Arctic sea ice concentration (SIC) has been studied extensively using passive microwave (PM) remote sensing. This technology could be used to improve navigation along vessel cruise paths; however, investigations on this topic have been limited. In this study, shipborne photographic observation (P-OBS) of sea ice was conducted using oblique-oriented cameras during the Chinese National Arctic Research Expedition in the summer of 2016. SIC and the areal fractions of open water, melt ponds, and sea ice (Aw, Ap, and Ai, respectively) were determined along the cruise path. The distribution of SIC along the cruise path was U-shaped, and open water accounted for a large proportion of the path. The SIC derived from the commonly used PM algorithms was compared with the moving average (MA) P-OBS SIC, including Bootstrap and NASA Team (NT) algorithms based on Special Sensor Microwave Imager/Sounder (SSMIS) data; and ARTIST sea ice, Bootstrap, Sea Ice Climate Change Initiative, and NASA Team 2 (NT2) algorithms based on Advanced Microwave Scanning Radiometer 2 (AMSR2) data. P-OBS performed better than PM remote sensing at detecting low SIC (< 10%). Our results indicate that PM SIC overestimates MA P-OBS SIC at low SIC, but underestimates it when SIC exceeds a turnover point (TP). The presence of melt ponds affected the accuracy of the PM SIC; the PM SIC shifted from an overestimate to an underestimate with increasing Ap, compared with MA P-OBS SIC below the TP, while the underestimation increased above the TP. The PM algorithms were then ranked; SSMIS-NT and AMSR2-NT2 are the best and worst choices for Arctic navigation, respectively.
The bottom topography of ridged sea ice differs greatly from that of other sea‐ice types. The form drag of ridge keels has an important influence on sea‐ice drift and deformation. In this study, both laboratory experiment (LabE) and fluid dynamics numerical simulation (FDS) have been carried out for a physical ridge model in a tank to better understand the quantitative characteristics of the form drag. The LabEs covered both laminar and turbulent conditions. The local form drag coefficient of a keel, Cdw, varied with the keel depth hw and the slope angle αw in the turbulent regime. After validated by the LabE measurements, the FDSs were employed to extend the parameterization from the finite water depth to deep water. The results gave Cdw = 0.68∙ln (αw/7.8°), R2 = 0.998, 10° ≤ αw ≤ 90°, with Cdw ranging from 0.17 to 1.66, when the keel depth was much less than the water depth. For a large ridging intensity (keel depth/spacing ≥0.01), the variation of the local form drag coefficient and its contribution to total drag coefficient were sensitive to the keel slope angle. Assuming the log‐normal distribution for this angle, the average value of the local form drag coefficient was 0.75, recommended for sea‐ice dynamic models.
In the ice-infested Bohai Sea, ice-breaking cones are generally installed on offshore wind turbine towers for ice resistance. Bending failure is a frequent ice failure mode occurring when ice interacts with ice-breaking cones. Global warming prolongs the ice formation period in the Bohai Sea, inducing an increasing trend of granular ice fraction in ice sheets. To better understand the bending mechanical behaviors of granular sea ice in the Bohai Sea, laboratory three-point bending tests were conducted using granular sea ice collected in the Bohai Sea during the winter of 2010–2011. A total of 42 ice samples were tested at −5, −10, and −15°C with strain rates of 1 × 10−6–6×10−4 s−1 in the downward direction vertical to the original ice surface. During tests, the salinity and density of each ice specimen were measured to calculate the porosity. Based on the results, negative exponential relationships were proposed between flexural strength and the square root of porosity and between effective elastic modulus and porosity. After normalization, the flexural strength showed no rate dependence at the whole strain rate range. In contrast, the effective elastic modulus increased with the strain rate. The effective elastic modulus of the ice samples was further parameterized based on the porosity and strain rate.
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