Long-time-series mesoscale eddy tracing method based on hybrid algorithm

Abstract

The invention belongs to the crossing field of physical oceanography and computer graphics and image processing, and particularly relates to a mesoscale eddy tracing method based on a hybrid algorithm. The hybrid algorithm mainly comprises nearest neighbor search, deformation control based similarity match and delay logic. The method comprises the following steps: step one, for the nearest neighbor search, eddies in a search range are delineated according to global mesoscale eddy data recognized with an SSH (sea surface height) method; step two, for a deformation control based similarity match method, the eddies in the range and attributes of the eddies are subjected to similarity calculation of area, amplitude, kinetic energy, relative vorticity and Hausdorff distance, the eddy with the maximum similarity is selected as the position of the next eddy, and jump of an eddy path is avoided through combination of physical attributes and geometric attributes of the eddies; step three, the delay logic is adopted, search at multiple time points is considered, the eddies temporarily disappearing at certain time points are processed, and discontinuity of the eddy path is avoided, so that the purpose of multi-year long-term efficient tracing on the eddies is achieved.

Description

technical field [0001] The invention relates to the field of physical ocean and computer graphics image processing, more specifically, it is a hybrid mesoscale eddy tracking algorithm combining nearest neighbor search, similarity matching of vortex deformation control and delay logic. Background technique [0002] As an important phenomenon in the ocean, the mesoscale vortex has a time scale of several days to several years and a spatial scale of tens of kilometers to hundreds of kilometers. It plays an important role in the transportation of matter and energy in the ocean, affecting Biogeochemical processes of materials in the atmosphere and ocean interior. Studying the migration path of eddies, that is, tracking mesoscale eddies is of great significance for better understanding of ocean phenomena and changes in ocean matter and energy. [0003] The tracking of mesoscale vortices relies on the identification results of mesoscale vortices as the input data for vortex tracki...

AI Technical Summary

Problems solved by technology

First, the threshold of W value needs to be formulated, but there is no uniform threshold for the whole world

Second, the estimation of the W parameter will also be affected by the noise of SSH

(3) WindingAngle (WA) winding angle method, which has been proven to have higher accuracy than the SSH method, but the computational complexity is too high

[0006] At present, most of the tracking algorithms for mesoscale eddies in the ocean community use the nearest neighbor method, that is, to search and match eddies within a certain range of adjacent time frames. If the matching is unsuccessful, the search is stopped, and the generated path is shorter and And inaccurate, can't handle the vortex that "disappears" for a short time

Some scholars use the method of horizontal tracking and vertical tracking to track mesoscale eddies, and use 2-day intervals for tracking in horizontal tracking, but this method cannot simultaneously track global mesoscale eddies for a long time, and 2 The day setting is too fixed, the actual vortex may disappear for 3 days or more, and the vertical tracking uses model data, the reliability is doubtful

At present, there are methods based on multi-objective assumptions to maintain multiple possible propagation paths of eddies, but the calculation is heavy and the efficiency is low, and it is not suitable for long-term tracking of eddies on the decadal time scale

Some algorithms use delay logic to delay the determination of the motion path of the vortex, but in the process of similarity matching, the matching attribute is selected to be single, and it is impossible to deal with the "jumping" problem of the generated vortex path

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