Revisiting mesoscale eddy genesis mechanism of nonlinear advection in a marginal ice zone

A three-dimensional（3-D） ocean model is coupled with a two-dimensional（2-D） sea ice model, to revisit a nonlinear advection mechanism, one of the most important mesoscale eddy genesis mechanisms in the marginal ice zone. Two-dimensional ocean model simulations suggest nonlinear advection mechanism is more important when the water gets shallower. Instead of considering the ocean as barotropic fluid in the 2-D ocean model, the 3-D ocean model allows the sea ice to affect the current directly in the surface layer via ocean-ice interaction. It is found that both mesoscale eddy and sea surface elevation are sensitive to changes in a water depth in the 3-D simulations. The vertical profile of a current velocity in 3-D experiments suggests that when the water depth gets shallower, the current move faster in each layer, which makes the sea surface elevation be nearly inverse proportional to the water depth with the same wind forcing during the same time. It is also found that because of the vertical motion, the magnitude of variations in the sea surface elevation in the 3-D simulations is very small,being only 1% of the change in the 2-D simulations. And it seems the vertical motion to be the essential reason for the differences between the 3-D and 2-D experiments.

Characteristics of sea ice kinematics from the marginal ice zone to the packed ice zone observed by buoys deployed during the 9th Chinese Arctic Expedition

Sea ice growth and consolidation play a significant role in heat and momentum exchange between the atmosphere and the ocean.However,few in situ observations of sea ice kinematics have been reported owing to difficulties of deployment of buoys in the marginal ice zone(MIZ).To investigate the characteristics of sea ice kinematics from MIZ to packed ice zone(PIZ),eight drifting buoys designed by Taiyuan University of Technology were deployed in the open water at the ice edge of the Canadian Basin.Sea ice near the buoy constantly increased as the buoy drifted,and the kinematics of the buoy changed as the buoy was frozen into the ice.This process can be determined using sea ice concentration,sea skin temperature,and drift speed of buoy together.Sea ice concentration data showed that buoys entered the PIZ in mid-October as the ice grew and consolidated around the buoys,with high amplitude,high frequency buoy motions almost ceasing.Our results confirmed that good correlation coefficient in monthly scale between buoy drift and the wind only happened in the ice zone.The correlation coefficient between buoys and wind was below 0.3 while the buoys were in open water.As buoys entered the ice zone,the buoy speed was normally distributed at wind speeds above 6 m/s.The buoy drifted mainly to the right of the wind within 45°at wind speeds above 8 m/s.During further consolidation of the ice in MIZ,the direct forcing on the ice through winds will be lessened.The correlation coefficient value increased to 0.9 in November,and gradually decreased to 0.7 in April.

Variation of Antarctic marginal ice zone extent (1989-2019)

The Antarctic marginal ice zone(MIZ)is the transition region between open water and consolidated pack ice,which is defined as an area with 15%-80%sea ice concentration.The MIZ represents the outer circle of Antarctic sea ice and the biological activity circle of Antarctic organisms,which provides a direct indication of the extent of Antarctic sea ice.In this study,the joint total variation and nonnegative constrained least square algorithm are applied to retrieve the Antarctic MIZ extent based on passive microwave data sets from 1989 to 2019.The spatial and temporal variations of the Antarctic MIZ extent and five regions are analyzed.The results show that the Antarctic MIZ extent follows a strong monthly variation pattern,decreasing from November to February and increasing from March to October.The annual MIZ extent is largest in the Weddell Sea and smallest in the Western Pacific Ocean.The edge of the sea ice begins to form a closed ring in May,which eventually closes near the Antarctic Peninsula.The ring width variation is large in summer,but generally stabilizes between 350 and 370 km in winter.The average latitude of the Antarctic MIZ is relatively stable in summer,but changes substantially in winter with a difference of approximately 3°.In October,the lowest mean latitude of the MIZ can reach 64.35°S.The sea surface pressure,2-m temperature,and 10-m wind speed are negatively correlated with the MIZ extent variation,among which the second-order partial correlation coefficient of the sea surface pressure and MIZ extent is−0.8773 in the Western Pacific Ocean.

DynIceData:a gridded ice-water classification dataset at short-time intervals based on observations from multiple satellites over the marginal ice zone

High-resolution observations of short-term changes in sea ice are critical to understanding ice dynamics and also provide important information used in advice to shipping,especially in the Arctic.Although individual satellite sensors provide periodic sea ice obser-vations with spatial resolutions of tens of meters,information regarding changes that occur over short time intervals of minutes or hours is limited.In this study,a gridded ice-water classification dataset with a high temporal resolution was developed based on observations acquired by multiple satellite sensors in the Marginal Ice Zone(MIZ).This dataset-DynIceData-which combines Sentinel-1 Synthetic Aperture Radar(SAR)data with Gaofen-3(GF-3)SAR and SDGSAT-1 thermal infrared imagery was used to obtain observations of the MIZ with a range of temporal resolutions ran-ging from minutes to tens of hours.The areas of the Arctic covered include the Kara Sea,Beaufort Sea,and Greenland Sea during the period from August 2021 to August 2022.Object-oriented segmen-tation and thresholding were used to obtain the ice-water classifi-cation map from Sentinel-1 and GF-3 SAR image pairs and Sentinel-1 SAR and SDGSAT-1 thermal image pairs.The time interval between the images in each pair ranged from 1 minute to 68 hours.Ten-kilometer grid sample granules with a spatial resolution of 25 m for the GF-3 SAR data and 30 m for the SDGSAT-1 thermal data were used.The classification was verified as having an overall accuracy of at least 95.58%.The DynIceData dataset consists of 7338 samples,which could be used as reference data for further research on rapid changes in sea ice patterns at different short time scales and provide support for research on thermodynamic and dynamic models of sea ice in combination with other environmen-tal data,thus potentially improving the accuracy of sea ice forecast-ing using Artificial Intelligence.The dataset can be accessed at https://doi.org/10.57760/sciencedb.j00001.00784.

Prediction of performance of a non-icebreaking ship in marginal ice zone

The Arctic is rapidly transforming into a navigable ocean because of global warming.The retreat of ice extent and widened marginal ice zone(MIZ)in the Arctic made it possible for non-icebreaking commercial vessels to sail into Arctic waters where ice floes of various concentrations and thicknesses exist.The main objective of this work is to estimate the performance of a non-icebreaking cargo ship that sails in the Arctic marginal ice zone.Different numerical approaches are utilized to calculate ice-induced resistance and compared with those proposed in empirical formulas.The comparison shows that the resistances predicted by the two numerical tools differ obviously and are in general smaller in comparison with the ones calculated from the empirical formulas under lower ice concentrations.The total resistances are further calculated to predict the required propulsion powers for the case study vessel to enable navigation under severe ice conditions.This work highlights the significance of developing new and more sophisticated tools for estimation of ship’s ice performance in MIZ,which is the prerequisite to enable non-icebreaking cargo fleet to utilize the Arctic shipping lane.