Sea wave data fusion correction method and system, electronic equipment and storage medium
By acquiring and fusing the effective wave height value and observation data of the forecast grid of the wave mode, the fusion weight factor is determined, and the problem of insufficient fusion accuracy of wave data is solved, and the high-precision fusion of wave wave high data is achieved, providing accuracy for marine environmental assessment. Assure.
Patent Information
- Application Number
- CN202411161076.2
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-08-22
- Publication Date
- 2024-12-13
AI Technical Summary
The existing technology cannot develop high-precision wave fusion data based on abundant marine observation data, resulting in the inability to accurately evaluate the maritime environment.
By obtaining the effective wave height value of the forecast grid of the wave mode to be fused, the wave wave height satellite observation data within the preset radius and the effective wave height value of the numerical mode grid point, the wave wave height fusion weight factor of each observation point is determined, and the fusion is treated based on these data The wave mode forecast grid point is corrected to obtain the wave fusion wave high value.
It improves the accuracy of high data fusion of wave waves and provides accuracy guarantee for marine environmental assessment.
Smart Images
Figure CN119128795A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the field of ocean wave data fusion, and in particular to an ocean wave data fusion correction method, system, electronic device and storage medium. Background Art
[0002] Data assimilation technology uses numerical models as dynamic forcing to determine the optimal estimate of the system state based on the evolution law of the dynamic system itself from observational data with uneven temporal and spatial distribution. In the late 1980s, the field of atmospheric science proposed a new method to restore long-term historical climate records using data assimilation technology in numerical weather forecasting, that is, to use data assimilation systems to integrate observational data of various sources and types with numerical weather forecast products. This formed the initial atmospheric reanalysis data, and then the United States, Europe and Japan successively started global ocean observation data reanalysis programs. Ocean observation data reanalysis is also an objective analysis process that uses advanced numerical models and data assimilation systems to unify and coordinate historical observational data of various types and sources. Ocean reanalysis products are the product of organically combining dynamic numerical models with multi-source observational data using assimilation systems, so they integrate the advantages of numerical simulation and observation: spatiotemporal continuity, relatively high spatiotemporal resolution, and the ability to form continuous data of the deep ocean, which to a certain extent makes up for the scarcity of deep ocean observational data. On the one hand, ocean reanalysis data products can be used as diagnostic data and widely used in ocean dynamics research and exploration of the ocean in climate change. On the other hand, they can provide initial fields for short-term numerical ocean forecasts and climate predictions.
[0003] At present, with the continuous enrichment of ocean observation data and the development of ocean data assimilation technology, there is still a lack of autonomous and controllable high-resolution wave reanalysis data for offshore areas. Therefore, it is urgent to propose a method to develop high-precision wave fusion data based on the existing rich ocean observation data for use in marine environmental assessment. Summary of the invention
[0004] The present application provides a wave data fusion correction method, system, electronic device and storage medium to at least solve the technical problem that the prior art has not developed high-precision wave fusion data based on abundant ocean observation data, thereby making it impossible to accurately assess the marine environment.
[0005] The first embodiment of the present application provides a wave data fusion correction method, the method comprising:
[0006] Acquire the effective wave height value of the wave model forecast grid point to be fused, the wave height satellite observation data of multiple observation points within a preset radius of the wave model forecast grid point to be fused, and the effective wave height values of the numerical model grid points corresponding to the multiple observation points;
[0007] Determine the wave height fusion weight factor of each observation point;
[0008] According to the wave height satellite observation data of multiple observation points within a preset radius of the wave pattern forecast grid point to be fused, the effective wave height values of the numerical pattern grid points corresponding to the multiple observation points and the wave height fusion weight factors of the observation points, the effective wave height values of the wave pattern forecast grid points to be fused are corrected to obtain the wave fusion wave height values of the wave pattern forecast grid points to be fused.
[0009] Preferably, the process of determining the preset radius includes:
[0010] Obtain multiple initial radii and conduct assimilation experiments;
[0011] Based on the assimilation experiment results, the prediction accuracy of the significant wave height corresponding to each initial radius is determined;
[0012] Arrange multiple initial radii from left to right in the order of high to low prediction accuracy to form a radius sequence;
[0013] Takes the first value from the left in the radius sequence as the preset radius.
[0014] Preferably, the calculation formula of the wave height fusion weight factor of each observation point is as follows:
[0015]
[0016] Where W i is the wave height fusion weight factor of observation point i, is the error covariance between the forecast grid point k and the observation point of the wave model to be fused, is the background error covariance between observation point i and observation point j, is the observation error covariance between observation point i and observation point j, λ i is the ratio of the error standard deviation of observation point i to the initial error standard deviation, λ j is the ratio of the error standard deviation of observation point j to the initial error standard deviation, and n is the total number of observation points within the preset radius.
[0017] Furthermore, the calculation formula of the background error covariance between the observation point i and the observation point j is as follows:
[0018]
[0019] Where N is the time step, B i (t) is the background field value of the wave height at observation point i at time t, is the mean value of the background field value of the sea wave height at observation point i, B j (t) is the background field value of the wave height at observation point j at time t, is the mean value of the background field value of the sea wave height at observation point j;
[0020] The calculation formula of the observation error covariance between the observation point i and the observation point j is as follows:
[0021]
[0022] In the formula, O i (t) is the observed value of the wave height at observation point i at time t, O i is the mean of the wave height observations at observation point i, O j (t) is the observed value of the wave height at observation point j at time t, is the mean of the wave height observations at observation point j;
[0023] The calculation formula of the ratio of the error standard deviation of the observation point i to the initial error standard deviation is as follows:
[0024]
[0025] In the formula, is the standard deviation of the observation error at observation point i, is the background error standard deviation of observation point i;
[0026] The calculation formula of the ratio of the error standard deviation of the observation point j to the initial error standard deviation is as follows:
[0027]
[0028] In the formula, is the standard deviation of the observation error at observation point j, is the standard deviation of the background error at observation point j.
[0029] Furthermore, the calculation formula for the wave fusion wave height value of the wave model forecast grid point to be fused is as follows:
[0030]
[0031] In the formula, A k is the fused wave height value of the wave model forecast grid point k to be fused, F k is the effective wave height value of the forecast grid point k of the wave model to be fused, F i is the effective wave height value of the numerical model grid point corresponding to observation point i.
[0032] The second embodiment of the present application provides a wave data fusion correction system, including:
[0033] An acquisition module is used to acquire the effective wave height value of the wave pattern forecast grid point to be fused, the wave height satellite observation data of multiple observation points within a preset radius of the wave pattern forecast grid point to be fused, and the effective wave height values of the numerical pattern grid points corresponding to the multiple observation points;
[0034] The first determination module is used to determine the wave height fusion weight factor of each observation point;
[0035] The fusion correction module is used to correct the effective wave height value of the wave pattern forecast grid point to be fused according to the wave height satellite observation data of multiple observation points within a preset radius of the wave pattern forecast grid point to be fused, the effective wave height values of the numerical pattern grid points corresponding to the multiple observation points and the wave height fusion weight factors of each observation point to obtain the wave fusion wave height value of the wave pattern forecast grid point to be fused.
[0036] Preferably, the system further comprises: a second determination module;
[0037] The second determining module is used to:
[0038] Obtain multiple initial radii and conduct assimilation experiments;
[0039] Based on the assimilation experiment results, the prediction accuracy of the significant wave height corresponding to each initial radius is determined;
[0040] Arrange multiple initial radii from left to right in the order of high to low prediction accuracy to form a radius sequence;
[0041] Takes the first value from the left in the radius sequence as the preset radius.
[0042] Preferably, the calculation formula of the wave height fusion weight factor of each observation point is as follows:
[0043]
[0044] Where W i is the wave height fusion weight factor of observation point i, is the error covariance between the forecast grid point k and the observation point of the wave model to be fused, is the background error covariance between observation point i and observation point j, is the observation error covariance between observation point i and observation point j, λ i is the ratio of the error standard deviation of observation point i to the initial error standard deviation, λ j is the ratio of the error standard deviation of observation point j to the initial error standard deviation, and n is the total number of observation points within the preset radius.
[0045] The third aspect of the present application provides an electronic device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the method described in the first aspect is implemented.
[0046] A fourth aspect of the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method described in the first aspect of the present application.
[0047] The technical solution provided by the embodiments of the present application brings at least the following beneficial effects:
[0048] The present application proposes a method, system, electronic device and storage medium for wave data fusion correction, wherein the method comprises: obtaining the effective wave height value of the wave pattern forecast grid point to be fused, the wave height satellite observation data of multiple observation points within the preset radius of the wave pattern forecast grid point to be fused, and the effective wave height values of the numerical pattern grid points corresponding to the multiple observation points; determining the wave height fusion weight factor of each observation point; correcting the effective wave height value of the wave pattern forecast grid point to be fused according to the wave height satellite observation data of multiple observation points within the preset radius of the wave pattern forecast grid point to be fused, the effective wave height values of the numerical pattern grid points corresponding to the multiple observation points, and the wave height fusion weight factor of each observation point, to obtain the wave fusion wave height value of the wave pattern forecast grid point to be fused. The technical solution proposed in the present application improves the accuracy of wave height data fusion.
[0049] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS
[0050] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:
[0051] Figure 1 A flow chart of a wave data fusion correction method provided according to an embodiment of the present application;
[0052] Figure 2 A first structural diagram of a wave data fusion correction system provided according to an embodiment of the present application;
[0053] Figure 3 This is a second structural diagram of a wave data fusion and correction system provided according to an embodiment of the present application. DETAILED DESCRIPTION
[0054] Embodiments of the present application are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.
[0055] The present application proposes a method, system, electronic device and storage medium for wave data fusion correction, wherein the method comprises: obtaining the effective wave height value of the wave pattern forecast grid point to be fused, the wave height satellite observation data of multiple observation points within the preset radius of the wave pattern forecast grid point to be fused, and the effective wave height values of the numerical pattern grid points corresponding to the multiple observation points; determining the wave height fusion weight factor of each observation point; correcting the effective wave height value of the wave pattern forecast grid point to be fused according to the wave height satellite observation data of multiple observation points within the preset radius of the wave pattern forecast grid point to be fused, the effective wave height values of the numerical pattern grid points corresponding to the multiple observation points, and the wave height fusion weight factor of each observation point, to obtain the wave fusion wave height value of the wave pattern forecast grid point to be fused. The technical solution proposed in the present application improves the accuracy of wave height data fusion.
[0056] The following describes an ocean wave data fusion correction method, system, electronic device and storage medium according to an embodiment of the present application with reference to the accompanying drawings.
[0057] Embodiment 1
[0058] Figure 1 Flow chart of a wave data fusion correction method provided according to one embodiment of the present application, such as Figure 1 As shown, the method includes:
[0059] Step 1: Obtain the effective wave height value of the wave model forecast grid point to be fused, the wave height satellite observation data of multiple observation points within a preset radius of the wave model forecast grid point to be fused, and the effective wave height values of the numerical model grid points corresponding to the multiple observation points.
[0060] In the embodiment of the present disclosure, the process of determining the preset radius includes:
[0061] Obtain multiple initial radii and conduct assimilation experiments;
[0062] Based on the assimilation experiment results, the prediction accuracy of the significant wave height corresponding to each initial radius is determined;
[0063] Arrange multiple initial radii from left to right in the order of high to low prediction accuracy to form a radius sequence;
[0064] Takes the first value from the left in the radius sequence as the preset radius.
[0065] It should be noted that the preset radius should match the resolution of the numerical model, usually 2-3 times the model resolution. Assimilation experiments with different radii (such as 100 km, 150 km, and 200 km) can be conducted to evaluate the forecast accuracy. Assuming that the forecast result using a radius of 150 km is the best through experiments, 150 km is determined as the final preset radius.
[0066] Step 2: Determine the wave height fusion weight factor for each observation point.
[0067] In the disclosed embodiment, the calculation formula of the wave height fusion weight factor of each observation point is as follows:
[0068]
[0069] Where W i is the wave height fusion weight factor of observation point i, is the error covariance between the forecast grid point k and the observation point of the wave model to be fused, is the background error covariance between observation point i and observation point j, is the observation error covariance between observation point i and observation point j, λ i is the ratio of the error standard deviation of observation point i to the initial error standard deviation, λ j is the ratio of the error standard deviation of observation point j to the initial error standard deviation, and n is the total number of observation points within the preset radius.
[0070] Furthermore, the error covariance between each pair of points is calculated by statistically analyzing the background field data;
[0071] The calculation formula of the background error covariance between the observation point i and the observation point j is as follows:
[0072]
[0073] Where N is the time step, B i (t) is the background field value of the wave height at observation point i at time t, is the mean value of the background field value of the sea wave height at observation point i, B j (t) is the background field value of the wave height at observation point j at time t, is the mean value of the background field value of the sea wave height at observation point j;
[0074] By analyzing the observed data, the error covariance between each pair of observation points is calculated;
[0075] The calculation formula of the observation error covariance between the observation point i and the observation point j is as follows:
[0076]
[0077] In the formula, O i (t) is the observed value of the wave height at observation point i at time t, is the mean of the wave height observations at observation point i, O j (t) is the observed value of the wave height at observation point j at time t, is the mean of the wave height observations at observation point j;
[0078] The calculation formula of the ratio of the error standard deviation of the observation point i to the initial error standard deviation is as follows:
[0079]
[0080] In the formula, is the standard deviation of the observation error at observation point i, is the background error standard deviation of observation point i;
[0081] The calculation formula of the ratio of the error standard deviation of the observation point j to the initial error standard deviation is as follows:
[0082]
[0083] In the formula, is the standard deviation of the observation error at observation point j, is the standard deviation of the background error at observation point j.
[0084] Step 3: According to the wave height satellite observation data of multiple observation points within a preset radius of the wave pattern forecast grid point to be fused, the effective wave height values of the numerical pattern grid points corresponding to the multiple observation points and the wave height fusion weight factors of each observation point, the effective wave height value of the wave pattern forecast grid point to be fused is corrected to obtain the wave fusion wave height value of the wave pattern forecast grid point to be fused.
[0085] In the disclosed embodiment, the calculation formula of the wave fusion wave height value of the wave pattern forecast grid point to be fused is as follows:
[0086]
[0087] In the formula, A k is the fused wave height value of the wave model forecast grid point k to be fused, F k is the effective wave height value of the forecast grid point k of the wave model to be fused, F i is the effective wave height value of the numerical model grid point corresponding to observation point i.
[0088] In summary, the wave data fusion correction method proposed in this embodiment improves the accuracy of wave height data fusion and provides a guarantee for the accuracy of marine environment assessment.
[0089] Embodiment 2
[0090] Figure 2 FIG. 1 is a structural diagram of a wave data fusion correction system provided according to an embodiment of the present application, such as Figure 2 As shown, the system comprises:
[0091] The acquisition module 100 is used to acquire the effective wave height value of the wave pattern forecast grid point to be fused, the wave height satellite observation data of multiple observation points within a preset radius of the wave pattern forecast grid point to be fused, and the effective wave height values of the numerical pattern grid points corresponding to the multiple observation points;
[0092] The first determination module 200 is used to determine the wave height fusion weight factor of each observation point;
[0093] The fusion correction module 300 is used to correct the effective wave height value of the wave pattern forecast grid to be fused according to the wave height satellite observation data of multiple observation points within a preset radius of the wave pattern forecast grid to be fused, the effective wave height values of the numerical pattern grid points corresponding to the multiple observation points and the wave height fusion weight factors of each observation point, so as to obtain the wave fusion wave height value of the wave pattern forecast grid to be fused.
[0094] In the embodiments of the present disclosure, Figure 3 As shown, the system further includes: a second determination module 400;
[0095] The second determining module 400 is configured to:
[0096] Obtain multiple initial radii and conduct assimilation experiments;
[0097] Based on the assimilation experiment results, the prediction accuracy of the significant wave height corresponding to each initial radius is determined;
[0098] Arrange multiple initial radii from left to right in the order of high to low prediction accuracy to form a radius sequence;
[0099] Takes the first value from the left in the radius sequence as the preset radius.
[0100] It should be noted that the calculation formula for the wave height fusion weight factor of each observation point is as follows:
[0101]
[0102] Where W i is the wave height fusion weight factor of observation point i, is the error covariance between the forecast grid point k and the observation point of the wave model to be fused, is the background error covariance between observation point i and observation point j, is the observation error covariance between observation point i and observation point j, λ i is the ratio of the error standard deviation of observation point i to the initial error standard deviation, λ j is the ratio of the error standard deviation of observation point j to the initial error standard deviation, and n is the total number of observation points within the preset radius.
[0103] The calculation formula of the background error covariance between the observation point i and the observation point j is as follows:
[0104]
[0105] Where N is the time step, B i (t) is the background field value of the wave height at observation point i at time t, B i is the mean value of the background field value of the sea wave height at observation point i, B j (t) is the background field value of the wave height at observation point j at time t, B j is the mean value of the background field value of the sea wave height at observation point j;
[0106] The calculation formula of the observation error covariance between the observation point i and the observation point j is as follows:
[0107]
[0108] In the formula, O i (t) is the observed value of the wave height at observation point i at time t, is the mean of the wave height observations at observation point i, O j (t) is the observed value of the wave height at observation point j at time t, is the mean of the wave height observations at observation point j;
[0109] The calculation formula of the ratio of the error standard deviation of the observation point i to the initial error standard deviation is as follows:
[0110]
[0111] In the formula, is the standard deviation of the observation error at observation point i, is the background error standard deviation of observation point i;
[0112] The calculation formula of the ratio of the error standard deviation of the observation point j to the initial error standard deviation is as follows:
[0113]
[0114] In the formula, is the standard deviation of the observation error at observation point j, is the standard deviation of the background error at observation point j.
[0115] It should be noted that the calculation formula for the wave fusion wave height value of the wave model forecast grid to be fused is as follows:
[0116]
[0117] In the formula, A k is the fused wave height value of the wave model forecast grid point k to be fused, F k is the effective wave height value of the forecast grid point k of the wave model to be fused, F i is the effective wave height value of the numerical model grid point corresponding to observation point i.
[0118] In summary, the wave data fusion correction system proposed in this embodiment improves the accuracy of wave height data fusion and provides a guarantee for the accuracy of marine environment assessment.
[0119] Embodiment 3
[0120] In order to implement the above embodiments, the present disclosure further proposes an electronic device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the method described in Embodiment 1 is implemented.
[0121] Embodiment 4
[0122] In order to implement the above embodiments, the present disclosure further proposes a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, the method described in the first embodiment is implemented.
[0123] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.
[0124] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, fragment or portion of code comprising one or more executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred embodiments of the present application includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in the reverse order depending on the functions involved, which should be understood by technicians in the technical field to which the embodiments of the present application belong.
[0125] Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limitations on the present application. Ordinary technicians in this field can change, modify, replace and modify the above embodiments within the scope of the present application.
Claims
1. A wave data fusion correction method, characterized in that: The method comprises: Acquire the effective wave height value of the wave model forecast grid point to be fused, the wave height satellite observation data of multiple observation points within a preset radius of the wave model forecast grid point to be fused, and the effective wave height values of the numerical model grid points corresponding to the multiple observation points; Determine the wave height fusion weight factor of each observation point; According to the wave height satellite observation data of multiple observation points within a preset radius of the wave pattern forecast grid point to be fused, the effective wave height values of the numerical pattern grid points corresponding to the multiple observation points and the wave height fusion weight factors of the observation points, the effective wave height values of the wave pattern forecast grid points to be fused are corrected to obtain the wave fusion wave height values of the wave pattern forecast grid points to be fused.
2. The method according to claim 1, characterized in that The process of determining the preset radius includes: Obtain multiple initial radii and conduct assimilation experiments; Based on the assimilation experiment results, the prediction accuracy of the significant wave height corresponding to each initial radius is determined; Arrange multiple initial radii from left to right in the order of high to low prediction accuracy to form a radius sequence; Takes the first value from the left in the radius sequence as the preset radius.
3. The method according to claim 1, characterized in that The calculation formula of the wave height fusion weight factor of each observation point is as follows: Where W i is the wave height fusion weight factor of observation point i, is the error covariance between the forecast grid point k and the observation point of the wave model to be fused, is the background error covariance between observation point i and observation point j, is the observation error covariance between observation point i and observation point j, λ i is the ratio of the error standard deviation of observation point i to the initial error standard deviation, λ j is the ratio of the error standard deviation of observation point j to the initial error standard deviation, and n is the total number of observation points within the preset radius.
4. The method according to claim 3, characterized in that The calculation formula of the background error covariance between the observation point i and the observation point j is as follows: Where N is the time step, B i (t) is the background field value of the wave height at observation point i at time t, is the mean value of the background field value of the sea wave height at observation point i, B j (t) is the background field value of the wave height at observation point j at time t, is the mean value of the background field value of the sea wave height at observation point j; The calculation formula of the observation error covariance between the observation point i and the observation point j is as follows: In the formula, O i (t) is the observed value of the wave height at observation point i at time t, is the mean of the wave height observations at observation point i, O j (t) is the observed value of the wave height at observation point j at time t, is the mean of the wave height observations at observation point j; The calculation formula of the ratio of the error standard deviation of the observation point i to the initial error standard deviation is as follows: In the formula, is the standard deviation of the observation error at observation point i, is the background error standard deviation of observation point i; The calculation formula of the ratio of the error standard deviation of the observation point j to the initial error standard deviation is as follows: In the formula, is the standard deviation of the observation error at observation point j, is the standard deviation of the background error at observation point j.
5. The method according to claim 4, characterized in that The calculation formula of the wave fusion wave height value of the wave model forecast grid point to be fused is as follows: In the formula, A k is the fused wave height value of the wave model forecast grid point k to be fused, F k is the effective wave height value of the forecast grid point k of the wave model to be fused, F i is the effective wave height value of the numerical model grid point corresponding to observation point i.
6. A wave data fusion correction system, characterized in that: The system comprises: An acquisition module is used to acquire the effective wave height value of the wave pattern forecast grid point to be fused, the wave height satellite observation data of multiple observation points within a preset radius of the wave pattern forecast grid point to be fused, and the effective wave height values of the numerical pattern grid points corresponding to the multiple observation points; The first determination module is used to determine the wave height fusion weight factor of each observation point; The fusion correction module is used to correct the effective wave height value of the wave pattern forecast grid point to be fused according to the wave height satellite observation data of multiple observation points within a preset radius of the wave pattern forecast grid point to be fused, the effective wave height values of the numerical pattern grid points corresponding to the multiple observation points and the wave height fusion weight factors of each observation point to obtain the wave fusion wave height value of the wave pattern forecast grid point to be fused.
7. The system according to claim 6, characterized in that The system further comprises: a second determination module; The second determining module is used to: Obtain multiple initial radii and conduct assimilation experiments; Based on the assimilation experiment results, the prediction accuracy of the significant wave height corresponding to each initial radius is determined; Arrange multiple initial radii from left to right in the order of high to low prediction accuracy to form a radius sequence; Takes the first value from the left in the radius sequence as the preset radius.
8. The system according to claim 6, characterized in that The calculation formula of the wave height fusion weight factor of each observation point is as follows: Where W i is the wave height fusion weight factor of observation point i, is the error covariance between the forecast grid point k and the observation point of the wave model to be fused, is the background error covariance between observation point i and observation point j, is the observation error covariance between observation point i and observation point j, λ i is the ratio of the error standard deviation of observation point i to the initial error standard deviation, λ j is the ratio of the error standard deviation of observation point j to the initial error standard deviation, and n is the total number of observation points within the preset radius.
9. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the method according to any one of claims 1 to 5 is implemented.
10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method according to any one of claims 1 to 5 is implemented.