Typhoon intensity evaluation method and system, electronic equipment and storage medium

Abstract

The invention provides a typhoon intensity evaluation method and system, electronic equipment and a storage medium. The typhoon intensity evaluation method comprises the steps that a satellite data set is acquired; the satellite data set comprises brightness temperature data and latitude and longitude data of a plurality of data grid points; determining a plurality of data grid points in the typhoon calculation area to obtain position information of a typhoon center point; related data grid points are intercepted in the satellite data set, and the typhoon calculation area is divided into a plurality of concentric circular ring areas based on the maximum value of the distance between the typhoon center point and the related data grid points; calculating typhoon intensity evaluation parameters of each concentric annulus region; and taking the brightness temperature data of the related data grid points, the position information of the typhoon center point and the typhoon intensity evaluation parameters as current analysis data to obtain an evaluation result of the typhoon intensity. According to the method, the typhoon intensity can be continuously evaluated in real time without being limited by terrains, traffic and human activities, remote evaluation of the typhoon intensity is achieved, and higher safety is achieved.

Description

Technical Field

[0001] The present application belongs to the technical field of typhoon monitoring, and in particular, relates to a typhoon intensity assessment method, system, electronic equipment and storage medium. Background Art

[0002] As a highly destructive natural disaster, the formation and development process of typhoons involves complex ocean-atmosphere interactions. According to the Saffir-Simpson Hurricane Wind Scale, typhoon intensity can be divided into five levels, among which the maximum sustained wind speed of super typhoons can reach more than 250 kilometers per hour. The destructive power of typhoons is not only reflected in the strong winds and heavy rains they bring, but also in the storm surges, floods and secondary geological disasters they cause. These disasters not only cause short-term damage to the economic and social development of the affected areas, but may also cause long-term ecological and economic problems. After a typhoon, it is often accompanied by a series of chain reactions such as damage to infrastructure, interruption of agricultural production, and destruction of ecosystems. These impacts may last for years or even decades.

[0003] In meteorological science and disaster prevention and mitigation work, typhoon intensity assessment is a key link. It not only provides a scientific basis for the government and relevant departments to formulate reasonable disaster prevention and mitigation strategies, but is also an important means to protect people's lives and property. Accurate intensity assessment can support more refined typhoon warning issuance and help decision makers formulate more effective emergency response plans, including measures such as personnel evacuation, material deployment and infrastructure protection. At the same time, the long-term accumulation of typhoon intensity data is also of great value for improving meteorological forecasting capabilities and disaster prevention and mitigation capabilities, and can provide basic data support for research such as typhoon path prediction and intensity change trend analysis.

[0004] Therefore, how to effectively assess typhoon intensity and improve the accuracy and timeliness of the assessment is a technical problem that needs to be urgently solved by technical personnel in this field. Summary of the invention

[0005] The present application provides a typhoon intensity assessment method, system, electronic device and storage medium, which can effectively assess typhoon intensity and improve the accuracy and timeliness of typhoon intensity assessment.

[0006] In a first aspect, the present application provides a method for evaluating typhoon intensity, the method comprising: Acquire a satellite data set; the satellite data set includes brightness temperature data and latitude and longitude data of a plurality of data grid points; Determine multiple data grid points within the typhoon calculation area to obtain the location information of the typhoon center point; intercepting data grid points within a certain longitude and latitude range centered on the typhoon center point from the satellite data set as relevant data grid points, and dividing the typhoon calculation area into a plurality of concentric ring areas based on the maximum value of the distance between the typhoon center point and the relevant data grid points; Calculating typhoon intensity assessment parameters for each of the concentric ring areas; The brightness temperature data of the relevant data grid points, the position information of the typhoon center point and the typhoon intensity assessment parameters are used as current analysis data, and the current analysis data is analyzed based on the known relationship between historical analysis data and typhoon intensity to obtain a typhoon intensity assessment result.

[0007] In an implementation of the first aspect, obtaining the location information of the typhoon center includes: Acquire a corresponding brightness temperature gradient vector based on the brightness temperature data of each data grid point in the typhoon calculation area; Acquire the extension line of each data grid point in the typhoon calculation area along the direction of each brightness temperature gradient vector; The number of the extension lines passed by each of the data grid points in the typhoon calculation area is obtained, and the position information of the typhoon center point is obtained based on the latitude and longitude data of the data grid points passing the most extension lines.

[0008] In an implementation of the first aspect, acquiring a corresponding brightness temperature gradient vector based on the brightness temperature data of each data grid point in the typhoon calculation area includes: Calculate the longitude change rate and latitude change rate of the brightness temperature data of each data grid point in the typhoon calculation area; The coordinates corresponding to the brightness temperature gradient vector are acquired based on the longitude change rate and the latitude change rate; wherein the longitude change rate is the longitude coordinate of the brightness temperature gradient vector, and the latitude change rate is the latitude coordinate of the brightness temperature gradient vector.

[0009] In an implementation of the first aspect, dividing the typhoon calculation area into a plurality of concentric ring areas based on the maximum value of the distance between the typhoon center point and the relevant data grid points includes: Calculating the distance between each of the relevant data grid points and the typhoon center point to obtain the maximum value of the distance; Dividing the maximum distance into equal parts to divide the typhoon calculation area into the same number of concentric ring areas; The distance between each of the data grid points in the typhoon calculation area and the typhoon center point is calculated to divide all the data grid points in the typhoon calculation area into corresponding concentric ring areas.

[0010] In an implementation of the first aspect, calculating the typhoon intensity assessment parameter of each of the concentric ring areas includes: Based on the brightness temperature data of the data grid points in each of the concentric ring regions, respectively calculate the corresponding brightness temperature average value, brightness temperature variance, brightness temperature maximum value and brightness temperature minimum value; and Based on the axisymmetric angles of the data grid points in each of the concentric circular ring regions, the corresponding axisymmetric angle variance and average deviation angle are calculated respectively.

[0011] In an implementation of the first aspect, the method includes: Acquire a corresponding center vector based on each data grid point in each of the concentric ring areas and the typhoon center point; Take a gradient point on the brightness temperature gradient vector corresponding to each data grid point in each of the concentric ring regions, and calculate the spherical distances between each data grid point in each of the concentric ring regions, the typhoon center point and the corresponding gradient points; The axisymmetric angles of the data grid points in each of the concentric circular ring regions are calculated based on the spherical distance correspondence.

[0012] In an implementation of the first aspect, obtaining the evaluation result of the typhoon intensity includes: Acquire typhoon symmetry based on the axisymmetric angle variance and the average deviation angle; Acquire typhoon brightness temperature characteristics based on the brightness temperature average value, the brightness temperature variance, the brightness temperature maximum value and the brightness temperature minimum value; The brightness temperature data of the relevant data grid points, the position information of the typhoon center point, the typhoon symmetry and the typhoon brightness temperature characteristics are used as the current analysis data, and the current analysis data is analyzed based on the known relationship between historical analysis data and typhoon intensity to obtain an assessment result of typhoon intensity.

[0013] In a second aspect, the present application provides a typhoon intensity assessment system, the system comprising: A data module is configured to obtain a satellite data set; the satellite data set includes brightness temperature data and latitude and longitude data of a plurality of data grid points; A typhoon center point module is configured to determine a plurality of data grid points within a typhoon calculation area to obtain location information of the typhoon center point; a segmentation module configured to intercept data grid points within a certain longitude and latitude range centered on the typhoon center point from the satellite data set as relevant data grid points, and to segment the typhoon calculation area into a plurality of concentric circular ring areas based on the maximum value of the distance between the typhoon center point and the relevant data grid points; A calculation module, configured to calculate typhoon intensity assessment parameters of each of the concentric ring areas; The evaluation module is configured to use the brightness temperature data of the relevant data grid points, the location information of the typhoon center point and the typhoon intensity evaluation parameters as current analysis data, and analyze the current analysis data based on the known relationship between historical analysis data and typhoon intensity to obtain an evaluation result of typhoon intensity.

[0014] In a third aspect, the present application provides an electronic device comprising: one or more processors; and one or more memories, wherein the memories store computer-readable codes, and when the computer-readable codes are executed by the one or more processors, the method for assessing typhoon intensity as described above is implemented.

[0015] In a fourth aspect, the present application provides a computer-readable storage medium having instructions stored thereon, and when the instructions are executed by a processor, the processor executes the typhoon intensity assessment method as described above.

[0016] As described above, the typhoon intensity assessment method, system, electronic device and storage medium described in the present application have the following beneficial effects:

[0017] 1. Wide observation range: This application can use satellite data to automatically and real-time assess typhoon intensity without being affected by terrain complexity, restricted by traffic conditions, or interfered by human activities.

[0018] 2. Realize long-distance observation with high safety: This application does not need to place meteorological equipment and meteorological observers in the extreme environment of the typhoon, and can directly use satellite data to assess the typhoon intensity. It not only ensures the safety of personnel and equipment, but also ensures the continuity and reliability of data, providing a solid foundation for typhoon research and disaster prevention and mitigation work.

[0019] 3. Continuity and real-time: This application can automatically obtain valuable typhoon intensity assessment parameters based on satellite data, and evaluate typhoon intensity in real time based on typhoon intensity assessment parameters and satellite data. There is no need to process and calculate satellite data every time to obtain dynamic information on typhoon intensity. It automatically ensures real-time updating of data, thereby effectively improving the scientificity and timeliness of typhoon defense work. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 It is a schematic diagram showing the application of the typhoon intensity assessment method described in an embodiment of the present application in one embodiment.

[0021] Figure 2 The figure shows a schematic diagram of a process of evaluating the typhoon intensity in an embodiment of the present application. Figure 1 .

[0022] Figure 3 The figure shows a schematic diagram of a process of evaluating the typhoon intensity in an embodiment of the present application. Figure 2 .

[0023] Figure 4 The figure shows a schematic diagram of a process of evaluating the typhoon intensity in an embodiment of the present application. Figure 3 .

[0024] Figure 5 The figure shows a schematic diagram of a process of evaluating the typhoon intensity in an embodiment of the present application. Figure 4 .

[0025] Figure 6 Shown is a structural schematic diagram of a typhoon intensity assessment system according to an embodiment of the present application.

[0026] Figure 7 Shown is a schematic structural diagram of an electronic device described in an embodiment of the present application. DETAILED DESCRIPTION

[0027] The following describes the embodiments of the present application through specific examples, and those skilled in the art can easily understand other advantages and effects of the present application from the contents disclosed in this specification. The present application can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present application. It should be noted that the following embodiments and features in the embodiments can be combined with each other without conflict.

[0028] It should be noted that the illustrations provided in the following embodiments are only schematic illustrations of the basic concept of the present application, and thus the drawings only show components related to the present application rather than being drawn according to the number, shape and size of components in actual implementation. In actual implementation, the type, quantity and proportion of each component may be changed at will, and the component layout may also be more complicated.

[0029] In addition, in this application, descriptions such as "first", "second", etc. are only used for descriptive purposes and cannot be understood as indicating or implying their relative importance or implicitly indicating the number of technical features indicated. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In addition, the technical solutions between the various embodiments can be combined with each other, but they must be based on the ability of ordinary technicians in this field to implement them. When the combination of technical solutions is contradictory or cannot be implemented, it should be deemed that such combination of technical solutions does not exist and is not within the scope of protection required by this application.

[0030] In today's global climate change, typhoons, as a highly destructive natural disaster, pose a serious threat to the safety of life and property, infrastructure construction and economic development in coastal areas and even wider areas. Accurate and timely information on typhoon intensity is of irreplaceable importance for disaster warning, disaster prevention and mitigation planning, and the rational arrangement of various activities at sea and on land.

[0031] Traditional methods of measuring typhoon intensity often rely on ground-based meteorological observation stations, ocean buoys, aircraft detection and other means, but these methods have many limitations. For example, ground-based meteorological observation stations are limited in distribution, making it difficult to fully cover vast ocean areas, and insufficient typhoon observation data is obtained far from land. The number of ocean buoys is relatively scarce, and data transmission and stability face challenges in severe sea conditions. In addition, although aircraft detection can obtain more accurate local data, it is costly and limited by flight conditions and range, making it difficult to achieve continuous, large-scale monitoring of typhoons.

[0032] With the development of remote sensing technology and numerical forecasting models, new typhoon intensity assessment methods continue to emerge. For example, ocean surface wind speed inversion technology based on microwave radiometers, sea surface wind field observation technology using synthetic aperture radar (SAR), and typhoon intensity prediction models combined with artificial intelligence algorithms. Among them, satellites can continuously monitor the earth's atmosphere and ocean environment on a global scale, obtain massive amounts of radiation data, and use this to assess typhoon intensity, which has improved the accuracy and timeliness of the assessment to a certain extent.

[0033] However, these raw radiation data need to be processed and calculated accurately before they can be transformed into valuable information for typhoon intensity assessment, which also affects the timeliness of typhoon intensity assessment, making it difficult to ensure timely typhoon warnings and the deployment of disaster prevention measures by relevant departments in advance. Therefore, the existing technology lacks an effective method for assessing typhoon intensity, which brings efficiency and safety issues to disaster prevention.

[0034] In order to at least solve the above-mentioned technical problems, the embodiments of the present application provide a typhoon intensity assessment method, system, electronic device and storage medium, which can obtain valuable typhoon intensity assessment parameters using satellite data without being affected by the complexity of the terrain, restricted by traffic conditions, and interfered with by human activities, and can assess the typhoon intensity in real time based on the typhoon intensity assessment parameters and satellite data, without having to process and calculate the satellite data every time to automatically ensure the real-time update of the typhoon intensity data, thereby effectively improving the scientific nature and timeliness of typhoon defense work. In addition, the present application uses satellite data to achieve long-distance observation, without placing meteorological equipment and meteorological observers in the extreme environment of the typhoon. The present application not only ensures the safety of personnel and equipment, but also ensures the continuity and reliability of the data, providing a solid foundation for typhoon research and disaster prevention and mitigation work.

[0035] Figure 1 The typhoon intensity assessment method provided in the embodiment of the present application is shown as an application schematic diagram. The typhoon intensity assessment method provided in the embodiment of the present application can be applied to Figure 1 The typhoon intensity assessment device 1 is shown in FIG. Figure 1 As shown, the typhoon intensity assessment device 1 can automatically obtain the data set of the Fengyun-4B satellite through the China Meteorological Satellite Data Center (NSMC), including the brightness temperature data and longitude and latitude data of multiple data grid points. Among them, the Fengyun-4B satellite actually collects radiation imaging data in the form of a grid, and the brightness temperature data corresponding to the radiation imaging data can be found through the corresponding temperature lookup table, and the longitude and latitude data of this data grid point can be found through the row and column numbers of the data grid point, combined with the longitude and latitude matching table, and finally the brightness temperature data and longitude and latitude of the data grid point are matched one by one, so that the brightness temperature data and longitude and latitude data of each data grid point can be obtained.

[0036] After acquiring the longitude and latitude data and brightness temperature data of the data grid points, the typhoon intensity assessment device 1 determines a plurality of data grid points in the typhoon calculation area, thereby determining the location information of the typhoon center point. Afterwards, the typhoon intensity assessment device 1 intercepts the data grid points within a certain longitude and latitude range centered on the typhoon center point in the satellite data set as relevant data grid points, and divides the typhoon calculation area into a plurality of concentric ring areas based on the location information of the typhoon center point and the relevant data grid points, thereby calculating the typhoon intensity assessment parameters of each of the concentric ring areas, and finally uses the brightness temperature data of the relevant data grid points, the location information of the typhoon center point and the typhoon intensity assessment parameters as the current analysis data, and analyzes the current analysis data based on the known relationship between the historical analysis data and the typhoon intensity to obtain the typhoon intensity assessment result. In addition, the typhoon intensity assessment device 1 can store the assessment results in the local database 2 in a structured data format, and generate a visual assessment report file at the same time, so as to facilitate the meteorological department to monitor the typhoon intensity and make early warning decisions.

[0037] Figure 2 The flowchart of the method for evaluating typhoon intensity provided in the embodiment of the present application is shown. Figure 2 As shown, the typhoon intensity assessment method includes steps S1 to S5.

[0038] S1. Obtain a satellite data set; the satellite data set includes brightness temperature data and longitude and latitude data of multiple data grid points.

[0039] In some embodiments, a data set of the Fengyun-4B satellite is obtained. The Fengyun-4B satellite data set is a data set in a grid format, including multiple data grid points. The brightness temperature data and longitude and latitude data of multiple data grid points can be obtained through the China Meteorological Satellite Data Center and the data usage instructions of the Fengyun-4B satellite.

[0040] S2. Determine a plurality of data grid points within the typhoon calculation area to obtain the location information of the typhoon center point.

[0041] In order to achieve real-time assessment of typhoon intensity, the typhoon intensity assessment method provided in the embodiment of the present application obtains the location information of the typhoon center in real time. Figure 3 As shown, obtaining the location information of the typhoon center point includes steps S21 to S23.

[0042] S21. Acquire a corresponding brightness temperature gradient vector based on the brightness temperature data of each data grid point in the typhoon calculation area.

[0043] In some embodiments, a square area including the center of the typhoon is selected as the calculation area, and the area is 10 degrees longitude and 10 degrees latitude, so as to determine n data grid points in the calculation area. By selecting the calculation area, the calculation range can be reduced and the calculation efficiency can be improved.

[0044] In some embodiments, after determining a plurality of data grid points, the longitude change rate and latitude change rate of the brightness temperature data of each data grid point in the typhoon calculation area can be calculated based on the brightness temperature data and longitude and latitude data of the plurality of data grid points; and the coordinates corresponding to the brightness temperature gradient vector are obtained based on the longitude change rate and the latitude change rate. The longitude change rate is the longitude coordinate of the brightness temperature gradient vector, and the latitude change rate is the latitude coordinate of the brightness temperature gradient vector.

[0045] In the above embodiment, after obtaining the change rate of the brightness temperature data of n data grid points with longitude and latitude, the brightness temperature gradient is obtained, and the gradient line is drawn based on the brightness temperature gradient.

[0046] Specifically, the brightness temperature gradient is calculated by taking the partial derivatives of the brightness temperature in the longitude and latitude directions, and its mathematical expression is:

[0047] in, and Respectively represent the rate of change of brightness temperature in the longitude and latitude directions. The calculation of brightness temperature gradient can reflect the drastic change characteristics of temperature distribution in the typhoon area. After obtaining the brightness temperature gradient, the rate of change of brightness temperature with longitude and latitude is further expressed as the coordinate component of the gradient vector. Specifically, the component of the gradient vector in the longitude direction is , the component in the latitude direction is Based on the brightness temperature gradient vector, gradient lines can be drawn in the calculation area. The direction of the gradient line is consistent with the direction of the fastest brightness temperature change, and its density reflects the intensity of the brightness temperature change. By drawing gradient lines, the spatial characteristics of the brightness temperature distribution in the typhoon area can be intuitively displayed, providing an important basis for the quantitative assessment of typhoon intensity.

[0048] S22. Obtain the extension line of each data grid point in the typhoon calculation area along the direction of each brightness temperature gradient vector.

[0049] Specifically, for each data grid point in the typhoon calculation area, an extension line is drawn in the direction of its gradient vector. In some embodiments, since there are n data grid points in the typhoon calculation area, n extension lines can be drawn.

[0050] S23, obtaining the number of the extension lines passed by each of the data grid points in the typhoon calculation area, and obtaining the position information of the typhoon center point based on the longitude and latitude data of the data grid points passing the most extension lines.

[0051] Specifically, the distance between each data grid point and the extension line in the typhoon calculation area is calculated. If the distance is less than 0.1, it is considered that the extension line passes through the data grid point.

[0052] In some embodiments, a GPU can be used for parallel computing to determine the data grid points that the n extension lines pass through, thereby increasing the computing speed. Finally, the data grid points that the extension lines pass through the most among the n data grid points in the typhoon calculation area are counted, and the average values ​​of the longitude and latitude data of these data grid points are calculated to obtain the location information of the typhoon center point.

[0053] S3. Data grid points within a certain longitude and latitude range centered on the typhoon center point are intercepted from the satellite data set as relevant data grid points, and the typhoon calculation area is divided into a plurality of concentric circular areas based on the maximum value of the distance between the typhoon center point and the relevant data grid points.

[0054] In some embodiments, according to the location information of the typhoon center point obtained in step S2, data grid points within a range of 15 longitudes and latitudes from the typhoon center point are intercepted from the data set of the Fengyun-4B satellite as relevant data points. For example, if the location information of the typhoon center point is (a, b), then data grid points within the range of longitude [a-15, a+15] and latitude [b-15, b+15] are intercepted from the satellite data set as relevant data points.

[0055] In order to analyze different parts of the typhoon more accurately, after obtaining the relevant data grid points, the typhoon calculation area is divided into multiple concentric ring areas based on the location information of the typhoon center point and the relevant data grid points. Each concentric ring area represents a typhoon area within a specific distance range. Figure 4 As shown, dividing the typhoon calculation area into a plurality of concentric ring areas based on the position information of the typhoon center point and the relevant data grid points includes steps S31 to S33.

[0056] S31, calculating the distance between each of the relevant data grid points and the typhoon center point to obtain the maximum distance value.

[0057] In some embodiments, when the latitude and longitude data of the relevant data grid points and the latitude and longitude information of the typhoon center point are known, the Haversine formula can be used to obtain the distance between each of the relevant data grid points and the typhoon center point, and the maximum distance value can be obtained therefrom. For example, assuming that there are m relevant data grid points, the Haversine formula is used to obtain the distances between the m relevant data grid points and the typhoon center point, which are d1, d2...dm, respectively, and the maximum distance d is determined therefrom.

[0058] Among them, assuming that the latitude and longitude data of the mth relevant data grid point is (m1, m2), and the position of the typhoon center is (a, b), the Haversine formula is used to calculate as follows:

[0059] Among them, R is the radius of the earth (usually 6371 kilometers), p is the angle between the mth relevant data grid point and the typhoon center point (in radians), and q is the intermediate variable.

[0060] S32: Divide the maximum distance into equal parts to divide the typhoon calculation area into the same number of concentric circular ring areas.

[0061] S33, calculating the distance between each of the data grid points in the typhoon calculation area and the typhoon center point, so as to divide all the data grid points in the typhoon calculation area into corresponding concentric ring areas.

[0062] In some embodiments, the maximum distance is divided into 70 equal parts to divide the typhoon calculation area into 70 concentric ring areas, and the width of each concentric ring is d / 70. Then, according to the distance between each data grid point in the typhoon calculation area and the typhoon center point, the n data grid points in the typhoon calculation area in step S2 are divided into 70 concentric ring areas.

[0063] It should be noted that the Haversine formula can also be used to obtain the distance dn between the n data grid points in the typhoon calculation area and the typhoon center point, which will not be described in detail here.

[0064] In some embodiments, the nth data grid point in the typhoon calculation area belongs to which concentric ring area according to the distance dn between the nth data grid point and the typhoon center point. The condition that the nth data grid point in the typhoon calculation area belongs to the i-th concentric ring area is:

[0065] The value range of i is 1 to 70.

[0066] According to the above formula, the distance between the typhoon calculation area and the typhoon center is The data grid points within the range are divided into the first circle, and so on. The distance between the typhoon calculation area and the typhoon center is The data grid points are divided into the i-th ring.

[0067] S4. Calculate the typhoon intensity assessment parameters of each of the concentric ring areas.

[0068] In some embodiments, the typhoon intensity assessment parameters include: axisymmetric angle variance, average deviation angle, brightness temperature average, brightness temperature variance, maximum brightness temperature and minimum brightness temperature.

[0069] Among them, for each concentric ring area, the axisymmetric angle variance is the variance of the axisymmetric angles of all data grid points in the concentric ring area. The average deviation angle is the average value of the axisymmetric angles of all data grid points in the concentric ring area. The average brightness temperature is the average value of the brightness temperature of all data grid points in the concentric ring area. The brightness temperature variance is the variance of the brightness temperature of all data grid points in the concentric ring area. The maximum brightness temperature is the maximum value of all data grid points in the concentric ring area. The minimum brightness temperature is the minimum value of the brightness temperature of all data grid points in the concentric ring area.

[0070] Among them, when calculating the axial symmetry angle variance and the average deviation angle of a certain concentric ring area, it is necessary to first calculate the axial symmetry angle of the data grid points in the concentric ring area, including: obtaining the corresponding center vector based on each data grid point in each of the concentric ring areas and the typhoon center point; taking a gradient point on the brightness temperature gradient vector corresponding to each data grid point in each of the concentric ring areas, and correspondingly calculating the spherical distances between each data grid point in each of the concentric ring areas, the typhoon center point and the corresponding gradient points; and correspondingly calculating the axial symmetry angles of the data grid points in each of the concentric ring areas based on the spherical distances.

[0071] In some embodiments, a central vector can be obtained from each typhoon calculation point to the typhoon center point, and the angle between each central vector and the brightness temperature gradient vector is an axial symmetry angle.

[0072] A data grid point 1 in a concentric annular region is taken as an example below to illustrate the specific process of calculating the axial symmetry angle of the data grid point 1 .

[0073] like Figure 5 As shown in the figure, assuming that the longitude and latitude data of data grid point 1 are (x1, y1), the position of the typhoon center is (a, b), and the brightness temperature gradient vector of data grid point 1 is (x, y), then a gradient point 1 is taken on the brightness temperature gradient vector (x, y) as (x1+0.001x, y1+0.001y). The spherical distance between the data grid point 1, the typhoon center and the gradient point 1 can be calculated according to the Haversine formula.

[0074] Assuming that the spherical distance between the data grid point 1 and the typhoon center is l1, the spherical distance between the data grid point 1 and the gradient point 1 is l2, and the spherical distance between the typhoon center and the gradient point 1 is l3, according to the spherical cosine theorem, we can get:

[0075] Where R is the radius of the earth and A1 is the axial symmetry angle of data grid point 1.

[0076] Therefore, through the above calculation process, the axial symmetry angles A1, A2, ...An corresponding to the n data grid points can be obtained.

[0077] For each concentric ring region, the corresponding axisymmetric angle variance and average deviation angle can be calculated according to the axisymmetric angles corresponding to the data grid points in the concentric ring region.

[0078] In addition, for each concentric ring region, the corresponding brightness temperature average value, brightness temperature variance, brightness temperature maximum value and brightness temperature minimum value can be calculated according to the brightness temperature data of the data grid points in the concentric ring region.

[0079] Through the above calculations, the typhoon intensity assessment parameters in each concentric ring area can be obtained.

[0080] S5. Use the brightness temperature data of the relevant data grid points, the location information of the typhoon center point and the typhoon intensity assessment parameters as current analysis data, and analyze the current analysis data based on the known relationship between historical analysis data and typhoon intensity to obtain a typhoon intensity assessment result.

[0081] Specifically, in order to comprehensively and accurately evaluate the typhoon intensity, the brightness temperature data of the relevant data grid points, the location information of the typhoon center point and the typhoon intensity assessment parameters described in this application are used as current analysis data for comprehensive analysis, so as to evaluate the typhoon intensity in order to obtain better assessment results.

[0082] In some embodiments, obtaining the evaluation result of typhoon intensity includes: obtaining typhoon symmetry based on the axisymmetric angle variance and the average deviation angle; obtaining typhoon brightness temperature characteristics based on the brightness temperature average value, the brightness temperature variance, the maximum brightness temperature and the minimum brightness temperature; using the brightness temperature data of the relevant data grid points, the position information of the typhoon center point, the typhoon symmetry and the typhoon brightness temperature characteristics as the current analysis data, and analyzing the current analysis data based on the known relationship between historical analysis data and typhoon intensity to obtain the evaluation result of typhoon intensity.

[0083] Among them, the symmetry of a typhoon refers to the degree of symmetry of its cloud structure in the horizontal direction. According to the symmetry of historical typhoons, it is known that a well-organized and strong typhoon often has a more rounded and symmetrical structure, showing good organization and strong rotational force, that is, the higher the symmetry of the typhoon, the greater the typhoon intensity. Therefore, when the current typhoon symmetry obtained according to the axisymmetric angle variance and the average deviation angle is higher, the assessed typhoon intensity is also greater.

[0084] Among them, according to the historical typhoon brightness temperature characteristics, it can be known that the temperature of the typhoon eye is higher than the temperature of the surrounding area and is circular, while the temperature of the eyewall area is low and cyclonic. That is, according to the brightness temperature average value, the brightness temperature variance, the brightness temperature maximum value and the brightness temperature minimum value, the current brightness temperature characteristics can be obtained, and the temperature change from the center point of the typhoon to the outside can be evaluated to determine whether there is an obvious eye and eyewall area. When the typhoon eye and eyewall areas are more obvious according to the current brightness temperature characteristics, the typhoon intensity is also greater.

[0085] Among them, the location information of the typhoon center is associated with the maximum sustained surface wind speed and average sea level pressure of the typhoon. The maximum sustained surface wind speed and average sea level pressure can be determined by the location information of the typhoon center, and according to historical data, the typhoon center is usually also the area with the highest wind speed and the lowest pressure. Therefore, according to the current location information of the typhoon center, the greater the maximum sustained surface wind speed and the smaller the average sea level pressure, the greater the typhoon intensity.

[0086] Among them, the cloud top temperature near the typhoon center can be estimated based on the brightness temperature data of the relevant data grid points. According to the historical brightness temperature data, it is known that when the cloud top temperature is lower, the convective activity is stronger, and the typhoon intensity is greater. Therefore, when the brightness temperature data of the relevant data grid points is lower, it means that the typhoon intensity is greater.

[0087] In fact, this application is based on the known relationship between historical analysis data and typhoon brightness to conduct a comprehensive analysis of the current analysis data obtained to evaluate the typhoon intensity. In some embodiments, in order to accurately obtain the evaluation level of typhoon intensity, a typhoon intensity evaluation model can also be established, that is, based on the known relationship between the above historical data and typhoon intensity, a model is established to evaluate the level of typhoon intensity, and the accuracy of the level of model evaluation is enhanced based on actual observation data to quantify the typhoon intensity, so as to better carry out targeted disaster prevention.

[0088] The protection scope of the typhoon intensity assessment method described in the embodiment of the present application is not limited to the execution order of the steps listed in the present embodiment. All solutions implemented by adding, reducing or replacing steps in the prior art based on the principles of the present application are included in the protection scope of the present application.

[0089] The embodiment of the present application also provides a typhoon intensity assessment system, which can implement the typhoon intensity assessment method described in the present application. However, the implementation device of the typhoon intensity assessment method described in the present application includes but is not limited to the structure of the typhoon intensity assessment system listed in the present embodiment. All structural deformations and replacements of the prior art made according to the principles of the present application are included in the protection scope of the present application.

[0090] Figure 6 The flowchart of the method for evaluating the typhoon intensity described in the embodiment of the present application is shown as follows: Figure 6 As shown, the embodiment of the present application further provides a typhoon intensity assessment system, the typhoon intensity assessment system comprising: The data module 41 is configured to obtain a satellite data set; the satellite data set includes brightness temperature data and longitude and latitude data of a plurality of data grid points; The typhoon center point module 42 is configured to determine a plurality of data grid points within the typhoon calculation area to obtain location information of the typhoon center point.

[0091] The segmentation module 43 is configured to intercept data grid points within a certain longitude and latitude range centered on the typhoon center point in the satellite data set as relevant data grid points, and divide the typhoon calculation area into multiple concentric ring areas based on the maximum value of the distance between the typhoon center point and the relevant data grid points.

[0092] The calculation module 44 is configured to calculate the typhoon intensity assessment parameters of each of the concentric ring areas.

[0093] The evaluation module 45 is configured to use the brightness temperature data of the relevant data grid points, the location information of the typhoon center point and the typhoon intensity evaluation parameters as current analysis data, and analyze the current analysis data based on the known relationship between historical analysis data and typhoon intensity to obtain an evaluation result of typhoon intensity.

[0094] Among them, the structures and principles of the data module 41, the typhoon center point module 42, the segmentation module 43, the calculation module 44, and the evaluation module 45 correspond one to one with the steps in the above-mentioned typhoon intensity evaluation method, so they are not repeated here.

[0095] This application can automatically use data collected by satellites to evaluate typhoon intensity in real time and continuously without being restricted by terrain, transportation and human activities, thereby realizing long-distance assessment of typhoon intensity with higher safety.

[0096] In the several embodiments provided in the present application, it should be understood that the disclosed system, device or method can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of modules / units is only a logical function division. There may be other division methods in actual implementation, such as multiple modules or units can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or modules or units, which can be electrical, mechanical or other forms.

[0097] The modules / units described as separate components may or may not be physically separated, and the components displayed as modules / units may or may not be physical modules, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules / units may be selected according to actual needs to achieve the purpose of the embodiments of the present application. For example, the functional modules / units in the various embodiments of the present application may be integrated into one processing module, or each module / unit may exist physically separately, or two or more modules / units may be integrated into one module / unit.

[0098] Those of ordinary skill in the art should further appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in the above description according to function. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0099] An embodiment of the present application also provides an electronic device, comprising: one or more processors; and one or more memories, wherein the memories store computer-readable codes, and when the computer-readable codes are run by the one or more processors, they execute the typhoon intensity assessment method as described in the present application.

[0100] The electronic device can be Figure 7 The exemplary computing device architecture shown in FIG. Figure 7 As shown, the exemplary computing device may include a bus 910, one or more GPUs 920, a read-only memory (ROM) 930, a random access memory (RAM) 940, a communication port 950 connected to a network, an input / output component 960, a hard disk 970, etc. The storage device in the exemplary computing device, such as ROM 930 or hard disk 970, can store various data or files used for computer processing and / or communication and program instructions executed by the GPU. The exemplary computing device may also include a user interface 980. Of course, Figure 7 The architecture shown is only exemplary and can be omitted according to actual needs when implementing different devices. Figure 7 One or more components of a computing device are shown.

[0101] The embodiment of the present application also provides a computer-readable storage medium, on which instructions are stored, and when the instructions are executed by a processor, the processor executes the typhoon intensity assessment method as described in the present application. A person of ordinary skill in the art can understand that all or part of the steps in the method for implementing the above embodiment can be executed by computer-readable instructions stored on a computer-readable storage medium. Computer-readable storage media include, but are not limited to, for example, volatile memory and / or non-volatile memory. Volatile memory may include, for example, random access memory (RAM) and / or cache memory (cache), etc. Non-volatile memory may include, for example, read-only memory (ROM), etc.

[0102] The embodiment of the present application also provides a computer program product or a computer program, which includes computer-readable instructions, and the computer-readable instructions are stored in a computer-readable storage medium. The processor of the computer device can read the computer-readable instructions from the computer-readable storage medium, and the processor executes the computer-readable instructions, so that the computer device executes the typhoon intensity assessment method described in the above embodiments.

[0103] The descriptions of the processes or structures corresponding to the above-mentioned figures have different emphases. For parts that are not described in detail in a certain process or structure, please refer to the relevant descriptions of other processes or structures.

[0104] The above embodiments are merely illustrative of the principles and effects of the present application and are not intended to limit the present application. Anyone familiar with the technology may modify or change the above embodiments without violating the spirit and scope of the present application. Therefore, all equivalent modifications or changes made by a person of ordinary skill in the art without departing from the spirit and technical ideas disclosed in the present application shall still be covered by the claims of the present application.

Claims

1. A method for evaluating typhoon intensity, characterized in that: The method comprises: Acquire a satellite data set; the satellite data set includes brightness temperature data and latitude and longitude data of a plurality of data grid points; Determine multiple data grid points within the typhoon calculation area to obtain the location information of the typhoon center point; intercepting data grid points within a certain longitude and latitude range centered on the typhoon center point from the satellite data set as relevant data grid points, and dividing the typhoon calculation area into a plurality of concentric ring areas based on the maximum value of the distance between the typhoon center point and the relevant data grid points; Calculating typhoon intensity assessment parameters for each of the concentric ring areas; The brightness temperature data of the relevant data grid points, the position information of the typhoon center point and the typhoon intensity assessment parameters are used as current analysis data, and the current analysis data is analyzed based on the known relationship between historical analysis data and typhoon intensity to obtain a typhoon intensity assessment result.

2. The method for evaluating typhoon intensity according to claim 1, characterized in that: Obtaining the location information of the typhoon center includes: Acquire a corresponding brightness temperature gradient vector based on the brightness temperature data of each data grid point in the typhoon calculation area; Acquire the extension line of each data grid point in the typhoon calculation area along the direction of each brightness temperature gradient vector; The number of the extension lines passed by each of the data grid points in the typhoon calculation area is obtained, and the position information of the typhoon center point is obtained based on the latitude and longitude data of the data grid points passing the most extension lines.

3. The method for evaluating typhoon intensity according to claim 2, characterized in that: Acquiring a corresponding brightness temperature gradient vector based on the brightness temperature data of each data grid point in the typhoon calculation area includes: Calculate the longitude change rate and latitude change rate of the brightness temperature data of each data grid point in the typhoon calculation area; The coordinates corresponding to the brightness temperature gradient vector are acquired based on the longitude change rate and the latitude change rate; wherein the longitude change rate is the longitude coordinate of the brightness temperature gradient vector, and the latitude change rate is the latitude coordinate of the brightness temperature gradient vector.

4. The method for evaluating typhoon intensity according to claim 1, characterized in that: Dividing the typhoon calculation area into a plurality of concentric ring areas based on the maximum value of the distance between the typhoon center point and the relevant data grid points includes: Calculating the distance between each of the relevant data grid points and the typhoon center point to obtain the maximum value of the distance; Dividing the maximum distance into equal parts to divide the typhoon calculation area into the same number of concentric ring areas; The distance between each of the data grid points in the typhoon calculation area and the typhoon center point is calculated to divide all the data grid points in the typhoon calculation area into corresponding concentric ring areas.

5. The method for evaluating typhoon intensity according to claim 1, characterized in that: Calculation of typhoon intensity assessment parameters for each of the concentric ring areas includes: Based on the brightness temperature data of the data grid points in each of the concentric ring regions, respectively calculate the corresponding brightness temperature average value, brightness temperature variance, brightness temperature maximum value and brightness temperature minimum value; and Based on the axisymmetric angles of the data grid points in each of the concentric circular ring regions, the corresponding axisymmetric angle variance and average deviation angle are calculated respectively.

6. The method for evaluating typhoon intensity according to claim 5, characterized in that: The method comprises: Acquire a corresponding center vector based on each data grid point in each of the concentric ring areas and the typhoon center point; Take a gradient point on the brightness temperature gradient vector corresponding to each data grid point in each of the concentric ring regions, and calculate the spherical distances between each data grid point in each of the concentric ring regions, the typhoon center point and the corresponding gradient points; The axisymmetric angles of the data grid points in each of the concentric circular ring regions are calculated based on the spherical distance correspondence.

7. The method for evaluating typhoon intensity according to claim 5, characterized in that: The assessment results of typhoon intensity include: Acquire typhoon symmetry based on the axisymmetric angle variance and the average deviation angle; Acquire typhoon brightness temperature characteristics based on the brightness temperature average value, the brightness temperature variance, the brightness temperature maximum value and the brightness temperature minimum value; The brightness temperature data of the relevant data grid points, the position information of the typhoon center point, the typhoon symmetry and the typhoon brightness temperature characteristics are used as the current analysis data, and the current analysis data is analyzed based on the known relationship between historical analysis data and typhoon intensity to obtain an assessment result of typhoon intensity.

8. A typhoon intensity assessment system, characterized in that: The system comprises: A data module is configured to obtain a satellite data set; the satellite data set includes brightness temperature data and latitude and longitude data of a plurality of data grid points; A typhoon center point module is configured to determine a plurality of data grid points within a typhoon calculation area to obtain location information of the typhoon center point; a segmentation module configured to intercept data grid points within a certain longitude and latitude range centered on the typhoon center point from the satellite data set as relevant data grid points, and to segment the typhoon calculation area into a plurality of concentric circular ring areas based on the maximum value of the distance between the typhoon center point and the relevant data grid points; A calculation module, configured to calculate typhoon intensity assessment parameters of each of the concentric ring areas; The evaluation module is configured to use the brightness temperature data of the relevant data grid points, the location information of the typhoon center point and the typhoon intensity evaluation parameters as current analysis data, and analyze the current analysis data based on the known relationship between historical analysis data and typhoon intensity to obtain an evaluation result of typhoon intensity.

9. An electronic device, characterized in that: include: one or more processors; and One or more memories, wherein the memories store computer-readable codes, and when the computer-readable codes are executed by the one or more processors, the method for evaluating the typhoon intensity according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores instructions, and when the instructions are executed by the processor, the processor executes the typhoon intensity assessment method according to any one of claims 1 to 7.

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