Method for automatically identifying the Kuroshio axis using ocean surface current velocity and sea surface height

Abstract

The present invention provides a method for automatically identifying the Kuroshio axis using ocean surface velocity and sea surface height. This method first obtains the meridional and zonal velocities of the sea surface to calculate the full-field flow field, and obtains the maximum velocity reference line through the forward, reverse, and bidirectional velocity extreme value method; then, using the sea surface altimetry data, calculates multiple values through data processing to generate sea surface reference contour lines; then calculates the minimum difference degree between the maximum velocity reference line and each reference contour line to determine the target reference contour line; finally, uses the velocity extreme value method again to correct the target reference contour line to obtain the Kuroshio main axis. The present invention effectively solves the problem that the classical velocity extreme value method is affected by vortices, can adapt to multi-source and multi-temporal data, realizes the automatic extraction of the real-time dynamic Kuroshio axis, improves the accuracy and integrity of Kuroshio axis identification, and is of great significance for studying the Kuroshio path and the law of flow rate change.

Description

Technical Field

[0001] The present invention relates to the technical field of marine environment monitoring and data analysis, and in particular to a method for automatically identifying a black current axis by utilizing ocean surface velocity and sea surface height. Background Art

[0002] The Kuroshio Current is a powerful warm current at the western boundary of the North Pacific Ocean. Characterized by high water temperature, high salinity, and rapid currents, it profoundly impacts the surrounding marine environment, climate, and biodiversity. Identifying the Kuroshio Current's axis is a crucial topic in oceanographic research. Currently, three main methods are employed: those based on currents or streamlines, those based on isotherms, and those based on absolute dynamic height (ADT). While these methods offer some effectiveness in practical applications, they each have significant limitations.

[0003] First, current or streamline-based identification methods rely on the Kuroshio's distinctive velocity characteristics as a strong western boundary current, offering intuitive and rapid results. However, these methods are susceptible to interference from surrounding eddies in complex flow fields, which can affect the accurate identification of the flow axis. Furthermore, transient changes in velocity can lead to unstable flow axis positions, limiting their application in dynamic ocean environments. Second, isotherm-based identification methods are widely used due to the Kuroshio's high temperature characteristics, but their selection criteria are subjective and often require adjustment for different sea areas and seasons. Especially when using daily data, the complexity of the ocean environment affects the reliability of flow axes, raising questions about the accuracy of automatic identification. Finally, identification methods based on absolute dynamic height combine sea level anomalies with mean dynamic topography data to provide more comprehensive flow field information. However, inconsistent sea surface height values across datasets from different versions and sources, combined with the fact that they are often analyzed based on multi-year averages, make them difficult to adapt to the dynamic, real-time dynamics of the Kuroshio, impacting the stability and accuracy of flow axis identification and increasing the complexity of their application.

[0004] In summary, while existing methods have certain advantages in identifying the Kuroshio Current axis, they generally face challenges such as subjectivity, complexity, and insufficient accuracy. Therefore, the present invention provides an innovative comprehensive identification method that aims to overcome the limitations of existing technologies, achieving automated confirmation of the Kuroshio Current axis while improving the accuracy and completeness of Kuroshio Current axis identification. Summary of the Invention

[0005] The present invention provides a method for automatically identifying the black current axis by using ocean surface velocity and sea surface height, so as to solve the problems of low accuracy, poor real-time performance and insufficient adaptability in the prior art, and realize automatic and high-precision identification of the black current axis.

[0006] The present invention provides a method for automatically identifying the black current axis using ocean surface velocity and sea surface height, comprising the following steps:

[0007] Step 1: Obtain data and calculate the full-field flow field;

[0008] Step 2: Use the velocity extreme value method to obtain the maximum velocity reference line;

[0009] Step 3: Calculate and identify the sea surface reference contour line;

[0010] Step 4: Determine the target reference contour line;

[0011] Step 5: Modify the target reference contour line to obtain the Kuroshio main axis.

[0012] Preferably, in Step 1, obtain the meridional velocity u and zonal velocity v of the sea surface of the sea area to be detected from satellite observations or numerical model data, and calculate the full-field flow velocity data V through vector synthesis. The formula is , and then obtain the full-field flow velocity and flow direction.

[0013] Preferably, in Step 2, it includes the forward velocity extreme value method and the reverse velocity extreme value method. Among them, the forward velocity extreme value method is specifically as follows: Select a representative point as the first fixed point; construct an auxiliary line vertically along the flow direction of the fixed point, and calculate the average flow direction for all grid points on the auxiliary line; the fixed point constructs a new auxiliary line vertically based on the average flow direction, and find the grid point with the maximum velocity on the new auxiliary line, which is defined as the maximum velocity reference point; this reference point advances along the average flow direction, and the advancing distance is set by itself according to the data resolution, set as d , move to the next fixed point, and repeat the above steps until the fixed point reaches the longitude or latitude boundary line of the sea area to be detected, and connect all the maximum flow velocity points to form the forward maximum velocity reference line;

[0014] The reverse velocity extreme value method is specifically as follows: Multiply the full-field flow velocity by -1 to obtain the reverse flow field; start from the given reverse starting point, perform the same operations as the forward velocity extreme value method to obtain the reverse maximum velocity reference line; if the reverse velocity extreme value method fails to successfully determine the maximum velocity reference line, then turn to the forward velocity extreme value method; after completing the analysis of the reverse and forward velocity extreme value methods, use the two-way method to reasonably splice the results of the two to finally determine the maximum velocity reference line segment of the sea area to be detected.

[0015] Preferably, Step 3 is specifically as follows: Obtain the sea surface altimetry data of the sea area to be detected from the data used, draw the sea surface altimetry contour lines of the entire sea area to be detected, and based on the obtained maximum velocity reference line, perform the calculation and identification of the sea surface reference contour line. The specific calculation method is as follows:

[0016] Data preprocessing: Statistically classify the sea surface Coronation height values of all points on the maximum velocity reference line; to improve the accuracy of statistics, multiply the sea surface height uniformly by ;Ensured that during subsequent statistical processes, all height values are on the same scale, reducing errors caused by numerical differences and thus enhancing data consistency;

[0017]

[0018] Among them, is the original sea surface height value, is the required number of decimal places;

[0019] Floor function: Take the floor of the magnified sea surface height value to obtain an integer value;

[0020]

[0021] Restore the original number of digits: Divide the rounded height value by 10 to restore the original number of digits, ensuring the true expression of the data and avoiding information loss caused by numerical scaling;

[0022]

[0023] Mode value calculation: Based on the obtained height values, calculate the mode value on the maximum speed reference line; this mode value is the sea surface altimetry reference contour value, and then add and subtract the interval value between this mode value and adjacent contours to generate three sea surface altimetry reference contours.

[0024] Preferably, in step four, by calculating the distance between the sea surface altimetry contour and the straight line of the maximum speed reference line, find the reference contour closest to it; the minimum difference calculation process is divided into the following steps:

[0025] Data preparation: The longitude and latitude points of the maximum speed reference line and the corresponding path points on different reference contours;

[0026] Define the longitude range: Set the optimal longitude range to be calculated, which is used to filter valid maximum speed reference line points and reference contour points;

[0027] Calculate the minimum difference: For each valid contour point of each sea surface altimetry reference contour in turn, calculate its minimum distance to the maximum speed reference line, and the distance calculation formula is:

[0028]

[0029] Among them, is the longitude and latitude of the current contour point, is the point on the maximum speed reference line;

[0030] Calculate the average difference degree: For each isoline in turn, accumulate the minimum distances from all its valid isoline points to the maximum velocity reference line to obtain the total difference degree, and calculate the average difference degree:

[0031]

[0032] Obtain the target reference isoline: Compare the average difference degrees of each reference isoline. The reference isoline with the smallest average difference degree is the target reference isoline.

[0033] Preferably, in the fifth step, the velocity extreme value method is used again to correct the target reference isoline to obtain the Kuroshio main axis. The specific correction process is as follows:

[0034] Data preparation: Identify and obtain the longitude and latitude positions, combined velocity, flow direction information, and sea surface altimetry data information of all points on the target reference isoline;

[0035] Interpolation calculation: For each point on the target isoline, construct an auxiliary line vertically along the flow direction at this point, and interpolate and calculate the velocity magnitude at this position at intervals. The distance range is defined by the actual resolution of the data used;

[0036] Find the maximum velocity points: For each auxiliary line, find the point with the maximum velocity on this line, which is defined as the point on the Kuroshio main axis;

[0037] Correct the main axis: Gather all the maximum velocity points. These points represent the Kuroshio axis path under the maximum velocity condition. Connect them into a line and smooth it to complete the correction.

[0038] Beneficial effects: The present invention calculates and generates the maximum velocity reference line through the velocity extreme value method in multiple directions, ensuring the maximum velocity characteristic of the Kuroshio axis. At the same time, using sea surface altimetry data to screen the reference isoline and adopting geometric distance and interpolation calculation methods effectively overcome the limitations of the traditional isoline method, greatly improving the accuracy and reliability of Kuroshio flow path recognition.

[0039] The present invention can adapt to different observation data and model data sets, directly obtain the real-time Kuroshio axis morphology based on the time resolution of the data used, realize the automatic extraction of the real-time dynamic Kuroshio main axis, no longer rely on long-term observation averages to obtain the reference isoline, reduce the demand for a large amount of computational processing, and avoid the negative impact of multi-year averages on the real-time presentation of the axis.

[0040] The present invention is applicable to various multi-source and multi-temporal satellite observation data and numerical model data, effectively solving the deviation and interruption problems that may be caused by the classical velocity extreme value method under the influence of vortices, and ensuring that the identified Kuroshio main axis points are all the maximum velocity points in the sea area to be measured.

[0041] The above description is only an overview of the technical solution of the embodiments of the present invention. In order to understand the technical means of the embodiments of the present invention more clearly, it can be implemented according to the content of the specification. And in order to make the above and other purposes, features and advantages of the embodiments of the present invention more obvious and understandable, the following specific embodiments of the present invention are specifically given. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0043] Figure 1 It is a flowchart of the speed extreme value method applied to the present invention;

[0044] Figure 2 It is the overall flowchart of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0045] In order to make the objectives, technical solutions and advantages of the embodiments of the present invention clearer, the following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts fall within the scope of protection of the present invention.

[0046] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the technical field to which this invention belongs; the terms used in the description of the present application herein are only for the purpose of describing specific embodiments and are not intended to limit the present invention; the terms "including" and "having" and any variations thereof in the description and claims of the present invention and the drawings are intended to cover non-exclusive inclusion.

[0047] Reference to "embodiment" herein means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the invention. The phrase "embodiment" appearing in various places in the specification is not necessarily all referring to the same embodiment, nor is it an independent or alternative embodiment mutually exclusive with other embodiments. Those skilled in the art will explicitly and implicitly understand that the embodiments described herein can be combined with other embodiments.

[0048] In order to enable those skilled in the art of this technology to better understand the solution of the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings.

[0049] As Figure 1 - Figure 2 shown, the present invention discloses a method for automatically identifying the Kuroshio axis using ocean surface current velocity and sea surface height, comprising the following steps:

[0050] Step 1: Obtain data and calculate the full-field flow field;

[0051] Step 2: Use the velocity extreme value method to obtain the maximum velocity reference line;

[0052] Step 3: Calculate and identify the sea surface reference isopleth;

[0053] Step 4: Determine the target reference isopleth;

[0054] Step 5: Modify the target reference isopleth to obtain the Kuroshio main axis.

[0055] In step 1 of the present invention, the meridional velocity of the sea surface in the sea area to be detected is obtained from satellite observation or numerical model data u , zonal velocity v , and the full-field flow velocity data is calculated through vector synthesis V , and the formula is , and then the full-field flow velocity and flow direction are obtained.

[0056] In step 2 of the present invention, it includes the forward velocity extreme value method and the reverse velocity extreme value method. Among them, the forward velocity extreme value method is specifically as follows: Select a representative point as the first fixed point; Construct an auxiliary line vertically along the flow direction of the fixed point, and calculate the average flow direction for all grid points on the auxiliary line; The fixed point constructs a new auxiliary line vertically based on the average flow direction, and finds the grid point with the maximum velocity on the new auxiliary line, which is defined as the maximum velocity reference point; The reference point advances along the average flow direction, and the advancing distance is set according to the data resolution by itself, set as d , move to the next fixed point, and repeat the above steps until the fixed point reaches the longitude or latitude boundary line of the sea area to be detected, and connect all the maximum velocity points to form the forward maximum velocity reference line;

[0057] The reverse velocity extreme value method is specifically as follows: Multiply the full-field flow velocity by -1 to obtain the reverse flow field; Starting from the given reverse starting point, perform the same operations as the forward velocity extreme value method to obtain the reverse maximum velocity reference line; If the reverse velocity extreme value method fails to successfully determine the maximum velocity reference line, then turn to the forward velocity extreme value method; After completing the analysis of the reverse and forward velocity extreme value methods, use the two-way method to reasonably splice the results of the two, and finally determine the maximum velocity reference segment of the sea area to be detected.

[0058] Since the flow field may be disturbed by surrounding vortices, if the reverse velocity extreme value method fails to successfully determine the maximum velocity reference line, the forward velocity extreme value method will be used instead. During this process, the same operation is performed using the given forward starting point to extract the forward maximum velocity reference line. Combining the forward and reverse velocity extreme value methods can significantly improve the success rate of extracting the maximum velocity reference line.

[0059] Specifically, step three of the present invention is as follows: Obtain the sea surface altimetry data of the sea area to be measured from the data used, draw the sea surface altimetry contour lines of the entire sea area to be measured, and based on the obtained maximum velocity reference line, calculate and identify the sea surface reference contour lines. The specific calculation method is as follows:

[0060] Data preprocessing: Statistically classify the sea surface height values of all points on the maximum velocity reference line; To improve the accuracy of statistics, multiply the sea surface height uniformly by ; It ensures that during subsequent statistical processes, all height values are on the same scale, reduces errors caused by numerical differences, and thus improves the consistency of the data;

[0061]

[0062] Among them, is the original sea surface height value, is the required number of decimal places;

[0063] Floor function: Take the floor of the magnified sea surface height value to obtain an integer value;

[0064]

[0065] Restore the original number of digits: Divide the rounded height value by 10 to restore the original number of digits, ensuring the true expression of the data and avoiding information loss caused by numerical scaling;

[0066]

[0067] Mode value calculation: Based on the obtained height values, statistically calculate the mode value on the maximum velocity reference line; This mode value is the sea surface altimetry reference contour line value, and then add and subtract the interval value between this mode value and the adjacent contour lines to generate three sea surface altimetry reference contour lines.

[0068] The specific step examples are as follows:

[0069] ① When the z values are 0.8934, 0.8734, 0.8265, 0.9875, etc., magnify the data by 10 times to get 8.934, 8.734, 8.265, 9.875;

[0070] ② Then perform rounding to obtain the values of 9, 9, 8, 10;

[0071] ③ Then 'reduce' it by 10 times to obtain the contour values corresponding to the decimal places, namely 0.9m, 0.9m, 0.8m, and 1.0m;

[0072] ④ Then calculate the mode value based on the obtained values.

[0073] This mode value is the sea surface altimetry reference contour value. Then add and subtract the interval value between this mode value and the adjacent contour to generate three sea surface altimetry reference contours. This method is of great significance. It can dynamically adapt to the resolution and data accuracy of different data sources, and automatically extract the contour group that can be used as a reference for any sea area to be measured. The mode value on the maximum speed reference line provides a key reference point for subsequent analysis. As the value with the highest frequency of occurrence in the dataset, the mode can effectively represent the typical sea surface height characteristics in this maximum speed area, laying a solid foundation for obtaining the continuous and maximum speed mainstream axis.

[0074] In step four of the present invention, by calculating the distance between the sea surface altimetry contour and the straight line of the maximum speed reference line, the reference contour closest to it is found; the calculation process of the minimum difference degree is divided into the following steps:

[0075] Data preparation: The longitude and latitude points of the maximum speed reference line and the corresponding path points on different reference contours;

[0076] Define the longitude range: Set the optimal longitude range that needs to be calculated to filter the valid maximum speed reference line points and reference contour points;

[0077] Calculate the minimum difference degree: For each valid contour point on each sea surface altimetry reference contour, calculate its minimum distance to the maximum speed reference line. The distance calculation formula is:

[0078]

[0079] where, is the longitude and latitude of the current contour point, is the point on the maximum speed reference line;

[0080] Calculate the average difference degree: For each contour, accumulate the minimum distances from all its valid contour points to the maximum speed reference line to obtain the total difference degree, and calculate the average difference degree:

[0081] Obtain the target reference contour: Compare the sizes of the average difference degrees of each reference contour. The reference contour with the smallest average difference degree is the target reference contour.

[0082] It not only improves the utilization efficiency of sea surface altimetry data, but also further enhances the accuracy of reference contour selection and the recognition accuracy of the Kuroshio main axis. By calculating the difference degree from the target reference contour, this method can adaptively adjust the position of the flow axis, provide a more accurate Kuroshio flow path, and provide an important basis for the subsequent determination of the Kuroshio main axis.

[0083] In step five of the present invention, the velocity extreme value method is used again to correct the target reference contour to obtain the Kuroshio main axis. The specific correction process is as follows:

[0084] Data preparation: Identify and obtain the longitude and latitude positions, combined flow velocity, flow direction information, and sea surface altimetry data information of all points on the target reference contour.

[0085] Interpolation calculation: For each point on the target contour, construct an auxiliary line vertically along the flow direction at this point, and interpolate and calculate the flow velocity magnitude at this position at intervals. The distance range is defined according to the actual resolution of the data used.

[0086] Find the maximum velocity point: For each auxiliary line, find the point with the maximum flow velocity on this line, which is defined as the point on the Kuroshio main axis.

[0087] Correct the main axis: Gather all the maximum velocity points. These points represent the Kuroshio flow axis path under the condition of maximum flow velocity. Connect them into a line and smooth it to complete the correction.

[0088] By using the velocity extreme value method to find the highest flow velocity point near specific contour points, the main axis of the Kuroshio can be depicted more accurately, ensuring that the flow field characteristics are accurately reflected in a complex flow field environment. Embodiment

[0089] In this embodiment, satellite altimeter sea surface flow field data and satellite remote sensing AVSIO absolute dynamic topography (ADT) are used to extract the Kuroshio surface flow axis. This data is provided by the French Satellite Ocean Archive Data Center and is a delayed daily sea surface product released by the Copernicus Marine Environment Monitoring Center. The data integrates the observation data of ERS-1 / 2, Envisat, Topex / Poseidon, and their subsequent satellites Jason-1 / 2. Its spatial resolution is 1 / 4°×1 / 4°, the time resolution is daily, and the time range is from 1993 to November 2023. The specific elements used include ADT data and geostrophic velocity data (meridional flow velocity , zonal flow velocity ) derived from ADT through geostrophic balance. The sea area range of the embodiment is 24.375°-30.875°N, 121.625°-130.625°E.

[0090] S101. Calculate the sea surface height contour lines of the entire implementation area using ADT data, with a contour interval of 0.1 m, to form an ADT sea surface height contour map.

[0091] S102. Calculate the flow velocity and flow direction results of the entire implementation area using geostrophic velocity data, , , and form an entire flow field map.

[0092] S20. Based on the flow velocity and flow direction results of the entire implementation area, calculate the maximum velocity reference line using the velocity extreme value method in multiple directions.

[0093] S201. Flow velocity reverse processing: First, multiply the flow velocity of the entire field by -1. The magnitude of the flow velocity in the reverse flow field is not affected, and the path recognition from north to south can effectively reduce the problem of vortex-induced flow field bifurcation. Using the reverse velocity extreme value method, starting from the given reverse starting point, construct a 200-km auxiliary line (100 km on each side of the fixed point) along the vertical direction of the fixed-point flow direction. For all grid points on this auxiliary line, calculate the average flow direction. The length of the auxiliary line can be defined according to the specific situation of the research area and the data used.

[0094] S202. Construct a new 100-km auxiliary line (50 km on each side of the fixed point) along the vertical direction of the average flow direction at the fixed point.

[0095] S203. Identify all grid points passing through on the new auxiliary line, read out the data information on the grid points, and determine and find the grid point with the maximum flow velocity on the new auxiliary line, which is recorded as the maximum velocity reference point.

[0096] S204. Move forward 30 km (which can be set according to the data resolution) along the average flow direction from the obtained maximum velocity reference point to the next fixed point.

[0097] S205. Repeat steps S202 - S205 until the fixed point reaches the longitude or latitude boundary line of the implementation area, and finally identify all maximum flow velocity points and connect these points to form a reverse maximum velocity reference line.

[0098] If the reverse velocity extreme value method fails due to the influence of vortices.

[0099] S206. Switch to flow velocity forward processing: During this process, perform the same operations using the given forward starting point to extract the forward maximum velocity reference line. Combining the forward and reverse velocity extreme value methods can significantly improve the success rate of extracting the maximum velocity reference line.

[0100] In the waters of this embodiment and the usage data results, the maximum speed reference line of each day can be successfully confirmed only by combining the reverse and forward speed extreme value methods. Therefore, to show the form of the two-way speed extreme value method, the usage data is specifically replaced with the numerical mode data HYCOM (Hybrid Coordinate Ocean Model) reanalysis dataset, which has a spatial resolution of 1 / 12°×1 / 12° and a time resolution of 3 hours.

[0101] S30. Based on the obtained maximum speed reference line, calculate and identify the sea surface reference contour line.

[0102] S301. Identify the ADT values of all grid points on the maximum speed reference line and perform statistical classification. To improve the accuracy of classification, multiply all ADT values by 10 (if the contour interval needs to be accurate to two decimal places, multiply by 100, and so on, multiply by the corresponding multiple).

[0103] S302. Round down the amplified ADT value to obtain its integer value.

[0104] S303. Divide the rounded height value by 10 to restore the original number of digits.

[0105] S304. Based on the obtained height value, count the mode value on the maximum speed reference line.

[0106] Through the classification statistics of this series of steps, in the process of calculating and identifying the ADT reference contour line around the maximum speed line, the accuracy of classification can be effectively improved and the data processing can be simplified.

[0107] S305. If the mode value is 1.0, then add and subtract the contour interval value of 0.1 from the value 1.0 to generate three sea surface altimetry reference contour lines, which are generated as 0.9 m, 1.0 m, and 1.1 m reference contour lines.

[0108] S40. Calculate the minimum difference degree between the maximum speed reference line and each ADT reference contour line to obtain the target reference contour line.

[0109] S401. Read out the position information of each point on the maximum speed reference line and the ADT reference contour line.

[0110] S402. Set the calculated longitude range, and filter out the position information of each point on each line within the corresponding longitude range to maximize the matching degree between the maximum speed and the ADT isopleth. If it is the reverse maximum speed reference line, the longitude range is 127.87°E - 130.125°E; if it is the forward maximum speed reference line, the longitude range is 121.875°E - 124.125°E; if it is a two-way maximum speed reference line, the accuracy ranges are 127.875°E - 130.125°E and 121.875°E - 124.125°E.

[0111] S403. Within the corresponding longitude range, calculate the minimum distance from each point on the maximum speed reference line to each valid isopleth point on each ADT reference isopleth in turn. The distance calculation formula is:

[0112] S404. Accumulate the minimum distances from the valid points on each isopleth to the maximum speed reference line to obtain the total difference degree, and then calculate the average difference degree of each isopleth. The calculation formula is: 。

[0113] S405. Compare the average difference degrees of each isopleth. The ADT isopleth with the minimum average difference degree is regarded as the target ADT reference isopleth.

[0114] After the calculation by the minimum difference degree, the accuracy of the selection of the reference isopleth is further enhanced, and the recognition accuracy of the Kuroshio main axis is improved.

[0115] S50. Use the velocity extreme value method again to correct the target ADT reference isopleth to obtain the Kuroshio main axis.

[0116] S501. Identify the longitude and latitude positions, combined flow velocity, flow direction information, and sea surface altimetry data information of all points on the target ADT reference isopleth.

[0117] S502. For each point on the target isopleth, construct a 60-km auxiliary line (30 km on each side) vertically along its flow direction, and interpolate and calculate the flow velocity magnitude every 3 km.

[0118] S503. For each auxiliary line in turn, find the point with the maximum flow velocity on the current auxiliary line, and replace each point on the original target ADT reference isopleth with the point with the maximum flow velocity on its corresponding auxiliary line to obtain the points on the Kuroshio main axis.

[0119] S504. Gather all the points with the maximum flow velocity and connect them into a line to complete the correction.

[0120] S505. After sliding average smoothing with a window size of 3, the final Kuroshio main axis is obtained.

[0121] As described above, the method for automatically comprehensively identifying and determining the main axis of the Kuroshio surface current assisted by sea surface altimetry data proposed by the present invention can ensure the maximum flow velocity characteristic of the Kuroshio axis to the greatest extent, thereby overcoming the limitations of the traditional contour method.

[0122] To sum up, the present invention generates a maximum velocity reference line by calculating the velocity extreme value method in multiple directions, ensuring the maximum flow velocity characteristic of the Kuroshio axis. At the same time, the sea surface altimetry data is used to screen the reference contour lines, and the geometric distance and interpolation calculation methods are adopted, effectively overcoming the limitations of the traditional contour method and greatly improving the accuracy and reliability of the identification of the Kuroshio flow path.

[0123] The present invention can adapt to different observation data and model data sets, directly obtain the real-time Kuroshio axis morphology based on the time resolution of the used data, realize the automatic extraction of the real-time dynamic Kuroshio main axis, no longer rely on long-term observation averages to obtain reference contour lines, reduce the demand for a large amount of computational processing, and avoid the negative impact of multi-year averages on the real-time presentation of the convection axis.

[0124] The present invention is applicable to various multi-source and multi-temporal satellite observation data and numerical model data, effectively solving the deviation and interruption problems that may be caused by the classical velocity extreme value method under the influence of vortices, and ensuring that the identified Kuroshio main axis points are all the maximum velocity points in the sea area to be measured.

[0125] As described above, 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 foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for automatically identifying the Kuroshio axis using ocean surface velocity and sea surface height, comprising the following steps: Step 1: Obtain data and calculate the full-field flow field; Step 2: Use the velocity extreme value method to obtain the maximum velocity reference line; Step 3: Calculate and identify the sea surface reference contour line; Step 4: Determine the target reference contour line; Step 5: Modify the target reference contour line to obtain the main Kuroshio axis; In the first step, obtain the meridional velocity u and zonal velocity v of the sea surface in the sea area to be detected from satellite observations or numerical model data, and calculate the full-field velocity data V through vector synthesis. The formula is Furthermore, obtain the full-field velocity and flow direction; In the second step, it includes the forward velocity extreme value method and the reverse velocity extreme value method, where The forward velocity extreme value method is specifically as follows: Select a representative point as the first fixed point; Construct an auxiliary line vertically along the flow direction of the fixed point, and calculate the average flow direction for all grid points on the auxiliary line; Based on the average flow direction of the fixed point, construct a new auxiliary line vertically, find the grid point with the maximum velocity on the new auxiliary line, and define it as the maximum velocity reference point; The reference point moves forward along the average flow direction, and the forward distance is set according to the data resolution, set as d, and move to the next fixed point, repeat the above steps until the fixed point reaches the longitude or latitude boundary line of the sea area to be measured, and connect all the maximum velocity points to form the forward maximum velocity reference line; The reverse velocity extreme value method is specifically as follows: Multiply the full-field flow velocity by -1 to obtain the reverse flow field; Starting from the given reverse starting point, perform the same operations as the forward velocity extreme value method to obtain the reverse maximum velocity reference line; If the reverse velocity extreme value method fails to successfully determine the maximum velocity reference line, then turn to the forward velocity extreme value method; After completing the analysis of the reverse and forward velocity extreme value methods, use the two-way method to reasonably splice the results of the two, and finally determine the maximum velocity reference line segment of the sea area to be measured; The third step is specifically as follows: Obtain the sea surface altimetry data of the sea area to be measured from the data used, draw the sea surface altimetry contour lines of the entire sea area to be measured, and based on the obtained maximum velocity reference line, calculate and identify the sea surface reference contour line. The specific calculation method is as follows: Data preprocessing: Statistically classify the sea surface Coronation height values of all points on the maximum speed reference line; To improve the accuracy of the statistics, multiply the sea surface height by 10 uniformly n ; It ensures that in the subsequent statistical process, all height values are on the same scale, reduces the error caused by numerical differences, and thus improves the data consistency; z1 = z × 10 n Where z is the original sea surface height value and n is the required number of decimal places; Floor function: Take the floor of the magnified sea surface height value to obtain an integer value; Restore the original number of digits: Divide the rounded height value by 10 to restore the original number of digits, ensuring the true expression of the data and avoiding information loss caused by numerical scaling; Mode value calculation: Based on the obtained height value, count the mode value on the maximum velocity reference line; This mode value is the sea surface altimetry reference contour line value, and then add and subtract the interval value between this mode value and the adjacent contour lines to generate three sea surface altimetry reference contour lines; In the fourth step, by calculating the distance between the sea surface altimetry contour line and the straight line of the maximum velocity reference line, find the reference contour line closest to it; The minimum difference calculation process is divided into the following steps: Data preparation: The longitude and latitude points of the maximum velocity reference line and the corresponding path points on different reference contour lines; Define the longitude range: Set the optimal longitude range that needs to be calculated to filter the valid maximum velocity reference line points and reference contour line points; Calculate the minimum difference: For each valid contour line point of each sea surface altimetry reference contour line in turn, calculate its minimum distance to the maximum velocity reference line. The distance calculation formula is: Among them, (lon, lat) is the longitude and latitude of the current contour point, (lon vmax , lat vmax ) is the point on the maximum speed reference line; Calculate the average difference degree: For each isoline in sequence, accumulate the minimum distances from all valid isoline points to the maximum velocity reference line to obtain the total difference degree, and calculate the average difference degree: Obtain the target reference isoline: Compare the average difference degrees of each reference isoline. The reference isoline with the minimum average difference degree is the target reference isoline; In step five, the velocity extreme value method is used again to correct the target reference isoline to obtain the Kuroshio main axis. The specific correction process is as follows: Data preparation: Identify and obtain the longitude and latitude positions, combined flow velocity, flow direction information, and sea surface altimetry data information of all points on the target reference isoline; Interpolation calculation: For each point on the target isoline, construct an auxiliary line vertically along the flow direction at this point, and interpolate and calculate the flow velocity magnitude at this position at intervals. The distance range is defined by the actual resolution of the data used; Find the maximum flow velocity point: For each auxiliary line, find the point with the maximum flow velocity on this line, which is defined as the point on the Kuroshio main axis; Correct the main axis: Gather all the maximum flow velocity points. These points represent the Kuroshio axis path under the maximum flow velocity condition. Connect them into a line and smooth it to complete the correction.

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