Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology/Key Laboratory for Land Satellite Remote Sensing Applications of Ministry of Natural Resources, School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China
Collaborative Innovation Center of Novel Software Technology and Industrialization, Nanjing 210023, China
Collaborative Innovation Center of South China Sea Studies, Nanjing 210023, China
The National Key Research and Development Program of China under contract Nos 2018YFC1407200 and 2018YFC1407203; the National Natural Science Foundation of China under contract No. 41976212.
Sea ice velocity impacts the distribution of sea ice, and the flux of exported sea ice through the Fram Strait increases with increasing ice velocity. Therefore, improving the accuracy of estimates of the sea ice velocity is important. We introduce a pyramid algorithm into the Horn-Schunck optical flow (HS-OF) method (to develop the PHS-OF method). Before calculating the sea ice velocity, we generate multilayer pyramid images from an original brightness temperature image. Then, the sea ice velocity of the pyramid layer is calculated, and the ice velocity in the original image is calculated by layer iteration. Winter Arctic sea ice velocities from 2014 to 2016 are obtained and used to discuss the accuracy of the HS-OF method and PHS-OF (specifically the 2-layer PHS-OF (2LPHS-OF) and 4-layer PHS-OF (4LPHS-OF)) methods. The results prove that the PHS-OF method indeed improves the accuracy of sea ice velocity estimates, and the 2LPHS-OF scheme is more appropriate for estimating ice velocity. The error is smaller for the 2LPHS-OF velocity estimates than values from the Ocean and Sea Ice Satellite Application Facility and the Copernicus Marine Environment Monitoring Service, and estimates of changes in velocity by the 2LPHS-OF method are consistent with those from the National Snow and Ice Data Center. Sea ice undergoes two main motion patterns, i.e., transpolar drift and the Beaufort Gyre. In addition, cyclonic and anticyclonic ice drift occurred during winter 2016. Variations in sea ice velocity are related to the open water area, sea ice retreat time and length of the open water season.
Figure 1. Map of the locations of the nine subregions of the Arctic.
Figure 2. n-layer pyramid image construction process (a), and flow chart of the n-layer pyramid HS-OF method (b). The bottom layer (0 layer) represents the original image, and the top layer represents the smallest image. The thin arrows in b indicate the direction of sea ice drift.
Figure 3. Spatial distribution of the region where velocity data for buoys in the Arctic Ocean are obtained. The buoys are numbered as nbx with x being 1 to 7.
Figure 4. Scatterplots of the data obtained by the HS-OF, 2LPHS-OF and 4LPHS-OF methods versus the buoy data in the u (x) and v (y) directions. a, b and c. HS-OF velocity, 2LPHS-OF velocity and 4LPHS-OF velocity in the u-direction; and d, e and f. HS-OF velocity, 2LPHS-OF velocity and 4LPHS-OF velocity in the v-direction.
Figure 5. The daily sea ice velocity in winter from 2014 to 2016 in the u-direction and v-direction, which are obtained from buoys and by the HS-OF, 2LPHS-OF and 4LPHS-OF methods. a, c, e and g. Velocities at the nb2, nb4, nb5 and nb7 position in the u-direction; and b. d, f and h, velocity at the nb2, nb4, nb5 and nb7 position in the v-direction.
Figure 6. The daily sea ice velocity in winter from 2014 to 2016 in the u-direction and v-direction, which are obtained from buoys and the OSI SAF and CMEMS dataset. a, c, e and g Velocities at the nb2, nb4, nb5 and nb7 position in the u-direction; and b, d, f and h. velocities at the nb2, nb4, nb5 and nb7 position in the v-direction.
Figure 7. Spatial distribution of the sea ice drift velocity on the 1st and 15th days of each month in the Arctic in 2016. The blue box indicates the occurrence of the Arctic cyclone, and the black box indicates the occurrence of the Arctic anticyclone, including the Beaufort Gyre.
Figure 8. The monthly sea ice velocity in nine subregions from January to March, 2016.