scholarly journals The seasonal cycle and break-up of landfast sea ice along the northwest coast of Kotelny Island, East Siberian Sea

2021 ◽  
pp. 1-13
Author(s):  
Mengxi Zhai ◽  
Bin Cheng ◽  
Matti Leppäranta ◽  
Fengming Hui ◽  
Xinqing Li ◽  
...  
Keyword(s):  
Sea Ice ◽  
Seasonal Cycle ◽  
Regional Climate ◽  
Northwest Coast ◽  
Ice Thickness ◽  
East Siberian Sea ◽  
Ice Fracturing ◽  
Break Up ◽  
Landfast Sea Ice ◽  
Initial Freezing

Abstract Arctic landfast sea ice (LFSI) represents an important quasi-stationary coastal zone. Its evolution is determined by the regional climate and bathymetry. This study investigated the seasonal cycle and interannual variations of LFSI along the northwest coast of Kotelny Island. Initial freezing, rapid ice formation, stable and decay stages were identified in the seasonal cycle based on application of the visual inspection approach (VIA) to MODIS/Envisat imagery and results from a thermodynamic snow/ice model. The modeled annual maximum ice thickness in 1995–2014 was 2.02 ± 0.12 m showing a trend of −0.13 m decade−1. Shortened ice season length (−22 d decade−1) from model results associated with substantial spring (2.3°C decade−1) and fall (1.9°C decade−1) warming. LFSI break-up resulted from combined fracturing and melting, and the local spatiotemporal patterns of break-up were associated with the irregular bathymetry. Melting dominated the LFSI break-up in the nearshore sheltered area, and the ice thickness decreased to an average of 0.50 m before the LFSI disappeared. For the LFSI adjacent to drift ice, fracturing was the dominant process and the average ice thickness was 1.56 m at the occurrence of the fracturing. The LFSI stages detected by VIA were supported by the model results.

scholarly journals Spatial variation of biogeochemical properties of landfast sea ice in the Gulf of Bothnia, Baltic Sea

2006 ◽  
Vol 44 ◽  
pp. 80-87 ◽  
Author(s):  
M. Steffens ◽  
M.A. Granskog ◽  
H. Kaartokallio ◽  
H. Kuosa ◽  
K. Luodekari ◽  
...  
Keyword(s):  
Sea Ice ◽  
Baltic Sea ◽  
Snow Depth ◽  
Large Scale ◽  
Spatial Scales ◽  
Thick Layer ◽  
Ice Cores ◽  
Ice Thickness ◽  
Gulf Of Bothnia ◽  
Landfast Sea Ice

AbstractHorizontal variation of landfast sea-ice properties was studied in the Gulf of Bothnia, Baltic Sea, during March 2004. In order to estimate their variability among and within different spatial levels, 72 ice cores were sampled on five spatial scales (with spacings of 10 cm, 2.5 m, 25 m, 250m and 2.5 km) using a hierarchical sampling design. Entire cores were melted, and bulk-ice salinity, concentrations of chlorophylla(Chla), phaeophytin (Phaeo), dissolved nitrate plus nitrite (DIN) as well as dissolved organic carbon (DOC) and nitrogen (DON) were determined. All sampling sites were covered by a 5.5–23 cm thick layer of snow. Ice thicknesses of cores varied from 26 to 58 cm, with bulk-ice salinities ranging between 0.2 and 0.7 as is typical for Baltic Sea ice. Observed values for Chla(range: 0.8–6.0 mg ChlaL–1; median: 2.9 mg ChlaL–1) and DOC (range: 37–397 μM; median: 95 μM) were comparable to values reported by previous sea-ice studies from the Baltic Sea. Analysis of variance among different spatial levels revealed significant differences on the 2.5km scale for ice thickness, DOC and Phaeo (with the latter two being positively correlated with ice thickness). For salinity and Chla, the 250 m scale was found to be the largest scale where significant differences could be detected, while snow depth only varied significantly on the 25 m scale. Variability on the 2.5 m scale contributed significantly to the total variation for ice thickness, salinity, Chlaand DIN. In the case of DON, none of the investigated levels exhibited variation that was significantly different from the considerable amount of variation found between replicate cores. Results from a principal component analysis suggest that ice thickness is one of the main elements structuring the investigated ice habitat on a large scale, while snow depth, nutrients and salinity seem to be of secondary importance.

Observation and thermodynamic modeling of the influence of snow cover on landfast sea ice thickness in Prydz Bay, East Antarctica

2020 ◽  
Author(s):  
Jiechen Zhao ◽  
Bin Cheng ◽  
Timo Vihma ◽  
Qinghua Yang ◽  
Fengming Hui ◽  
...  
Keyword(s):  
Sea Ice ◽  
Snow Cover ◽  
Annual Cycle ◽  
Snow Depth ◽  
Snow Accumulation ◽  
East Antarctica ◽  
Prydz Bay ◽  
Ice Thickness ◽  
Sea Ice Thickness ◽  
Landfast Sea Ice

<p>The observed snow depth and ice thickness on landfast sea ice in Prydz Bay, East Antarctica, were used to determine the role of snow in (a) the annual cycle of sea ice thickness at a fixed location (SIP) where snow usually blows away after snowfall and (b) early summer sea ice thickness within the transportation route surveys (TRS) domain farther from coast, where annual snow accumulation is substantial. The annual mean snow depth and maximum ice thickness had a negative relationship (r = −0.58, p < 0.05) at SIP, indicating a primary insulation effect of snow on ice thickness. However, in the TRS domain, this effect was negligible because snow contributes to ice thickness. A one-dimensional thermodynamic sea ice model, forced by local weather observations, reproduced the annual cycle of ice thickness at SIP well. During the freeze season, the modeled maximum difference of ice thickness using different snowfall scenarios ranged from 0.53–0.61 m. Snow cover delayed ice surface and ice bottom melting by 45 and 24 days, respectively. The modeled snow ice and superimposed ice accounted for 4–23% and 5–8% of the total maximum ice thickness on an annual basis in the case of initial ice thickness ranging from 0.05–2 m, respectively.</p>

scholarly journals Medium-range predictability of early summer sea ice thickness distribution in the East Siberian Sea based on the TOPAZ4 ice–ocean data assimilation system

2018 ◽  
Vol 12 (6) ◽  
pp. 2005-2020 ◽  
Author(s):  
Takuya Nakanowatari ◽  
Jun Inoue ◽  
Kazutoshi Sato ◽  
Laurent Bertino ◽  
Jiping Xie ◽  
...  
Keyword(s):  
Sea Ice ◽  
Lead Time ◽  
Early Summer ◽  
Ice Thickness ◽  
Sea Ice Thickness ◽  
Ocean Data Assimilation ◽  
East Siberian Sea ◽  
Medium Range ◽  
Maritime Navigation ◽  
Data Assimilation System

Abstract. Accelerated retreat of Arctic Ocean summertime sea ice has focused attention on the potential use of the Northern Sea Route (NSR), for which sea ice thickness (SIT) information is crucial for safe maritime navigation. This study evaluated the medium-range (lead time below 10 days) forecast of SIT distribution in the East Siberian Sea (ESS) in early summer (June–July) based on the TOPAZ4 ice–ocean data assimilation system. A comparison of the operational model SIT data with reliable SIT estimates (hindcast, satellite and in situ data) showed that the TOPAZ4 reanalysis qualitatively reproduces the tongue-like distribution of SIT in ESS in early summer and the seasonal variations. Pattern correlation analysis of the SIT forecast data over 3 years (2014–2016) reveals that the early summer SIT distribution is accurately predicted for a lead time of up to 3 days, but that the prediction accuracy drops abruptly after the fourth day, which is related to a dynamical process controlled by synoptic-scale atmospheric fluctuations. For longer lead times ( >  4 days), the thermodynamic melting process takes over, which contributes to most of the remaining prediction accuracy. In July 2014, during which an ice-blocking incident occurred, relatively thick SIT ( ∼  150 cm) was simulated over the ESS, which is consistent with the reduction in vessel speed. These results suggest that TOPAZ4 sea ice information has great potential for practical applications in summertime maritime navigation via the NSR.

scholarly journals Medium-range predictability of early summer sea ice thickness distribution in the East Siberian Sea: Importance of dynamical and thermodynamic melting processes

2018 ◽  
Author(s):  
Takuya Nakanowatari ◽  
Jun Inoue ◽  
Kazutoshi Sato ◽  
Laurent Bertino ◽  
Jiping Xie ◽  
...  
Keyword(s):  
Sea Ice ◽  
Lead Time ◽  
Early Summer ◽  
Prediction Skill ◽  
Ice Thickness ◽  
Dynamical Process ◽  
Sea Ice Thickness ◽  
East Siberian Sea ◽  
Medium Range ◽  
Maritime Navigation

Abstract. Accelerated retreat of Arctic Ocean summertime sea ice has focused attention on the potential use of the Northern Sea Route (NSR), for which sea ice thickness (SIT) information is crucial for safe maritime navigation. This study evaluated the medium-range (lead time below 10 days) forecast skill of SIT distribution in the East Siberian Sea (ESS) in early summer (June–July) based on the TOPAZ4 ice ocean data assimilation system. Comparison of the operational model SIT data to all available observations (in situ and satellite) showed that the TOPAZ4 reanalysis reproduces the observed seasonal cycle and the rates of advance and melting of SIT in the ESS, with average bias of approximately ±20 cm. Pattern correlation analysis of the SIT forecast data over 4 years (2013–2016) reveals that the early summer SIT distribution is skillfully predicted for a lead time of up to 3 days, but that the prediction skill drops abruptly after the 4th day, which is related to dynamical process controlled by synoptic-scale atmospheric fluctuations. For longer lead times (> 4 days), the thermodynamic melting process takes over, which makes most of the remaining prediction skill. In July 2014, during which an ice-blocking incident occurred, relatively thick SIT (approximately 150 cm) was simulated over the ESS, which is consistent with the reduction of vessel speed. These results suggest that TOPAZ4 sea ice information has a great potential for practical applications in summertime maritime navigation via the NSR.

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 Seasonal Cycle of Sea Ice Thickness on the North East Greenland Shelf

2015 ◽  
Author(s):  
E. Hansen ◽  
S. Gerland ◽  
G. Spreen ◽  
K. Høyland
Keyword(s):  
Sea Ice ◽  
Seasonal Cycle ◽  
Ice Thickness ◽  
Sea Ice Thickness ◽  
East Greenland ◽  
North East ◽  
The North

scholarly journals Seasonal dynamics of Totten Ice Shelf controlled by sea ice buttressing

2018 ◽  
Vol 12 (9) ◽  
pp. 2869-2882 ◽  
Author(s):  
Chad A. Greene ◽  
Duncan A. Young ◽  
David E. Gwyther ◽  
Benjamin K. Galton-Fenzi ◽  
Donald D. Blankenship
Keyword(s):  
Sea Ice ◽  
Seasonal Cycle ◽  
Satellite Image ◽  
Back Stress ◽  
Surface Velocity ◽  
Ice Shelf ◽  
Ice Velocity ◽  
Glacier Velocity ◽  
Landfast Sea Ice ◽  
Image Pairs

Abstract. Previous studies of Totten Ice Shelf have employed surface velocity measurements to estimate its mass balance and understand its sensitivities to interannual changes in climate forcing. However, displacement measurements acquired over timescales of days to weeks may not accurately characterize long-term flow rates wherein ice velocity fluctuates with the seasons. Quantifying annual mass budgets or analyzing interannual changes in ice velocity requires knowing when and where observations of glacier velocity could be aliased by subannual variability. Here, we analyze 16 years of velocity data for Totten Ice Shelf, which we generate at subannual resolution by applying feature-tracking algorithms to several hundred satellite image pairs. We identify a seasonal cycle characterized by a spring to autumn speedup of more than 100 m yr−1 close to the ice front. The amplitude of the seasonal cycle diminishes with distance from the open ocean, suggesting the presence of a resistive back stress at the ice front that is strongest in winter. Springtime acceleration precedes summer surface melt and is not attributable to thinning from basal melt. We attribute the onset of ice shelf acceleration each spring to the loss of buttressing from the breakup of seasonal landfast sea ice.

scholarly journals Parameter Optimization in Sea Ice Models with Elastic-Viscoplastic Rheology

2019 ◽  
Author(s):  
Gleb Panteleev ◽  
Max Yaremchuk ◽  
Jacob N. Stroh ◽  
Oceana P. Francis ◽  
Richard Allard
Keyword(s):  
Sea Ice ◽  
Stress Tensor ◽  
Initial Conditions ◽  
Adjoint Equation ◽  
Model Performance ◽  
Observation System ◽  
Ice Thickness ◽  
Sea Ice Thickness ◽  
Minimization Procedure ◽  
Landfast Sea Ice

Abstract. Ice rheology formulation is the key component of the modern sea ice modeling. In the CICE6 community model, rheology and landfast grounding/arching effects are simulated by functions of the sea ice thickness and concentration with a set of fixed parameters empirically adjusted to optimize the model performance. In this study we consider a spatially variable extension of representing these parameters in the two-dimensional EVP sea ice model with a formulation similar to CICE6. Feasibility of optimization of the rheological and landfast sea ice parameters is assessed by applying variational data assimilation to the synthetic observations of ice concentration, thickness and velocity. It is found that the tangent linear and adjoint models featuring EVP rheology are unstable, but can be stabilized by adding Newtonian damping term into the adjoint equation. The set of the observation system simulation experiments shows that landfast parameter distributions can be reconstructed after 5–10 iterations of the minimization procedure. Optimization of the sea ice initial conditions and spatially varying parameters in the equation for the stress tensor requires more computation, but provides a better hindcast of the sea ice state and the internal stress tensor. Analysis of the inaccuracy in the wind forcing and errors in the sea ice thickness observations have shown reasonable robustness of the variational DA approach and feasibility of its application to the available and incoming observations.

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