Ocean equidensity layer depth and thickness calculation method based on density interpolation

Abstract

The invention discloses a density interpolation-based ocean equidensity layer depth and thickness calculation method, which comprises the following steps of: acquiring an oceanographic data file which comprises salinity, temperature, layer thickness and topographic data, and filtering non-ocean region data by utilizing a land mask; based on the temperature and salinity data, calculating seawater density distribution by adopting a seawater state equation; calculating salinity and temperature gradient, and dynamically adjusting a density threshold value, so as to calculate a density gradient and generate a dynamic density threshold value; generating a target equidensity value based on the dynamic density threshold, and calculating depth distribution of a target equidensity layer through an interpolation algorithm by using a relationship between density and depth; calculating the thickness of the equal-density layer based on the depth of the equal-density layer; and performing boundary processing on the depth and thickness data of the equal-density layer obtained by calculation. According to the method, the depth and the thickness of the equal-density layer are efficiently calculated, and the calculation result can be directly used for research of a marine vertical structure, water mass analysis, position vortex calculation and marine circulation system dynamics analysis.

Description

Technical Field

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

[0002] The ocean is an important part of the Earth system, and its density distribution determines the stratification structure and dynamic characteristics of the ocean. Isopycnic layers are important reference surfaces for studying ocean physical processes. By tracking the changes in the depth and thickness of isopycnic layers, the internal movement laws, thermohaline structures, and water mass characteristics of the ocean can be understood more clearly. Therefore, accurately calculating the depth and thickness of isopycnic layers is a key task in marine scientific research.

[0003] Currently, global ocean models (such as HYCOM) usually adopt a hybrid coordinate system, dividing the vertical direction into fixed depth layers 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 dynamic phenomena, researchers usually need to convert this fixed - depth layer data into isopycnic layer data. However, the existing methods have the following problems in the processing process:

[0004] Complex data calculation: Existing methods need to calculate the density for the temperature and salinity at each vertical depth point, and then determine the isopycnic layer depth through interpolation methods. The calculation process is cumbersome and it is difficult to efficiently process large - scale data;

[0005] Insufficient accuracy: In the depth interpolation process of isopycnic 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 have low processing efficiency for complex ocean data and cannot meet the requirements of modern marine scientific research for high - efficiency and automated data - processing technologies.

[0007] To solve the above problems, the present invention proposes a method for calculating the depth and thickness of ocean isopycnic layers based on density interpolation. Through the automated pre - processing, density calculation, and interpolation calculation of ocean data, this method can efficiently and accurately determine the depth and thickness of isopycnic layers. At the same time, the processing of boundary conditions and outliers ensures the physical rationality of the calculation results. The present invention can be widely applied to the dynamic research of ocean vertical structures, water mass analysis, potential vorticity calculation, and ocean circulation systems, providing important technical support and data basis for marine scientific research. Summary of the Invention

[0008] The object of the present invention is to solve the problems of low calculation efficiency, insufficient accuracy and imperfect boundary processing in the calculation of the depth and thickness of the isopycnal layer in current ocean data processing, and to provide a method for calculating the depth and thickness of the ocean isopycnal layer based on density interpolation. By improving the calculation process and logic design of the existing algorithm, the calculation efficiency and result accuracy are significantly improved, and at the same time, the processing ability for boundary conditions and abnormal data is enhanced.

[0009] The object of the present invention is achieved by the following technical solutions: A method for calculating the depth and thickness of the ocean isopycnal layer based on density interpolation, including:

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

[0011] Based on the temperature and salinity data, use the seawater equation of state to calculate the seawater density distribution;

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

[0013] Generate the target isopycnal value based on the dynamic density threshold, and use the relationship between density and depth to calculate the depth distribution of the target isopycnal layer through an interpolation algorithm;

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

[0015] Perform boundary processing on the calculated isopycnal layer 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 outliers and missing values using interpolation or filling methods.

[0017] Furthermore, based on the temperature and salinity data, using the seawater equation of state to calculate the seawater density distribution, it also includes:

[0018] Improve the calculation efficiency through vectorized operations to achieve batch calculation of density; and / or

[0019] Perform outlier correction on the calculated density values.

[0020] Furthermore, calculate the salinity and temperature gradients; dynamically adjust the density threshold to ensure the rationality and stability of the density gradient change, including:

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

[0022] Adopt the linear combination method to calculate the density gradient by weighting the temperature and salinity gradients;

[0023] Smoothing processing is performed on the density gradient data through a sliding window smoothing technique;

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

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

[0026] During the interpolation process, in combination with the range of the dynamic density threshold, it is ensured that the interpolation points are located within the effective density gradient interval.

[0027] Furthermore, calculating the depth distribution of the target isopycnal layer through an interpolation algorithm also includes:

[0028] For the problem of non-monotonicity of depth in the interpolation results, an automatic correction algorithm is designed;

[0029] The specific automatic correction algorithm is: by traversing the interpolation results point by point, checking whether each data point satisfies 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, so as to forcibly ensure the monotonically increasing property 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 layer, the depth difference between adjacent isopycnal layers is calculated; this depth difference is defined as the thickness of the isopycnal layer, thereby obtaining the thickness of the isopycnal layer.

[0032] Furthermore, boundary processing is performed on the calculated isopycnal layer depth and thickness data, including:

[0033] Processing for the shallow sea area:

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

[0035] A thickness range is set, and the outliers exceeding the thickness range are replaced with the mean value of adjacent values;

[0036] Processing for the land area:

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

[0038] The present invention also provides an apparatus for calculating the depth and thickness of ocean isopycnal layers based on density interpolation, including:

[0039] A data processing module for obtaining oceanographic data files, including salinity, temperature, layer thickness, and terrain data, and filtering non-ocean area data using a land mask;

[0040] A first calculation module for calculating the seawater density distribution using the seawater equation of state based on temperature and salinity data;

[0041] A second calculation module for calculating the salinity and temperature gradients, thereby calculating the density gradient; dynamically adjusting the density threshold to ensure the rationality and stability of the density gradient change;

[0042] A third calculation module for generating target isopycnic values based on the dynamic density threshold and calculating the depth distribution of isopycnic layers using an interpolation algorithm based on the relationship between density and depth;

[0043] A fourth calculation module for calculating the thickness of isopycnic layers based on the depth of isopycnic layers;

[0044] A boundary processing module for performing boundary processing on the calculated isopycnic layer depth and thickness data.

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

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

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

[0048] Stability: The newly added boundary processing and dynamic adaptation functions enhance the applicable range of the algorithm and can adapt to various complex ocean terrains and model data;

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

[0050] Compatibility: Supports output data of multiple ocean models (such as HYCOM, etc.) and can be extended to other ocean data types, having broad application prospects.

[0051] The present invention can be widely applied to ocean vertical structure analysis, water mass property research, potential vorticity calculation, and ocean circulation system dynamics analysis, providing important technical support and data basis for ocean science research and climate change research. Description of the Drawings

[0052] To more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the accompanying drawings required for the description of the embodiments. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0053] Figure 1 It is a schematic flow chart of converting the layer depth information output by the hybrid coordinate ocean model into the depth and thickness data of isopycnal layers in the 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 of isopycnal layers and density differences;

[0056] Figure 4 It is a schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. Specific embodiments

[0057] The following will describe the present invention in detail with reference to the accompanying drawings. Without conflict, the features in the following embodiments and implementation manners can be combined with each other.

[0058] A method for calculating the depth and thickness of ocean isopycnal layers based on density interpolation according to the present invention combines the fields of computer science and ocean science, aiming to solve the problem that the fixed-depth layer data output by traditional models is difficult to accurately reflect the internal density structure of the ocean. In view of the characteristics of HYCOM (Hybrid Coordinate Ocean Model), the present invention designs an efficient interpolation algorithm to convert the model layer depth information into the depth and thickness data of isopycnal layers, providing an accurate calculation tool and comprehensive data technical support for oceanographic research. The present invention innovatively combines the hybrid coordinate characteristics of the HYCOM model and designs an interpolation calculation method based on density, which is realized through the following steps: ① Data preprocessing: Read the salinity, temperature, layer thickness, and terrain data in NetCDF format, and filter the non-ocean area data using the land mask; ② Density calculation: Based on the temperature and salinity data, calculate the seawater density distribution through the state equation; ③ Dynamic density threshold adaptation: Calculate the salinity and temperature gradients, and dynamically adjust the density threshold to ensure the rationality and stability of the density gradient change; ④ Isopycnal layer interpolation: Combine the results of the dynamic density threshold adjustment, use the relationship between density and depth to construct a density-depth relationship curve; within the target isopycnal density value range, use the interpolation algorithm to accurately calculate the corresponding isopycnal layer depth; ⑤ Layer thickness calculation: Further calculate the thickness of each isopycnal layer to obtain complete stratification information; ⑥ Boundary processing: Perform special processing on the seabed terrain and land area boundaries to ensure the physical rationality of the interpolation results.

[0059] Figure 1 The flowchart of a method for calculating the depth and thickness of ocean isopycnic layers based on density interpolation provided by an embodiment of the present invention. The method specifically includes the following processes:

[0060] Process 1: Data preprocessing

[0061] First, load basic physical quantity data such as salinity, temperature, and layer thickness from the numerical model output. At the same time, obtain bathymetric depth data and land mask data, specifically including:

[0062] Data loading: Support 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: Based on the land mask, filter out non-ocean area data 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 the temperature and salinity data, call the internationally common seawater equation of state to calculate the density distribution of each depth layer, specifically including:

[0068] Density calculation formula: Improve the calculation efficiency through vectorized operations to achieve batch calculation of the density of the entire layer.

[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 flowchart of the dynamic density threshold adaptation algorithm is shown, specifically including:

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

[0073] Gradient calculation preparation: Use temperature and salinity data to calculate their gradients in the vertical direction to provide a basis for estimating the density gradient.

[0074] Density gradient calculation: Combine the temperature gradient and salinity gradient, and calculate the density gradient according to the empirical weights (such as the temperature gradient weight is 0.8 and the salinity gradient weight is 0.2).

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

[0076] Smoothing and correction: Smooth the density gradient extreme values using a sliding window, and at the same time limit the density threshold within a reasonable range (such as 0.1 to 1) to eliminate the influence 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 process and range limitation is the dynamic density threshold.

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

[0078] Process 4: Depth interpolation of isodensity layers

[0079] Based on the density data, depth data, and dynamic density threshold, calculate the depth distribution of the target isodensity layer. Specifically as follows:

[0080] 1. Generation of dynamic density values

[0081] According to the dynamic density threshold , generate a set of target isodensity values :

[0082]

[0083] where N is the number of target isodensity layers, which is determined according to specific research requirements to ensure that the density layers cover the density characteristics of the research area.

[0084] 2. Calculation of target depth differences

[0085] For the target isodensity value , its corresponding depth can be calculated by the following formula:

[0086]

[0087] where:

[0088] and : The density values of adjacent known density layers;

[0089] and : The corresponding depth values;

[0090] : The target isodensity value, that is , 1 ≤ n ≤ N;

[0091] : The depth of the target isodensity layer obtained by interpolation.

[0092] 3. Schematic of the interpolation process

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

[0094] and are the known density values respectively, and the red curve represents the variation law 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 is obtained by linear interpolation calculation.

[0097] Process 5: Layer thickness calculation

[0098] Based on the depth data of the isodensity layers, calculate the thickness between adjacent isodensity layers, specifically including:

[0099] Calculate the isodensity layer thickness based on the depth difference between adjacent isodensity layers , and its formula is:

[0100] (i = 1…N)

[0101] Where:

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

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

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

[0105] After calculating the depth and thickness of the isodensity layers, it is necessary to perform boundary processing on the difference results, specifically including:

[0106] 1. Shallow sea area processing

[0107] When the calculated depth exceeds the seabed topography depth, it is automatically truncated to the seabed topography range to avoid non-physical results.

[0108] Dynamically adjust the calculation range of layer thickness in the shallow sea area, set the layer thickness within the reasonable range of the research area, and replace the out-of-range outliers with the average value of adjacent values to ensure that the results conform to the physical characteristics of the shallow sea.

[0109] 2. Land area processing

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

[0111] Ensure that the difference calculation is only carried out for the valid ocean area to avoid the interference of the land area on the results.

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

[0113] Dynamic density threshold adaptive algorithm: Combine the vertical gradients of temperature and salinity to dynamically adjust the density threshold to ensure the rationality and stability of the density gradient change. Solve the problem of unreasonable density gradient change in traditional methods, and is particularly suitable for density stratification analysis in areas with complex density distribution or sudden gradient changes.

[0114] Improved isopycnal layer depth interpolation algorithm: Based on the relationship between density and depth, use linear interpolation or spline interpolation methods to accurately calculate the depth of the isopycnal layer and improve the interpolation process. Greatly improve the accuracy and physical rationality of isopycnal layer depth interpolation, and are applicable to isopycnal layer calculations in complex ocean environments.

[0115] Efficient density calculation method: Replace point-by-point calculation with vectorized operations to achieve batch calculation of the full-depth layer; automatically detect and linearly interpolate and correct abnormal density values to ensure the physical rationality of the calculation results. Significantly reduce the calculation time, and at the same time improve the accuracy and reliability of the density calculation results.

[0116] Accurate layer thickness calculation method: Based on the isopycnal layer depth, calculate the thickness between adjacent isopycnal layers and correct the outliers. Provide an accurate description of the ocean stratification structure, and the results can be directly used for water mass analysis, potential vorticity calculation, and dynamics research.

[0117] Boundary Processing and Shallow Sea Adaptation Mechanism: A dynamic boundary processing mechanism is designed for the special conditions of the seabed topography and land areas. It effectively avoids the generation of non-physical results and enhances the applicability of the method, especially in shallow seas and areas with complex topography.

[0118] The present invention also provides an apparatus for calculating the depth and thickness of ocean isopycnic layers based on density interpolation, including:

[0119] A data processing module, configured to obtain oceanographic data files, including salinity, temperature, layer thickness, and topography data, and filter out non-ocean area data using a land mask;

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

[0121] A second calculation module, configured 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] A third calculation module, configured to generate target isopycnic values based on the dynamic density threshold, and use the relationship between density and depth to calculate the depth distribution of isopycnic layers through an interpolation algorithm;

[0123] A fourth calculation module, configured to calculate the thickness of isopycnic layers based on the depth of isopycnic layers;

[0124] A boundary processing module, configured to perform boundary processing on the calculated depth and thickness data of isopycnic layers.

[0125] It should be noted that the apparatus embodiment shown in this embodiment matches the content of the above method embodiment. The content of the above method embodiment can be referred to and will not be elaborated here.

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

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

[0128] Those skilled in the art should understand that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to 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 methods, apparatuses (systems), and computer program products according to the embodiments of the present application. It should be understood that each flow and / or block in the flowchart and / or block diagram, as well as the combination of flows 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 the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate means for implementing the functions specified in Figure 1 one or more of the processes and / or blocks Figure 1 or multiple blocks.

[0130] These computer program instructions can 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 generate a manufactured article including instruction means, and the instruction means implements the functions specified in Figure 1 one or more of the processes and / or blocks Figure 1 or multiple blocks.

[0131] These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process, and thus the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in Figure 1 one or more of the processes and / or blocks Figure 1 or multiple blocks.

[0132] The specific embodiments of the present invention have been described in detail above in conjunction with the accompanying drawings. By improving the density interpolation algorithm and boundary processing method, the present invention not only realizes the efficient and accurate calculation of the depth and thickness of isopycnic layers, but also ensures the physical rationality of the results under complex boundary conditions, providing technical support and data basis for ocean dynamics research and climate model evaluation.

[0133] The above embodiments are only used to illustrate the design concept and features of the present invention, and the purpose is to enable those skilled in the art to understand the content of the present invention and implement it accordingly. The protection scope of the present invention is not limited to the above embodiments. Therefore, all equivalent changes or modifications made based on the principles and design concepts disclosed by the present invention are within the protection scope 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 land masks; 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 density thresholds to calculate density gradients and generate dynamic density thresholds; 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; Based on the depth of the isopycnal layer, the thickness of the isopycnal layer is calculated; Perform boundary processing on the calculated isopycnic layer 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 state equation, including: Improve computational efficiency through vectorized operations to achieve batch calculation of density; and / or The calculated density values ​​were corrected for outliers.

4. The method according to claim 1, characterized in that: 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 gradients 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, characterized in that 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 solve the problem of depth non-monotonicity in 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 smaller than the previous point, the value of the current point is corrected to be equal to the previous point, thereby forcing the monotonically increasing property of the data distribution to be guaranteed.

7. The method according to claim 1, characterized in that Based on the depth of the isopycnal layer, the thickness of the isopycnal layer is calculated, 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 Boundary processing is performed on the calculated isopycnal depth and thickness data, including: For shallow sea areas: When the calculated depth exceeds the depth of the seabed terrain, it is automatically truncated to the seabed terrain range; Set the thickness range and replace the abnormal values ​​beyond 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 the 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; A 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; A fourth calculation module, used for calculating the thickness of the isopycnic layer based on the depth of the isopycnic layer; The boundary processing module is used to perform boundary processing on the calculated isodensity layer 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 a method for calculating the depth and thickness of ocean isopycnic layers based on density interpolation as described in any one of claims 1 to 8.

Images