation of a sea ice drift jet in agreement with an observed sea ice drift jet (Johannessen et al.). The increase in ice drift speed is dependent upon the angle between the ice edge and wind and results in up to a 40% increase in ice transport along the sea ice edge. The possibility of oceanic jet formation and the resultant effect upon the sea ice edge is less conclusive. Observations and climate model data of the polar oceans have been analyzed to show areas of likely atmospheric jet formation, with the Fram Strait being of particular interest.

scholarly journals Sea-ice edge is more important than closer open water access for foraging Adélie penguins: evidence from two colonies

2020 ◽  
Vol 640 ◽  
pp. 215-230
Author(s):  
C Michelot ◽  
A Kato ◽  
T Raclot ◽  
K Shiomi ◽  
P Goulet ◽  
...  
Keyword(s):  
Sea Ice ◽  
Environmental Changes ◽  
Early Stage ◽  
Open Water ◽  
Gps Tracking ◽  
Ice Edge ◽  
Sea Ice Edge ◽  
Study Sites ◽  
The Impact ◽  
Adélie Penguins

Sentinel species, like Adélie penguins, have been used to assess the impact of environmental changes, and their link with sea ice has received considerable attention. Here, we tested if foraging Adélie penguins from 2 colonies in East Antarctica target the distant sea-ice edge or take advantage of closer open waters that are readily available near their colony. We examined the foraging behaviour of penguins during the incubation trips of females in 2016 and males in 2017, using GPS tracking and diet data in view of daily sea-ice data and bathymetry. In 2016-2017, sea-ice cover was extensive during females’ trips but flaw leads and polynyas were close to both study sites. Sea ice receded rapidly during males’ trips in 2017-2018. Despite close open water near both colonies in both years, females and males preferentially targeted the continental slope and the sea-ice edge to forage. In addition, there was no difference in the diet of penguins from both colonies: all penguins fed mostly on Antarctic krill and males also foraged on Antarctic silverfish. Our results highlight the importance of the sea-ice edge for penguins, an area where food abundance is predictable. It is likely that resource availability was not sufficient in closer open water areas at such an early stage in the breeding season. The behaviours displayed by the penguins from both colonies were similar, suggesting a common behaviour across colonies in Terre Adélie, although additional sites would be necessary to confirm this hypothesis.

scholarly journals The impact of a seasonally ice free Arctic Ocean on the climate and surface mass balance of Svalbard

2011 ◽  
Vol 5 (4) ◽  
pp. 1887-1920
Author(s):  
J. J. Day ◽  
J. L. Bamber ◽  
P. J. Valdes ◽  
J. Kohler
Keyword(s):  
Sea Ice ◽  
Arctic Ocean ◽  
Mass Balance ◽  
21St Century ◽  
Surface Mass Balance ◽  
Surface Mass ◽  
Sea Ice Decline ◽  
Ice Edge ◽  
Sea Ice Edge ◽  
The Impact

Abstract. General circulation models (GCMs) predict a rapid decrease in Arctic sea ice extent in the 21st century. The decline of September sea ice is expected to continue until the Arctic Ocean is seasonally ice free, leading to a much perturbed Arctic climate with large changes in surface energy flux. Svalbard, located on the present day sea ice edge, contains many low lying ice caps and glaciers which are extremely sensitive to changes in climate. Records of past accumulation indicate that the surface mass balance (SMB) of Svalbard is also sensitive to changes in the position of the sea ice edge. To investigate the impact of 21st Century sea ice decline on the climate and surface mass balance of Svalbard a high resolution (25 km) regional climate model (RCM) was forced with a repeating cycle of sea surface temperatures (SSTs) and sea ice conditions for the periods 1961–1990 and 2061–2090. By prescribing 20th Century SSTs and 21st Century sea ice for one simulation, the impact of sea ice decline is isolated. This study shows that the coupled impact of sea ice decline and SST increase results in a decrease in SMB, whereas the impact of sea ice decline alone causes an increase in SMB of similar magnitude.

scholarly journals Evaluation of Arctic sea-ice drift and its dependency on near-surface wind and sea-ice concentration and thickness in the coupled regional climate model HIRHAM-NAOSIM

2019 ◽  
Author(s):  
Xiaoyong Yu ◽  
Annette Rinke ◽  
Wolfgang Dorn ◽  
Gunnar Spreen ◽  
Christof Lüpkes ◽  
...  
Keyword(s):  
Wind Speed ◽  
Sea Ice ◽  
Climate Model ◽  
Regional Climate ◽  
Surface Wind ◽  
Arctic Sea Ice ◽  
Near Surface ◽  
Drift Speed ◽  
Ice Drift ◽  
Sea Ice Drift

Abstract. We examine the simulated Arctic sea-ice drift speed for the period 2003–2014 in the coupled Arctic regional climate model HIRHAM-NAOSIM 2.0. In particular, we evaluate the dependency of the drift speed on the near-surface wind speed and sea-ice conditions. Considering the seasonal cycle of Arctic basin averaged drift speed, the model reproduces the summer-autumn drift speed well, but significantly overestimates the winter-spring drift speed, compared to satellite-derived observations. Also, the model does not capture the observed seasonal phase lag between drift and wind speed, but the simulated drift speed is more in phase with near-surface wind. The model calculates a realistic negative relationship between drift speed and ice thickness and between drift speed and ice concentration during summer-autumn when concentration is relatively low, but the correlation is weaker than observed. A daily grid-scale diagnostic indicates that the model reproduces the observed positive relationship between drift and wind speed. The strongest impact of wind changes on drift speed occurs for high and moderate wind speeds, with a low impact for calm conditions. The correlation under low-wind conditions is overestimated in the simulations, compared to observation/reanalysis. A sensitivity experiment demonstrates the significant effects of sea-ice form drag included by an improved parameterization of the transfer coefficients for momentum and heat over sea ice. However, this does not improve the agreement of the modelled drift speed/wind speed ratio with observations based on reanalysis for wind and remote sensing for sea ice drift. An improvement might be possible, among others, by tuning the open parameters of the parameterization in future.

Towards a swath-to-swath sea-ice drift product for the Copernicus Imaging Microwave Radiometer (CIMR) mission.

2021 ◽  
Author(s):  
Thomas Lavergne ◽  
Montserrat Piñol Solé ◽  
Emily Down ◽  
Craig Donlon
Keyword(s):  
Sea Ice ◽  
Thickness Distribution ◽  
Microwave Radiometer ◽  
Arctic Sea Ice ◽  
Sea Ice Thickness ◽  
Spatial And Temporal Scales ◽  
Location Uncertainty ◽  
Ice Drift ◽  
Sea Ice Drift ◽  
The Impact

<p>Across spatial and temporal scales, sea-ice motion has implications on ship navigation, the sea-ice thickness distribution, sea ice export to lower latitudes and re-circulation in the polar seas, among others. Satellite remote sensing is an effective way to monitor sea-ice drift globally and daily, especially using the wide swaths of passive microwave missions. Since the late 1990s, many algorithms and products have been developed for this task. Here, we investigate how processing sea-ice drift vectors from the intersection of individual swaths of the Advanced Microwave Scanning Radiometer 2 (AMSR2) mission compares to today’s status-quo (processing from daily averaged maps of brightness temperature).</p><p>We document that the “swath-to-swath” (S2S) approach results in many more (two orders of magnitude) sea-ice drift vectors than the “daily-maps” (DM) approach. These S2S vectors also validate better when compared to trajectories of on-ice drifters. For example, the RMSE of the 24 hour Arctic sea-ice drift is 0.9 km for S2S vectors, and 1.3 km for DM vectors from the 36.5 GHz imagery of AMSR2.</p><p>Through a series of experiments with actual AMSR2 data and simulated Copernicus Imaging Microwave Radiometer (CIMR) data, we study the impact that geo-location uncertainty and imaging resolution have on the accuracy of the sea-ice drift vectors. We conclude by recommending that a “swath-to-swath” approach is adopted for the future operational Level-2 sea-ice drift product of the CIMR mission. We outline some potential next steps towards further improving the algorithms, and making the user community ready to fully take advantage of such a product.</p><p>This work is currently under revision at EGU The Cryosphere as https://tc.copernicus.org/preprints/tc-2020-332/</p>

scholarly journals Impact of assimilating a merged sea ice thickness from CryoSat-2 and SMOS in the Arctic reanalysis

2018 ◽  
Author(s):  
Jiping Xie ◽  
Francois Counillon ◽  
Larent Bertino
Keyword(s):  
Sea Ice ◽  
Degrees Of Freedom ◽  
The Arctic ◽  
Ice Thickness ◽  
Large Set ◽  
Sea Ice Thickness ◽  
Ice Drift ◽  
Accurate Forecast ◽  
Sea Ice Drift ◽  
The Impact

Abstract. Accurate forecast of Sea Ice Thickness (SIT) represents a major challenge for Arctic forecasting systems. The new CS2SMOS SIT product merges measurements from the CryoSat-2 and SMOS satellites and is available weekly during the winter months since October 2010. The impact of assimilating CS2SMOS is tested for the TOPAZ4 system – the Arctic component of the Copernicus Marine Environment Monitoring Service (CMEMS). TOPAZ4 currently assimilates a large set of ocean and sea ice observations with the Deterministic Ensemble Kalman Filter (DEnKF). Two parallel reanalyses are conducted with and without assimilation of the previously weekly CS2SMOS for the period from 19th March 2014 to 31st March 2015. The SIT bias (too thin) is reduced from 16 cm to 5 cm and the RMSD decreases from 53 cm to 38 cm (reduction by 28 %) when compared to the simultaneous SIT from CS2SMOS. Furthermore, compared to independent SIT observations, the errors are reduced by 24 % against the Ice Mass Balance (IMB) buoy 2013F and by 11 % against SIT data from the IceBridge campaigns. When compared to sea ice drift derived from International Arctic Buoy Program (IABP) drifting buoys, we find that the assimilation of C2SMOS is beneficial in the sea ice pack areas, where the influence of SIT on the sea ice drift is strongest, with an error reduction of 0.2–0.3 km/day. Finally, we quantify the influence of C2SMOS compared to the other assimilated data by the number of Degrees of Freedom for Signal (DFS) and find that CS2SMOS is the main source of observations in the central Arctic and in the Kara Sea. These results suggest that C2SMOS observations should be included in Arctic reanalyses in order to improve the ice thickness and the ice drift, although some inconsistencies were found in the version of the data used.

scholarly journals Observed Antarctic sea ice expansion reproduced in a climate model after correcting biases in sea ice drift velocity

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Shantong Sun ◽  
Ian Eisenman
Keyword(s):  
Climate Change ◽  
Sea Ice ◽  
Drift Velocity ◽  
Climate Model ◽  
Future Climate Change ◽  
Antarctic Sea Ice ◽  
Ice Drift ◽  
Recent Climate ◽  
Sea Ice Drift ◽  
The Antarctic

AbstractThe Antarctic sea ice area expanded significantly during 1979–2015. This is at odds with state-of-the-art climate models, which typically simulate a receding Antarctic sea ice cover in response to increasing greenhouse forcing. Here, we investigate the hypothesis that this discrepancy between models and observations occurs due to simulation biases in the sea ice drift velocity. As a control we use the Community Earth System Model (CESM) Large Ensemble, which has 40 realizations of past and future climate change that all undergo Antarctic sea ice retreat during recent decades. We modify CESM to replace the simulated sea ice velocity field with a satellite-derived estimate of the observed sea ice motion, and we simulate 3 realizations of recent climate change. We find that the Antarctic sea ice expands in all 3 of these realizations, with the simulated spatial structure of the expansion bearing resemblance to observations. The results suggest that the reason CESM has failed to capture the observed Antarctic sea ice expansion is due to simulation biases in the sea ice drift velocity, implying that an improved representation of sea ice motion is crucial for more accurate sea ice projections.

scholarly journals Impacts of Oceanic and Atmospheric Heat Transports on Sea Ice Extent

2020 ◽  
Vol 33 (16) ◽  
pp. 7197-7215
Author(s):  
Jake Aylmer ◽  
David Ferreira ◽  
Daniel Feltham
Keyword(s):  
Sea Ice ◽  
Heat Transport ◽  
Climate Model ◽  
Balance Model ◽  
Sea Ice Extent ◽  
Transport Component ◽  
Atmospheric Heat Transport ◽  
Ice Edge ◽  
Atmospheric Heat ◽  
The Impact

AbstractClimate-model biases in ocean heat transport (OHT) have been proposed as a major contributor to uncertainties in projections of sea ice extent. To better understand the impact of OHT on sea ice extent and compare it to that of atmospheric heat transport (AHT), an idealized, zonally averaged energy balance model (EBM) is developed. This is distinguished from previous EBM work by coupling a diffusive mixed layer OHT and a prescribed OHT contribution, with an atmospheric EBM and a reduced-complexity sea ice model. The ice-edge latitude is roughly linearly related to the convergence of each heat transport component, with different sensitivities depending on whether the ice cover is perennial or seasonal. In both regimes, Bjerknes compensation (BC) occurs such that the response of AHT partially offsets the impact of changing OHT. As a result, the effective sensitivity of ice-edge retreat to increasing OHT is only ~2/3 of the actual sensitivity (i.e., eliminating the BC effect). In the perennial regime, the sensitivity of the ice edge to OHT is about twice that to AHT, while in the seasonal regime they are similar. The ratio of sensitivities is, to leading order, determined by atmospheric longwave feedback parameters in the perennial regime. Here, there is no parameter range in which the ice edge is more sensitive to AHT than OHT.

scholarly journals Summer extreme cyclone impacts on Arctic sea ice

2021 ◽  
pp. 1-54
Author(s):  
J. V. Lukovich ◽  
Julienne Stroeve ◽  
Alex Crawford ◽  
Lawrence Hamilton ◽  
Michel Tsamados ◽  
...  
Keyword(s):  
Sea Ice ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Dynamic Processes ◽  
Ice Volume ◽  
The Pacific ◽  
Arctic Sea ◽  
Ice Edge ◽  
Sea Ice Edge ◽  
The Impact

AbstractIn this study the impact of extreme cyclones on Arctic sea ice in summer is investigated. Examined in particular are relative thermodynamic and dynamic contributions to sea ice volume budgets in the vicinity of Arctic summer cyclones in 2012 and 2016. Results from this investigation illustrate sea ice loss in the vicinity of the cyclone trajectories during each year were associated with different dominant processes: thermodynamic (melting) in the Pacific sector of the Arctic in 2012, and both thermodynamic and dynamic processes in the Pacific sector of the Arctic in 2016. Comparison of both years further suggests that the Arctic minimum sea ice extent is influenced by not only the strength of the cyclone, but also by the timing and location relative to the sea ice edge. Located near the sea ice edge in early August in 2012, and over the central Arctic later in August in 2016, extreme cyclones contributed to comparable sea ice area (SIA) loss, yet enhanced sea ice volume loss in 2012 relative to 2016.Central to a characterization of extreme cyclone impacts on Arctic sea ice from the perspective of thermodynamic and dynamic processes, we present an index describing relative thermodynamic and dynamic contributions to sea ice volume changes. This index helps to quantify and improve our understanding of initial sea ice state and dynamical responses to cyclones in a rapidly warming Arctic, with implications for seasonal ice forecasting, marine navigation, coastal community infrastructure and designation of protected and ecologically sensitive marine zones.

scholarly journals Evaluation of Arctic sea ice drift and its dependency on near-surface wind and sea ice conditions in the coupled regional climate model HIRHAM–NAOSIM

2020 ◽  
Vol 14 (5) ◽  
pp. 1727-1746
Author(s):  
Xiaoyong Yu ◽  
Annette Rinke ◽  
Wolfgang Dorn ◽  
Gunnar Spreen ◽  
Christof Lüpkes ◽  
...  
Keyword(s):  
Wind Speed ◽  
Sea Ice ◽  
Climate Model ◽  
Regional Climate ◽  
Surface Wind ◽  
Arctic Sea Ice ◽  
Near Surface ◽  
Drift Speed ◽  
Ice Drift ◽  
Sea Ice Drift

Abstract. We examine the simulated Arctic sea ice drift speed for the period 2003–2014 in the coupled Arctic regional climate model HIRHAM–NAOSIM 2.0. In particular, we evaluate the dependency of the drift speed on the near-surface wind speed and sea ice conditions. Considering the seasonal cycle of the Arctic basin averaged drift speed, the model reproduces the summer–autumn drift speed well but significantly overestimates the winter–spring drift speed, compared to satellite-derived observations. Also, the model does not capture the observed seasonal phase lag between drift and wind speed, but the simulated drift speed is more in phase with the near-surface wind. The model calculates a realistic negative correlation between drift speed and ice thickness and between drift speed and ice concentration during summer–autumn when the ice concentration is relatively low, but the correlation is weaker than observed. A daily grid-scale diagnostic indicates that the model reproduces the observed positive correlation between drift and wind speed. The strongest impact of wind changes on drift speed occurs for high and moderate wind speeds, with a low impact for rather calm conditions. The correlation under low-wind conditions is overestimated in the simulations compared to observation/reanalysis data. A sensitivity experiment demonstrates the significant effects of sea ice form drag from floe edges included by an improved parameterization of the transfer coefficients for momentum and heat over sea ice. However, this does not improve the agreement of the modeled drift speed / wind speed ratio with observations based on reanalysis data for wind and remote sensing data for sea ice drift. An improvement might be achieved by tuning parameters that are not well established by observations.

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