Wave prediction method and system based on typhoon path angle and partition structure
By using a wave prediction method based on typhoon path angle and zonal structure, combined with models of high-energy eyewall region and low-energy peripheral region, the problem of low prediction accuracy in existing technologies is solved, achieving efficient and accurate prediction of typhoon waves, adapting to climate change, and supporting marine disaster prevention and mitigation.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-11-05
- Publication Date
- 2026-03-31
AI Technical Summary
Existing wave prediction models are based on the assumption of uniform and steady-state wind fields, which makes it difficult to accurately characterize the transient energy injection process of complex vortex systems in typhoons. Moreover, most studies are based on limited cases or short-term data, which has poor universality and cannot adapt to the interdecadal evolution of typhoon wind-wave relationships, resulting in low prediction accuracy.
A wave prediction method based on typhoon path angle and zonal structure is adopted. By receiving the path angle data of the target typhoon and the ocean zonal structure data, a prediction model is constructed using a nonlinear wind and wave prediction model in the high-energy zone of the eyewall and a linear wind and wave prediction model in the low-energy zone of the periphery, combined with historical typhoon meteorological data and wave data, so as to achieve accurate prediction of typhoon waves.
It significantly improves the ability to predict extreme typhoon waves, enhances prediction accuracy, adapts to long-term climate evolution, and provides reliable technical support for marine disaster prevention and mitigation.
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Figure CN121766493A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of meteorological disaster forecasting technology, specifically a wave prediction method and system based on typhoon path angle and zonal structure. Background Technology
[0002] Typhoons are powerful weather systems that generate extreme waves that seriously threaten marine activities and coastal safety. Accurate typhoon wave forecasting is crucial for disaster early warning and engineering disaster prevention.
[0003] Most existing wave prediction models are based on the assumption of uniform, steady-state wind fields, making it difficult to accurately characterize the transient energy injection process of typhoons, a complex vortex system. Furthermore, most studies are based on limited individual cases or short-term data, resulting in models with poor generalizability that fail to systematically reflect the variability in wind-wave relationships among different typhoons. More importantly, typhoon wind-wave relationships are not static but exhibit significant interdecadal evolution. Using a single, fixed prediction model introduces systematic biases and cannot adapt to the long-term climate change context. Therefore, a wave prediction method that can adapt to long-term climate evolution patterns is needed. Summary of the Invention
[0004] To address the shortcomings mentioned in the background art, the present invention aims to provide a wave prediction method and system based on typhoon path angle and zonal structure.
[0005] Firstly, the objective of this invention can be achieved through the following technical solution: a wave prediction method based on typhoon path angle and zonal structure, the method comprising the following steps: Receive target typhoon path angle data and ocean partition structure data. The target typhoon path angle data includes the latitude and longitude coordinate sequence of the typhoon center and the angle between the typhoon's direction of movement and the reference direction. The ocean partition has a predefined spatial range and a corresponding partition identifier. Based on the partition identifier, the ocean partition is distinguished into an eyewall high-energy region and an outer low-energy region. The latitude and longitude coordinate sequence of the typhoon center is matched with the predefined spatial range of the ocean zoning structure data to determine the zoning identifier of the target typhoon. The path angle data of the target typhoon and the zoning identifier of the target typhoon are input into the pre-established wave prediction model to output the wave prediction results. The pre-established wave prediction model is constructed based on historical typhoon meteorological data and wave data, including a nonlinear wind and wave prediction model for the high-energy region of the eyewall and a linear wind and wave prediction model for the low-energy region of the periphery.
[0006] In conjunction with the first aspect, in some implementations of the first aspect, the method further includes: the division of the high-energy region of the eyewall and the low-energy region of the periphery is based on the relative radius with the typhoon center as the origin.
[0007] In conjunction with the first aspect, in some implementations of the first aspect, the method further includes: calculating the angle between the typhoon's movement direction and the reference direction based on the latitude and longitude coordinate sequence of the typhoon center, calculating the movement direction through vector difference, and obtaining the angle between the movement direction and the preset reference direction, wherein the preset reference direction is due north. In conjunction with the first aspect, in some implementations of the first aspect, the method further includes: the angle between the typhoon's movement direction and the reference direction divides the target typhoon into east-west or north-south oriented typhoons.
[0008] In conjunction with the first aspect, in some implementations of the first aspect, the method further includes: the process of classifying typhoons in an east-west or north-south direction, including: The angle θ between the typhoon's direction of movement and the reference direction is 0° in the due east direction and increases to 360° in the counterclockwise direction; the path direction is classified as follows: when 45°≤θ<135°, it is defined as north-south; otherwise, it is defined as east-west.
[0009] In conjunction with the first aspect, in some implementations of the first aspect, the method further includes: the nonlinear wind and wave prediction model of the high-energy region of the eyewall is a quadratic polynomial model, and the linear wind and wave prediction model of the peripheral low-energy region is a linear function model.
[0010] In conjunction with the first aspect, in some implementations of the first aspect, the method further includes: the historical typhoon meteorological data includes wind speed, significant wave height and maximum wave height; through a preprocessing process, including unifying the wind field and wave field data to the same grid resolution through spatial interpolation, and identifying grid point data that intersect with the typhoon path trajectory as typhoon weather data.
[0011] Secondly, in order to achieve the above objectives, this invention discloses a wave prediction system based on typhoon path angle and zonal structure, comprising: The data receiving module is used to receive the path angle data and ocean partition structure data of the target typhoon. The path angle data of the target typhoon includes the latitude and longitude coordinate sequence of the typhoon center and the angle between the typhoon's movement direction and the reference direction. The ocean partition has a predefined spatial range and a corresponding partition identifier. Based on the partition identifier, the ocean partition includes the eyewall high-energy region and the peripheral low-energy region. The wave prediction module is used to match the latitude and longitude coordinate sequence of the typhoon center with the predefined spatial range of the ocean zoning structure data to determine the zoning identifier of the target typhoon. The target typhoon's path angle data and zoning identifier are input into the pre-established wave prediction model, and the wave prediction results are output. The pre-established wave prediction model is constructed based on historical typhoon meteorological data and wave data, including a nonlinear wind and wave prediction model for the high-energy region of the eyewall and a linear wind and wave prediction model for the low-energy region of the periphery.
[0012] In another aspect of the present invention, in order to achieve the above-mentioned objective, a terminal device is disclosed, including a memory, a processor, and a computer program stored in the memory and capable of running on the processor. The memory stores the computer program capable of running on the processor. When the processor loads and executes the computer program, it employs the wave prediction method based on typhoon path angle and zonal structure as described above.
[0013] In another aspect of the present invention, in order to achieve the above objectives, a computer-readable storage medium is disclosed, wherein a computer program is stored in the computer-readable storage medium, and when the computer program is loaded and executed by a processor, it employs the wave prediction method based on typhoon path angle and zonal structure as described above.
[0014] The beneficial effects of this invention are: This invention employs a model library and path selector architecture, which effectively solves the problems of poor adaptability and low prediction accuracy of traditional single models under the conditions of complex typhoon structure and interdecadal evolution of wind and wave relationships. It significantly improves the prediction capability of extreme typhoon waves and provides reliable technical support for marine disaster prevention and mitigation and engineering safety. Attached Figure Description
[0015] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort. Figure 1 This is a schematic diagram of the method flow of the present invention; Figure 2 This is a schematic diagram of the overall process framework of the present invention; Figure 3 This is a schematic diagram illustrating the construction results of the historical prediction maximum wave height model library of this invention; Figure 4 This is a schematic diagram of typhoon path statistical analysis according to the present invention; Figure 5 This is an error analysis diagram of the predicted and true maximum wave height under the influence of Typhoons Hagel and Fitow. Figure 6 This is a schematic diagram of the system structure of the present invention. Detailed Implementation
[0016] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. 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 are within the scope of protection of the present invention.
[0017] Example 1: like Figure 1 As shown, a wave prediction method based on typhoon path angle and zonal structure includes the following steps: S101: Receive the path angle data and ocean partition structure data of the target typhoon. The path angle data of the target typhoon includes the latitude and longitude coordinate sequence of the typhoon center and the angle between the typhoon's movement direction and the reference direction. The ocean partition has a predefined spatial range and a corresponding partition identifier. Based on the partition identifier, the ocean partition includes the eyewall high-energy region and the peripheral low-energy region. The angle between the typhoon's direction of movement and the reference direction is calculated based on the latitude and longitude coordinate sequence of the typhoon's center. The direction of movement is calculated by vector difference, and the angle between the direction of movement and the preset reference direction is obtained. The preset reference direction is due east.
[0018] The angle between the typhoon's direction of movement and the reference direction classifies a target typhoon as either east-west or north-south oriented.
[0019] The process of classifying typhoons by east-west or north-south orientation includes: The angle θ between the typhoon's direction of movement and the reference direction is 0° in the due east direction and increases to 360° in the counterclockwise direction; the path direction is classified as follows: when 45°≤θ<135°, it is defined as north-south; otherwise, it is defined as east-west.
[0020] Specifically, the data source selection and download are as follows: Data for 51 years, from 1970 to 2020, was downloaded from the ERA5 reanalysis database of the Center for Medium-Range Weather Forecasts (ECMWF). Required variables include: U / V wind components (U10, V10) at 10 meters height, significant wave height (swh), and maximum wave height (mwp). The spatiotemporal resolution of the data is 6-hour intervals with a 0.25° × 0.25° grid. Concurrent Northwest Pacific typhoon data was also downloaded from the China Meteorological Administration (CMA) Tropical Cyclone Optimum Track Dataset, including the typhoon center latitude and longitude and maximum sustained wind speed near the center every 6 hours.
[0021] Data Preprocessing and Matching: The target sea area was determined to be (27°-32°N, 120.5°-124°E). All ERA5 grid point data within this area were extracted. Due to the different original resolutions of the ERA5 wind field (0.25°) and wave field (0.5°), bilinear interpolation was used to resample the wind field data to a 0.5° grid, ensuring that each wave grid point had a corresponding wind speed value. For each typhoon record in the CMA dataset, if the path of a typhoon intersects with the specified rectangular area, it is considered that the typhoon affected the target area. The time period corresponding to a wind speed level greater than or equal to level 12 was selected and defined as typhoon weather, forming the "Typhoon Weather" dataset. The remaining data within the area were labeled as the "Non-Typhoon Weather" dataset. A historical forecasting model library was constructed: data from 1970 to 2020 was divided into five periods, each with a 10-year time window: 1970-1980, 1980-1990, 1990-2000, 2000-2010, and 2010-2020. For each sample in the dataset, the composite wind speed was calculated based on the U10 and V10 components. .
[0022] S102: Match the latitude and longitude coordinate sequence of the typhoon center with the predefined spatial range of the ocean zoning structure data to determine the zoning identifier of the target typhoon. Input the path angle data of the target typhoon and the zoning identifier of the target typhoon into the pre-established wave prediction model and output the wave prediction results. The pre-established wave prediction model is constructed based on historical typhoon meteorological data and wave data, including a nonlinear wind and wave prediction model for the high-energy region of the eyewall and a linear wind and wave prediction model for the low-energy region of the periphery.
[0023] The division between the high-energy region of the eyewall and the low-energy region of the periphery is based on the relative radius with the typhoon center as the origin.
[0024] The nonlinear wind and wave prediction model for the high-energy region of the eyewall is a quadratic polynomial model, while the linear wind and wave prediction model for the peripheral low-energy region is a linear function model.
[0025] Historical typhoon meteorological data includes wind speed, significant wave height, and maximum wave height. The preprocessing process includes unifying the wind field and wave field data to the same grid resolution through spatial interpolation, and identifying grid point data that intersect with the typhoon path trajectory as typhoon weather data.
[0026] Specifically, an objective classification method based on the relative position of the typhoon is adopted. The area within a radius of 100 kilometers around the typhoon center is defined as the "eyewall high-energy zone," and the area between a radius of 100 kilometers and 250 kilometers is defined as the "outer low-energy zone." For the data points (wind speed W, significant wave height Hs, maximum wave height Hmax) in the "high-energy zone," a quadratic polynomial model is synthesized: A linear model was fitted to the data points in the "low energy region": The same applies to the maximum wave height. The model coefficients for this period are retained, ultimately resulting in a historical prediction model library containing 5 sets of models.
[0027] Establish model selection rules based on path characteristics: For each historical typhoon, calculate the average direction angle θ based on its trajectory. Starting with due east as 0°, increase counterclockwise to 360°. Calculate the direction angle θ of the typhoon to be predicted before it enters the study area. If θ belongs to [45°, 135°], indicating a "north-south" orientation, prioritize the model library from 1990-2000; if it is another angle, indicating an "east-west" orientation, prioritize the model library from 2000-2010 or 2010-2020.
[0028] Zonal Prediction and Result Output: For a specific offshore platform location (grid point) within the study area, the platform is first determined to be in a high-energy or low-energy zone based on the real-time center location of the typhoon to be measured. The real-time wind speed is then used to calculate the predicted effective wave height Hs and maximum wave height Hmax. The prediction results for all grid points within the entire study area are then color-coded to generate an extreme wave field distribution forecast map, which visually displays the typhoon danger zone and issues marine disaster warnings of different levels accordingly.
[0029] To verify the effectiveness and superiority of the wave prediction method based on typhoon path angle and zonal structure proposed in this invention, this embodiment selects the typical typhoon "Haeger" that occurred in the Northwest Pacific in 2020 and "Fitow" in 2013 as test cases, and compares and analyzes the prediction results of this method with the true values.
[0030] Verification data and settings Test Typhoon: Typhoon "Hegel": Its path is oriented north-south, which meets the criteria for selecting the 1990-2000 model library in this invention.
[0031] Test Typhoon: Typhoon Fitow: Its path is east-west, which meets the criteria for selecting the 2010-2020 model library in this invention.
[0032] Validation of data source: The actual observed wave field data of this typhoon process from the ECMWF ERA5 reanalysis data was used as the "true value" to evaluate the accuracy of each prediction method. Validation results and analysis. like Figure 5 As shown, for the prediction case of Typhoon "Hegel", the goodness of fit (R²) of the linear fit is as high as 0.87; for Typhoon "Fitow", the R² reaches as high as 0.84. Both indicators clearly show that there is a high linear correlation between the prediction results of this invention and the actual observations, and the model can reliably capture and explain more than 80% of the spatial variation characteristics of the typhoon wave field. The linear fit slopes of the two cases are 0.72 and 0.88, respectively, both less than 1. This statistical characteristic reveals a slight systematic underestimation of the model, that is, for extremely high waves, the model's predictions tend to be lower than the actual observations.
[0033] Example 2: To achieve the above objective, such as Figure 6 As shown, based on Embodiment 1, this invention discloses a wave prediction system based on typhoon path angle and zonal structure, including: The data receiving module 11 is used to receive the path angle data and ocean partition structure data of the target typhoon. The path angle data of the target typhoon includes the latitude and longitude coordinate sequence of the typhoon center and the angle between the typhoon's movement direction and the reference direction. The ocean partition has a predefined spatial range and a corresponding partition identifier. Based on the partition identifier, the ocean partition includes the eyewall high-energy region and the peripheral low-energy region. The wave prediction module 12 is used to match the latitude and longitude coordinate sequence of the typhoon center with the predefined spatial range of the ocean zoning structure data to determine the zoning identifier of the target typhoon. The target typhoon's path angle data and the target typhoon's zoning identifier are input into the pre-established wave prediction model, and the wave prediction results are output. The pre-established wave prediction model is constructed based on historical typhoon meteorological data and wave data, including a nonlinear wind and wave prediction model for the high-energy region of the eyewall and a linear wind and wave prediction model for the low-energy region of the periphery.
[0034] Based on the same inventive concept, this invention also provides a computer device, comprising: one or more processors, and a memory for storing one or more computer programs; the programs include program instructions, and the processor executes the program instructions stored in the memory. The processor may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing and control core of the terminal, used to implement one or more instructions, specifically for loading and executing one or more instructions stored in a computer storage medium to implement the above-described method.
[0035] It should be further explained that, based on the same inventive concept, the present invention also provides a computer storage medium storing a computer program, which, when executed by a processor, performs the above-described method. This storage medium can be any combination of one or more computer-readable media. The computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of computer-readable storage media (a non-exhaustive list) include: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In the present invention, the computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.
[0036] In the description of this specification, references to terms such as "an embodiment," "example," "specific example," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this disclosure. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.
[0037] The foregoing has shown and described the basic principles, main features, and advantages of this disclosure. Those skilled in the art should understand that this disclosure is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of this disclosure. Various changes and modifications can be made to this disclosure without departing from its spirit and scope, and all such changes and modifications fall within the scope of this disclosure as claimed.
Claims
1. A wave prediction method based on typhoon path angle and zonal structure, characterized in that, The method includes the following steps: Receive target typhoon path angle data and ocean partition structure data. The target typhoon path angle data includes the latitude and longitude coordinate sequence of the typhoon center and the angle between the typhoon's direction of movement and the reference direction. The ocean partition has a predefined spatial range and a corresponding partition identifier. Based on the partition identifier, the ocean partition is distinguished into an eyewall high-energy region and an outer low-energy region. The latitude and longitude coordinate sequence of the typhoon center is matched with the predefined spatial range of the ocean zoning structure data to determine the zoning identifier of the target typhoon. The path angle data of the target typhoon and the zoning identifier of the target typhoon are input into the pre-established wave prediction model to output the wave prediction results. The pre-established wave prediction model is constructed based on historical typhoon meteorological data and wave data, including a nonlinear wind and wave prediction model for the high-energy region of the eyewall and a linear wind and wave prediction model for the low-energy region of the periphery.
2. The wave prediction method based on typhoon path angle and zonal structure according to claim 1, characterized in that, The division between the high-energy region of the eyewall and the low-energy region of the periphery is based on the relative radius with the typhoon center as the origin.
3. The wave prediction method based on typhoon path angle and zonal structure according to claim 1, characterized in that, The angle between the typhoon's moving direction and the reference direction is calculated based on the latitude and longitude coordinate sequence of the typhoon's center. The moving direction is calculated by vector difference, and the angle between the moving direction and the preset reference direction is obtained. The preset reference direction is due north.
4. The wave prediction method based on typhoon path angle and zonal structure according to claim 3, characterized in that, The angle between the typhoon's direction of movement and the reference direction classifies the target typhoon as either east-west or north-south oriented.
5. The wave prediction method based on typhoon path angle and zoning structure according to claim 4, characterized in that, The process of classifying typhoons into east-west or north-south oriented categories includes: The angle θ between the typhoon's direction of movement and the reference direction is 0° in the due east direction and increases to 360° in the counterclockwise direction; the path direction is classified as follows: when 45°≤θ<135°, it is defined as north-south; otherwise, it is defined as east-west.
6. The wave prediction method based on typhoon path angle and zonal structure according to claim 1, characterized in that, The nonlinear wind and wave prediction model for the high-energy region of the eyewall is a quadratic polynomial model, and the linear wind and wave prediction model for the peripheral low-energy region is a linear function model.
7. The wave prediction method based on typhoon path angle and zonal structure according to claim 1, characterized in that, The historical typhoon meteorological data includes wind speed, significant wave height, and maximum wave height; the preprocessing process includes unifying the wind field and wave field data to the same grid resolution through spatial interpolation, and identifying grid point data that intersect with the typhoon path trajectory as typhoon weather data.
8. A wave prediction system based on typhoon path angle and zonal structure, employing the wave prediction method based on typhoon path angle and zonal structure as described in any one of claims 1 to 7, characterized in that, include: The data receiving module is used to receive the path angle data and ocean partition structure data of the target typhoon. The path angle data of the target typhoon includes the latitude and longitude coordinate sequence of the typhoon center and the angle between the typhoon's movement direction and the reference direction. The ocean partition has a predefined spatial range and a corresponding partition identifier. Based on the partition identifier, the ocean partition includes the eyewall high-energy region and the peripheral low-energy region. The wave prediction module is used to match the latitude and longitude coordinate sequence of the typhoon center with the predefined spatial range of the ocean zoning structure data to determine the zoning identifier of the target typhoon. The target typhoon's path angle data and zoning identifier are input into the pre-established wave prediction model, and the wave prediction results are output. The pre-established wave prediction model is constructed based on historical typhoon meteorological data and wave data, including a nonlinear wind and wave prediction model for the high-energy region of the eyewall and a linear wind and wave prediction model for the low-energy region of the periphery.
9. A terminal device, comprising a memory, a processor, and a computer program stored in the memory and capable of running on the processor, characterized in that, The memory stores a computer program that can run on a processor. When the processor loads and executes the computer program, it employs the wave prediction method based on typhoon path angle and zonal structure as described in any one of claims 1 to 7.
10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is loaded and executed by the processor, it employs the wave prediction method based on typhoon path angle and zonal structure as described in any one of claims 1 to 7.