A method for calculating the depth and thickness of ocean isopycnal layers based on density interpolation

Abstract

The present invention discloses a method for calculating the depth and thickness of ocean isopycnals based on density interpolation, comprising: obtaining an oceanographic data file, including salinity, temperature, layer thickness, and topographic data, and filtering non-ocean area data using a land mask; calculating the seawater density distribution using the seawater equation of state based on the temperature and salinity data; calculating the salinity and temperature gradients, and dynamically adjusting the density threshold to calculate the density gradient and generate a dynamic density threshold; generating a target isopycnal value based on the dynamic density threshold, and calculating the depth distribution of the target isopycnal layer using an interpolation algorithm based on the relationship between density and depth; calculating the thickness of the isopycnal layer based on its depth; and performing boundary processing on the calculated isopycnal layer depth and thickness data. The present invention achieves efficient calculation of the depth and thickness of isopycnal layers, and the calculation results can be directly used to study ocean vertical structure, water mass analysis, potential vorticity calculation, and analysis of ocean circulation system dynamics.

Description

Technical Field

[0001] The present invention belongs to the interdisciplinary field of ocean science and computing technology, and specifically relates to a method for calculating the depth and thickness of ocean isopycnal layers based on density interpolation. Background Art

[0002] The ocean is a vital component of the Earth system, and its density distribution determines its layered structure and dynamic properties. Isopycnal layers are crucial reference surfaces for studying ocean physical processes. By tracking the changes in the depth and thickness of isopycnal layers, we can gain a clearer understanding of the ocean's internal motion patterns, thermohaline structure, and water mass properties. Therefore, accurately calculating the depth and thickness of isopycnal layers is a critical task in marine science research.

[0003] Currently, global ocean models (such as HYCOM) typically use a hybrid coordinate system, dividing the vertical direction into fixed depth or density layers. However, the layer data output by these models is often based on fixed depths and cannot directly reflect the distribution of isopycnic layers. To study ocean dynamics, researchers often need to convert these fixed-depth layer data into isopycnic layer data. However, existing methods have the following problems in the processing process:

[0004] Complex data calculations: Existing methods require density calculations for temperature and salinity at each vertical depth point, and then determine the depth of the isopycnal layer through interpolation. This computational process is cumbersome and makes it difficult to efficiently process large-scale data.

[0005] Insufficient accuracy: During the depth interpolation process of isodensity layers, traditional methods are prone to introducing calculation errors when dealing with density non-monotonicity or boundary problems, affecting the reliability of the final results.

[0006] Low degree of automation: Existing tools are inefficient in processing complex ocean data and cannot meet the needs of modern marine scientific research for efficient and automated data processing technologies.

[0007] To address these issues, the present invention proposes a method for calculating the depth and thickness of ocean isopycnals based on density interpolation. This method, through automated ocean data preprocessing, density calculation, and interpolation, efficiently and accurately determines the depth and thickness of isopycnals. Furthermore, addressing boundary conditions and outliers ensures the physical plausibility of the calculation results. This method can be widely applied to studies of ocean vertical structure, water mass analysis, potential vorticity calculation, and the dynamics of ocean circulation systems, providing important technical support and a data foundation for marine scientific research. Summary of the Invention

[0008] This paper aims to address the current challenges of low efficiency, insufficient accuracy, and imperfect boundary processing in calculating the depth and thickness of isopycnal layers in ocean data processing. It provides a method for calculating the depth and thickness of isopycnal layers in the ocean based on density interpolation. By improving the computational flow and logic design of existing algorithms, this method significantly improves computational efficiency and accuracy, while also enhancing the ability to handle boundary conditions and abnormal data.

[0009] The object of the present invention is achieved through the following technical solution: a method for calculating the depth and thickness of ocean isopycnal layers based on density interpolation, comprising:

[0010] Obtain oceanographic data files, including salinity, temperature, layer thickness, and topography data, and filter non-ocean area data using a land mask;

[0011] Based on temperature and salinity data, the seawater density distribution is calculated using the seawater state equation;

[0012] Calculate salinity and temperature gradients and dynamically adjust the density threshold to calculate the density gradient and generate a dynamic density threshold;

[0013] Generate target isodensity values based on dynamic density thresholds, and use the relationship between density and depth to calculate the depth distribution of target isodensity layers through interpolation algorithms;

[0014] Calculate the thickness of the isopycnal layer based on its depth;

[0015] Perform boundary processing on the calculated isopycnal depth and thickness data.

[0016] Furthermore, it also includes: performing outlier processing on the data in the oceanographic data file; the outlier processing includes: correcting the outliers and missing values using interpolation or filling methods.

[0017] Furthermore, based on the temperature and salinity data, the seawater density distribution is calculated using the seawater state equation, which also includes:

[0018] Improve computational efficiency through vectorized operations and achieve batch computation of density; and / or

[0019] The calculated density values were corrected for outliers.

[0020] Furthermore, the salinity and temperature gradients are calculated; the density threshold is dynamically adjusted to ensure the rationality and stability of density gradient changes, including:

[0021] Using salinity and temperature data, call the gradient calculation function to calculate the vertical gradient of temperature and salinity;

[0022] The density gradient was calculated by weighting the temperature and salinity gradients using a linear combination method;

[0023] The density gradient data is smoothed by sliding window smoothing technique;

[0024] For the thermocline area, the density threshold is dynamically adjusted to ensure that the threshold range is within the preset range.

[0025] Furthermore, the depth distribution of the target isodensity layer is calculated by an interpolation algorithm, including:

[0026] During the interpolation process, the range of the dynamic density threshold is combined to ensure that the interpolation point is within the valid density gradient range.

[0027] Furthermore, the depth distribution of the target isodensity layer is calculated by an interpolation algorithm, which also includes:

[0028] Design an automatic correction algorithm to address the depth non-monotonicity problem in the interpolation results;

[0029] The automatic correction algorithm is specifically as follows: by traversing the interpolation results point by point, checking whether each data point meets the monotonically increasing condition; if it is found that the value of the current point is less than the previous point, the value of the current point is corrected to be equal to the previous point, thereby forcing the monotonically increasing nature of the data distribution.

[0030] Furthermore, based on the depth of the isopycnal layer, the thickness of the isopycnal layer is calculated, including:

[0031] Based on the depth data of the isopycnal layers, the depth difference between adjacent isopycnal layers is calculated; the depth difference is defined as the thickness of the isopycnal layers, thereby obtaining the thickness of the isopycnal layers.

[0032] Furthermore, the calculated isopycnal depth and thickness data are subjected to boundary processing, including:

[0033] For shallow sea area treatment:

[0034] When the calculated depth exceeds the depth of the seabed topography, it is automatically truncated to the seabed topography range;

[0035] Set the thickness range and replace the abnormal values outside the thickness range with the mean of the adjacent values;

[0036] For land area processing:

[0037] For land areas, the calculated isopycnal depth and thickness data are marked as invalid values.

[0038] The present invention also provides a device for calculating the depth and thickness of an ocean isopycnal layer based on density interpolation, comprising:

[0039] Data processing module, used to obtain oceanographic data files, including salinity, temperature, layer thickness and topography data, and filter non-ocean area data using land masks;

[0040] A first calculation module is used to calculate the seawater density distribution using the seawater state equation based on temperature and salinity data;

[0041] The second calculation module is used to calculate the salinity and temperature gradients, and thus calculate the density gradient; dynamically adjust the density threshold to ensure the rationality and stability of the density gradient change;

[0042] The third calculation module is used to generate a target isodensity value based on a dynamic density threshold, and calculate the depth distribution of the isodensity layer through an interpolation algorithm using the relationship between density and depth;

[0043] A fourth calculation module is used to calculate the thickness of the isopycnal layer based on the depth of the isopycnal layer;

[0044] The boundary processing module is used to perform boundary processing on the calculated isopycnal depth and thickness data.

[0045] The present invention also provides an electronic device comprising a memory and a processor, wherein the memory is coupled to the processor; wherein the memory is used to store program data, and the processor is used to execute the program data to implement the above-mentioned method for calculating the depth and thickness of ocean isopycnal layers based on density interpolation.

[0046] The beneficial effects of the present invention are:

[0047] Accuracy: Dynamic density threshold adaptive algorithm, improved interpolation algorithm and outlier correction mechanism ensure high accuracy of isopycnic layer depth and thickness calculation results;

[0048] Stability: New boundary processing and dynamic adaptation features enhance the algorithm's applicability, making it adaptable to a variety of complex ocean terrains and pattern data.

[0049] Automation: The entire process is automated, from data reading to interpolation calculation and boundary correction, reducing manual intervention and improving the repeatability and reliability of data processing;

[0050] Compatibility: It supports multiple ocean model output data (such as HYCOM, etc.) and can be expanded to other ocean data types, with broad application prospects.

[0051] The present invention can be widely used in ocean vertical structure analysis, water mass characteristics research, potential vortex calculation and ocean circulation system dynamics analysis, providing important technical support and data basis for marine scientific research and climate change research. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0053] Figure 1 This is a schematic diagram of a process for converting layer depth information output by a hybrid coordinate ocean model into isopycnic layer depth and thickness data according to an embodiment of the present invention;

[0054] Figure 2 is a flow chart of the dynamic density threshold adaptive algorithm;

[0055] Figure 3 It is a schematic diagram of the depth and density difference of isopycnic layers;

[0056] Figure 4 A schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0057] The present invention will be described in detail below with reference to the accompanying drawings. Unless there is any conflict, the features of the following embodiments and implementations may be combined with each other.

[0058] This method, based on density interpolation, combines computer science and ocean science to calculate the depth and thickness of ocean isopycnals. It aims to address the problem that fixed-depth layer data output by traditional models cannot accurately reflect the internal density structure of the ocean. Targeting the characteristics of the HYCOM (Hybrid Coordinate Ocean Model), this method designs an efficient interpolation algorithm to convert model layer depth information into isopycnal depth and thickness data, providing precise calculation tools and comprehensive data technology support for oceanographic research. The present invention innovatively combines the hybrid coordinate characteristics of the HYCOM model and designs a density-based interpolation calculation method, which is implemented through the following steps: ① Data preprocessing: reading salinity, temperature, layer thickness and topography data in NetCDF format, and filtering non-ocean area data using a land mask; ② Density calculation: calculating the seawater density distribution through the state equation based on temperature and salinity data; ③ Dynamic density threshold adaptation: calculating the salinity and temperature gradients, and dynamically adjusting the density threshold to ensure the rationality and stability of the density gradient change; ④ Iso-dense layer interpolation: combining the dynamic density threshold adjustment results, using the relationship between density and depth to construct a density-depth relationship curve; within the target isopycnic value range, using the interpolation algorithm to accurately calculate the corresponding isopycnic layer depth; ⑤ Layer thickness calculation: further calculating the thickness of each isopycnic layer to obtain complete stratification information; ⑥ Boundary processing: special processing is performed on the seabed topography and land area boundaries to ensure the physical rationality of the interpolation results.

[0059] Figure 1 A schematic flow chart of a method for calculating the depth and thickness of ocean isopycnal layers based on density interpolation provided in an embodiment of the present invention, the method specifically includes the following steps:

[0060] Process 1: Data Preprocessing

[0061] First, load basic physical quantity data such as salinity, temperature, and layer thickness from the numerical model output, and obtain seabed topography depth data and land mask data, including:

[0062] Data loading: supports multiple data formats (such as NetCDF format) and batch loading.

[0063] Outlier processing: Use interpolation or filling methods to correct outliers and missing values to ensure data quality.

[0064] Land mask filtering: Eliminate non-ocean area data based on the land mask to ensure the validity of the input data.

[0065] Through this step, a complete and reliable input data set can be constructed to support subsequent calculations.

[0066] Process 2: Density calculation

[0067] Based on temperature and salinity data, the internationally accepted seawater state equation is used to calculate the density distribution of each depth layer, including:

[0068] Density calculation formula: Improve computing efficiency through vectorized operations and achieve batch calculation of full-layer density.

[0069] Outlier correction: Detect and correct non-physical density values that appear during the calculation process.

[0070] Process 3: Dynamic Density Threshold Adaptation

[0071] Figure 2 The flow chart of the dynamic density threshold adaptive algorithm is shown, which includes:

[0072] Load basic physical quantity data such as salinity, temperature, and layer thickness from the numerical model output, and calculate or load auxiliary data required for density gradient, including:

[0073] Gradient calculation preparation: Using temperature and salinity data, calculate their vertical gradients to provide a basis for density gradient estimation.

[0074] Density gradient calculation: Combine the temperature gradient and salinity gradient and calculate the density gradient based on empirical weights (e.g., the temperature gradient weight is 0.8 and the salinity gradient weight is 0.2).

[0075] Gradient extreme value extraction: The density gradient extreme value of each grid point is extracted along the vertical depth direction to reflect the strength of local density changes.

[0076] Smoothing and correction: Sliding window smoothing is performed on extreme density gradient values, while limiting the density threshold to a reasonable range (e.g., 0.1 to 1) to eliminate the impact of local outliers and noise on subsequent calculations and ensure the rationality and stability of density gradient changes. The density threshold obtained after the above smoothing and range limiting is the dynamic density threshold.

[0077] Through this step, a dynamic density threshold dataset can be generated to support the dynamic adjustment of the subsequent isodensity layer depth interpolation.

[0078] Process 4: Depth interpolation of isopycnal layers

[0079] Based on density data, depth data and dynamic density threshold, the depth distribution of the target isodensity layer is calculated. The details are as follows:

[0080] 1. Dynamic density value generation

[0081] Based on dynamic density threshold , generate a set of target isodensity values :

[0082]

[0083] Among them, N is the number of target equal density layers, which is determined according to specific research needs to ensure that the density layers cover the density characteristics of the study area.

[0084] 2. Target depth difference calculation

[0085] For target isopycnic values , the corresponding depth It can be calculated by the following formula:

[0086]

[0087] in:

[0088] and : Density value of the adjacent known density layer;

[0089] and : corresponding depth value;

[0090] : Target density value, i.e. , 1≤n≤N;

[0091] : The interpolated depth of the target isodensity layer.

[0092] 3. Interpolation process diagram

[0093] Figure 3 The density-depth relationship curve and interpolation calculation process are shown:

[0094] and are known density values respectively, and the red curve represents the change pattern of density;

[0095] and are the corresponding depth values respectively;

[0096] is the target density value, that is, the isodensity value generated according to the dynamic density threshold Its corresponding depth Calculated by linear interpolation.

[0097] Process 5: Layer Thickness Calculation

[0098] Based on the isopycnal depth data, the thickness between adjacent isopycnal layers is calculated, including:

[0099] Calculate the thickness of isopycnal layers based on the depth difference between adjacent isopycnal layers , the formula is:

[0100] (i=1…N)

[0101] in:

[0102] is the thickness of the first isopycnal layer, which is equal to the depth of the first isopycnal layer ;

[0103] is the thickness of the last isopycnic layer, which is equal to the depth of the seabed minus the depth of the last isopycnic layer. .

[0104] Process 6: Boundary processing of data after difference

[0105] After completing the calculation of the depth and thickness of the isopycnal layer, the difference results need to be processed by boundary processing, including:

[0106] 1. Shallow sea area treatment

[0107] When the calculation depth exceeds the depth of the seabed topography, it is automatically truncated to the seabed topography range to avoid unphysical results.

[0108] In shallow sea areas, the layer thickness calculation range is dynamically adjusted to set the layer thickness within a reasonable layer thickness range in the study area, and outliers outside the range are replaced with the mean of adjacent values to ensure that the results conform to the physical characteristics of the shallow sea.

[0109] 2. Land area processing

[0110] For land areas, all calculated results (including depth and thickness) are marked as invalid values (NaN).

[0111] Ensure that the difference calculation is only performed on the valid ocean area to avoid interference from land areas on the results.

[0112] In summary, this application provides a dynamic density threshold adaptive algorithm, an improved isopycnal depth interpolation algorithm, an efficient density calculation method, an accurate layer thickness calculation method, and a boundary processing and shallow water adaptation mechanism, enabling efficient calculation of isopycnal depth and thickness. The results of this invention can be directly used to study ocean vertical structure, water mass analysis, potential vorticity calculation, and ocean circulation system dynamics, providing important data support for oceanographers to explore the formation mechanism and evolution process of ocean circulation and its impact on the global climate system.

[0113] Dynamic Density Threshold Adaptive Algorithm: Dynamically adjusts the density threshold based on the vertical gradients of temperature and salinity, ensuring the rationality and stability of density gradient changes. This algorithm addresses the irrational density gradient changes found in traditional methods and is particularly suitable for density stratification analysis in areas with complex density distributions or sudden gradient changes.

[0114] Improved isopycnal depth interpolation algorithm: Based on the relationship between density and depth, this algorithm uses linear or spline interpolation to accurately calculate the depth of isopycnal layers and improves the interpolation process. This significantly improves the accuracy and physical rationality of isopycnal depth interpolation, making it suitable for isopycnal calculations in complex ocean environments.

[0115] Efficient density calculation method: Vectorized operations replace point-by-point calculations to achieve batch calculations for the entire depth layer. Automatic detection and linear interpolation correction of abnormal density values ensure the physical rationality of the calculation results. This significantly reduces calculation time while improving the accuracy and reliability of density calculation results.

[0116] Accurate layer thickness calculation method: Based on the depth of the isopycnal layers, the thickness between adjacent isopycnal layers is calculated and corrected for outliers. This provides a precise description of the ocean's stratified structure, and the results can be directly used for water mass analysis, potential vorticity calculations, and dynamics studies.

[0117] Boundary Processing and Shallow Water Adaptation: A dynamic boundary processing mechanism is designed to address the special circumstances of submarine topography and land areas. This effectively avoids the generation of unphysical results and enhances the applicability of the method, especially in shallow waters and complex terrain areas.

[0118] The present invention also provides a device for calculating the depth and thickness of an ocean isopycnal layer based on density interpolation, comprising:

[0119] Data processing module, used to obtain oceanographic data files, including salinity, temperature, layer thickness and topography data, and filter non-ocean area data using land masks;

[0120] A first calculation module is used to calculate the seawater density distribution using the seawater state equation based on temperature and salinity data;

[0121] The second calculation module is used to calculate the salinity and temperature gradients, and thus calculate the density gradient; dynamically adjust the density threshold to ensure the rationality and stability of the density gradient change;

[0122] The third calculation module is used to generate a target isodensity value based on a dynamic density threshold, and calculate the depth distribution of the isodensity layer through an interpolation algorithm using the relationship between density and depth;

[0123] A fourth calculation module is used to calculate the thickness of the isopycnal layer based on the depth of the isopycnal layer;

[0124] The boundary processing module is used to perform boundary processing on the calculated isopycnal depth and thickness data.

[0125] It should be noted that the device embodiment shown in this embodiment matches the content of the above method embodiment. You can refer to the content of the above method embodiment and will not repeat it here.

[0126] Figure 4 This is a schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. Figure 4 The electronic device provided in this embodiment includes: a memory and a processor, wherein the memory is used to store information including program instructions, and the processor is used to control the execution of the program instructions. When the program instructions are loaded and executed by the processor, a method for calculating the depth and thickness of ocean isopycnal layers based on density interpolation of the present invention is implemented.

[0127] It should be noted that, in addition to Figure 4 In addition to the memory and processor shown, the electronic device may also include other hardware according to its actual functions, which will not be described in detail.

[0128] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0129] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0130] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0131] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0132] The above describes in detail the specific embodiments of the present invention with reference to the accompanying drawings. By improving the density interpolation algorithm and boundary processing method, the present invention not only achieves efficient and accurate calculation of the depth and thickness of isopycnal layers, but also ensures the physical rationality of the results under complex boundary conditions. This provides technical support and a data foundation for ocean dynamics research and climate model assessment.

[0133] The above embodiments are intended only to illustrate the design concepts and features of the present invention. Their purpose is to enable those skilled in the art to understand the contents of the present invention and implement them accordingly. The scope of protection of the present invention is not limited to the above embodiments. Therefore, any equivalent changes or modifications made based on the principles and design concepts disclosed in the present invention are within the scope of protection of the present invention.

Claims

1. A method for calculating the depth and thickness of ocean isopycnal layers based on density interpolation, characterized in that: include: Obtain oceanographic data files, including salinity, temperature, layer thickness, and topography data, and filter non-ocean area data using a land mask; Based on temperature and salinity data, the seawater density distribution is calculated using the seawater state equation; Calculate salinity and temperature gradients and dynamically adjust the density threshold to calculate the density gradient and generate a dynamic density threshold; Based on dynamic density threshold Generate target isodensity values , and using the relationship between density and depth, the depth distribution of the target isodensity layer is calculated through interpolation algorithm; include: ； ； in, N is the number of target isopycnal layers; and is the density value of the adjacent known density layer, and is the corresponding depth value; is the target density value, that is , 1≤n≤N, is the interpolated target density layer depth; Calculate the thickness of the isopycnal layer based on its depth; Perform boundary processing on the calculated isopycnal depth and thickness data.

2. The method according to claim 1, characterized in that Also includes: Perform outlier processing on data in oceanographic data files; The outlier processing includes: correcting outliers and missing values using interpolation or filling methods.

3. The method according to claim 1, characterized in that Based on temperature and salinity data, the seawater density distribution is calculated using the seawater equation of state, including: Improve computational efficiency through vectorized operations and achieve batch computation of density; and / or The calculated density values were corrected for outliers.

4. The method according to claim 1, wherein Calculate salinity and temperature gradients, dynamically adjust density thresholds, and ensure the rationality and stability of density gradient changes, including: Using salinity and temperature data, call the gradient calculation function to calculate the vertical gradient of temperature and salinity; The density gradient was calculated by weighting the temperature and salinity gradients using a linear combination method; The density gradient data is smoothed by sliding window smoothing technique; For the thermocline area, the density threshold is dynamically adjusted to ensure that the threshold range is within the preset range.

5. The method according to claim 1, wherein The depth distribution of the target isodensity layer is calculated by interpolation algorithm, including: During the interpolation process, the range of the dynamic density threshold is combined to ensure that the interpolation point is within the valid density gradient range.

6. The method according to claim 1, characterized in that The depth distribution of the target isodensity layer is calculated by interpolation algorithm, which also includes: Design an automatic correction algorithm to address the depth non-monotonicity problem in the interpolation results; The automatic correction algorithm is specifically as follows: by traversing the interpolation results point by point, checking whether each data point meets the monotonically increasing condition; if it is found that the value of the current point is less than the previous point, the value of the current point is corrected to be equal to the previous point, thereby forcing the monotonically increasing nature of the data distribution.

7. The method according to claim 1, characterized in that Calculate the thickness of the isopycnal layer based on its depth, including: Based on the depth data of the isopycnal layers, the depth difference between adjacent isopycnal layers is calculated; the depth difference is defined as the thickness of the isopycnal layers, thereby obtaining the thickness of the isopycnal layers.

8. The method according to claim 1, characterized in that Perform boundary processing on the calculated isopycnal depth and thickness data, including: For shallow sea area treatment: When the calculated depth exceeds the depth of the seabed topography, it is automatically truncated to the seabed topography range; Set the thickness range and replace the abnormal values outside the thickness range with the mean of the adjacent values; For land area processing: For land areas, the calculated isopycnal depth and thickness data are marked as invalid values.

9. A device for calculating the depth and thickness of ocean isopycnal layers based on density interpolation, characterized in that: include: Data processing module, used to obtain oceanographic data files, including salinity, temperature, layer thickness and topography data, and filter non-ocean area data using land masks; A first calculation module is used to calculate the seawater density distribution using the seawater state equation based on temperature and salinity data; The second calculation module is used to calculate the salinity and temperature gradients, and thus calculate the density gradient; dynamically adjust the density threshold to ensure the rationality and stability of the density gradient change; The third calculation module is used to calculate the density of the Generate target isodensity values , and using the relationship between density and depth, the depth distribution of isodensity layers is calculated through interpolation algorithm; include: ； ； in, N is the number of target isopycnal layers; and is the density value of the adjacent known density layer, and is the corresponding depth value; is the target density value, that is , 1≤n≤N, is the interpolated target density layer depth; A fourth calculation module is used to calculate the thickness of the isopycnal layer based on the depth of the isopycnal layer; The boundary processing module is used to perform boundary processing on the calculated isopycnal depth and thickness data.

10. An electronic device comprising a memory and a processor, characterized in that: The memory is coupled to the processor; wherein the memory is used to store program data, and the processor is used to execute the program data to implement the method for calculating the depth and thickness of ocean isopycnal layers based on density interpolation as described in any one of claims 1 to 8.

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