The size distribution of sea-ice floes is an important descriptor of the sea-ice cover. Most studies report that floe sizes follow a power-law distribution over some size range, but the power-law exponents often differ substantially. Other studies report two power-law regimes over different size ranges, or more complicated behavior. We review the construction of power-law floe size distributions and compare the results of previous studies. Differences between studies may be due to spatial and temporal variability of the floe size distribution, sampling variability, inadequacy of the power-law model, or flaws in the mathematical analysis. For a power-law model, the most accurate method for determining the exponent from data is Maximum Likelihood Estimation; least-squares methods based on log-log plots of the data yield biased estimates. After calculating the power-law exponent from data, a goodness-of-fit test should be applied to determine whether or not the power-law model actually describes the distribution of the data. These analysis principles have been described in the literature but have not generally been applied to floe size distributions. Numerical ice-ocean models are beginning to simulate the floe size distribution, which should give further insight into the interpretation of observational studies.

The size distribution of ice floes in the polar seas affects the dynamics and thermodynamics of the ice cover, and ice-ocean models are beginning to include the floe size distribution (FSD) in their simulations. The FSD has previously been reported to follow a power law of the form x –α , where x is the floe size and – α characterizes how steeply the number of floes decreases as x increases. Different studies have found different values of α and different ranges of x over which the power law applies. We found that a power law describes the FSD in the Beaufort and Chukchi seas reasonably well over floe sizes from 2 to 30 km, based on 187 visible-band satellite images (resolution 250 m) acquired during spring through fall of 2013 and 2014. The mean power-law exponent goes through a seasonal cycle in which α increases in spring, peaks in July or August, and decreases in fall. June is the transition month from spring FSD to summer FSD. This cycle is consistent with the processes of floe break-up in spring followed by preferential melting of smaller floes in summer and the return of larger floes after fall freeze-up. We also analyzed 12 high-resolution satellite images acquired near the low-resolution images in space and time. We found that the FSDs from the high-resolution images follow power laws over floe sizes from 10 m to 3 km. While the power-law exponents of the corresponding high- and low-resolution images do not always match in a strict statistical sense, they suggest the plausibility that the FSD follows a single power law over a wide range of floe sizes. This study covers a larger spatial and temporal sampling space and is based on more satellite images than previous studies. Results have been used for model calibration and validation.

The interplay between sea ice concentration, sea ice roughness, ocean stratification, and momentum transfer to the ice and ocean is subject to seasonal and decadal variations that are crucial to understanding the present and future air-ice-ocean system in the Arctic. In this study, continuous observations in the Canada Basin from March through December 2014 were used to investigate spatial differences and temporal changes in under-ice roughness and momentum transfer as the ice cover evolved seasonally. Observations of wind, ice, and ocean properties from four clusters of drifting instrument systems were complemented by direct drill-hole measurements and instrumented overhead flights by NASA operation IceBridge in March, as well as satellite remote sensing imagery about the instrument clusters. Spatially, directly estimated ice-ocean drag coefficients varied by a factor of three with rougher ice associated with smaller multi-year ice floe sizes embedded within the first-year-ice/multi-year-ice conglomerate. Temporal differences in the ice-ocean drag coefficient of 20–30% were observed prior to the mixed layer shoaling in summer and were associated with ice concentrations falling below 100%. The ice-ocean drag coefficient parameterization was found to be invalid in September with low ice concentrations and small ice floe sizes. Maximum momentum transfer to the ice occurred for moderate ice concentrations, and transfer to the ocean for the lowest ice concentrations and shallowest stratification. Wind work and ocean work on the ice were the dominant terms in the kinetic energy budget of the ice throughout the melt season, consistent with free drift conditions. Overall, ice topography, ice concentration, and the shallow summer mixed layer all influenced mixed layer currents and the transfer of momentum within the air-ice-ocean system. The observed changes in momentum transfer show that care must be taken to determine appropriate parameterizations of momentum transfer, and imply that the future Arctic system could become increasingly seasonal.

An array of novel directional wavebuoys was designed and deployed into the Beaufort Sea ice cover in March 2014, as part of the Office of Naval Research Marginal Ice Zone experiment. The buoys were designed to drift with the ice throughout the year and monitor the expected breakup and retreat of the ice cover, forced by waves travelling into the ice from open water. Buoys were deployed from fast-and-light air-supported ice camps, based out of Sachs Harbour on Canada’s Banks Island, and drifted westwards with the sea ice over the course of spring, summer and autumn, as the ice melted, broke up and finally re-froze. The buoys transmitted heave, roll and pitch timeseries at 1 Hz sample frequency over the course of up to eight months, surviving both convergent ice dynamics and significant waves-in-ice events. Twelve of the 19 buoys survived until their batteries were finally exhausted during freeze-up in late October/November. Ice impact was found to have contaminated a significant proportion of the Kalman-filter-derived heave records, and these bad records were removed with reference to raw x/y/z accelerations. The quality of magnetometer-derived buoy headings at the very high magnetic field inclinations close to the magnetic pole was found to be generally acceptable, except in the case of four buoys which had probably suffered rough handling during transport to the ice. In general, these new buoys performed as expected, though vigilance as to the veracity of the output is required.

Breakup of the near-continuous winter sea ice into discrete summer ice floes is an important transition that dictates the evolution and fate of the marginal ice zone (MIZ) of the Arctic Ocean. During the winter of 2014, more than 50 autonomous drifting buoys were deployed in four separate clusters on the sea ice in the Beaufort Sea, as part of the Office of Naval Research MIZ program. These systems measured the ocean-ice-atmosphere properties at their location whilst the sea ice parameters in the surrounding area of these buoy clusters were continuously monitored by satellite TerraSAR-X Synthetic Aperture Radar. This approach provided a unique Lagrangian view of the winter-to-summer transition of sea ice breakup and floe size distribution at each cluster between March and August. The results show the critical timings of a) temporary breakup of winter sea ice coinciding with strong wind events and b) spring breakup (during surface melt, melt ponding and drainage) leading to distinctive summer ice floes. Importantly our results suggest that summer sea ice floe distribution is potentially affected by the state of winter sea ice, including the composition and fracturing (caused by deformation events) of winter sea ice, and that substantial mid-summer breakup of sea ice floes is likely linked to the timing of thermodynamic melt of sea ice in the area. As the rate of deformation and thermodynamic melt of sea ice has been increasing in the MIZ in the Beaufort Sea, our results suggest that these elevated factors would promote faster and more enhanced breakup of sea ice, leading to a higher melt rate of sea ice and thus a more rapid advance of the summer MIZ.

To better simulate the seasonal evolution of sea ice in the Arctic, with particular attention to the marginal ice zone, a sea ice model of the distribution of ice thickness, floe size, and enthalpy was implemented into the Pan-arctic Ice–Ocean Modeling and Assimilation System (PIOMAS). Theories on floe size distribution (FSD) and ice thickness distribution (ITD) were coupled in order to explicitly simulate multicategory FSD and ITD distributions simultaneously. The expanded PIOMAS was then used to estimate the seasonal evolution of the Arctic FSD in 2014 when FSD observations are available for model calibration and validation. Results indicate that the simulated FSD, commonly described equivalently as cumulative floe number distribution (CFND), generally follows a power law across space and time and agrees with the CFND observations derived from TerraSAR-X satellite images. The simulated power-law exponents also correlate with those derived using MODIS images, with a low mean bias of –2%. In the marginal ice zone, the modeled CFND shows a large number of small floes in winter because of stronger winds acting on thin, weak first-year ice in the ice edge region. In mid-spring and summer, the CFND resembles an upper truncated power law, with the largest floes mostly broken into smaller ones; however, the number of small floes is lower than in winter because floes of small sizes or first-year ice are easily melted away. In the ice pack interior there are fewer floes in late fall and winter than in summer because many of the floes are “welded” together into larger floes in freezing conditions, leading to a relatively flat CFND with low power-law exponents. The simulated mean floe size averaged over all ice-covered areas shows a clear annual cycle, large in winter and smaller in summer. However, there is no obvious annual cycle of mean floe size averaged over the marginal ice zone. The incorporation of FSD into PIOMAS results in reduced ice thickness, mainly in the marginal ice zone, which improves the simulation of ice extent and yields an earlier ice retreat.