Mesoscale vortex three-dimensional visualization method fused with ocean three-dimensional thermohaline structure

Abstract

The invention belongs to the crossing field of ocean science and ocean visualization, and discloses a mesoscale vortex three-dimensional visualization method fusing an ocean three-dimensional thermohaline structure, which comprises the following steps: 1) acquiring ocean reanalysis data, and segmenting the ocean reanalysis data according to an ocean standard layer; 2) carrying out layer-by-layer identification on the segmented data, and carrying out interlayer vortex matching to obtain three-dimensional mesoscale vortex information; 3) based on the three-dimensional mesoscale vortex information, intercepting temperature and salinity information of each layer of the vortex from the reanalysis data set, and cutting temperature and salinity data of each layer according to vortex boundary points; and 4) visualizing the cut temperature-salt data, and connecting the vortex inner diameter extreme points of each layer to obtain the three-dimensional mesoscale vortex. According to the method, the three-dimensional form and the thermohaline structure of the mesoscale ocean vortex can be fused and visualized, and the visual expression of the combination of the mesoscale vortex and other ocean hydrological elements is improved.

Description

TECHNICAL FIELD

[0001] The application belongs to the field of marine science and marine visualization, and particularly relates to a method for three-dimensional visualization of mesoscale eddies by fusing marine three-dimensional temperature and salinity structures. BACKGROUND

[0002] Mesoscale eddies are an important feature of marine mesoscale processes and an important carrier of marine material and energy transport and exchange, and are closely related to the safe navigation of waterborne vehicles. The three-dimensional structure of the mesoscale eddies plays a key role in revealing the marine dynamic processes, and the three-dimensional information visualization of the mesoscale eddies can provide auxiliary support for related marine activities and research. However, the existing mesoscale eddy identification and visualization are mostly based on the satellite ocean remote sensing interpretation of sea surface height anomaly data, and only the characteristics of the sea surface layer of the mesoscale eddies can be inverted, and the three-dimensional structure characteristics are not analyzed. Some studies involve the identification and extraction of three-dimensional mesoscale eddies, but the geometric characteristics of the eddies and the three-dimensional temperature and salinity field data in the water body are processed separately, and effective data fusion and visualization expression are not performed, and the changes of the three-dimensional water body physical and chemical parameters of the mesoscale eddies cannot be more intuitively analyzed. Moreover, the three-dimensional structure of the eddies only supports static three-dimensional visualization model display, and the three-dimensional temperature and salinity and the mesoscale eddies cannot be intuitively viewed from multiple angles, which limits the depth of the research on the mechanism of the marine mesoscale phenomena. At present, the visualization of the mesoscale eddies based on the fusion of the marine three-dimensional temperature and salinity structures is still a challenging and promising work. SUMMARY

[0003] The application aims to provide a method for reconstructing marine three-dimensional mesoscale eddies and marine three-dimensional temperature and salinity by fusing, which can fuse and visualize the three-dimensional morphology of the marine mesoscale eddies and the temperature and salinity structure, and improve the intuitive expression of the combination of the mesoscale eddies and other marine hydrological elements.

[0004] The technical scheme adopted by the application to achieve the above-mentioned purpose is as follows:

[0005] A method for three-dimensional visualization of mesoscale eddies by fusing marine three-dimensional temperature and salinity structures, comprising the following steps:

[0006] 1) Obtain marine reanalysis data and divide the data according to marine standard layers;

[0007] 2) Identify the divided data layer by layer, and perform eddy matching between layers to obtain three-dimensional mesoscale eddy information;

[0008] 3) Based on the three-dimensional mesoscale eddy information, cut the temperature and salinity information of each layer where the eddy is located from the reanalysis data set, and cut the temperature and salinity data of each layer according to the eddy boundary points;

[0009] 4) Visualize the cut warm salt data and connect the extreme points of the inner diameter of each layer eddy to obtain a three-dimensional mesoscale eddy.

[0010] The step 1) comprises the following steps:

[0011] 1.1) Obtain any three-dimensional ocean reanalysis data containing temperature, salinity and ocean current of full water depth;

[0012] 1.2) Layer the ocean reanalysis data using the standard layering scheme of the ocean to obtain the layer slice data set Data layer :

[0013] Data layer ={T ijk ,S ijk ,U ijk ,V ijk}

[0014] Wherein, T is temperature data, S is salinity data, U is the component data of ocean current in the east-west direction, V is the component data of ocean current in the north-south direction, i, j are horizontal grid indexes, k is the depth layer index, k∈1~N, k=1 is the surface layer, k=N is the bottom layer, and N is the total number of layers.

[0015] The step 2) comprises the following steps:

[0016] 2.1) Use Okubo-Weiss eddy detection algorithm to detect and identify the mesoscale eddy information of each standard layer, to obtain a single eddy feature e including the longitude of each eddy center center lon , the latitude of the eddy center center lat , the eddy type type, the eddy radius radius, the eddy kinetic energy EKE, and the eddy boundary point set boundary_points.

[0017] e={center lon ,center lat ,type,radius,EKE,boundary_points}

[0018] Then the kth layer eddy set E k ={e k 1 ,e k 2 ,...,e k M}, the k+1th layer eddy set E k+1 ={e k+1 1 ,e k+1 2..., e k+1 M}, e k M is the number of vortices in the layer;

[0019] 2.2) Using the equal layer vortex matching method based on the vertical correlation algorithm to calculate the three-dimensional correlation of each layer vortex.

[0020] The step 2.2) includes the following steps:

[0021] 2.2.1) Calculate the vortex core offset and radius change rate of the current layer and the next layer respectively;

[0022] 2.2.2) The vortex whose vortex core offset and radius change rate both meet the threshold value is regarded as the same vortex, and the corresponding relationship between the same vortex in each layer is established to obtain a set of vertically correlated two-dimensional mesoscale vortex information, i.e. three-dimensional mesoscale vortex information C(e i ), which contains the center longitude and latitude, type, radius, and boundary point information of a number of vertically correlated vortices in each layer:

[0023] C(e i )={e k+1 i ∣dist(center(e k i ),center(e k+1 i ))≤D thresh}

[0024] D thresh =min(20km,P×radius(e k i ))

[0025] Where center(e k i ) is the center longitude and latitude of the i-th vortex in the k-th layer, D thresh is the double threshold value of vortex core offset and radius change rate, and P is the radius change rate parameter.

[0026] The step 3) includes the following steps:

[0027] 3.1) Arbitrarily select a set of vertically correlated two-dimensional mesoscale vortex information C(e i ), according to the layer range k where the vortex is located, the vortex center point center lon,lat , the vortex boundary point information E boundary_points , and the vortex radius E radius, obtain the three-dimensional vortex water depth range boundary, the plane extreme range boundary, use the extreme boundary information to cut the three-dimensional ocean reanalysis data, obtain the cut three-dimensional temperature and salinity data;

[0028] 3.2) based on the cut three-dimensional temperature and salinity data, data cutting is carried out from the slice data set Data layer which it is located, and the temperature and salinity data of each layer of the vortex are intercepted.

[0029] The step 4) comprises the following steps:

[0030] 4.1) fuse the two-dimensional vortex feature e of each layer with the temperature and salinity surface data;

[0031] 4.2) connect the vortex inner diameter extreme points of each layer after vertical correlation to obtain a three-dimensional mesoscale vortex.

[0032] A mesoscale vortex three-dimensional visualization system fusing ocean three-dimensional temperature and salinity structure comprises:

[0033] A data downloading and processing module is used for obtaining ocean reanalysis data and cutting the data according to ocean standard layers;

[0034] A vortex feature recognition and vertical correlation module is used for layer-by-layer recognition of the cut data and layer-to-layer vortex matching to obtain three-dimensional mesoscale vortex information;

[0035] A three-dimensional temperature and salinity data extraction module is used for intercepting the temperature and salinity information of each layer of the vortex from the reanalysis data set based on the three-dimensional mesoscale vortex information, and cutting the temperature and salinity data of each layer according to the vortex boundary points;

[0036] A mesoscale vortex visualization module is used for visualizing the cut temperature and salinity data and connecting the vortex inner diameter extreme points of each layer to obtain a three-dimensional mesoscale vortex.

[0037] The present application has the following beneficial effects and advantages:

[0038] 1. The present application realizes the depth fusion visualization of the three-dimensional geometric structure of the mesoscale vortex in the ocean and the temperature and salinity parameters of the water body, expands the integrated three-dimensional expression perspective of "vortex morphology-ocean environmental physical field", can directly observe the abnormal distribution of the temperature and salinity in the vortex, helps to understand the three-dimensional morphological structure and vertical variation law of the vortex, is beneficial to the analysis of the correlation change between the physical structure of the vortex and the temperature and salinity field parameters of the ocean environment, and reveals the dynamic-heat-salt coupling mechanism.

[0039] 2. The isointerval vortex matching method based on the vertical correlation algorithm can improve the coherence of the three-dimensional morphology of the vortex, and improves the traditional mesoscale vortex which depends on the experience value for vertical matching, so that the vortex visualization result is more reliable.

[0040] 3. The application generates a rotatable, zoomable, and cutaway three-dimensional dynamic model, which supports researchers to observe the spatial correlation between the vortex morphology and the temperature and salinity field from any perspective, and accelerates the mechanism research. BRIEF DESCRIPTION OF DRAWINGS

[0041] Figure 1 Method flowchart of the application;

[0042] Figure 2 Three-dimensional temperature and salinity cube based on vortex characteristics (a: three-dimensional temperature, b: three-dimensional salinity);

[0043] Figure 3 Three-dimensional mesoscale vortex with fused temperature and salinity characteristics. DETAILED DESCRIPTION

[0044] The application will be further described in detail below in combination with the drawings and examples.

[0045] A mesoscale vortex three-dimensional visualization method based on marine three-dimensional temperature and salinity structure is to identify mesoscale vortex characteristics (vortex center point, vortex radius, vortex boundary, etc.), perform interlayer vortex matching on mesoscale vortex through vertical correlation algorithm, depict the three-dimensional morphology of mesoscale vortex, fuse three-dimensional temperature and salinity data, and perform mesoscale vortex three-dimensional visualization, which is beneficial to quantitatively analyze the correlation between vortex core area temperature and salinity and vortex and the vertical gradient change, reveal the three-dimensional structural characteristics of mesoscale vortex, and is suitable for marine dynamics research, vortex energy transfer analysis, and marine environment prediction.

[0046] As Figure 1As shown, the method comprises: 1) a data download and processing module: download global ocean full-depth reanalysis data, and divide the data according to marine standard layers; 2) a vortex feature recognition and vertical correlation module: introduce a two-dimensional vortex detection algorithm and an interlayer vortex matching method such as a vertical correlation algorithm, to respectively identify mesoscale vortex feature information (vortex center point longitude, vortex center point latitude, vortex type, vortex radius, vortex energy, vortex boundary point set and other information) in each standard layer in a specified sea area, and obtain three-dimensional mesoscale vortex data with strong correlation through a vortex core vertical correlation algorithm; 3) a three-dimensional temperature and salinity data extraction module: according to the mesoscale vortex feature information recognition result, intercept the temperature and salinity information of each layer where the vortex is located from the reanalysis data set, and cut the temperature and salinity data of each layer according to the vortex boundary points; 4) mesoscale vortex visualization: according to the two-dimensional mesoscale vortex information identified according to the standard layer and the intercepted temperature and salinity data of the same layer, perform three-dimensional visualization, respectively connect the inner diameter extreme points of each layer vortex, and obtain a three-dimensional mesoscale vortex. The full-depth marine mesoscale vortex three-dimensional structure of the application can be visualized and fused with temperature and salinity data, and in combination with the temperature and salinity information at the position of the vortex, the vortex feature variation law from the surface layer to the bottom layer in the marine water body can be judged, and the dimension of the marine mesoscale vortex expression is enriched.

[0047] The specific technical solutions are as follows:

[0048] S1, a data download and processing module, mainly downloads marine reanalysis data, and divides the data according to marine standard layers;

[0049] S1-1 downloads full-depth reanalysis data published internationally, such as HYCOM reanalysis data (containing three-dimensional grid data of temperature, salinity and current velocity); or any marine reanalysis data containing full-depth three-dimensional temperature, salinity and current; and enters S1-2.

[0050] S1-2, according to the data downloaded in S1-1, divides the data according to a marine standard layering scheme, such as a commonly used international standard depth layer (World Ocean Atlas, WOA depth layer), a model-specific layering (HYCOM hybrid coordinate layer, adaptive layering). Generate layer slice data set:

[0051] Data layer ={T ijk ,S ijk ,U ijk ,V ijk}

[0052] i,j is the horizontal grid index, and k is the depth layer index (k=1 is the surface layer, and k=N is the bottom layer)

[0053] S2 Vortex feature recognition and vertical correlation module: Introduce two-dimensional vortex detection algorithm to identify mesoscale vortex feature information; use vertical correlation algorithm and other interlayer vortex matching methods to obtain three-dimensional mesoscale vortex information.

[0054] S2-1 uses an improved Okubo-Weiss vortex detection algorithm to identify each layer vortex, and detects and identifies the mesoscale vortex information of the single standard layer identified by S1-2, outputs single-layer vortex features, including the longitude of the vortex center point, the latitude of the vortex center point, the vortex type, the vortex radius, the vortex kinetic energy, and the vortex boundary point set information of each layer;

[0055] e = {center lon ,center lat , type, radius, EKE, boundary_points}

[0056] The kth layer vortex set E k = {e k 1 , e k 2 ,..., e k M}(k is the vortex layer, M is the number of surface vortexes)

[0057] The k+1th layer vortex set E k+1 = {e k+1 1 , e k+1 2 ,..., e k+1 M}(k+1 is the vortex layer, M is the number of surface vortexes)

[0058] S2-2 uses vertical correlation algorithm and other interlayer vortex matching methods to calculate the three-dimensional correlation of each layer vortex. Calculate the double constraints of the center offset and the radius change rate of each layer and the next layer, establish the corresponding relationship between the vortexes of each layer; obtain a set of two-dimensional mesoscale vortex information vertically correlated, namely three-dimensional mesoscale vortex information C(e i ), containing the center longitude and latitude, type, radius, boundary point information of several vertically correlated vortexes of each layer.

[0059] C(e i ) = {e k+1 i | dist(center(e k i ), center(e k+1 i )) ≤ D thresh}

[0060] Dthresh = min(20km, P x radius(e k i )(P is a radius change rate parameter, generally 0.5)

[0061] S3 three-dimensional temperature and salinity data extraction module:

[0062] S3-1 arbitrarily select two-dimensional mesoscale vortex information C(e i ) with vertical correlation, according to the vortex layer k where the vortex center point center lon,lat , vortex boundary point information E boundary_points , vortex radius E radius , and mesoscale vortex extreme value information (the shallowest depth, the deepest depth, the plane longitude and latitude four to the information), the temperature and salinity data are cut off three-dimensionally, and the cut three-dimensional temperature and salinity data are obtained, as shown in Figure 2 ;

[0063] S3-2 data cutting from the corresponding slice data set Data layer , intercept the temperature and salinity data of each layer where the vortex is located.

[0064] S4 mesoscale vortex visualization: according to the two-dimensional mesoscale vortex information identified according to the standard layer and the temperature and salinity data of the same layer, the three-dimensional visualization is carried out, and the extreme points of the inner diameter of the vortex of each layer are connected to obtain the three-dimensional mesoscale vortex.

[0065] S4-1 fuse each layer two-dimensional vortex feature point with temperature and salinity surface data, as shown in Figure 3 ;

[0066] S4-2 according to the standard layer, the S4-1 data are vertically associated, and the extreme points of the inner diameter of the vortex of each layer are connected to obtain the three-dimensional mesoscale vortex.

Claims

1. A method for three-dimensional visualization of mesoscale eddies in fusion with ocean three-dimensional temperature-salinity structure, characterized in that, The method comprises the following steps: 1) obtaining marine reanalysis data and slicing it according to marine standard layers; 2) identifying the sliced data layer by layer and performing interlayer vortex matching to obtain three-dimensional mesoscale vortex information; 3) based on the three-dimensional mesoscale vortex information, cutting the temperature and salinity information of each layer where the vortex is located from the reanalysis data set, and cutting the temperature and salinity data of each layer according to the vortex boundary points; 4) visualizing the cut temperature and salinity data and connecting the extreme points of the inner diameter of each layer vortex to obtain a three-dimensional mesoscale vortex.

2. The method according to claim 1, wherein, The step 1) comprises the following steps: 1.1) obtaining marine reanalysis data containing three-dimensional temperature, salinity and ocean current data of the entire water depth; 1.2) stratify the ocean reanalysis data using the ocean standard layering scheme to obtain a layer-slice dataset Data layer : Data layer = {T ijk , S ijk , U ijk , V ijk} wherein T is temperature data, S is salinity data, U is the component data of the ocean current in the east-west direction, V is the component data of the ocean current in the north-south direction, i and j are horizontal grid indices, k is a depth layer index, k∈1~N, k=1 is the surface layer, k=N is the bottom layer, and N is the total number of layers.

3. The method according to claim 1, wherein the method is characterized by, The step 2) comprises the following steps: 2.1) Using Okubo-Weiss vortex detection algorithm to detect and identify the mesoscale vortex information of each standard layer, get the single vortex characteristics e of each layer including the vortex center point longitude center lon , vortex center point latitude center lat , vortex type type, vortex radius radius, eddy energy EKE, vortex boundary point set boundary_points; e = {center lon , center lat , type, radius, EKE, boundary_points} then the kth level vortex set E k = {e k 1 ,e k 2 ,...,e k M}, the k+1th level vortex set E k+1 = {e k+1 1 ,e k+1 2 ,...,e k+1 M}, e k is a single vortex feature, and M is the number of vortices in this level. 2.2) performing three-dimensional correlation calculation on each layer vortex using an isointerlayer vortex matching method based on a vertical correlation algorithm.

4. The method according to claim 3, wherein the method is characterized by, The step 2.2) comprises the following steps: 2.2.1) calculating the vortex core offset and the radius change rate of the current layer and the next layer, respectively; 2.2.2) The vortex core offset and the radius change rate of the vortex that meets the threshold value are considered as the same vortex. The corresponding relationship between the layers is established, and a set of vertically related two-dimensional mesoscale vortex information, i.e. three-dimensional mesoscale vortex information C(e i ), is obtained, which contains the central longitude and latitude, type, radius, and boundary point information of the vortex at each layer. C(e i ) = {e k+1 i ∣dist(center(e k i ),center(e k+1 i ))≤D thresh} D thresh = min(20 km, P x radius(e k i )) wherein, center(e k i ) is the longitude and latitude of the i-th vortex center point of the k-th layer, D thresh is the double threshold of the vortex center offset and the radius change rate, and P is the radius change rate parameter.

5. The method according to claim 1, wherein, The step 3) comprises the following steps: 3.1) randomly select a group of two-dimensional mesoscale vortex information C(e i ) with vertical correlation, according to the range of the layer position k where the vortex is located, the vortex center point center lon,lat , the vortex boundary point information E boundary_points , the vortex radius E radius , the range boundary of the three-dimensional vortex where the vortex is located, the plane extreme range boundary, using the extreme boundary information to cut the three-dimensional ocean reanalysis data, and obtaining the cut three-dimensional temperature and salinity data; 3.2) Based on the three-dimensional temperature-salinity data after cutting, the data of each layer where the vortex is located is cut from the slice data set Data layer and the temperature and salinity data of each layer where the vortex is located are intercepted.

6. The method according to claim 1, wherein, The step 4) comprises the following steps: 4.1) fusing each layer two-dimensional vortex feature e with the temperature and salinity surface data; 4.2) connecting the extreme points of the inner diameter of each layer vortex after vertical correlation to obtain a three-dimensional mesoscale vortex.

7. A system for stereoscopic visualization of mesoscale eddies in fusion with ocean three-dimensional temperature-salinity structure, characterized by, comprise: a data download and processing module for obtaining marine reanalysis data and slicing it according to marine standard layers; a vortex feature recognition and vertical correlation module for identifying the sliced data layer by layer and performing interlayer vortex matching to obtain three-dimensional mesoscale vortex information; a three-dimensional temperature and salinity data extraction module for cutting the temperature and salinity information of each layer where the vortex is located from the reanalysis data set based on the three-dimensional mesoscale vortex information, and cutting the temperature and salinity data of each layer according to the vortex boundary points; a mesoscale vortex visualization module for visualizing the cut temperature and salinity data and connecting the extreme points of the inner diameter of each layer vortex to obtain a three-dimensional mesoscale vortex.

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