Sea Ice Cover Deformation on the Local Scale and Mesoscale and Its Relationship to Atmosphere-Ocean Processes

This thesis is concerned with the study of sea ice cover deformation caused by the processes in the atmosphere and ocean. Only a modest number of studies has addressed the cross-scale analysis of the ice deformation. The aim of the present research has two foci: to investigate the variability of ice deformations and identify mechanisms responsible for their generation, and to explore the relationships of the ice deformation in the range of spatial scales. Two types of ice, the multi-year pack ice in the central Arctic and the seasonal ice in the northern Baltic Sea, are studied. The research includes a field experiment, observation analysis and modelling. Stresses in the ice generated by non-uniform drift of ice, ocean waves, and ice deformation due to variations in the ambient air temperature are considered. To separate thermal and motion induced deformation on the floe scale a thermo-mechanical non-linear viscous-elastic model has been developed. The results from these simulations are compared with the observations from the field experiment. To study the aggregate behaviour of the ice cover the mesoscale deformations are analysed along with the local ice strain. The continuum anisotropic and granular ice models are employed to simulate the highly inhomogeneous spatial structure of the deformation fields observed. The wave emission due to ice failure is also investigated. A comparison of field observations and laboratory tests in an ice tank and asymptotic analysis allow us to identify mechanisms of the wave emission at frequencies between 0.2 Hz and 1.0 Hz. The scaling formalism for the ice deformation and stress is suggested. The results of the data analysis and modelling have converged into a coherent scheme describing the spatial and temporal variability of the sea ice cover deformation from the local scale through the single floe scale to the mesoscale

On the future navigability of Arctic sea routes: high-resolution projections of the Arctic Ocean and sea ice

The rapid Arctic summer sea ice reduction in the last decade has lead to debates in the maritime industries on the possibility of an increase in cargo transportation in the region. Average sailing times on the North Sea Route along the Siberian Coast have fallen from 20 days in the 1990s to 11 days in 2012–2013, attributed to easing sea ice conditions along the Siberian coast. However, the economic risk of exploiting the Arctic shipping routes is substantial. Here a detailed high-resolution projection of ocean and sea ice to the end of the 21st century forced with the RCP8.5 IPCC emission scenario is used to examine navigability of the Arctic sea routes. In summer, opening of large areas of the Arctic Ocean previously covered by pack ice to the wind and surface waves leads to Arctic pack ice cover evolving into the Marginal Ice Zone. The emerging state of the Arctic Ocean features more fragmented thinner sea ice, stronger winds, ocean currents and waves. By the mid 21st century, summer season sailing times along the route via the North Pole are estimated to be 13–17 days, which could make this route as fast as the North Sea Route

The effects of tides on the water mass mixing and sea ice in the Arctic Ocean

In this study, we use a novel pan-Arctic sea ice-ocean coupled model to examine the effects of tides on sea ice and the mixing of water masses. Two 30 year simulations were performed: one with explicitly resolved tides and the other without any tidal dynamics. We find that the tides are responsible for a ∼15% reduction in the volume of sea ice during the last decade and a redistribution of salinity, with surface salinity in the case with tides being on average ∼1.0–1.8 practical salinity units (PSU) higher than without tides. The ice volume trend in the two simulations also differs: −2.09 × 103 km3/decade without tides and −2.49 × 103 km3/decade with tides, the latter being closer to the trend of −2.58 × 103 km3/decade in the PIOMAS model, which assimilates SST and ice concentration. The three following mechanisms of tidal interaction appear to be significant: (a) strong shear stresses generated by the baroclinic clockwise rotating component of tidal currents in the interior waters; (b) thicker subsurface ice-ocean and bottom boundary layers; and (c) intensification of quasi-steady vertical motions of isopycnals (by ∼50%) through enhanced bottom Ekman pumping and stretching of relative vorticity over rough bottom topography. The combination of these effects leads to entrainment of warm Atlantic Waters into the colder and fresher surface waters, supporting the melting of the overlying ice

On the origin of water masses in the Beaufort Gyre

Author Posting. © American Geophysical Union, 2019. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research-Oceans 124(7), (2019): 4696-4709, doi: 10.1029/2019JC015022.The Beaufort Gyre is a key feature of the Arctic Ocean, acting as a reservoir for freshwater in the region. Depending on whether the prevailing atmospheric circulation in the Arctic is anticyclonic or cyclonic, either a net accumulation or release of freshwater occurs. The sources of freshwater to the Arctic Ocean are well established and include contributions from the North American and Eurasian Rivers, the Bering Strait Pacific water inflow, sea ice meltwater, and precipitation, but their contribution to the Beaufort Gyre freshwater accumulation varies with changes in the atmospheric circulation. Here we use a Lagrangian backward tracking technique in conjunction with the 1/12‐degree resolution Nucleus for European Modelling of the Ocean model to investigate how sources of freshwater to the Beaufort Gyre have changed in recent decades, focusing on increase in the Pacific water content in the gyre between the late 1980s and early 2000s. Using empirical orthogonal functions we analyze the change in the Arctic oceanic circulation that occurred between the 1980s and 2000s. We highlight a “waiting room” advective pathway that was present in the 1980s and provide evidence that this pathway was caused by a shift in the center of Ekman transport convergence in the Arctic. We discuss the role of these changes as a contributing factor to changes in the stratification, and hence potentially the biology, of the Beaufort Gyre region.The underpinning high‐resolution NEMO simulation was performed using the ARCHER UK National Supercomputing Service (http://www.archer.ac.uk). ARIANE simulations were performed using the JASMIN data analysis environment (http://www.jasmin.ac.uk). Lagrangian analysis was carried out using computational tool ARIANE developed by B. Blanke and N. Grima. Arctic dynamic topography/geostrophic currents data were provided by the Centre for Polar Observation and Modelling, University College London (www.cpom.ucl.ac.uk/dynamic_topography; Armitage et al., 2016). The funding for A. Proshutinsky was provided by the NSF under grants supporting the Beaufort Gyre Observing System since 2003 (1845877, 1719280, 1604085) and by the Woods Hole Oceanographic Institution. Y. Aksenov was supported from the NERC Program “The North Atlantic Climate System Integrated Study (ACSIS), NE/N018044/1 and from the project “Advective pathways of nutrients and key ecological substances in the Arctic (APEAR)” NE/R012865/1, as a part of the joint UK/Germany “Changing Arctic Ocean” Programme. A. Yool and E. Popova were supported by NERC grants CLASS NE/R015953/1, and National Capability in Ocean Modelling. We acknowledge the FAMOS (http://web.whoi.edu/famos/) program for providing a framework for many fruitful discussions which thoroughly enhanced this work. Finally, we thank the two anonymous reviewers who greatly improved this work with their insightful input.2019-12-2

Shelf-basin exchange in the Laptev Sea in the warming climate: a model study

GCM-based forecast simulations predict continuously increasing seasonality of the sea ice cover and an almost ice-free, summer-time, Arctic Ocean within several decades from the present. In this study we use a primitive equation ocean model: NEMO, coupled with the sea ice model LIM2, to test the hypothesis that under such an increased range in seasonal ice cover the intensity of shelf-basin water exchange will significantly increase. We use the simulated results for the Laptev Sea from a global model run 1958–2007 and compare results for two years with anomalously high and low summer sea ice extents: 1986–1987 and 2006–2007. The shelf–basin fluxes of volume, heat and salt during specific seasons are evaluated and attributed to plausible driving processes, with particular attention to dense water cascading. Analyses of the model temperature distribution at the depth of the intermediate maximum, associated with Atlantic Water, have shown a marked increase of the amount of the local origin cold water in late winter 2007 in the region, where dense water typically appears as a result of its formation on the shelf and subsequent downslope leakage. Calculation of the shelf-basin exchange during March-May in both years confirmed a substantial increase (a factor of two) of fluxes in “ice-free” 2007 compared to the “icy” 1987. According to several past model studies, dense water production on Arctic shelves in winter driven by ice freezing and brine rejection is not likely to cease in a warmer climate, but rather to increase. There is also observational evidence that cascading in the seasonally ice covered seas (e.g. the Barents Sea) is much more efficient than it is in the permanently ice covered Arctic Ocean, which supports these model results

Arctic Ocean and Hudson Bay freshwater exports: New estimates from 7 decades of hydrographic surveys on the Labrador Shelf

While reasonable knowledge of multi-decadal Arctic freshwater storage variability exists, we have little knowledge of Arctic freshwater exports on similar timescales. A hydrographic time series from the Labrador Shelf, spanning seven decades at annual resolution, is here used to quantify Arctic Ocean freshwater export variability west of Greenland. Output from a high-resolution coupled ice-ocean model is used to establish the representativeness of those hydrographic sections. Clear annual to decadal variability emerges, with high freshwater transports during the 1950s and 1970s–80s, and low transports in the 1960s, and from the mid-1990s to 2016, with typical amplitudes of 30 mSv (1 Sv = 106 m3 s-1). The variability in both the transports and cumulative volumes correlates well both with Arctic and North Atlantic freshwater storage changes on the same timescale. We refer to the "inshore branch" of the Labrador Current as the Labrador Coastal Current, because it is a dynamically- and geographically-distinct feature. It originates as the Hudson Bay outflow, and preserves variability from river runoff into the Hudson Bay catchment. We find a need for parallel, long-term freshwater transport measurements from Fram and Davis Straits, to better understand Arctic freshwater export control mechanisms and partitioning of variability between routes west and east of Greenland, and a need for better knowledge and understanding of year-round (solid and liquid) freshwater fluxes on the Labrador shelf. Our results have implications for wider, coherent atmospheric control on freshwater fluxes and content across the Arctic and northern North Atlantic Oceans

Impact of sea ice floe size distribution on seasonal fragmentation and melt of Arctic sea ice

Recent years have seen a rapid reduction in the summer Arctic sea ice extent. To both understand this trend and project the future evolution of the summer Arctic sea ice, a better understanding of the physical processes that drive the seasonal loss of sea ice is required. The marginal ice zone, here defined as regions with between 15 % and 80 % sea ice cover, is the region separating pack ice from the open ocean. Accurate modelling of this region is important to understand the dominant mechanisms involved in seasonal sea ice loss. Evolution of the marginal ice zone is determined by complex interactions between the atmosphere, sea ice, ocean, and ocean surface waves. Therefore, this region presents a significant modelling challenge. Sea ice floes span a range of sizes but sea ice models within climate models assume they adopt a constant size. Floe size influences the lateral melt rate of sea ice and momentum transfer between atmosphere, sea ice, and ocean, all important processes within the marginal ice zone. In this study, the floe size distribution is represented as a power law defined by an upper floe size cut-off, lower floe size cut-off, and power-law exponent. This distribution is also defined by a new tracer that varies in response to lateral melting, wave-induced break-up, freezing conditions, and advection. This distribution is implemented within a sea ice model coupled to a prognostic ocean mixed-layer model. We present results to show that the use of a power-law floe size distribution has a spatially and temporally dependent impact on the sea ice, in particular increasing the role of the marginal ice zone in seasonal sea ice loss. This feature is important in correcting existing biases within sea ice models. In addition, we show a much stronger model sensitivity to floe size distribution parameters than other parameters used to calculate lateral melt, justifying the focus on floe size distribution in model development. We also find that the attenuation rate of waves propagating under the sea ice cover modulates the impact of wave break-up on the floe size distribution. It is finally concluded that the model approach presented here is a flexible tool for assessing the importance of a floe size distribution in the evolution of sea ice and is a useful stepping stone for future development of floe size modelling

Arctic sea surface height variability and change from satellite radar altimetry and GRACE, 2003-2014

Arctic sea surface height (SSH) is poorly observed by radar altimeters due to the poor coverage of the polar oceans provided by conventional altimeter missions and because large areas are perpetually covered by sea ice, requiring specialized data processing. We utilize SSH estimates from both the ice-covered and ice-free ocean to present monthly estimates of Arctic Dynamic Ocean Topography (DOT) from radar altimetry south of 81.5°N and combine this with GRACE ocean mass to estimate steric height. Our SSH and steric height estimates show good agreement with tide gauge records and geopotential height derived from Ice-Tethered Profilers. The large seasonal cycle of Arctic SSH (amplitude ∼5 cm) is dominated by seasonal steric height variation associated with seasonal freshwater fluxes, and peaks in October–November. Overall, the annual mean steric height increased by 2.2 ± 1.4 cm between 2003 and 2012 before falling to circa 2003 levels between 2012 and 2014 due to large reductions on the Siberian shelf seas. The total secular change in SSH between 2003 and 2014 is then dominated by a 2.1 ± 0.7 cm increase in ocean mass. We estimate that by 2010, the Beaufort Gyre had accumulated 4600 km3 of freshwater relative to the 2003–2006 mean. Doming of Arctic DOT in the Beaufort Sea is revealed by Empirical Orthogonal Function analysis to be concurrent with regional reductions in the Siberian Arctic. We estimate that the Siberian shelf seas lost ∼180 km3 of freshwater between 2003 and 2014, associated with an increase in annual mean salinity of 0.15 psu yr−1. Finally, ocean storage flux estimates from altimetry agree well with high-resolution model results, demonstrating the potential for altimetry to elucidate the Arctic hydrological cycle

Arctic Ocean boundary exchanges: A review

The Arctic Ocean has long been—and to a large extent remains—a data-​sparse region. Paucity of ocean and atmosphere measurements impacts the fidelity of atmospheric reanalyses, and ungauged rivers lead to uncertainties in measurement-​based estimates of river runoff. However, there exists a data resource that can provide material help: sustained (long-term) ice and ocean measurements around the Arctic Ocean boundary. The Arctic Ocean is surrounded by land and connects to adjacent ocean basins via four main gateways: to the Pacific through Bering Strait, to the Atlantic through Davis Strait, and to the Nordic Seas via Fram Strait and the Barents Sea Opening. In addition, the Nordic Seas connect to the Atlantic across the Greenland-Iceland-Scotland Ridge, which has a substantial measurement history. Inverse methods combine these data sets to generate conservative velocity fields that are then used to generate estimates of surface fluxes of heat and freshwater as well as other quantities of interest, including net biogeochemical fluxes and (with other methods) estimates of ocean water transformation rates. Data resources are available to greatly extend the duration and the temporal resolution of present analyses