Изменчивость сплоченности, возраста и толщины льда в летний период в арк­тическом бассейне по данным специальных судовых ледовых наблюдений

Ice thickness and surface roughness measurements of first‐year (FY) sea ice were collected with a fix‐mounted helicopter‐borne electromagnetic (HEM) ‐laser system in Amundsen Gulf in April to May 2004. The modal ice thickness values are in good qualitative agreement with different ice types identified in synthetic aperture radar (SAR) imagery and shown on ice charts produced by the Canadian Ice Service. Modal ice thickness values which generally represent level ice thicknesses were about 2.0 m over landfast ice. A large range of modal ice thicknesses was observed in the mobile ice region, with values of about 0.2 m (young ice) in leads (where there was high radar backscatter), 0.6 m (thin FY ice) in the polynya (where there was medium to high backscatter), and about 1.1–1.9 m (thick FY ice) elsewhere. High surface roughnesses are strongly associated with high radar backscatter in SAR imagery, and are observed in areas of large shear. The ratio of the standard deviations of ice draft and averaged roughness in an area of landfast ice is in good agreement with the ratio of the standard deviations of ice draft and ice‐equivalent roughness expected from isostasy, with constant level ice and snow thickness. However, the standard deviation of ice‐equivalent roughness may be significantly underestimated, due to differences in snow thickness between level and deformed ice, and limitations of the laser processing method. Modal ice (plus snow) thicknesses measured with the HEM system are within the range of historical values measured at Cape Parry.

Evaluation of selected state-of-the-art methods for ship transit simulation in various ice conditions based on full-scale measurement

The USS Nautilus (SSN‐571) was the first vessel to cross the Arctic Basin via the north pole in early August 1958. During this expedition, almost continuous acoustic under‐ice thickness profiles were recorded. In August 1970 USS Queenfish (SSN‐651) retraced Nautilus' route, yielding the only duplicate transect of under‐ice topography across the Arctic Basin. Comparisons of the statistical analysis of the under‐ice draft measurements obtained through use of wide‐beam and narrow‐beam and narrow‐beam only acoustic profilers by Nautilus and Queenfish, respectively, along the coincidental route are presented. Geographic areas found to have distinct under‐ice characteristics and ice composition are identified. The under‐ice statistics of both cruises are considered in relation to representative field observations and modeling results of other researchers. Principal findings are (1) Nautilus recorded generally more severe ice conditions within the Canada Basin than did Queenfish 12 years later; overall mean drafts were 3.08 and 2.39 m, respectively, (2) the under‐ice topography becomes progressively more severe when proceeding from the Canadian to the Eurasian side of the Arctic Basin, (3) the Canada Basin may contain the most moderate under‐ice topography and the greatest number of open water and refrozen polynyas and leads within the central Arctic Basin, (4) the Makarov and Amundsen basins and the Arctic mid‐ocean ridge may contain some of the most severe under‐ice topography within the Arctic Basin, and (5) the present study indicates an overall Arctic Basin mean of 3–4% open water/new ice (less than 30 cm) in summer.

Time series of sea ice thickness observed by moored sonars in the Transpolar Drift in Fram Strait show significant thinning during the 1990–2011 period. The thickness of old level ice is reduced by 25 %, while the fraction of (ridged) ice thicker than 5 m is reduced by 50 %. The combined effect on the mean ice thickness is a reduction from an annual average of 3.0 m during the 1990s to 2.2 m at the end of the record. Due to the steady advection of ice from many sites across the Arctic, the ice observed in Fram Strait carries an integrated signal of Arctic change. The thickness of old level ice is approaching values more typical for seasonal ice. While such low thicknesses prevail, larger areas of sea ice can melt away during the melt season. Hence conditions favorable to melt (or favorable winds) will result in new summers of very low sea ice extent. It is an important implication that the sea ice extent then depends more on the actual weather each melt season than previously. A relatively warm summer may remove much larger areas of ice than a slightly colder summer. This is exemplified through the relatively cold summer of 2013, which featured a sea ice extent nearly 50 % higher than the preceeding warm summer of 2012. This, again, implies that one may expect larger year to year variability in summer sea ice extent in the coming years, with the ramifications this has on human activity in the Arctic. In addition to this general reflection of the state of the Arctic sea ice cover, the Fram Strait ice thickness observations are of particular relevance to development of offshore petroleum fields on the North East Greenland shelf just downstream of the monitoring site. Most relevant design parameters may be deduced from this data set, such as level ice thickness and frequency and depth of pressure ridges.

This paper discusses the development of a coupled atmospheric‐ice model with a comprehensive ice dynamics, cavitating fluid rheology and an open water parameterization. The results center on the ice thickness and concentration distribution in the Arctic basin where the inclusion of ice rheology has maximum impact. The influence of the wind stresses calculated by an atmospheric model with stability dependent surface drag coefficients is discussed along with the role of the ocean currents and ocean‐ice drag coefficient. Under winter wind stress conditions the model had a tendency to buildup ice on the Siberian coast. The introduction of a partial slip condition at land‐ice boundaries in the model designed to prevent this buildup is discussed, and the best choice for the amplitude of the slip at the land boundaries in this model is found to be 0.4. The ice model results are compared with the available observational data sets on ice thickness, concentration and ice velocity fields to test the validity of the model simulations.

The USS Nautilus (SSN-571) was the first vessel to cross the Arctic Basin via the North Pole in early August 1958. During this expedition almost continuous acoustic under-ice thickness distribution profiles were recorded. This article presents an overall statistical analysis of the under-ice draft measurements obtained during this historic cruise. Geographic areas found to have distinct under-ice-characteristics and ice compositions are identified. Principal findings are: (1) Nautilus recorded an overall mean under-ice draft of 3.68 m across the Arctic Basin; (2) the under-ice topography becomes progressively more severe when proceeding from the Canadian to the Eurasian side of the Arctic Basin; (3) the Canada Basin was observed to contain the most moderate under-ice topography and the greatest number of open water and referent polynyas and leads along the transpolar route taken by Nautilus; (4) Nautilus encountered the most severe under-ice topography of the voyage over the Arctic Mid-Ocean Ridge; and (5) an overall Arctic Basin mean of 2.6% open water/new ice (<30 cm) was encountered during her voyage beneath the sea ice cover of the Arctic Ocean.Key words: sea ice, under-ice thickness distribution, sonar, Canada Basin, Central Arctic, Eurasian Basin, arctic submarine

Field programs were conducted in the Beaufort Sea in April 2010 and off Labrador in March 2011 to collect sea-ice and snow thickness data, for validation of RADARSAT-2 and TerraSAR-X synthetic aperture radar (SAR) ice signatures and CryoSAT ice thickness data. Measurements of snow-plus-ice thickness and surface freshwater layer thickness were collected with an electromagnetic (EM)-induction/laser system, fix-mounted on a helicopter. Measurements of snow thickness and the thickness of level ice in low-salinity waters were collected with a 1000-MHz ground-penetrating radar. The SAR imagery provides a good indication of where each method can be used for ice thickness measurement. The ice and snow thickness datasets collected can be used for developing SAR algorithms for ice types and surface roughness, and for validating Cryosat ice thickness data.

Passive microwave snow depth, ice concentration, and ice motion estimates are combined with snowfall from the European Centre for Medium‐Range Weather Forecasting (ECMWF) reanalysis (ERA‐40) from 1979–2001 to estimate the prevalence of snow‐to‐ice conversion (snow‐ice formation) on level sea ice in the Antarctic for April–October. Snow ice is ubiquitous in all regions throughout the growth season. Calculated snow‐ice thicknesses fall within the range of estimates from ice core analysis for most regions. However, uncertainties in both this analysis and in situ data limit the usefulness of snow depth and snow‐ice production to evaluate the accuracy of ERA‐40 snowfall. The East Antarctic is an exception, where calculated snow‐ice production exceeds observed ice thickness over wide areas, suggesting that ERA‐40 precipitation is too high there. Snow‐ice thickness variability is strongly controlled not just by snow accumulation rates, but also by ice divergence. Surprisingly, snow‐ice production is largely independent of snow depth, indicating that the latter may be a poor indicator of total snow accumulation. Using the presence of snow‐ice formation as a proxy indicator for near‐zero freeboard, we examine the possibility of estimating level ice thickness from satellite snow depths. A best estimate for the mean level ice thickness in September is 53 cm, comparing well with 51 cm from ship‐based observations. The error is estimated to be 10–20 cm, which is similar to the observed interannual and regional variability. Nevertheless, this is comparable to expected errors for ice thickness determined by satellite altimeters. Improvement in satellite snow depth retrievals would benefit both of these methods.

Late-summer thickness distributions of large ice floes in the Transpolar Drift between Svalbard and the North Pole in 1991, 1996, 1998, and 2001 are compared. They have been derived from drilling and electromagnetic (EM) sounding. Results show a strong interannual variability, with significantly reduced thickness in 1998 and 2001. The mean thickness decreased by 22.5% from 3.11 m in 1991 to 2.41 m in 2001, and the modal thickness by 22% from 2.50 m in 1991 to 1.95 m in 2001. Since modal thickness represents the thickness of level ice, the observed thinning reflects changes in thermodynamic conditions. Together with additional data from the Laptev Sea obtained in 1993, 1995, and 1996, results are in surprising agreement with recently published thickness anomalies retrieved from satellite radar altimetry for Arctic regions south of 81.5°N. This points to a strong sensitivity of radar altimetry data to level ice thickness.

Ship‐based observations are used to describe regional and seasonal changes in the thickness distribution and characteristics of sea ice and snow cover thickness around Antarctica. The data set comprises 23,373 observations collected over more than 2 decades of activity and has been compiled as part of the Scientific Committee on Antarctic Research (SCAR) Antarctic Sea Ice Processes and Climate (ASPeCt) program. The results show the seasonal progression of the ice thickness distribution for six regions around the continent together with statistics on the mean thickness, surface ridging, snow cover, and local variability for each region and season. A simple ridge model is used to calculate the total ice thickness from the observations of level ice and surface topography, to provide a best estimate of the total ice mass, including the ridged component. The long‐term mean and standard deviation of total sea ice thickness (including ridges) is reported as 0.87 ± 0.91 m, which is 40% greater than the mean level ice thickness of 0.62 m. Analysis of the structure function along north/south and east/west transects revealed lag distances over which sea ice thickness decorrelates to be of the order of 100–300 km, which we use as a basis for presenting near‐continuous maps of sea ice and snow cover thickness plotted on a 2.5° × 5.0° grid.

[1] Time series (1990–2011) of sea ice thickness observed by moored sonars in the Transpolar Drift in Fram Strait are examined. Contrasting the post-2007 years against the 1990s, three remarkable changes in the monthly ice thickness distributions are highlighted: (1) The thickness of old level ice (modal thickness) is reduced by 32%, (2) the old ice modal peak width is reduced by 25%, and (3) the fraction of (ridged) ice thicker than 5 m is reduced by 50%. The combined effect on the mean ice thickness is a reduction from an annual average of 3.0 m during the 1990s to 2.2 m during 2008–2011. Most of the thinning took place after 2005–2006. While the old ice modal thickness and peak width show signs of recovery after 2008, the decreasing trend in fraction of ridged ice and mean ice thickness persists until the end of the record in 2011. The ice observed in Fram Strait carries an integrated signal of Arctic change due to the advection of ice from many sites in the Arctic. Based on concurrence in timing, we conclude that much of the thinning quantified here is reflecting recent change in the age composition of the Arctic ice cover toward younger ice. The old level ice remains thin, and as such the ice cover remains preconditioned for new summers of very low sea ice extent.

Results obtained with a unique dual-antenna impulse radar system used to profile first- and multi-year sea ice near Prudhoe Bay, Alaska, are discussed. A description of the radar system is given along with representative field data. Continuous ice thickness profiles are required for studies related to modeling and understanding the dynamics of the sea ice cover, heat exchange between the ocean and the atmosphere and mass balance of the ice cover. Ice thickness profiles are also required for studies related to the determination of ice load distributions and force analyses, and the subsurface roughness as it pertains to under-ice sound propagation and to the quantity of oil that would be trapped in the undulating bottom relief of first-year and multiyear ice should an oil blowout occur in an ice covered sea. From the radar impulse travel times obtained with the use of dual antennas, calculations of thickness, electromagnetic impulse velocity and effective dielectric constant of the ice were made. Ice thicknesses determined by direct measurement and those calculated using the radar impulse travel times were found to be in good agreement. Continuous ice thickness profiles obtained with the radar were analyzed to provide representative cross sections of first-year and multi-year sea ice. These cross sections reveal the undulating bottom surface relief of both ice types. Calculations are presented that indicate a significant amount of oil could be trapped within this bottom relief should the oil be released under the ice from a sea-floor oi1production system. INTRODUCTION ' There is need for a system that can measure the top and bottom relief of both first-year and multi-year sea ice continuously, not only from the ice surface, but preferably at high speed from the air. This information is required for studies related to modeling and understanding the dynamics of the sea ice cover, heat exchange the ocean and the atmosphere, mass balance of the ice cover, ice load distributions and force analyses, and subsurface roughness as it pertains to under-ice sound propagation, marine life habitats and oil entrapment. Numerous ways of determining sea ice types and thicknesses have been tried in recent years, for example, visual observation, aerial photography, side-looking airborne radar (SLAR imagery), laser profi10meters, drop electrometers and sonar. Visual observations and aerial photography, such as those obtained on the U.S. Navy Birdseye sea ice reconnaissance flights, are highly valuable for compiling data on ice type and number of ridges and open leads per unit length. SLAR imagery results are highly variable and interpretation is difficult; for example, radar returns can indicate thin ice when in fact thick multi-year ice exists. Laser profile meter data are useful for determining such ridge statistics as number of ridges per unit length of track, surface roughness versus location, and ridge height distribution.

Level ice thickness distribution pattern in the Bohai Sea in the winter of 2009–2010 was investigated in this paper using MODIS night-time thermal infrared imagery. The cloud cover in the imagery was masked out manually. Level ice thickness was calculated using MODIS ice surface temperature and an ice surface heat balance equation. Weather forcing data was from the European Centre for Medium-Range Weather Forecasts (ECMWF) analyses. The retrieved ice thickness agreed reasonable well with in situ observations from two off-shore oil platforms. The overall bias and the root mean square error of the MODIS ice thickness are–1.4 cm and 3.9 cm, respectively. The MODIS results under cold conditions (air temperature <–10°C) also agree with the estimated ice growth from Lebedev and Zubov models. The MODIS ice thickness is sensitive to the changes of the sea ice and air temperature, in particular when the sea ice is relatively thin. It is less sensitive to the wind speed. Our method is feasible for the Bohai Sea operational ice thickness analyses during cold freezing seasons.

Physical model and theoretical model study of level ice and wide sloping structure interactions

Sea-ice-thickness variability in the Chukchi Sea, spring and summer 2002–2004