A method for extracting sea surface temperature and salinity anomalies of ocean vortices

Abstract

The present invention provides a method for extracting ocean vortex sea surface temperature and salinity anomalies, comprising the following steps: Step 1, data collection and preprocessing; Step 2, identifying vortex features; Step 3, constructing the background fields of vortex sea surface temperature and salinity; Step 4, extracting the anomaly fields of vortex sea surface temperature and salinity. The present invention extracts the observed sea surface temperature and salinity data within the vortex environment area, and conducts regression analysis in combination with the climatological sea surface temperature and salinity data to construct a more reasonable background temperature and salinity field. This method can adapt to the temperature and salinity changes in different seasons and different regions, improve the self-adaptability of the background temperature and salinity field, and avoid the errors caused by simply using the multi-year average climatological data.

Description

Technical Field

[0001] The present invention relates to the technical fields of physical oceanography and data analysis, and particularly relates to a method for extracting sea surface temperature and salinity anomalies of ocean eddies. Background Art

[0002] Ocean eddies are an important part of ocean circulation and have important impacts on material transport, energy exchange, and the ocean ecosystem. Sea surface temperature and salinity anomalies are important indicators reflecting the dynamic characteristics of mesoscale eddies and can characterize the dynamic thermodynamic structure of eddies. However, traditional calculations of sea surface temperature and salinity anomalies of eddies often simply subtract climatological data from observational data or perform spatio-temporal filtering on observational data. These methods often struggle to completely eliminate large-scale signals such as seasonal variations and ENSO, or are subject to human subjectivity and difficult to accurately capture the detailed characteristics of sea surface temperature and salinity anomalies of eddies. There are still huge challenges in accurately extracting sea surface temperature and salinity anomalies of eddies.

[0003] The existing methods for extracting sea surface temperature and salinity anomalies of ocean eddies have the following main problems:

[0004] (1) Inaccurate estimation of the background temperature and salinity fields;

[0005] Traditional methods usually use large-scale climatological sea surface temperature and salinity as the background temperature and salinity fields, without fully considering local temperature and salinity variations, resulting in relatively large errors in the calculated sea surface temperature anomalies and sea surface salinity anomalies. Directly using long-term average temperature and salinity fields (such as multi-year climatological means) as the background temperature and salinity fields may ignore the impacts of seasonal variations and local temperature and salinity gradients, affecting the physical accuracy of anomaly values.

[0006] (2) Unable to effectively distinguish temperature and salinity anomalies caused by eddies from large-scale background variations;

[0007] The observed sea surface temperature and sea surface salinity include not only signals generated by eddy dynamic processes but may also be affected by other large-scale signals (such as El Niño events, seasonal warming, etc.). Existing methods are relatively rough in separating eddies from the background field and are difficult to eliminate sea surface temperature and sea surface salinity changes caused by non-eddy factors. Summary of the Invention

[0008] Object of the Invention: The technical problem to be solved by the present invention is to provide a method for extracting sea surface temperature and salinity anomalies of ocean eddies in view of the deficiencies of the prior art, including the following steps:

[0009] Step 1, data collection and preprocessing;

[0010] Step 2, identifying eddy characteristics;

[0011] Step 3, construct the background fields of the sea surface temperature and salinity of the vortex;

[0012] Step 4, extract the anomaly fields of the sea surface temperature and salinity of the vortex.

[0013] Step 1 includes:

[0014] Step 1.1, collect the climatological data, including the sea surface temperature, salinity, and sea surface height;

[0015] Step 1.2, collect the sea surface observation data, including the sea surface temperature, salinity, and sea surface height data;

[0016] Step 1.3, standardize the climatological data and the sea surface observation data, and interpolate them onto the grid points with a unified spatial resolution.

[0017] Step 2 includes:

[0018] Step 2.1, identify the vortex center:

[0019] For the sea surface height data Y1 with the AVISO spatial resolution of subtract the climatological sea surface height data Y2 from it to obtain the sea surface height anomaly data Y3 = Y1 - Y2, and scan the sea surface height anomaly data with a 5×5 grid point window to find the extreme points. The maximum point is the center of the anticyclonic vortex, and the minimum point is the center of the cyclonic vortex;

[0020] Step 2.2, identify the vortex boundary: Starting from the sea surface height anomaly of the vortex center, gradually increase or decrease the value of the sea surface height anomaly outward until the outermost contour line only contains the unique vortex center. At this time, the contour line is the vortex boundary;

[0021] Step 2.3, define the radius corresponding to the circle with the same area as the area enclosed by the vortex boundary as the vortex radius;

[0022] Step 2.4, select the annular region between 1 times and 1.5 times the vortex radius as the environmental region of the vortex.

[0023] Step 3 includes:

[0024] Step 3.1, construct the background field of the sea surface temperature of the vortex, which specifically includes the following steps:

[0025] Step 3.1.1, for the observed sea surface temperature data, extract the sea surface temperature data of the environmental region of the vortex .

[0026] Step 3.1.2, establish the climatological temperature field of the vortex sea surface environmental region:

[0027] Read the month in which the vortex is located , respectively extract the climatological monthly average month, month, monthly sea surface environmental regional temperature data of the vortex , , , where month is the month before the month in which the vortex is located, is the month after the month in which the vortex is located;

[0028] Step 3.1.3, for the sea surface temperature data in the environmental area of the vortex and the climatological monthly average month, month, monthly sea surface environmental regional temperature data of the vortex , , perform a linear regression analysis:

[0029] (1),

[0030] where is the error term, and the regression coefficient is obtained;

[0031] Step 3.1.4, respectively extract the climatological monthly average month, month, monthly sea surface temperature data , , , and use the regression coefficient to obtain the sea surface temperature background field of the vortex :

[0032] (2);

[0033] Step 3.2, construct the sea surface salinity background field of the vortex, including the following steps:

[0034] Step 3.2.1, for the observed sea surface salinity data, extract the sea surface salinity data in the environmental area of the vortex ;

[0035] Step 3.2.2, establish the climatological salinity field in the sea surface environmental area of the vortex:

[0036] Read the month in which the vortex is located , respectively extract the climatological monthly average month, month, monthly sea surface environmental regional salinity data , , ;

[0037] Step 3.2.3, perform a linear regression analysis on the sea surface salinity data and the monthly mean of the climatological state month, month, month of the salinity data in the eddy sea surface environmental area , , :

[0038] (3),

[0039] where is the error term, and the regression coefficient ;

[0040] Step 3.2.4, establish the eddy sea surface salinity background field: separately extract the monthly mean of the climatological state in the eddy area month, month, month of the sea surface salinity data , , , and use the regression coefficient to obtain the eddy sea surface salinity background field .

[0041] In Step 3.2.4, the eddy sea surface salinity background field is obtained using the following formula :

[0042] (4).

[0043] Step 4 includes:

[0044] Step 4.1, extract the eddy sea surface temperature anomaly: calculate the difference between the observed sea surface temperature field inside the eddy and the background temperature field to obtain the eddy sea surface temperature anomaly field ;

[0045] Step 4.2, extract the eddy sea surface salinity anomaly: calculate the difference between the observed sea surface salinity field inside the eddy and the background salinity field to obtain the eddy sea surface salinity anomaly field.

[0046] In Step 4.1, the eddy sea surface temperature anomaly field is obtained using the following formula :

[0047] (5),

[0048] where is the observed sea surface temperature field in the eddy area (the observed sea surface temperature field within 1 radius of the eddy), It is the constructed sea surface temperature background field of the vortex region.

[0049] In step 4.2, the following formula is used to obtain the sea surface salinity anomaly field of the vortex :

[0050] (6),

[0051] where is the observed sea surface salinity field in the vortex region (the observed sea surface salinity field within the 1-fold radius of the vortex), is the constructed sea surface salinity background field of the vortex region.

[0052] The present invention also provides an electronic device, including a processor and a memory. The memory stores program code. When the program code is executed by the processor, the processor executes the steps of the method.

[0053] The present invention also provides a storage medium, storing a computer program or instruction. When the computer program or instruction runs on a computer, the steps of the method are executed.

[0054] The present invention improves the calculation accuracy and applicability through the following technical means:

[0055] (1) Using the sea surface height anomaly to accurately extract the vortex range. Avoiding the uncertainty of artificially setting the vortex boundary and improving the physical rationality of the calculation.

[0056] (2) Constructing the background temperature and salinity field based on the vortex environment region (the annular region between 1-fold radius and 1.5-fold radius). Using regression analysis of climatological data and observed data to ensure the accuracy and self-adaptability of the background temperature and salinity field.

[0057] (3) Removing the influence of large-scale background. Through the construction of the background field, eliminating the influence of large-scale signal anomalies such as seasonal changes and El Niño on the sea surface temperature anomaly and sea surface salinity anomaly, making the extracted sea surface temperature anomaly and sea surface salinity anomaly more accurate.

[0058] (4) Providing a standardized and automated calculation process to ensure that the method is applicable to different sea areas globally, improving the data processing efficiency and the repeatability of the results.

[0059] The present invention can be widely applied to fields such as marine scientific research, climate change monitoring, fishery resource management, and marine forecasting, and has important scientific value and application prospects.

[0060] The present invention effectively solves the deficiencies of traditional methods in aspects such as the estimation of the background temperature-salinity field, the differentiation between the eddy field and the large-scale background field changes, the calculation accuracy of temperature-salinity anomalies, and the degree of automation by precisely extracting eddy sea surface temperature-salinity anomalies. Specifically, it includes the following beneficial effects: (1) Improving the accuracy of the background temperature-salinity field: By extracting observed sea surface temperature-salinity data within the eddy environment area and conducting regression analysis in combination with climatological sea surface temperature-salinity data, a more reasonable background temperature-salinity field is constructed. This method can adapt to temperature-salinity changes in different seasons and different regions, improve the self-adaptability of the background temperature-salinity field, and avoid errors caused by simply using multi-year average climatological data.

[0061] (2) Effectively differentiating eddy temperature-salinity anomalies from large-scale background changes: By establishing a background temperature-salinity field through regression analysis, the interference of large-scale phenomena such as seasonal changes and El Niño on the calculation of sea surface temperature anomalies and sea surface salinity anomalies is eliminated, making the calculated temperature-salinity anomalies more accurately reflect the dynamic thermodynamic characteristics of the eddies themselves. This method can more precisely differentiate the local sea surface temperature and sea surface salinity anomalies caused by eddies from external background changes, improving the physical rationality of sea surface temperature anomalies and sea surface salinity anomalies.

[0062] (3) Improving the rationality of the comparison of temperature-salinity inside and outside the eddy: Traditional methods usually use the average temperature-salinity of a certain fixed range outside the eddy as the background temperature-salinity, without fully considering the local temperature-salinity gradient. This method optimizes the background temperature-salinity field through regression analysis, which can more accurately reflect the temperature-salinity distribution characteristics around the eddies. By using the method of dynamically constructing the background temperature-salinity field, the calculation of sea surface temperature anomalies and sea surface salinity anomalies is more stable, reducing errors caused by improper selection of background temperature-salinity.

[0063] (4) Improving the standardization and automation of calculations: This method automatically extracts the eddy center and radius through sea surface height anomalies, constructs a background temperature-salinity field in combination with the regression analysis method, forms a standardized calculation process, reduces human subjective intervention, and improves the consistency and repeatability of the results. This method can be widely applied to the analysis of eddy sea surface temperature anomalies and sea surface salinity anomalies in different regions and different time scales, and can be integrated into the ocean data analysis system to improve data processing efficiency.

[0064] Through the present invention, the key technical problems in the extraction of eddy sea surface temperature-salinity anomalies are solved, providing new tools and methods for research and application in related fields. The inventive method is not only applicable to the extraction of eddy sea surface temperature-salinity anomalies, but also applicable to the extraction of anomalies of other eddy variables such as chlorophyll. Brief Description of the Drawings

[0065] Figure 1 is the flowchart according to the method of the present invention.

[0066] Figure 2 It is a schematic diagram of the sea surface height anomaly on January 1, 2010 in the research sea area provided by the embodiments of the present invention, as well as the identified vortex center (five-pointed star), boundary (black solid line), 1 times radius and 1.5 times radius (black dashed line).

[0067] Figure 3 It is a schematic diagram of the observed sea surface temperature of the vortex provided by the embodiments of the present invention.

[0068] Figure 4 It is a schematic diagram of the background field of the sea surface temperature of the vortex provided by the embodiments of the present invention.

[0069] Figure 5 It is a schematic diagram of the anomaly field of the sea surface temperature of the vortex provided by the embodiments of the present invention.

[0070] Figure 6 It is a schematic diagram of the observed sea surface salinity of the vortex provided by the embodiments of the present invention.

[0071] Figure 7 It is a schematic diagram of the background field of the sea surface salinity of the vortex provided by the embodiments of the present invention.

[0072] Figure 8 It is a schematic diagram of the anomaly field of the sea surface salinity of the vortex provided by the embodiments of the present invention. Detailed implementation manners

[0073] The following further specifically describes the present invention in conjunction with the accompanying drawings and specific implementation manners, and the above and / or other advantages of the present invention will become clearer.

[0074] The embodiments of the present invention provide a method for extracting anomalies of sea surface temperature and salinity of ocean vortices, including the following steps:

[0075] Step 1, data collection and preprocessing, specifically including the following steps:

[0076] Step 1.1, climatological data: The required climatological data includes sea surface temperature, salinity, and sea surface height. Among them, the monthly average climatological sea surface temperature and salinity data are extracted from the World Ocean Atlas WOA database, and the monthly average sea surface height is obtained by calculating the monthly average of the ocean satellite remote sensing data AVISO from January 1, 2010 to December 31, 2019.

[0077] Step 1.2, sea surface observation data: The sea surface observation data includes sea surface temperature, salinity, and sea surface height data. The observed sea surface temperature uses the Optimal Interpolation Sea Surface Temperature (OISST) v2.1 version of the National Oceanic and Atmospheric Administration of the United States, with a time resolution of 1 day and a spatial resolution 。The sea surface salinity is observed using the multivariate optimal interpolation sea surface salinity developed by the National Research Council of Italy (CNR), with a time resolution of 1 day and a spatial resolution of 。The sea surface height is observed from AVISO, with a time resolution of 1 day and a spatial resolution of 。The sea surface height anomaly caused by the vortex is the observed sea surface height minus the climatological monthly mean sea surface height.

[0078] Step 1.3, uniformly interpolate the climatological monthly mean sea surface temperature, salinity, sea surface height, and the observed sea surface temperature, salinity, and sea surface height data to the grid points with a spatial resolution of 。

[0079] Step 2, vortex feature identification, which specifically includes the following steps:

[0080] Step 2.1, vortex center identification;

[0081] For the sea surface height anomaly data with an AVISO spatial resolution of scan with a 5×5 grid point window to find the extreme points. The maximum point is the potential center of the anticyclonic vortex, and the minimum point is the potential center of the cyclonic vortex.

[0082] Step 2.2, vortex boundary identification;

[0083] Taking the sea surface height anomaly at the vortex center as the starting value, gradually increase (for cyclonic vortices) or decrease (for anticyclonic vortices) the value of the sea surface height anomaly outward (the change step can be taken as 0.001 m) until the outermost contour line only contains the unique vortex center. At this time, this contour line is the vortex boundary.

[0084] Step 2.3, vortex radius;

[0085] The radius corresponding to the circle with the same area as the area enclosed by the vortex boundary is defined as the vortex radius.

[0086] Step 2.4, vortex environmental area;

[0087] Select the annular region between 1 times the vortex radius and 1.5 times the vortex radius as the vortex environmental area.

[0088] As Figure 2 shown, it is a schematic diagram of the sea surface height anomaly in the study sea area on January 1, 2010. The pentagram is the identified vortex center, the black solid line is the vortex identification boundary, the black dashed lines are the circles of 1 times the vortex radius and 1.5 times the vortex radius, and the annular region between the two black dashed lines is the vortex environmental area.

[0089] Step 3, construct the vortex sea surface temperature field and salinity background field, which specifically includes the following steps:

[0090] Step 3.1, construct the background field of the sea surface temperature of the vortex, specifically including the following steps:

[0091] Step 3.1.1, the temperature field of the sea surface environment area of the vortex;

[0092] For the observed sea surface temperature data, extract the sea surface temperature data in the vortex environment area (the area between 1 times the radius and 1.5 times the radius), , that is, Figure 3 the temperature data at the black dots in

[0093] (the pentagram represents the center of the vortex, the black dotted line represents 1 times the radius and 1.5 times the radius of the vortex, and the black dots represent the positions of the grid points of the observed sea surface temperature in the vortex environment area).

[0094] Read the month in which the vortex is located , and extract the climatological monthly average month, month, month of the sea surface temperature data in the vortex sea surface environment area , , , where month is the month before the month in which the vortex is located, is the month after the month in which the vortex is located.

[0095] Step 3.1.3, perform a linear regression analysis on the sea surface temperature data in the environment area of the vortex and the climatological monthly average month, month, month of the sea surface temperature data in the vortex sea surface environment area , , :

[0096] (1),

[0097] where is the error term, and the regression coefficient is obtained;

[0098] Step 3.1.4, respectively extract the climatological monthly average month, month, month of the sea surface temperature data , , , and use the regression coefficient to obtain the background field of the sea surface temperature of the vortex :

[0099] (2);

[0100] In this example, the constructed background field of the sea surface temperature of the vortex is as Figure 4 shown (the pentagram represents the center of the vortex, the black dashed line represents the 1-fold radius and 1.5-fold radius of the vortex, and the black dots represent the positions of the grid points of the background field of the sea surface temperature in the vortex environment area).

[0101] Step 3.2: Construct the background field of the sea surface salinity of the vortex, which specifically includes the following steps:

[0102] Step 3.2.1: The salinity field in the vortex sea surface environment area;

[0103] For the observed sea surface salinity data, extract the sea surface salinity data in the vortex environment area (the area between the 1-fold radius and 1.5-fold radius), that is, the temperature data at the black dots in Figure 6 (the pentagram represents the center of the vortex, the black dashed line represents the 1-fold radius and 1.5-fold radius of the vortex, and the black dots represent the positions of the grid points of the observed sea surface salinity in the vortex environment area).

[0104] Step 3.2.2: The climatological salinity field in the vortex sea surface environment area;

[0105] Read the month in which the vortex is located , and extract the climatological monthly average month, month, month's sea surface salinity data in the vortex environment area , , ; where month is the month before the month in which the vortex is located, is the month after the month in which the vortex is located.

[0106] Step 3.2.3: Analysis of the salinity field and the climatological salinity field in the vortex sea surface environment area;

[0107] Perform a linear regression analysis on the observed sea surface salinity data in the vortex sea surface environment area and the climatological sea surface salinity data , , :

[0108] (3),

[0109] Obtain the regression coefficient .

[0110] Step 3.2.4: The background field of the sea surface salinity of the vortex;

[0111] Extract the climatological monthly average month, Month, Sea surface salinity data of the lunar maria , , , using the regression coefficient to obtain the background field of the sea surface salinity of the vortex :

[0112] (4),

[0113] The background field of the sea surface salinity of the vortex constructed in this example is as Figure 7 shown (the pentagram represents the center of the vortex, the black dotted line represents the 1-fold radius and 1.5-fold radius of the vortex, and the black dots represent the grid point positions of the background field of the sea surface salinity in the vortex environment area).

[0114] Step 4, extract the sea surface temperature field and salinity anomaly field of the vortex, which specifically includes the following steps:

[0115] Step 4.1, extract the sea surface temperature anomaly field of the vortex;

[0116] Calculate the difference between the observed sea surface temperature field inside the vortex and the background temperature field to obtain the sea surface temperature anomaly field SSTA:

[0117] (5),

[0118] wherein, is the observed sea surface temperature field in the vortex area, is the background field of the sea surface temperature of the vortex constructed. The sea surface temperature anomaly field of the vortex extracted in this example is as Figure 5 shown (the pentagram represents the center of the vortex, the black solid line represents the boundary of the vortex, the black dotted line represents the 1-fold radius and 1.5-fold radius of the vortex, and the black dots represent the grid point positions of the sea surface temperature anomaly field in the vortex environment area).

[0119] Step 4.2, extract the sea surface salinity anomaly field of the vortex;

[0120] Calculate the difference between the observed sea surface salinity field inside the vortex and the background salinity field to obtain the sea surface salinity anomaly field SSSA:

[0121] (6),

[0122] wherein, is the observed sea surface salinity field in the vortex area, is the background field of the sea surface salinity of the vortex area constructed. The sea surface salinity anomaly field of the vortex extracted in this example is as Figure 8As shown (the pentagram represents the vortex center, the black solid line represents the vortex boundary, the black dashed line represents 1 times and 1.5 times the radius of the vortex, and the black dots represent the grid point positions of the sea surface salinity anomaly field in the vortex environment area).

[0123] The present invention provides a method for extracting sea surface temperature and salinity anomalies of ocean vortices. There are many methods and ways to specifically implement this technical solution. The above description is only the preferred embodiment of the present invention. It should be noted that for those of ordinary skill in the art of this technology, without departing from the principle of the present invention, several improvements and refinements can be made, and these improvements and refinements should also be regarded as the protection scope of the present invention. Each component not clearly defined in this embodiment can be implemented by existing technologies.

Claims

1. A method for extracting anomalies of sea surface temperature and salinity of ocean vortices, characterized in that: The following steps are involved: Step 1, data collection and preprocessing; Step 2, identifying vortex characteristics; Step 3, constructing the vortex sea surface temperature background field and salinity background field; Step 4, extracting the vortex sea surface temperature anomaly field and salinity anomaly field; Step 1 includes: Step 1.1, collect climate data, including sea surface temperature, salinity, and sea surface height; Step 1.2, collect sea surface observation data, including sea surface temperature, salinity, and sea surface height data; Step 1.3: Standardize the climatological data and sea surface observation data and interpolate them to grid points with uniform spatial resolution; Step 2 includes: Step 2.1, identify the vortex center: For the sea surface height data Y1 with a spatial resolution of 1 / 4°×1 / 4° of the ocean satellite remote sensing data AVISO, subtract the climatological sea surface height data Y2 to obtain the sea surface height anomaly data Y3=Y1-Y2. The sea surface height anomaly data is scanned with a 5×5 grid point window to find the extreme point. The maximum point is the anticyclonic vortex center, and the minimum point is the cyclonic vortex center. Step 2.2, identify the vortex boundary: take the sea surface height anomaly at the vortex center as the starting value, and gradually increase or decrease the value of the sea surface height anomaly outward until the outermost contour line only contains the unique vortex center. At this time, the contour line is the vortex boundary; Step 2.3, define the radius corresponding to a circle with the same area as the vortex boundary as the vortex radius; Step 2.4, selecting an annular region between 1 times the radius and 1.5 times the radius of the vortex as the environment region of the vortex; Step 3 includes: Step 3.1, constructing the vortex sea surface temperature background field, specifically includes the following steps: Step 3.1.1: Extract the sea surface temperature data SST of the vortex environment area from the observed sea surface temperature data env ; Step 3.1.2, establish the climatological temperature field of the eddy sea surface environment: Read the month M where the vortex is located, and extract the climatological monthly average M-1, M, and M+1 vortex sea surface environment regional temperature data SSTM env (M-1), SSTM env (M), SSTM env (M+1), where M-1 is the month before the month in which the vortex occurs, and M+1 is the month after the month in which the vortex occurs; Step 3.1.3: sea surface temperature data SST for the eddy environment env SSTM data of eddy sea surface environment regional temperature in the climatological monthly average M-1, M, and M+1 env (M-1), SSTM env (M), SSTM env (M+1) linear regression analysis: SST env =b0+b1·SSTM env (M-1)+b2·SSTM env (M)+b3·SSTM env (M+1)+ε T (1), where ε T is the error term, and the regression coefficients b0, b1, b2, and b3 are obtained; Step 3.1.4: Extract the SSTM data of the monthly mean sea surface temperature in the eddy region for month M-1, month M, and month M+1 respectively eddy (M-1), SSTM eddy (M), SSTM eddy (M+1), using the regression coefficients b0, b1, b2, and b3, we can get the vortex sea surface temperature background field SST background : SST background =b0+b1·SSTM eddy (M-1)+b2·SSTM eddy (M)+b3·SSTM eddy (M+1) (2), Step 3.2, constructing the vortex sea surface salinity background field, includes the following steps: Step 3.2.1: Extract the sea surface salinity data SSS of the vortex environment area from the observed sea surface salinity data env ; Step 3.2.2, establish the regional climatological salinity field of the eddy sea surface environment: Read the month M where the vortex is located, and extract the climatological monthly average M-1, M, and M+1 vortex sea surface environment regional salinity data SSSM env (M-1), SSSM env (M), SSSM env (M+1); Step 3.2.3, the sea surface salinity observation data SSS in the eddy sea surface environment area env Compared with the climatological monthly average M-1, M, M+1 eddy sea surface environment regional salinity data SSSM env (M-1), SSSM env (M), SSSM env (M+1) linear regression analysis: SSS env =c0+c1·SSSM env (M-1)+c2·SSSM env (M)+c3·SSSM env (M+1)+ε S (3), where ε S is the error term, and the regression coefficients c0, c1, c2, and c3 are obtained; Step 3.2.4, establish the eddy sea surface salinity background field: extract the climatological monthly average sea surface salinity data SSSM of the eddy region for month M-1, month M, and month M+1 respectively eddy (M-1), SSSM eddy (M), SSSM eddy (M+1), using the regression coefficients c0, c1, c2, c3 to obtain the eddy sea surface salinity background field SSS background .

2. The method according to claim 1, characterized in that In step 3.2.4, the vortex sea surface salinity background field SSS is obtained using the following formula: background : SSS background =c0+c1·SSSM eddy (M-1)+c2·SSSM eddy (M)+c3·SSSM eddy (M+1) (4)。 3. The method according to claim 2, characterized in that Step 4 includes: Step 4.1, extracting the vortex sea surface temperature anomaly: calculating the difference between the observed sea surface temperature field inside the vortex and the background temperature field, and obtaining the vortex sea surface temperature anomaly field SSTA; Step 4.2, extract the vortex sea surface salinity anomaly: calculate the difference between the observed sea surface salinity field inside the vortex and the background salinity field to obtain the vortex sea surface salinity anomaly field.

4. The method according to claim 3, characterized in that: In step 4.1, the vortex sea surface temperature anomaly field SSTA is obtained using the following formula: SSTA=SST eddy -SST background (5), Among them, SST eddy To observe the sea surface temperature field in the vortex area, SST background This is the background field of sea surface temperature in the constructed eddy area.

5. The method according to claim 4, characterized in that In step 4.2, the eddy sea surface salinity anomaly field SSSA is obtained using the following formula: SSSA=SSS eddy -SSS background , (6), Among them, SSS eddy To observe the sea surface salinity field in the eddy region, SSS background This is the sea surface salinity background field in the constructed eddy area.

6. An electronic device, characterized in that: The method comprises a processor and a memory, wherein the memory stores program codes, and when the program codes are executed by the processor, the processor executes the steps of the method according to any one of claims 1 to 5.

7. A storage medium, characterized in that: A computer program or instruction is stored, and when the computer program or instruction is run on a computer, the steps of the method according to any one of claims 1 to 5 are executed.

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