Characterization of the oceanic mesoscale eddy field from Lagrangian statistics of ice floes acquire
Abstract
Turbulence is arguably one of the most important unresolved problems in classical physics. In the ocean, it has a very important rol,e in the transfer of heat, vertical mixing, and the redistribution of nutrients, oxygen, and carbon, thus having a critical role in, sustaining local ecosystems and global ocean biogeochemistry. In particular, small-to-moderate scale eddies or meso/submeso-scales,(1-100 m) have been estimated to account for most of the sub-inertial kinetic energy in the upper ocean. However, acquiring a quanti,tative characterization of the eddy field within this spatial range has proven challenging. In situ field measurements remain spars,e given the difficult conditions of performing fieldwork in the Arctic. And, even though satellite altimetry has provided a window i,the difficulty of processing data in ice-covered regions have hindered our ability to observe the meso/submeso-scale eddy field in m,ost Arctic regions.In recent years, the use of satellite remote sensing imagery, particularly from Synthetic Aperture Radar (SAR), h,as emerged s a good alternative to traditional eddy identification methods. While invaluable information has been gathered, several,issues remain to be add,fficult to quantify robustly. The greatest limitation of manual detection is the inability to process sufficiently long time series, of imagery to analyze decadal trends. Second, the expression of eddies in SAR imagery depends on theoccurrence of surface roughness, patterns resulting from wave-current interactions in ice-free regions and on the divergence/convergence of ice floes leaving streak,s in ice-covered regions. Images are evaluated based on these patterns alone and sometimes complemented with a cross-correlation ana,lysis of image pairs to extract the Eulerian velocity field of an image sequence. Thus, at high-to-moderate wind conditions, the ide,ntification of eddies is dependent on the concentration of sea ice such that meso/submeso-scale eddy signatures are readily observed, in an image. Even then, without convergence/divergence patterns, it is unfeasible to retrieve information regarding eddy characteri,stics. Hence, even though this method provides the location, spatial scales, sense of rotation of eddies, and short trajectories of,identified eddy cores, it is insufficient to characterize the eddy field properly.We propose to use our methodology to extract the g, dispersion characteristics) of ice floes to characterize meso/submeso-scales with subsurface expression. We will leverage the tight, connection between the ocean eddy field at small-to-moderate scales and the dynamics of ice floes in Marginal Ice Zones (MIZ). We w,ill acquire sea ice observations from NASA?s Moderate Resolution Imaging Spectroradiometer (MODIS) dataset, which represents the lon,gest record of Earth ever compiled. As such, MODIS imagery can provide valuable daily observations with high spatial coverage of sea, ice at moderate spatial resolutions (250 m) extending throughout the 21BC century. Our newly developed ice floe tracker algorithm e,ffectively deals with the limitations of visual imagery concerning clouds and illumination autonomously. Preliminary results demonst,rate the feasibility of our technique to quantitatively characterize ocean eddies in the Beaufort Sea and Fram Strait regions during, the spring-to-summer period. This project will allow us to develop and validate this method to characterize meso/submeso-scale eddy, fields and analyze the decadal evolution of eddies. The proposed scope of work is Fundamental Research having civil and military ap,plications.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Sep 08, 2022
- Source ID
- N000142212741
Entities
People
- Monica M. Wilhelmus
Organizations
- Brown University
- Office of Naval Research
- United States Navy