Method and system for calculating tropical cyclone temperature structure

Abstract

The application discloses a kind of tropical cyclone temperature body structure calculation method and system, wherein the method includes: based on satellite microwave detection data and tropical cyclone position information, the three-dimensional temperature data of tropical cyclone area is smoothed, and temperature grid with tropical cyclone center as origin is formed.Three-dimensional temperature anomaly value is calculated according to the smoothed temperature grid.Based on three-dimensional temperature anomaly value, three-dimensional region growth method is used to extract tropical cyclone warm core main area.Based on the extracted tropical cyclone warm core main area, the isosurface is calculated using Marching Cubes algorithm.According to the isosurface, the light model is rendered to draw the three-dimensional visualization structure of tropical cyclone warm core.Based on the three-dimensional temperature anomaly value of tropical cyclone warm core main area, the tropical cyclone warm core intensity index is calculated.Thus, the application effectively solves the problem of insufficient overall understanding of tropical cyclone temperature structure in the prior art, and provides the ability of systematic quantitative analysis.

Description

TECHNICAL FIELD

[0001] The embodiment of the present application relates to meteorological data processing technical field, especially relates to a tropical cyclone temperature body structure calculation method and system. BACKGROUND

[0002] As a disastrous weather system with a scale of hundreds to thousands of kilometers, the internal temperature structure of tropical cyclone has significant characteristics, especially the existence of warm core in the middle and high layers of the central core area. The warm core is the key identifier that distinguishes it from other weather systems. The range and intensity of the warm core are directly related to the intensity evolution process of the tropical cyclone, and are important indicators for monitoring and predicting its development. However, the existing technology has obvious limitations in the study of the temperature structure of tropical cyclone, mainly focusing on the qualitative description of the position of the warm core center in the middle and high layers, and lacking systematic understanding of the overall three-dimensional temperature distribution. Specifically, the traditional method fails to establish an effective quantitative calculation framework, making it difficult to accurately obtain the complete temperature body structure of the tropical cyclone region from the ground to the upper atmosphere, and also difficult to analyze the spatial form, temperature anomaly distribution of the warm core main area and its difference with the surrounding area. This limitation leads to the inability to fully evaluate the role of the internal temperature structure in analyzing the intensity variation mechanism of the tropical cyclone, which restricts the accuracy of meteorological prediction and the timeliness of disaster warning.

[0003] Therefore, there is an urgent need for a comprehensive calculation method that can realize fine processing of three-dimensional temperature field, automatic extraction of warm core main area and visual presentation based on satellite observation data, to overcome the shortcomings of the existing technology in the overall understanding of temperature structure. SUMMARY

[0004] The embodiment of the present application provides a tropical cyclone temperature body structure calculation method and system, which has the advantage of providing systematic quantitative analysis capability.

[0005] To achieve the above-mentioned purpose, in a first aspect, the present application provides a tropical cyclone temperature body structure calculation method, comprising: based on satellite microwave detection data and tropical cyclone position information, performing smoothing processing on three-dimensional temperature data of a tropical cyclone region to form a temperature grid with the center of the tropical cyclone as the origin. Calculating three-dimensional temperature anomaly values according to the smoothed temperature grid. Based on the three-dimensional temperature anomaly values, using a three-dimensional region growing method to extract the main area of the warm core of the tropical cyclone. Based on the extracted main area of the warm core of the tropical cyclone, using a Marching Cubes algorithm to calculate isosurfaces. According to the isosurfaces, using a lighting model to render to draw the three-dimensional visualization structure of the warm core of the tropical cyclone. Based on the three-dimensional temperature anomaly values of the main area of the warm core of the tropical cyclone, calculating the warm core intensity index of the tropical cyclone.

[0006] In a second aspect, the present application provides a tropical cyclone temperature body structure calculation system, comprising: a temperature grid forming module, a three-dimensional temperature anomaly value calculation module, a tropical cyclone warm core main body area extraction module, an isosurface calculation module, a three-dimensional visual structure drawing module, and a tropical cyclone warm core intensity index calculation module. The temperature grid forming module is configured to perform smoothing processing on three-dimensional temperature data of a tropical cyclone area based on satellite microwave detection data and tropical cyclone position information, and form a temperature grid with the center of the tropical cyclone as the origin. The three-dimensional temperature anomaly value calculation module is configured to calculate a three-dimensional temperature anomaly value based on the smoothed temperature grid. The tropical cyclone warm core main body area extraction module is configured to extract a tropical cyclone warm core main body area based on the three-dimensional temperature anomaly value by using a three-dimensional region growing method. The isosurface calculation module is configured to calculate an isosurface based on the extracted tropical cyclone warm core main body area by using a Marching Cubes algorithm. The three-dimensional visual structure drawing module is configured to render a three-dimensional visual structure of the tropical cyclone warm core by using a lighting model based on the isosurface. The tropical cyclone warm core intensity index calculation module is configured to calculate a tropical cyclone warm core intensity index based on the three-dimensional temperature anomaly value of the tropical cyclone warm core main body area.

[0007] In a third aspect, the present application provides an electronic device, comprising:

[0008] at least one processor; and

[0009] a memory connected to the at least one processor in communication;

[0010] wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the tropical cyclone temperature body structure calculation method as described above.

[0011] In a fourth aspect, the present application provides a computer-readable storage medium comprising a computer program and instructions, which, when executed on a computer, cause the computer to perform the tropical cyclone temperature body structure calculation method as described above.

[0012] Compared with the prior art, the tropical cyclone temperature body structure calculation method and system according to the present application realize fine processing of a three-dimensional temperature field, automatic extraction of a warm core main body area, and visual presentation based on satellite microwave detection data, effectively solving the problem of insufficient overall understanding of the temperature structure of a tropical cyclone in the prior art, and having the advantage of providing systematic quantitative analysis capability. BRIEF DESCRIPTION OF DRAWINGS

[0013] Figure 1 is a flowchart of a tropical cyclone temperature body structure calculation method in the first embodiment of the present application;

[0014] Figure 2 This is a schematic diagram of a tropical cyclone temperature body structure calculation system according to Embodiment 2 of the present invention;

[0015] Figure 3 This is a schematic diagram of the structure of an electronic device according to Embodiment 3 of the present invention;

[0016] Figure 4 This is a schematic diagram of 15 basic cases of the Marching Cubes algorithm in a specific embodiment of the present invention;

[0017] Figure 5 This is a schematic diagram of the indexing rules for vertices and edges on each voxel unit in a specific embodiment of the present invention;

[0018] Figure 6 This is a schematic diagram in a specific embodiment of the present invention, showing that the values ​​at other vertices are greater than the surface value. Detailed Implementation

[0019] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0020] It should be noted that the terms "first," "second," "target," etc., used in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0021] To facilitate understanding, the main implementation concepts of the various embodiments of the present invention will be briefly described first.

[0022] Traditional tropical cyclone temperature structure analysis relies solely on single temperature characteristics at the center of the mid-to-upper-level warm core, lacking a comprehensive quantitative description of the three-dimensional temperature structure of tropical cyclones. This prevents a systematic characterization of the intrinsic correlation between changes in the intensity of the warm core and the evolution of tropical cyclone intensity. Furthermore, the spatial distribution of temperature data is not integrated into a unified coordinate system, environmental background interference is not effectively eliminated, and the connectivity of the warm core's physical boundaries depends on two-dimensional slices. Consequently, the geometric morphology and dynamic evolution of temperature anomaly regions are difficult to quantify precisely, thus affecting a comprehensive assessment of the role of internal temperature structure in tropical cyclone intensity changes.

[0023] For example, in the real-time monitoring of Tropical Cyclone Mangkhut in 2018, meteorological departments obtained three-dimensional temperature information of the tropical cyclone region based on satellite microwave sounding data. However, existing methods can only output the temperature anomaly value at the center point of the warm core, and cannot construct a three-dimensional temperature distribution model with the center of the tropical cyclone as the origin. Furthermore, when the intensity of a tropical cyclone rapidly intensifies, the changes in the vertical extension height and horizontal expansion range of the main body of the warm core are not effectively identified, and the three-dimensional spatial distribution of temperature anomalies is not accurately calculated. As a result, the temperature difference between the warm core and the surrounding environment cannot be visualized, causing the intensity prediction model to deviate due to the lack of key structural parameters, and significantly restricting the reliability of early warning information.

[0024] If the aforementioned problems are not addressed, tropical cyclone monitoring systems will remain limited to one-sided analyses of local temperature characteristics, failing to establish a measurable correlation between the dynamic changes of the warm core and the evolution of tropical cyclone intensity. Specifically, the lack of a holistic description of temperature structure will create systematic blind spots in intensity prediction models, and the unclear mechanism for the synchronous quantification of the warm core's extent and intensity indicators may lead to serious misjudgments in pre-landfall intensity assessments of tropical cyclones. This increases the uncertainty of disaster risk assessments, thereby weakening the scientific rigor and timeliness of disaster prevention and mitigation decisions.

[0025] In this regard, such as Figure 1 As shown, Example 1 provides a method for calculating the temperature body structure of a tropical cyclone, including:

[0026] Y100, based on satellite microwave detection data and tropical cyclone location information, smooths the three-dimensional temperature data of the tropical cyclone region to form a temperature grid with the center of the tropical cyclone as the origin.

[0027] In one implementation, based on satellite microwave sounding data and tropical cyclone location information, the three-dimensional temperature data of the tropical cyclone region is smoothed to form a temperature grid with the center of the tropical cyclone as the origin. Step Y100 of the method provided by this invention includes:

[0028] Y110, acquires temperature data of each pressure layer and tropical cyclone location information from the satellite microwave detection data.

[0029] Y120, based on the tropical cyclone location information, interpolates the temperature data onto a radial grid with the tropical cyclone center as the initial position and a spatial resolution set to a first preset kilometer.

[0030] Y130 uses a Gaussian weighting function to smooth the interpolated temperature data, resulting in a uniformly spaced temperature grid. The Gaussian weighting function determines the weights based on the distance from the scan point to the center of the tropical cyclone.

[0031] Among them, radial grid points refer to a grid system distributed radially around the center of the tropical cyclone. It can be implemented by dividing the grid at equal angles in polar coordinates or by adaptive radial density adjustment to naturally fit the axisymmetric physical structure of the tropical cyclone. Gaussian weight function refers to an exponentially decaying weight allocation mechanism based on Euclidean distance. It can be implemented by adopting a standard Gaussian distribution or by introducing a variant with an adjustable decay coefficient. It is used to dynamically quantify the contribution of each data point to the target position during the smoothing process. Its purpose is to eliminate random noise while preserving the physical continuity of the temperature gradient through distance-sensitive weight allocation.

[0032] Specifically, this invention acquires temperature data and location information of each pressure layer in step Y110, ensuring that the data is focused on the core region of the tropical cyclone and avoiding interference from irrelevant pressure layers. Then, in step Y120, the data is interpolated onto a radial grid with the center as the origin. Utilizing the inherent rotational symmetry of tropical cyclones, the grid distribution naturally matches the cyclone structure, eliminating geometric distortion in the Cartesian coordinate system and ensuring grid uniformity through a unified spatial resolution. Finally, in step Y130, a distance-based Gaussian weighting function is used for smoothing. This ensures that the central region retains key warm core features due to its high weight, while the peripheral region effectively suppresses noise due to decreasing weights, thus maintaining the accuracy of the temperature gradient while eliminating random fluctuations in the data. This sequential data processing flow, through the collaborative design of interpolation and smoothing, solves the grid distortion problem caused by the irregular distribution of the original data, providing a high-precision data foundation for subsequent three-dimensional temperature anomaly calculations.

[0033] As a preferred embodiment, the present invention is implemented as follows: After satellite microwave sounding data is acquired in step Y110, the system interpolates the temperature data onto a radial grid with the center as the origin, based on the tropical cyclone location information, with a spatial resolution of 25 km. Subsequently, a Gaussian weighting function is applied, where the weight decreases exponentially with increasing distance from the scanning point to the center, to smooth the interpolated data and generate a uniformly spaced temperature grid. In this embodiment, the radial grid is divided using polar coordinates, and the attenuation coefficient of the Gaussian weighting function is dynamically adjusted according to the cyclone scale, ensuring a balance between preserving central region features and suppressing peripheral noise.

[0034] In practical applications, tropical cyclones have a warm core structure, and their horizontal pressure gradient gradually decreases with altitude. When the updraft reaches a certain altitude, the resultant force of the inertial centrifugal force and the Coriolis force maintaining the gradient balance will exceed the pressure gradient force, causing air to diverge outwards. By interpolating the temperature data of each pressure layer onto a radial grid with the tropical cyclone center as the initial position, the temperature value of each grid point can be expressed as a function of the tropical cyclone radius and pressure. Since the scanning resolution of tropical cyclones reaches 50 km near the nadir point, but becomes coarser towards the boundaries, smoothing of the temperature data is necessary. This smoothing process can be achieved using a Gaussian weighted function scanning analysis. If the tropical cyclone center is taken as the origin, the grid points in its radial direction... Temperature at the location It can be represented as:

[0035] (1);

[0036] (2);

[0037] In the above equations (1) and (2), For grid points Temperature calculated after weighted average The weights of each scan point to the center of the tropical cyclone are given. These are the temperature values ​​at each scanning point. To smooth the spacing of the grid points, This represents the distance from each scanning point in the corresponding pressure layer to the center of the tropical cyclone. The smoothness of the interpolation region is determined, typically set to 30 km. After smoothing the air layer data, smoothed temperature values ​​can be obtained for each grid point with a radius of 600 km and an interval of 25 km (the first preset kilometer) centered on the tropical cyclone center.

[0038] Based on the above analysis, it can be seen that the present invention effectively overcomes the problem of uneven temperature grid caused by irregular spatial distribution and noise interference of satellite microwave detection data, ensuring the accurate preservation of key warm core characteristics and the physical authenticity of temperature gradient, thereby improving the accuracy of three-dimensional temperature anomaly calculation and warm core main region extraction, and providing stable data support for reliable analysis of tropical cyclone intensity changes.

[0039] Y200 calculates the three-dimensional temperature anomaly based on the smoothed temperature grid.

[0040] In one implementation, the three-dimensional temperature anomaly value is calculated based on the smoothed temperature grid. Step Y200 of the method provided by this invention includes:

[0041] Y210 obtains the temperature values ​​of each grid point from the smoothed temperature grid.

[0042] Y220, calculate the average temperature value of the surrounding area, wherein the surrounding area is a ring-shaped area with the center of the tropical cyclone as the center and an outer radius of a second preset kilometer.

[0043] Y230, the difference between the temperature value of each grid point and the average temperature value is obtained as the three-dimensional temperature anomaly value.

[0044] Step Y210 refers to extracting temperature data from the smoothed temperature grid, which can be achieved by directly reading the stored grid data. The purpose is to provide a basic temperature value for subsequent calculations and avoid interference from local fluctuations. Step Y220 refers to calculating the average temperature value of the surrounding area, which is a ring-shaped area. This can be achieved by using a ring-shaped area centered on the center of the tropical cyclone and with an outer radius set based on the typical scale of tropical cyclones. The purpose is to eliminate the influence of the warm core region and provide a stable environmental temperature benchmark. Step Y230 refers to obtaining the temperature difference as a three-dimensional temperature anomaly value, which can be achieved by simple arithmetic subtraction. The purpose is to quantify the degree of temperature anomaly and provide an objective basis for the extraction of warm core features.

[0045] Specifically, this invention obtains smoothed temperature grid data in step Y210, ensuring that the input data eliminates the original detection noise. Step Y220 calculates the average temperature of a ring-shaped region centered on the tropical cyclone center with an outer radius of a second preset kilometer (600 km). This region is designed to exclude the warm core region and focus only on the external ambient temperature, thus accurately anchoring the ambient temperature benchmark. Step Y230 calculates the difference between the temperature value of each grid point and this benchmark to obtain the three-dimensional temperature anomaly value, ensuring that the positive temperature anomaly truly reflects the intensity of the warm core. Overall, this invention solves the problem of arbitrary benchmark selection in temperature anomaly calculation by systematically defining the benchmark region, providing a reliable basis for extracting the warm core characteristics of tropical cyclones.

[0046] As a specific implementation method, the present invention is implemented as follows: When calculating the three-dimensional temperature anomaly, the temperature value of each grid point is first read from the smoothed temperature grid; then, an annular region with the center of the tropical cyclone as the center and an outer radius of the second preset kilometer (600km) is defined, and the average temperature of all grid points in the region is calculated; finally, the average temperature is subtracted from the temperature value of each grid point to obtain the three-dimensional temperature anomaly.

[0047] Based on the above analysis, it can be seen that the present invention solves the problem of unclear definition of temperature anomaly reference area, avoids temperature anomaly quantification distortion caused by the reference area being too small or too large, and improves the accuracy of tropical cyclone warm core identification and the reliability of subsequent intensity index calculation.

[0048] Y300, based on the aforementioned three-dimensional temperature anomaly values, uses a three-dimensional region growing method to extract the main body region of the warm core of tropical cyclones.

[0049] In one implementation, based on the three-dimensional temperature anomaly value, a three-dimensional region growing method is used to extract the main warm core region of a tropical cyclone. Step Y300 of the method provided by this invention includes:

[0050] Y310 sequentially scans the three-dimensional temperature anomaly values ​​to find unassigned grid points as seed points.

[0051] Y320 expands 26 neighboring grid points centered on the seed point. If the three-dimensional temperature anomaly value of the neighboring grid points is within a preset threshold range, then the neighboring grid points are merged with the seed point and pushed onto the stack.

[0052] Y330, remove grid points from the stack and repeat the neighborhood expansion process until the stack is empty.

[0053] Y340, repeat the scanning and expansion process until all grid points are assigned, to obtain the main body of the tropical cyclone warm core.

[0054] Specifically, this invention initiates a region growth process by sequentially scanning and locating unassigned grid points as seed points. Then, a 26-neighborhood expansion is performed centered on the seed point. Only grid points whose temperature anomalies fall within a preset threshold range are included in the warm core region and pushed onto a stack. This preset threshold range is, for example, 2K to 5K. Grid points are then removed from the stack, and expansion continues until the stack is empty, completing the extraction of a single connected region. Finally, the scanning and expansion process is repeated until all grid points are assigned a location. This process, through systematic seed point selection, strict threshold filtering, and efficient stack management, achieves robust extraction of complex temperature structures.

[0055] As a specific implementation method, the solution of the present invention is implemented as follows: When the system executes the region growing algorithm, it first performs a layer-first scan of the three-dimensional temperature anomaly values, and sets unassigned grid points as seed points after finding them; then it checks all grid points in 26 directions around the seed point. If the temperature anomaly value of a neighboring grid point is greater than a threshold, it is marked as a warm core region and added to the stack; the system continues to take grid points from the top of the stack for expansion until the stack is empty; after completing the current region, it continues to scan the remaining unassigned grid points and repeats the above process until the entire temperature field is completely divided.

[0056] In practical applications, this invention primarily utilizes a three-dimensional region growing method to extract the warm core region of tropical cyclones, thereby eliminating non-warm core centers. Then, the Marching Cubes algorithm is used to extract the isosurfaces of the three-dimensional temperature anomalies of the tropical cyclones.

[0057] 3D region growing refers to starting from a certain point and gradually adding 3D neighboring pixels according to certain criteria. Region growing terminates when certain conditions are met. The quality of region growing depends on the selection of the initial point (seed point), the growth criteria, and the termination conditions. Region growing starts from one or more grid points and eventually obtains the entire region, thereby achieving target extraction.

[0058] To put it simply, here are three rules for dividing 3D mesh points:

[0059] 1. Select one point of data as the seed point (the selection of the seed point is determined based on the vertical and horizontal distribution range of the tropical cyclone's warm core).

[0060] 2. Perform a 26-neighborhood expansion at the seed point. The criterion is: if the points in the considered neighborhood are within the specified threshold range (e.g., 2K to 5K), then the grid point is included in the 3D region where the seed point is located.

[0061] 3. Region growth stops when no more grid points meet the criteria for joining the region.

[0062] 1) Scan the 3D data sequentially to find the first unassigned grid point, and assign this grid point (x0, y0, z0);

[0063] 2) Taking (x0, y0, z0) as the center, consider the 26 neighborhood grid points (x, y, z) of (x0, y0, z0). If (x, y, z) satisfies the growth criterion, merge (x, y, z) with (x0, y0, z0) (within the same region) and push (x, y, z) onto the stack;

[0064] 3) Retrieve a grid point from the stack, treat it as (x0, y0, z0), and return to step 2);

[0065] 4) Return to step 1) when the stack is empty.

[0066] 5) Repeat steps 1)-4) until every point in the data has a home, at which point the growth ends.

[0067] Starting from the seed point, points that satisfy the growth criteria are found in its 26 neighborhoods and merged into the 3D region where the seed point is located. In the program, this is achieved by adding them to the stack. Each piece of data that is traversed is marked. Any marked element will not be considered in the next detection because it has already been assigned a region. The purpose of region growth is to separate the part that belongs to the seed point region.

[0068] Based on the above analysis, it can be seen that the present invention effectively solves the problem of regional fragmentation or mis-inclusion caused by noise interference during the extraction of the warm core main region, and significantly improves the integrity and accuracy of the extraction results.

[0069] Y400, based on the extracted warm core region of the tropical cyclone, uses the Marching Cubes algorithm to calculate isosurfaces.

[0070] In one implementation, based on the extracted warm core region of the tropical cyclone, isosurfaces are calculated using the Marching Cubes algorithm. Step Y400 of the method provided by this invention includes:

[0071] Y410 divides the warm core body region into voxel units and obtains the scalar value of each voxel vertex.

[0072] Y420, determine and mark the position of the vertex relative to the isosurface based on the scalar value.

[0073] Y430, if the voxel edge intersects with the isosurface, the coordinates of the intersection point are calculated by linear interpolation.

[0074] Y440 generates triangular patches based on voxel vertex markings, resulting in isosurfaces.

[0075] Y450 uses the central difference method to calculate the gradient vector and normalize it, and interpolates to obtain the vertex normal vector of the triangular facet.

[0076] Specifically, this invention discretizes the warm core region into voxel units and obtains vertex scalar values, establishing a basic structure adapted to meteorological data characteristics for isosurface calculation. Then, vertices are accurately marked based on the scalar values ​​to avoid topological misjudgments caused by data noise. When voxel edges intersect with the isosurface, linear interpolation is used to dynamically calculate the intersection coordinates, effectively eliminating geometric distortion caused by abrupt temperature gradient changes. Triangular facets are generated based on vertex markings to form a complete surface mesh, ensuring the logical consistency of the warm core morphology. Finally, gradient vectors are calculated and normalized using central difference, combined with interpolation to obtain accurate vertex normal vectors for the triangular facets, providing reliable optical characteristic parameters for subsequent lighting rendering. These steps are executed sequentially to form a closed-loop processing flow, with each stage closely connected to ensure the robustness and accuracy of isosurface calculation in meteorological data environments.

[0077] As a specific implementation method, the present invention is implemented as follows: Within the warm core region, the space is divided into regular cubic voxel units, and the scalar value of each voxel vertex is obtained by interpolation of adjacent temperature grid points; the vertices are marked internally and externally using a threshold comparison method, wherein the marking process is based on a preset temperature anomaly threshold; for intersecting edges, the coordinates of the intersection point are calculated linearly according to the difference in scalar values ​​of the two endpoints; triangular facets are generated by applying the Marching Cubes standard lookup table based on the vertex marking combination; the gradient is calculated using the central difference and then normalized, and the vertex normal vector of the triangular facet is obtained by bilinear interpolation.

[0078] In practical applications, after segmenting the main body of a tropical cyclone, the Marching Cubes algorithm is used to extract the isosurface of the main body. The main idea is to approximate the isosurface in a 3D data field using linear interpolation, specifically as follows: Each grid cell in the 3D data field is a voxel, and each vertex of the voxel has a corresponding scalar value. If the value at a voxel vertex is greater than or equal to the isosurface value, the vertex is defined as being outside the isosurface and marked as "0"; conversely, if the value at a voxel vertex is less than the isosurface value, the vertex is defined as being inside the isosurface and marked as "1". Since each voxel cell has 8 vertices, there are a total of 2... 8 =256 cases, as shown in Figure 4 Figure 4 These are the 15 basic cases of the Marching Cubes algorithm. The other 241 cases can be implemented by rotating, mapping, etc., these 15 basic cases.

[0079] The indexing rules for vertices and edges on each voxel unit are as follows: Figure 5 As shown (where normal numbers 0 to 11 are edge indices, and circled numbers 0 to 7 are vertex indices), if the value of vertex 3 below the voxel is less than the isosurface value, and the values ​​of all other vertices are greater than the isosurface value (e.g., ... Figure 6 As shown, whereFigure 6 The triangle formed by the dashed lines in the lower left corner is part of the isosurface. Then, a triangular facet that intersects with the voxel edges 2, 3, and 11 can be generated. The specific position of the vertex of the triangular facet needs to be calculated by linear interpolation based on the isosurface value and the values ​​of the edge vertices 3-2, 3-0, and 3-7.

[0080] For a voxel edge that intersects with an isosurface, the coordinates of the intersection point are denoted by P, where P1 and P2 represent the coordinates of the two endpoints of the edge, V1 and V2 represent the values ​​at these two endpoints, and V represents the isosurface value. The formula for calculating the coordinates of the intersection point is as follows:

[0081] P=P1+(V–V1)·(P2–P1) / (V2–V1) (3);

[0082] The first step of the algorithm is to determine which edge of the isosurface intersects with the voxel cell. Figure 5 and Figure 6 As shown in the example, only vertex 3 is marked as "1" and the other vertices are marked as "0", which means that the edges 2, 3, and 11 of the voxel unit intersect with the isosurface. Then, the position of each intersection point is calculated by linear interpolation.

[0083] Algorithm step two: still Figure 5 and Figure 6 As shown in the example, this vertex state can generate a triangular facet (3,11,2), which means that the three vertices of the triangular facet are the intersection points of the edges 3, 11, 2 and the isosurface.

[0084] After the above steps, the point and surface information of the isosurface can be obtained. To further improve the display effect, the vertex normals need to be adjusted. Assuming the value at vertex (i,j,k) is f(i,j,k), the gradient vector G at that point can be calculated using the central difference method. Normalizing G yields the unit normal vector at vertex (i,j,k), and then linear interpolation of the normal vectors of the eight vertices on the voxel unit can obtain the display normal vectors of each vertex of the triangular facet.

[0085] Based on the above analysis, it can be seen that the present invention effectively avoids geometric distortion and topological errors of isosurface caused by temperature field discontinuity or noise interference, and significantly improves the realism of the three-dimensional visualization structure of the warm core of tropical cyclones and the reliability of the analysis of warm core intensity index.

[0086] Y500, based on the isosurface, uses a lighting model to render the three-dimensional visualization structure of the warm core of a tropical cyclone.

[0087] In one implementation, a lighting model is used to render the three-dimensional visualization structure of the warm core of a tropical cyclone based on the isosurface. The method step Y500 provided by this invention includes:

[0088] Y510, obtain the point and surface information and vertex normal vectors of the isosurface.

[0089] Y520 uses a diffuse reflection illumination model to calculate the reflected light intensity, wherein the reflected light intensity is determined based on the cosine values ​​of the incident light intensity, the incident direction, and the surface normal.

[0090] Y530, based on the calculated reflected light intensity, renders the isosurface to obtain the three-dimensional visualization structure of the tropical cyclone warm core.

[0091] Specifically, step Y510 refers to acquiring the geometric topology data and surface orientation information of the isosurface, which can be achieved using the vertex coordinate index list and normal vector array output from the Marching Cubes algorithm. The purpose is to provide an accurate surface geometric description basis for lighting calculations. Step Y520 can be understood as a physically based light scattering model, which can be implemented using Lambert's law combined with an ambient light compensation mechanism. Its purpose is to eliminate false highlights caused by specular reflection and make the gradual changes in temperature anomalies smoothly presented in visualization. Step Y530 is specifically the process of mapping the reflected light intensity to the isosurface geometry, for example, through the fragment shader program of the graphics processing unit. Its purpose is to generate a three-dimensional visualization result with depth and realism, making it easier to identify the morphological features of the warm core.

[0092] Specifically, the present invention ensures accurate representation of surface curvature changes by obtaining point and surface information and vertex normal vectors in step Y510; step Y520 calculates diffuse reflection intensity based on the incident direction and normal cosine value, adapting to the continuous characteristics of the temperature field and avoiding detail distortion caused by specular reflection; and step Y530 directly applies the calculated reflected light intensity to isosurface rendering, making the three-dimensional structure realistic, thereby highlighting the vertical extension range and horizontal morphological characteristics of the warm core main area, forming a complete temperature gradient visualization chain.

[0093] As a specific implementation method, the present invention is implemented as follows: In the rendering system, step Y510 extracts the vertex normal vector array from the isosurface data generated by the Marching Cubes algorithm; step Y520 calculates the reflected light intensity using the diffuse reflection model in the standard graphics library, wherein the incident light direction is set to a fixed azimuth angle; and step Y530 maps the reflected light intensity value onto the isosurface mesh through the OpenGL shader program to generate a three-dimensional visualization structure of the tropical cyclone warm core.

[0094] In practical applications, to better demonstrate the three-dimensional temperature structure of the warm core of a tropical cyclone, a diffuse reflection lighting model is chosen to render the extracted isosurfaces. The lighting model used in this invention is based on the Lambert lighting model. The Lambert lighting model assumes that the intensity of diffuse light approximately obeys Lambert's law, that is, the intensity of diffuse light depends only on the direction of the incident light and the surface normal at the reflection point. The angle is proportional to the cosine of the included angle:

[0095] ;

[0096] in, The intensity of reflected light. The intensity of the incident light ray (direction such as...) Figure 6 (as shown) For the incident ray and the normal to the vertex The cosine of; therefore, the final mathematical expression is: .

[0097] Based on the above analysis, it can be seen that the present invention effectively avoids the problems of high light interference and detail blurring, and truly restores the three-dimensional morphology and temperature gradient change characteristics of the warm core, which facilitates the accurate analysis of the overall temperature structure characteristics of tropical cyclones.

[0098] Y600 is used to calculate the intensity index of the tropical cyclone warm core based on the three-dimensional temperature anomaly values ​​of the main body of the tropical cyclone warm core.

[0099] In one implementation, the tropical cyclone warm core intensity index includes one or more of the following:

[0100] Intensity characteristics: The temperature values ​​of each pressure layer are obtained from the three-dimensional temperature anomalies, and their maximum values ​​are calculated;

[0101] Vertical structure: Determine the air pressure at which the temperature value reaches the maximum value as the height apex, and calculate the thickness from the lowest air pressure to the height apex;

[0102] Gradient: The horizontal temperature difference between each pressure layer is calculated as the horizontal gradient, and the vertical temperature difference between adjacent pressure layers is calculated as the vertical gradient.

[0103] Horizontal shape: Calculate the total area of ​​the positive temperature range from the grid points and the distance between the outer rings as the perimeter;

[0104] Volume characteristics: The volume of the main body of the tropical cyclone warm core is calculated based on the three-dimensional grid markers of the main body of the tropical cyclone warm core.

[0105] Among them, intensity characteristics refer to the core indicators for quantifying the thermal intensity of the warm core. This can be achieved by traversing temperature data from various pressure layers and calculating statistical values. The aim is to identify the location of peak intensity and reflect the uniformity of the overall thermal distribution of the warm core, avoiding the one-sidedness of assessments caused by relying solely on a single extreme value. Vertical structure can be understood as parameters describing the vertical extension characteristics of the warm core. It can be achieved by locating the height peak based on the maximum temperature anomaly and calculating the thickness through pressure differences. The aim is to accurately capture the changes in the vertical center of the warm core and quantify the vertical extension range, providing a basis for identifying the maturity of the warm core's development. Gradient specifically refers to indicators characterizing the sharpness of the warm core's boundaries and its thermal stability. This can be achieved by utilizing horizontal temperature differences and vertical... The horizontal temperature difference is calculated separately for the horizontal and vertical gradients, aiming to reveal the boundary characteristics of the warm core in the horizontal direction and the thermal dynamic evolution process in the vertical direction. The horizontal morphology refers to the quantitative characteristics of the horizontal coverage and shape regularity of the warm core, which can be achieved by defining the area by statistically counting the number of positive temperature anomalies in the grid and calculating the perimeter of the outer contour, aiming to provide an intuitive representation of the spatial morphology of the warm core and reflect the horizontal diffusion trend. The volumetric characteristics refer to the indicators that comprehensively reflect the three-dimensional scale of the warm core, which can be achieved by calculating the volume based on the three-dimensional grid markers through spatial integration methods, aiming to integrate vertical and horizontal dimensional information and more comprehensively indicate the intrinsic relationship between the overall changes of the warm core and the evolution of tropical cyclone intensity.

[0106] Specifically, this invention systematically quantifies the structural characteristics of the warm core by constructing a multi-dimensional index system encompassing intensity features, vertical structure, gradient, horizontal morphology, and volumetric features. Intensity features extract the maximum temperature values ​​of each pressure layer from the aforementioned three-dimensional temperature anomalies. Since the three-dimensional temperature anomalies have eliminated the influence of background circulation, this ensures that the temperature values ​​focus on the anomalous thermodynamic characteristics of the warm core. Vertical structure, based on the three-dimensional temperature anomalies, locates the highest point and calculates the thickness, quantifying the vertical extension range of the warm core and directly indicating the correlation between the warm core's height and the intensification stage of the tropical cyclone. Gradients calculate the horizontal temperature difference between each pressure layer and the vertical temperature difference between adjacent pressure layers, revealing the sharpness of the warm core's boundary in the horizontal direction and its thermodynamic stability in the vertical direction, jointly characterizing the dynamic evolution of the warm core's structure. Horizontal morphology defines the area by summing the positive temperature anomaly grid points and calculates the perimeter by connecting the outer rings, describing the regularity and diffusion trend of the warm core's horizontal shape. Volumetric features calculate the volume based on the three-dimensional grid markers of the main body of the tropical cyclone warm core, integrating spatial information and realizing the quantification of the warm core's scale in three-dimensional space. These indicators complement each other, forming a complete representation system from local to overall and from static to dynamic, solving the problem that a single indicator cannot fully capture the evolution of the temperature structure of tropical cyclones.

[0107] As a specific implementation method, the present invention is implemented as follows: After the main body of the tropical cyclone warm core is determined, temperature data of each pressure layer from the lower to the upper layers are first extracted from the above three-dimensional temperature anomaly values, and the maximum value of the temperature anomaly on each pressure layer is calculated as the intensity feature; then, the pressure layer where the temperature anomaly reaches the maximum value is determined as the height peak, and the pressure difference from the lowest pressure layer to the height peak is calculated as the thickness; next, the average temperature difference between adjacent grid points in the horizontal direction within each pressure layer is calculated as the horizontal gradient, and the temperature difference between grid points at the same position between adjacent pressure layers is calculated as the vertical gradient; at the same time, the total number of positive temperature anomaly grid points is counted as the area, and the perimeter is calculated by connecting the outer positive temperature anomaly grid points to form a closed loop; finally, based on the three-dimensional grid point identification of the main body of the warm core, the total volume is calculated by accumulating the volume units of each grid point.

[0108] In practical applications, the intensity of the tropical cyclone's warm core is calculated based on the three-dimensional temperature data of the main tropical cyclone region obtained above.

[0109] 1. Calculate the three-dimensional gradient of the warm core of a tropical cyclone. The calculation principle for each layer of the warm core horizontal gradient is:

[0110] (4);

[0111] in, This represents the warm core temperature difference in the horizontal direction at each atmospheric pressure level. For the horizontal position and height of the layer temperature, For the horizontal position and height of the layer temperature difference, Between 300 km and 700 km from the center of a tropical cyclone The average temperature of the layer For the first Stratified pressure height, , The number of all pressure levels containing warm and inviting atmospheres. These are indices for the longitude, latitude, and perpendicular directions, respectively. The location of the meridional grid point. This represents the position of the latitudinal grid point.

[0112] 2. Calculate the maximum warm core value of a tropical cyclone. Calculate the maximum warm core value at each pressure level within the inner region of a tropical cyclone:

[0113] (5);

[0114] in, This represents the maximum temperature anomaly on this layer. for Temperature anomaly at point These are indices for the longitude, latitude, and perpendicular directions, respectively. The location of the meridional grid point. The position of the latitudinal grid point. For the first Layer pressure height.

[0115] 3. The maximum altitude of the warm core of a tropical cyclone. Calculate the altitude at which the warm core of a tropical cyclone reaches its maximum pressure:

[0116] (6);

[0117] in, It represents the maximum height that warmth can reach (an abbreviation of the top height of warm core). For the first Stratified pressure height, , It is the number of all atmospheric pressure levels containing the warm feeling.

[0118] 4. Tropical cyclone warm core thickness. Calculate the distance between the lowest pressure altitude of the tropical cyclone's warm core and the top of the warm core altitude:

[0119] (7);

[0120] in, This represents the lowest level of the warm core (an abbreviation for the bottom height of the warm core). For the first Stratified pressure height, , It is the number of all atmospheric pressure levels containing the warm feeling.

[0121] (8);

[0122] in, The thickness is heartwarming (km). This represents the conversion of the maximum altitude and lowest atmospheric pressure (hPa) reached by the heart-warming message into altitude values ​​in kilometers. This represents the highest level of warmth that can be achieved. It represents the lowest level of warmth and comfort.

[0123] 5. Heartwarming vertical gradient:

[0124] (9);

[0125] in, This represents the warm core temperature difference in the vertical direction of the air pressure layer. For the first Stratified pressure height, For the first Stratified pressure height, for and temperature difference, for The temperature of the layer for The temperature of the layer , This refers to the number of all atmospheric pressure levels containing the warm-hearted atmosphere.

[0126] 6. Number of warm core pixels in tropical regions: Calculate the total number of warm core pixels in each pressure level.

[0127] (10)

[0128] in, This represents the sum of all pixels with positive temperature anomalies at each atmospheric pressure level. This represents the total number of pixels in this layer. For the horizontal position and height of the layer temperature, The position of a point in three-dimensional space. The location of the meridional grid point. The position of the latitudinal grid point. For the first Layer pressure height.

[0129] 7. Tropical Warm Core Area: Calculates the total area of ​​all warm core pixels at each pressure level.

[0130] (11);

[0131] in, This represents the total area of ​​all pixels with positive temperature anomalies at each atmospheric pressure level. This represents the total number of pixels in this layer. The area of ​​each pixel, The position of a point in three-dimensional space. The location of the meridional grid point. The position of the latitudinal grid point. For the first Layer pressure height.

[0132] 8. Perimeter of the heart-warming ring: Calculate the line connecting the outermost ring around the heart.

[0133] (12);

[0134] in, This indicates the circumference of the heartwarming ring. , These represent two adjacent points on the heartwarming ring. and latitude, , These represent two adjacent points on the heartwarming ring. and longitude, This is the Earth's radius (a constant).

[0135] 9. Warm Core Volume: The warm core volume refers to the sum of the volumes corresponding to all warm core grid points within a 3D warm core region. Warm core regions are typically obtained through 3D region growing, thresholding, or connected component extraction.

[0136] Let the coordinates of the three-dimensional grid points be...

[0137] ;

[0138] in, These are indices for the longitude, latitude, and perpendicular directions, respectively. These are the longitudinal, latitudinal, and vertical directions, respectively.

[0139] If the grid point belongs to the warm core region, then its volume contribution is:

[0140] (13);

[0141] in, The volume of each grid cell, and This refers to the horizontal grid spacing (if the latitude and longitude grids are not uniform, it should be converted to spherical distance). The thickness of the vertical layer (which can be calculated from the pressure layer or the difference in geometric height).

[0142] The total volume of the warm core is:

[0143] (14);

[0144] in, The total volume of the warm core region. To sum the volume values ​​of all grid cells within the warm core region, The volume of each grid cell.

[0145] Example 2, Figure 2 This is a schematic diagram of a tropical cyclone temperature body structure calculation system according to Embodiment 2 of the present invention, as shown below. Figure 2As shown in Embodiment 2, a tropical cyclone temperature body structure calculation system is provided, including: a temperature grid forming module 201, a three-dimensional temperature anomaly calculation module 202, a tropical cyclone warm core main body region extraction module 203, an isosurface calculation module 204, a three-dimensional visualization structure drawing module 205, and a tropical cyclone warm core intensity index calculation module 206. The temperature grid forming module 201 is used to smooth the three-dimensional temperature data of the tropical cyclone region based on satellite microwave sounding data and tropical cyclone location information, forming a temperature grid with the tropical cyclone center as the origin. The three-dimensional temperature anomaly calculation module 202 is used to calculate the three-dimensional temperature anomaly value based on the smoothed temperature grid. The tropical cyclone warm core main body region extraction module 203 is used to extract the tropical cyclone warm core main body region based on the three-dimensional temperature anomaly value using a three-dimensional region growing method. The isosurface calculation module 204 is used to calculate the isosurface based on the extracted tropical cyclone warm core main body region using the MarchingCubes algorithm. The 3D visualization structure drawing module 205 is used to draw the 3D visualization structure of the tropical cyclone warm core using a lighting model based on the isosurface. The tropical cyclone warm core intensity index calculation module 206 is used to calculate the tropical cyclone warm core intensity index based on the 3D temperature anomaly value of the main region of the tropical cyclone warm core.

[0146] In this embodiment, the temperature grid forming module 201 includes a first acquisition unit, an interpolation unit, and a first obtaining unit. The first acquisition unit acquires temperature data of each pressure layer and tropical cyclone location information from the satellite microwave sounding data. The interpolation unit interpolates the temperature data into a radial grid with the tropical cyclone center as the initial position and a spatial resolution set to a first preset kilometer, based on the tropical cyclone location information. The first obtaining unit smooths the interpolated temperature data using a Gaussian weighting function to obtain a uniformly spaced temperature grid, wherein the Gaussian weighting function determines the weights based on the distance from the scanning point to the tropical cyclone center.

[0147] In this embodiment, the three-dimensional temperature anomaly calculation module 202 includes: a second acquisition unit, a first calculation unit, and a second acquisition unit. The second acquisition unit is used to acquire the temperature values ​​of each grid point from the smoothed temperature grid. The first calculation unit is used to calculate the average temperature value of the surrounding area, wherein the surrounding area is a ring-shaped area centered on the center of the tropical cyclone with an outer radius of a second preset kilometer. The second acquisition unit is used to acquire the difference between the temperature values ​​of each grid point and the average temperature value as the three-dimensional temperature anomaly value.

[0148] In this embodiment, the tropical cyclone warm core main region extraction module 203 includes: a scanning unit, an expansion unit, a repeating unit, and a second obtaining unit. The scanning unit sequentially scans the three-dimensional temperature anomaly values ​​to find unassigned grid points as seed points. The expansion unit expands 26 neighboring grid points centered on the seed point. If the three-dimensional temperature anomaly value of the neighboring grid points is within a preset threshold range, the neighboring grid points are merged with the seed point and pushed onto a stack. The repeating unit removes grid points from the stack and repeats the neighbor expansion process until the stack is empty. The second obtaining unit repeats the scanning and expansion process until all grid points are assigned, thus obtaining the tropical cyclone warm core main region.

[0149] In this embodiment, the isosurface calculation module 204 includes: a third acquisition unit, a judgment unit, a second calculation unit, a third obtaining unit, and a fourth obtaining unit. The third acquisition unit is used to divide the warm core body region into voxel units and acquire the scalar value of each voxel vertex. The judgment unit is used to determine and mark the position of the vertex relative to the isosurface based on the scalar value. The second calculation unit is used to calculate the intersection point coordinates by linear interpolation if a voxel edge intersects the isosurface. The third obtaining unit is used to generate triangular facets based on the voxel vertex markings to obtain the isosurface. The fourth obtaining unit is used to calculate and normalize the gradient vector using the central difference method, and interpolate to obtain the vertex normal vectors of the triangular facets.

[0150] In this embodiment, the 3D visualization structure rendering module 205 includes a fourth acquisition unit, a third calculation unit, and a fifth obtaining unit. The fourth acquisition unit is used to acquire the point and surface information and vertex normal vectors of the isosurface. The third calculation unit is used to calculate the reflected light intensity using a diffuse reflection lighting model, wherein the reflected light intensity is determined based on the cosine value of the incident light intensity, the incident direction, and the surface normal. The fifth obtaining unit is used to render the isosurface based on the calculated reflected light intensity to obtain the 3D visualization structure of the tropical cyclone's warm core.

[0151] In this embodiment, the tropical cyclone warm core intensity index includes one or more of the following: Intensity characteristics: Obtain the temperature values ​​of each pressure layer from the three-dimensional temperature anomaly values ​​and calculate their maximum values. Vertical structure: Determine the pressure at which the temperature value reaches the maximum value as the altitude apex, and calculate the thickness from the lowest pressure to the altitude apex. Gradient: Calculate the horizontal temperature difference between each pressure layer as the horizontal gradient, and calculate the vertical temperature difference between adjacent pressure layers as the vertical gradient. Horizontal morphology: Calculate the sum of the positive temperature anomaly grid points as the area, and calculate the distance between the lines connecting the outer rings as the perimeter. Volume characteristics: Calculate the volume of the tropical cyclone warm core main region based on the three-dimensional grid point identifiers of the tropical cyclone warm core main region.

[0152] The various variations and specific examples of the tropical cyclone temperature body structure calculation method provided in Example 1 are also applicable to the tropical cyclone temperature body structure calculation system provided in this example. Through the foregoing detailed description of a tropical cyclone temperature body structure calculation method, those skilled in the art can clearly understand the implementation method of the tropical cyclone temperature body structure calculation system in this example. Therefore, for the sake of brevity, it will not be described in detail here.

[0153] Example 3, Figure 3 This is a schematic diagram of the structure of an electronic device according to Embodiment 3 of the present invention, as shown below. Figure 3 As shown, Embodiment 3 also provides an electronic device 300, which may include a processor 301 and a memory 302.

[0154] Memory 302 is used to store programs. Memory 302 may include volatile memory, such as random-access memory (RAM), such as static random-access memory (SRAM), double data rate synchronous dynamic random-access memory (DDR SDRAM), etc.; memory may also include non-volatile memory, such as flash memory. Memory 302 is used to store computer programs (such as application programs, functional modules, etc. that implement the above methods), computer instructions, etc. The computer programs, computer instructions, etc., can be partitioned and stored in one or more memories 302. Furthermore, the computer programs, computer instructions, data, etc., can be accessed by processor 301.

[0155] The aforementioned computer programs and instructions can be stored in one or more partitions of memory 302. Furthermore, the aforementioned computer programs and instructions can be invoked by processor 301.

[0156] The processor 301 is configured to execute the computer program stored in the memory 302 to implement the various steps in the methods described in the above embodiments.

[0157] For details, please refer to the relevant descriptions in the preceding method embodiments.

[0158] The processor 301 and the memory 302 can be independent structures or integrated structures. When the processor 301 and the memory 302 are independent structures, the memory 302 and the processor 301 can be coupled together via bus 303.

[0159] The electronic device in this embodiment can execute the technical solution in the above method. Its specific implementation process and technical principle are the same, and will not be repeated here.

[0160] Example 4: Example 4 also provides a computer-readable storage medium including a computer program and instructions, which, when run on a computer, cause the computer to execute the tropical cyclone temperature body structure calculation method of any embodiment of the present invention.

[0161] Computer-readable storage media include various media that can store program code, such as USB flash drives, external hard drives, ROM, RAM, magnetic disks, or optical disks.

[0162] This embodiment also provides a computer program product, which includes: a computer program stored in a readable storage medium, at least one processor of an electronic device can read the computer program from the readable storage medium, and the at least one processor executes the computer program to cause the electronic device to perform the solution provided in any of the above embodiments.

[0163] It should be understood that the various forms of processes shown above can be used to rearrange, add, or delete steps. For example, the steps described in this invention disclosure can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution disclosed in this invention can be achieved, and this is not limited herein.

[0164] Note that the above description is merely a preferred embodiment of the present invention and the technical principles employed. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and various obvious changes, readjustments, and substitutions can be made without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in detail through the above embodiments, the present invention is not limited to the above embodiments, and may include many other equivalent embodiments without departing from the concept of the present invention, the scope of which is determined by the scope of the appended claims.

Claims

1. A method for calculating the temperature body structure of a tropical cyclone, characterized in that, include: Based on satellite microwave detection data and tropical cyclone location information, the three-dimensional temperature data of the tropical cyclone region is smoothed to form a temperature grid with the center of the tropical cyclone as the origin. Calculate the three-dimensional temperature anomaly based on the smoothed temperature grid; Based on the aforementioned three-dimensional temperature anomaly values, the warm core region of tropical cyclones is extracted using a three-dimensional region growing method. Based on the extracted warm core region of the tropical cyclone, isosurfaces are calculated using the Marching Cubes algorithm; Based on the isosurface, a lighting model is used to render the three-dimensional visualization structure of the warm core of the tropical cyclone. The intensity index of the tropical cyclone warm core is calculated based on the three-dimensional temperature anomaly values ​​of the main body region of the tropical cyclone warm core. The process of smoothing the three-dimensional temperature data of the tropical cyclone region based on satellite microwave detection data and tropical cyclone location information to form a temperature grid with the tropical cyclone center as the origin includes: Acquire temperature data of each pressure layer and tropical cyclone location information from the satellite microwave sounding data; Based on the tropical cyclone location information, the temperature data is interpolated onto a radial grid with the tropical cyclone center as the initial position and a spatial resolution set to a first preset kilometer. The interpolated temperature data is smoothed using a Gaussian weighting function to obtain a uniformly spaced temperature grid. The Gaussian weighting function determines the weights based on the distance from the scanning point to the center of the tropical cyclone. The extraction of the warm core region of tropical cyclones using a three-dimensional region growing method based on three-dimensional temperature anomalies includes: The three-dimensional temperature anomaly values ​​are scanned sequentially to find unassigned grid points as seed points; Expand 26 neighboring grid points with the seed point as the center. If the three-dimensional temperature anomaly value of the neighboring grid points is within the preset threshold range, then merge the neighboring grid points with the seed point and push them onto the stack. Remove grid points from the stack and repeat the neighborhood expansion process until the stack is empty; The scanning and expansion process is repeated until all grid points are assigned, thus obtaining the main body of the tropical cyclone warm core.

2. The method for calculating the temperature body structure of a tropical cyclone as described in claim 1, characterized in that, The calculation of the three-dimensional temperature anomaly value based on the smoothed temperature grid includes: The temperature values ​​of each grid point are obtained from the smoothed temperature grid. Calculate the average temperature value of the surrounding area, wherein the surrounding area is a ring-shaped area with the center of the tropical cyclone as the center and an outer radius of a second preset kilometer; The difference between the temperature value of each grid point and the average temperature value is obtained as the three-dimensional temperature anomaly value.

3. The method for calculating the temperature body structure of a tropical cyclone as described in claim 1, characterized in that, The calculation of isosurfaces based on the extracted warm core region of the tropical cyclone, using the Marching Cubes algorithm, includes: The warm core region is divided into voxel units, and the scalar value of each voxel vertex is obtained; Determine and mark the position of the vertex relative to the isosurface based on the scalar value; If a voxel edge intersects with an isosurface, the coordinates of the intersection point are calculated using linear interpolation. Triangular facets are generated based on voxel vertex markings to obtain isosurfaces; The gradient vector is calculated and normalized using the central difference method, and the interpolation yields the vertex normal vector of the triangular facet.

4. The method for calculating the temperature body structure of a tropical cyclone as described in claim 1, characterized in that, The step of rendering the three-dimensional visualization structure of the warm core of a tropical cyclone using a lighting model based on isosurfaces includes: Obtain the point and surface information and vertex normal vectors of the isosurface; The reflected light intensity is calculated using a diffuse reflection illumination model, wherein the reflected light intensity is determined based on the cosine values ​​of the incident light intensity, the incident direction, and the surface normal. The isosurface is rendered based on the calculated reflected light intensity to obtain a three-dimensional visualization structure of the tropical cyclone's warm core.

5. The method for calculating the temperature body structure of a tropical cyclone as described in claim 1, characterized in that, The tropical cyclone warm core intensity index includes one or more of the following: Intensity characteristics: The temperature values ​​of each pressure layer are obtained from the three-dimensional temperature anomalies, and their maximum values ​​are calculated; Vertical structure: Determine the air pressure at which the temperature value reaches the maximum value as the height apex, and calculate the thickness from the lowest air pressure to the height apex; Gradient: The horizontal temperature difference between each pressure layer is calculated as the horizontal gradient, and the vertical temperature difference between adjacent pressure layers is calculated as the vertical gradient. Horizontal shape: Calculate the total area of ​​the positive temperature range from the grid points and the distance between the outer rings as the perimeter; Volume characteristics: The volume of the main body of the tropical cyclone warm core is calculated based on the three-dimensional grid markers of the main body of the tropical cyclone warm core.

6. A tropical cyclone temperature body structure calculation system, based on the tropical cyclone temperature body structure calculation method as described in any one of claims 1-5, characterized in that, The tropical cyclone temperature body structure calculation system includes: The temperature grid forming module is used to smooth the three-dimensional temperature data of the tropical cyclone region based on satellite microwave detection data and tropical cyclone location information, and form a temperature grid with the center of the tropical cyclone as the origin. The three-dimensional temperature anomaly calculation module is used to calculate the three-dimensional temperature anomaly based on the smoothed temperature grid. The tropical cyclone warm core main region extraction module is used to extract the tropical cyclone warm core main region based on the three-dimensional temperature anomaly value using a three-dimensional region growth method; The isosurface calculation module is used to calculate isosurfaces based on the extracted warm core region of the tropical cyclone using the Marching Cubes algorithm; The three-dimensional visualization structure drawing module is used to draw the three-dimensional visualization structure of the warm core of the tropical cyclone by using a lighting model based on the isosurface. The tropical cyclone warm core intensity index calculation module is used to calculate the tropical cyclone warm core intensity index based on the three-dimensional temperature anomaly value of the main body region of the tropical cyclone warm core.

7. An electronic device, characterized in that, include: At least one processor; as well as A memory that is communicatively connected to the at least one processor; The memory stores instructions that can be executed by the at least one processor, which are executed by the at least one processor to enable the at least one processor to perform the tropical cyclone temperature body structure calculation method according to any one of claims 1-5.

8. A computer-readable storage medium, characterized in that, It includes computer programs and instructions that, when the computer program or the instructions are run on a computer, cause the computer to perform the tropical cyclone temperature body structure calculation method as described in any one of claims 1-5.

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