A multi-scale estuarine eddy identification method based on velocity field
By using a multi-scale estuarine vortex identification method based on velocity field, utilizing local normalized angular momentum and MATLAB programming, the problem of inaccurate estuarine vortex identification was solved, and accurate identification and tracking of vortices of different scales were achieved.
Patent Information
- Application Number
- CN202410068481.3
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2024-01-17
- Publication Date
- 2025-09-26
- Estimated Expiration
- 2044-01-17
AI Technical Summary
Existing technologies have difficulty in effectively identifying and tracking estuarine eddies, especially eddies of different scales and structures, resulting in inaccurate identification and omissions.
A multi-scale estuarine eddy identification method based on velocity field was adopted. The eddy center was determined by local normalized angular momentum (LNAM). Combined with streamlines and geometric characteristics at different scales, MATLAB programming was used to accurately identify the eddy boundary.
The accuracy and efficiency of estuarine eddy identification are improved, and the boundaries of eddies of different scales can be identified and adapted to complex velocity field data sets.
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Figure CN118015452B_ABST
Abstract
Description
Technical Field
[0001] The present invention belongs to the fields of marine science and physical oceanography, and in particular relates to a multi-scale estuary vortex identification method based on velocity field. Background Art
[0002] Estuarine eddies, a key type of ocean eddy, are rotating, closed ocean circulation bodies primarily at mesoscale and submesoscale scales. Their formation is closely linked to a variety of offshore dynamic processes and meteorological factors, and they are primarily active near river estuaries worldwide. Mesoscale eddies contain approximately 90% of the ocean's kinetic energy, and they profoundly influence nearshore flow patterns and energy distribution, the transport of land-based materials to the sea, and the dissemination of nutrients and pollutants. Consequently, automated identification and tracking of estuary eddies has become a research hotspot in recent years.
[0003] At present, the technology for identifying ocean eddies has been developed relatively maturely both at home and abroad. For example, LE VU et al. (2018) proposed an optimization algorithm for detecting and tracking eddies in two-dimensional velocity fields. The algorithm adopts a hybrid method based on the physical parameters and geometric characteristics of the velocity field. It can be applied to various fields with different spatial resolutions without the need for specific fine-tuning of the parameters. The algorithm is robust to the grid resolution and uses a minimum number of adjustable parameters to quantify the dynamic characteristics of the detected eddies, thereby providing the complete dynamic evolution of the detected ocean eddies during their life cycle. However, the above algorithm is more suitable for eddies in deep sea areas, but it cannot be fully adapted to the unique flow field structure of estuarine eddies. It is difficult to continuously identify eddies of different scales and structures in the estuary area. Therefore, it is urgent to propose a multi-scale estuarine eddy identification method based on the velocity field to solve the above problems. Summary of the Invention
[0004] In response to the above-mentioned gaps in the existing technology, the present invention proposes a multi-scale estuarine vortex identification method based on velocity field, which can accurately and effectively identify estuarine vortices of different scales, solves the defect of missing sub-mesoscale non-closed flow field vortices in the existing technology, and provides richer technical support for the universality of ocean vortex identification.
[0005] The present invention provides a multi-scale estuary vortex identification method based on velocity field, which specifically comprises the following steps:
[0006] Step 1: Extract the estuarine vortex-related dataset from the collected PIV particle image set. The relevant dataset includes the horizontal coordinate x, the vertical coordinate y, the horizontal velocity component u, and the vertical velocity component v. The horizontal velocity component u in step 1 is defined as positive toward the east, and the vertical velocity component v is defined as positive toward the north. All subsequent calculations are based on this.
[0007] Step 2: Calculate the local normalized angular momentum (LNAM) of any grid point within the set estuarine eddy identification range using the relevant data collected in step 1.
[0008] The absolute value of LNAM in step 2 is at the grid point G at the center of the vortex motion. i At each grid point G i , its LNAM value is:
[0009]
[0010] where X j and V j The grid points G i Nearby position and velocity vectors. When the scalar value When the value of is high, it is the center point of the hyperbola, and when it approaches 0, it is the center point of the ellipse (that is, the vortex center that meets the requirements). At this time, when the value of LNAM at this point is 1 (-1), the vortex is a cyclonic vortex (anticyclonic vortex).
[0011] Step 3: Determine the location and properties (cyclone / anticyclone) of the vortex center based on the value of LNAM calculated in step 2.
[0012] Step 4: Based on the vortex center position obtained in step 3, calculate the streamlines along the absolute value of the contour velocity within a range of 10 times the first baroclinic Rossby radius around each vortex center.
[0013] The streamline acquisition method is as follows: for all grid points that meet the LNAM method, a second geometric criterion is added, that is, only the grid points G around which closed streamlines can be found are retained. i . Select the grid point G i is the geometric center, 10 times the first baroclinic Rossby radius (10R d ) is the range of side lengths, and the local streamlines within this range are calculated:
[0014]
[0015] where g ′ is the reduced gravity, H is the thickness of the eddy source, and f is the Coriolis force parameter;
[0016] Statistics 10R d All closed and non-closed streamlines within the edge length range.
[0017] Step 5: Based on the vortex center location and attributes obtained in Step 3 and the streamlines obtained in Step 4, the vortex attributes are first determined: If it is a mesoscale anticyclonic vortex (LNAM = -1), due to its large size and complete and closed streamlines, the streamlines with the maximum average absolute velocity along the contour can be directly extracted as its vortex boundary. If it is a submesoscale cyclonic vortex (LNAM = 1), although its size is small, its streamlines are complete and closed, and the streamlines passing through the vertices with the maximum absolute velocity in the four quadrants can be extracted as its vortex boundary. If it is a submesoscale cyclonic circulation (LNAM = 1), due to its small size and open streamlines, the closed area consisting of the zero vorticity contour line and the horizontal shoreline near its vortex center can be extracted as its vortex boundary. Based on this, the vortex attribute determination and boundary extraction method in Step 5 is as follows: First, the LNAM value of the grid point is used to determine whether it is an anticyclone or a cyclone. Then, different boundary identification methods are applied to the vortex based on the streamline closure. The optimal boundary streamlines of different types of estuarine vortices are obtained, ultimately achieving multi-scale estuarine vortex identification.
[0018] The beneficial effects of the present invention are as follows:
[0019] (1) The present invention targets estuarine vortices, a special vortex form among ocean vortices, and makes multiple judgments by fully considering the geometric characteristics of vortices of different scales. It then uses different boundary recognition methods to determine the vortex boundaries, thereby improving the efficiency and accuracy of estuarine vortex recognition.
[0020] (2) The LNAM method used in the present invention for vortex center identification is highly robust and is not affected by complex velocity fields; the three boundary algorithms used for vortex boundary identification cover all types of estuary vortices and can cope with complex velocity field data sets. BRIEF DESCRIPTION OF THE DRAWINGS
[0021] Figure 1 This is a flow chart of a multi-scale estuarine vortex identification method based on velocity field according to the present invention;
[0022] Figure 2 Schematic diagram of vortex boundary identification in an anticyclonic estuary according to an embodiment of the present invention (* indicates the vortex center, and the black line indicates the streamline with the maximum average absolute value of velocity along the contour);
[0023] Figure 3 Schematic diagram of vortex boundary identification in a cyclone estuary according to an embodiment of the present invention (* represents the vortex center, black lines represent streamlines passing through the vertices of the maximum absolute velocity values in the four quadrants, and ● represents the vertices of the maximum absolute velocity values in the four quadrant directions);
[0024] Figure 4 This is a schematic diagram of the vortex boundary identification in the cyclonic circulation estuary according to an embodiment of the present invention (* is the vortex center, the black line is the streamline of the 0 vorticity value contour line, and the two coordinate points are the left and right boundaries of the horizontal coastline that forms a closed area with the former, which can be set manually). DETAILED DESCRIPTION
[0025] The specific embodiments of the present invention are further described in detail below with reference to the accompanying drawings.
[0026] The data set used in this embodiment comes from the PIV measurement system of the geofluid dynamics rotating test bench of the Marine Fluid Dynamics Laboratory of Zhejiang University. This data set provides the two-dimensional coordinates and velocity components required by the present invention. This embodiment is implemented by MATLAB programming, as shown in the following example. Figure 1 As shown in FIG, the multi-scale estuarine vortex identification method based on the velocity field specifically includes the following steps:
[0027] Step 1: Extract the estuarine vortex-related dataset from the collected PIV particle image set using MATLAB. The relevant dataset includes the horizontal coordinate x, the vertical coordinate y, the horizontal velocity component u, and the vertical velocity component v. The horizontal velocity component u in step 1 is defined as positive toward the east, and the vertical velocity component v is defined as positive toward the north. All subsequent calculations are based on this.
[0028] Step 2: Calculate the local normalized angular momentum (LNAM) of any grid point within the set estuarine eddy identification range using the relevant data collected in step 1.
[0029] The absolute value of LNAM in step 2 is at the grid point G at the center of the vortex motion. i At each grid point G i , its LNAM value is:
[0030]
[0031] where X j and V j The grid points G i Nearby position and velocity vectors.
[0032] When the scalar value When the value of is high, it is the center point of the hyperbola, and when it approaches 0, it is the center point of the ellipse (that is, the vortex center that meets the requirements). At this time, when the value of LNAM at this point is 1 (-1), the vortex is a cyclonic vortex (anticyclonic vortex).
[0033] Step 3: Determine the location and properties (cyclone / anticyclone) of the vortex center based on the value of LNAM calculated in step 2.
[0034] Step 4: Based on the vortex center position obtained in step 3, obtain the streamlines along the absolute value of the contour velocity within a range of 10 times the first baroclinic Rossby radius around each vortex center.
[0035] The streamline acquisition method is as follows: for all grid points that meet the LNAM method, a second geometric criterion is added, that is, only the grid points G around which closed streamlines can be found are retained. i . Select the grid point G i is the geometric center, 10 times the first baroclinic Rossby radius (10R d ) is the range of side lengths, and the local streamlines within this range are calculated:
[0036]
[0037] where g ′ is the simplified gravity, H is the thickness of the eddy current source, and f is the Coriolis force parameter.
[0038] Statistics 10R through MATLAB's streamline function d All closed and non-closed streamlines within the side length range (combined with the horizontal coastline to form a closed area) are used to obtain its perimeter L p And the area enclosed is A. Then for any closed streamline, the radius of the equivalent circle of the enclosed area is:
[0039]
[0040] And its average velocity along the contour is:
[0041]
[0042] Extract the maximum average velocity along the contour V from max =max( <v>) The streamline of the absolute value, its corresponding equivalent circle radius is R max . Final V max and R max and its corresponding L p and A define the geometric characteristics of the vortex.
[0043] When the average velocity of the outermost closed streamline along the contour is less than 0.97 times V max Time (i.e. <v>(R end )<0.97V max ), if the vortex criterion is met, the flow field is defined as an eddy; otherwise, it is defined as a gyre.
[0044] The properties of vortices and circulations determine their dynamic characteristics. Vortices can survive for a long time without external forces, while circulations are usually accompanied by external forces (such as geostrophic currents, flow sleeves, and stress effects between adjacent vortices).
[0045] For any detected vortex (circulation), its Rossby number is calculated as:
[0046] R O =V max / fR max 5)
[0047] And its radial vorticity is:
[0048]
[0049] In addition, for the above streamlines, the equivalent ellipticity (also known as flattening parameter) is calculated as:
[0050] ε=1-a1 / a2 7)
[0051] Where a1 is the semi-minor axis and a2 is the semi-major axis.
[0052] In order to ignore highly distorted streamlines, the embodiment of the present application also calculates the local curvature along each streamline. If more than 20% of the streamline circumference has a relatively negative curvature, the streamline is removed from the analysis and cannot be used as a feature boundary line. For large-scale circulations that may appear due to errors in practice, an additional R is set. lim is the threshold, and all R max >R lim After the above calculations, the characteristic boundary of the vortex (circulation) is finally obtained.
[0053] Step 5: Based on the vortex center position and properties obtained in step 3 and the streamlines obtained in step 4, first determine the vortex properties: if it is a mesoscale anticyclonic vortex (LNAM = -1), such as Figure 2 As shown in the figure, due to its large size, the streamlines are complete and closed, and the streamline with the maximum average absolute value of the velocity along the contour can be directly extracted as its vortex boundary through the streamline function of MATLAB. Figure 3 As shown in , if it is a submesoscale cyclonic vortex (LNAM = 1), although its size is small, its streamlines are complete and closed, and the streamlines passing through the vertices of the maximum absolute velocity values in the four quadrants can be extracted as its vortex boundaries. Figure 4 As shown, for a submesoscale cyclonic circulation (LNAM = 1), due to its small size and non-closed streamlines, the MATLAB contour function is used to extract the closed region formed by the zero vorticity contour line and the horizontal shoreline near the vortex center as its vortex boundary. Therefore, the vortex attribute identification and boundary acquisition method in step 5 are as follows: first, the LNAM value of the grid point is used to determine whether it is an anticyclone or a cyclone. Then, different boundary identification methods are applied to the vortex based on the streamline closure mentioned above to obtain the optimal boundary streamlines for different types of estuarine vortices.
[0054] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.< / v> < / v>
Claims
1. A multi-scale estuarine vortex identification method based on velocity field, characterized in that: The specific steps include: Step 1: Extracting an estuarine vortex-related dataset from the collected PIV particle image set, wherein the dataset includes abscissa x, ordinate y, horizontal velocity component u, and vertical velocity component v; Step 2: Calculate the local normalized angular momentum of any grid point within the set estuarine vortex identification range using the relevant data collected in step 1; Step 3: Determine the location and properties of the vortex center based on the value of the local normalized angular momentum calculated in step 2; Step 4: Based on the vortex center position obtained in step 3, obtain the streamline along the absolute value of the contour velocity within a range of n times the first baroclinic Rossby radius around each vortex center; n is a positive integer; Step 5: Determine whether it is an anticyclone or a cyclone based on the value of the local normalized angular momentum of the grid point. Then, use different boundary identification methods for the vortex according to the streamline closure situation to obtain the optimal boundary streamlines of different types of estuarine vortices, and finally realize multi-scale estuarine vortex identification. Specifically: If it is a mesoscale anticyclonic vortex, the streamline with the maximum average absolute value of velocity along the contour is directly extracted as its vortex boundary; If it is a sub-mesoscale cyclonic vortex, the streamline passing through the vertices of the maximum absolute velocity in the four quadrants is extracted as its vortex boundary; If it is a sub-mesoscale cyclonic circulation, the closed area composed of the 0 vorticity value contour line and the horizontal coastline near the vortex center is extracted as its vortex boundary.
2. The multi-scale estuary vortex identification method based on velocity field according to claim 1 is characterized in that: The horizontal velocity component u of step 1 is defined as positive toward the east, and the vertical velocity component v is defined as positive toward the north.
3. The multi-scale estuary vortex identification method based on velocity field according to claim 1 is characterized in that: The absolute value of the local normalized angular momentum in step 2 is at the grid point G at the center of the vortex motion. i Reaching maximum.
4. The multi-scale estuary vortex identification method based on velocity field according to claim 3 is characterized in that: For each grid point G i , the value of its local normalized angular momentum is: where X j and V j The grid points G i Nearby position and velocity vectors.
5. A multi-scale estuary vortex identification method based on velocity field according to claim 1 or 4, characterized in that: The streamline acquisition in step 4 is specifically as follows: For all grid points that meet the requirements, a second geometric criterion is added, that is, only the grid points G around which closed streamlines can be found are retained. i ; Select the grid point G i is the geometric center, 10 times the first baroclinic Rossby radius R d For the range of side lengths, calculate the local streamlines within this range: Statistics 10R d All closed and non-closed streamlines within the edge length range.