CN115993670A - Method, system, equipment and storage medium for predicting influence of tropical disturbance - Google Patents

Abstract

The invention relates to a method, system, device and storage medium for predicting the impact of tropical disturbances, wherein the method includes the following steps: determining the target sea area, obtaining historical tropical disturbance data in the target sea area; obtaining the numerical distribution of the historical tropical disturbance data, and obtaining In the numerical distribution of the disturbance data, select the value corresponding to the characteristic point in the sea level pressure numerical distribution as the sea level air pressure threshold, and select the value corresponding to the characteristic point in the wind speed numerical distribution as the wind speed threshold; obtain the weather forecast data, from the weather forecast data Obtain the air pressure field data within the target sea area at a specified time in the future, traverse the grid points that meet the sea level air pressure threshold, and link the acquired grid points to form the tropical disturbance range area at the specified time; obtained from the weather forecast data The wind speed data of each grid point in the tropical disturbance range area, based on the wind speed threshold to judge the influence range of the tropical disturbance at a specified time.

Description

A method, system, device and storage medium for predicting the impact of tropical disturbances

technical field

The invention relates to a tropical disturbance impact prediction method, system, equipment and storage medium, belonging to the technical field of meteorological prediction.

Background technique

A tropical disturbance is the embryonic state of a tropical cyclone, a group of thunderstorm clouds with no apparent organization that may have the opportunity to develop into a tropical cyclone.

At present, the main method of identifying tropical disturbances is through manual judgment. This method not only requires analysts to have professional meteorological knowledge, but also the analysis process is time-consuming and laborious, and the error of the analysis results may be large. In a short period of time, it is difficult to identify tropical disturbances and analyze trends through complex manual analysis and judgment.

Contents of the invention

In order to solve the above-mentioned problems in the prior art, the present invention proposes a method, system, device and storage medium for predicting the impact of tropical disturbances.

Technical scheme of the present invention is as follows:

On the one hand, the present invention proposes a method for predicting the impact of tropical disturbances, comprising the following steps:

Determine the target sea area and obtain historical tropical disturbance data in the target sea area;

Obtain the numerical distribution of historical tropical disturbance data, select the value corresponding to the characteristic point in the sea level pressure numerical distribution from the numerical distribution of historical tropical disturbance data as the sea level pressure threshold, and select the value corresponding to the characteristic point in the wind speed numerical distribution as wind speed threshold;

Obtain the weather forecast data, obtain the pressure field data within the target sea area at a specified time in the future from the weather forecast data, and traverse the grid points corresponding to the sea level pressure values that meet the sea level pressure threshold less than or equal to the sea level pressure threshold in the obtained pressure field data, and will get The grid points are linked to form the tropical disturbance range area at a specified moment;

The wind speed data of each grid point in the tropical disturbance range area at the specified time is obtained from the weather forecast data, and the influence range of the tropical disturbance at the specified time is judged based on the wind speed threshold and the wind speed data of the obtained grid points.

As a preferred embodiment, the value corresponding to the characteristic point in the sea level pressure numerical distribution is selected from the numerical distribution of the historical tropical disturbance data as the sea level air pressure threshold, and the value corresponding to the characteristic point in the wind speed numerical distribution is selected as the wind speed threshold The specific method is:

Obtain historical sea level pressure data from historical tropical disturbance data, and analyze the Gaussian distribution of historical sea level pressure data, and use the μ+2σ endpoint of the Gaussian distribution of historical sea level pressure data as the sea level pressure threshold;

Extract historical tropical disturbance wind force and wind circle radius data from historical tropical disturbance data and obtain the Gaussian distribution of historical wind speed within the wind circle range, and take the μ-2σ endpoint of the Gaussian distribution of historical wind speed within the wind circle range as the wind speed threshold;

Among them, μ represents the mean value and σ represents the standard deviation.

As a preferred embodiment, the method for judging the influence range of tropical disturbance at a specified moment based on the wind speed threshold and the obtained wind speed data of grid points is specifically:

Compare the wind speed data obtained at any grid point with the wind speed threshold, and perform binarization on the image based on the comparison result, specifically:

If the wind speed data of the grid point is greater than the threshold value, then the pixel value of the corresponding grid point is set to black, and if the wind speed data of the grid point is less than or equal to the threshold value, then the pixel value of the corresponding grid point is set to white;

Connect the grid points set to black to form a wind speed influence mask mask;

Obtain the minimum circumscribed circle of the wind speed influence mask, and use the coverage of the minimum circumscribed circle as the influence range of the tropical disturbance at a specified moment.

As a preferred embodiment, the method also includes the following steps:

Obtain the topographic shp data of the specified area and the topographic shp data of the affected range of tropical disturbances, and use the method of spatial distribution superposition analysis to determine whether there is surface intersection, so as to determine whether the predicted tropical disturbances will affect the specified area.

On the other hand, the present invention also proposes a system for predicting the impact of tropical disturbances, including:

The historical data acquisition module is used to determine the target sea area and obtain the historical tropical disturbance data of the target sea area;

The characteristic value selection module is used to obtain the numerical distribution of historical tropical disturbance data, select the value corresponding to the characteristic point in the numerical distribution of sea level air pressure from the numerical distribution of historical tropical disturbance data as the sea level air pressure threshold, and select the value in the numerical distribution of wind speed The value corresponding to the characteristic point of is used as the wind speed threshold;

The tropical disturbance area prediction module is used to obtain weather forecast data, obtain the pressure field data within the target sea area at a specified time in the future from the weather forecast data, and traverse the sea level pressure values in the obtained pressure field data that are less than or equal to the sea level pressure threshold Corresponding grid points, linking the obtained grid points to form the tropical disturbance range area at a specified moment;

The impact prediction module is used to obtain the wind speed data of each grid point in the tropical disturbance range area at a specified time from the weather forecast data, and judge the influence range of the tropical disturbance at a specified time based on the wind speed threshold and the wind speed data obtained at the grid point.

As a preferred embodiment, the feature value selection module specifically includes:

The sea level pressure threshold selection unit is used to obtain the historical sea level pressure data from the historical tropical disturbance data, and analyze the Gaussian distribution of the historical sea level pressure data, and take the μ+2σ endpoint of the Gaussian distribution of the historical sea level pressure data as the sea level barometric pressure threshold;

The wind speed threshold selection unit is used to extract the historical tropical disturbance wind force and wind circle radius data from the historical tropical disturbance data and obtain the Gaussian distribution of the historical wind speed within the wind circle range, and take the μ-2σ endpoint of the Gaussian distribution of the historical wind speed within the wind circle range as the wind speed threshold;

Among them, μ represents the mean value and σ represents the standard deviation.

As a preferred embodiment, the impact prediction module includes a mask generation unit and an influence range determination unit, wherein:

The mask generation unit is used to compare the acquired wind speed data of any grid point with the wind speed threshold, and perform binarization processing on the image based on the comparison result, specifically: if the wind speed data of the grid point is greater than the threshold, then Set the pixel value of the corresponding grid point to black. If the wind speed data of the grid point is less than or equal to the threshold value, set the pixel value of the corresponding grid point to white; link the grid points set to black to form the wind speed Affect mask masks;

The influence range determination unit is used to obtain the minimum circumscribed circle of the wind speed influence mask, and use the coverage range of the minimum circumscribed circle as the influence range of the tropical disturbance at a specified moment.

As a preferred embodiment, the system also includes a specified area impact judgment unit, which is used for:

Obtain the terrain shp data of the specified area and the terrain shp data of the range affected by the tropical disturbance, and use the method of spatial distribution superposition analysis to determine whether there is a surface intersection, so as to determine whether the predicted tropical disturbance will affect the specified area.

In yet another aspect, the present invention also proposes an electronic device, including a memory, a processor, and a computer program stored on the memory and operable on the processor. When the processor executes the program, any implementation of the present invention can be realized. The impact prediction method of the tropical disturbance described in the example.

In another aspect, the present invention also proposes a computer-readable storage medium, on which a computer program is stored, and when the program is executed by a processor, the method for predicting the impact of tropical disturbances as described in any embodiment of the present invention is implemented.

The present invention has following beneficial effect:

The invention relates to a tropical disturbance impact prediction method, system, equipment and storage medium, which automatically predicts the impact of future tropical disturbances based on meteorological data processing and image processing, can automatically identify the location of tropical disturbances, and analyze the location of tropical disturbances The development trend, as well as the possible impact on the designated area, has the characteristics of automation and high timeliness, which can prevent possible disasters in advance.

Description of drawings

FIG. 1 is a flow chart of the method in Embodiment 1 of the present invention.

Detailed ways

The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

It should be understood that the step numbers used herein are only for convenience of description, and are not intended to limit the execution order of the steps.

It should be understood that the terminology used in the description of the present invention is for the purpose of describing particular embodiments only and is not intended to limit the present invention. As used in this specification and the appended claims, the singular forms "a", "an" and "the" are intended to include plural referents unless the context clearly dictates otherwise.

The terms "comprising" and "comprising" indicate the presence of described features, integers, steps, operations, elements and/or components, but do not exclude the presence of one or more other features, integers, steps, operations, elements, components and/or The presence or addition of its collection.

The term "and/or" refers to any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

Embodiment one:

Referring to Figure 1, based on the technical problems in the background technology, this embodiment proposes a method for predicting the impact of tropical disturbances, including the following steps:

S100. Determine the target sea area, and obtain historical tropical disturbance data in the target sea area, for example, obtain historical tropical disturbance data within the Northwest Pacific Ocean to participate in calculation and analysis.

S200. Perform threshold analysis to obtain the numerical distribution of historical tropical disturbance data, obtain the numerical distribution of historical sea level air pressure from the numerical distribution of historical tropical disturbance data, and select the sea level air pressure corresponding to the feature point from the numerical distribution of historical sea level air pressure The value is used as the sea level pressure threshold thresholdSlp;

The numerical distribution of historical wind speed is obtained from the numerical distribution of historical tropical disturbance data, and the wind speed value corresponding to the feature point is selected from the numerical distribution of historical wind speed as the wind speed threshold thresholdWind.

S300. Obtain the weather forecast data, and obtain the pressure field data slpData within the range of the Northwest Pacific Ocean at the time ti in the future from the weather forecast data, and first determine whether the minimum pressure data minSlp within the range of the Northwest Pacific Ocean at the time ti is less than or equal to the sea level pressure threshold thresholdSlp: minSlp <=thresholdSlp; if yes, traverse and obtain the grid points corresponding to the sea-level pressure values in the pressure field data in the Northwest Pacific Ocean at time ti that meet the sea-level pressure threshold value (consistent with the judgment method of the above formula), and extract relevant information if it is satisfied , including the longitude, latitude, air pressure value, and time of the grid point, linking the obtained grid points to form the tropical disturbance range area at ti time, and taking the geometric center of the tropical disturbance range area as the tropical disturbance center point position; otherwise, take ti +1 moment to keep repeating the steps above.

S400. Obtain the wind field data at the time corresponding to the identified tropical disturbance from the weather forecast data, obtain the wind speed data of each grid point in the tropical disturbance range area at the corresponding time, and combine the wind speed threshold thresholdWind with the obtained wind speed data of the grid point Determine the influence range of tropical disturbance at a given moment.

As a preferred implementation of this embodiment, in step S200, the value corresponding to the feature point in the sea level air pressure numerical distribution is selected from the numerical distribution of the historical tropical disturbance data as the sea level air pressure threshold, and the value in the wind speed numerical distribution is selected The method of using the value corresponding to the feature point as the wind speed threshold is as follows:

S201. Obtain historical sea level pressure data from historical tropical disturbance data, and analyze the Gaussian distribution of historical sea level pressure data, and use the μ+2σ endpoint of the Gaussian distribution of historical sea level pressure data as the sea level pressure threshold; where μ represents Mean, σ denotes standard deviation.

S202. Similarly, extract historical tropical disturbance wind force and wind circle radius data from historical tropical disturbance data, and obtain the Gaussian distribution of historical wind speed within the wind circle range, and use the μ-2σ endpoint of the Gaussian distribution of historical wind speed within the wind circle range as Wind speed threshold; where μ represents the mean value and σ represents the standard deviation.

As a preferred implementation of this embodiment, in step S400, the method of judging the influence range of the tropical disturbance at a specified time based on the wind speed threshold and the obtained wind speed data of the grid point is specifically as follows:

S401. Comparing the acquired wind speed data of grid points in any tropical disturbance range area with the wind speed threshold, and binarizing the image based on the comparison result to generate a mask, which is a kind of image processing The processing operation, covering part of the image area, only retaining the image of a specific area of interest, the main step is to set the data greater than a certain threshold to 1, and other data to 0, so as to realize the process of image binarization; The concrete steps of this embodiment are:

If the wind speed data of the grid point is greater than the threshold value, then the pixel value of the corresponding grid point is set to black, and if the wind speed data of the grid point is less than or equal to the threshold value, then the pixel value of the corresponding grid point is set to white;

Link the grid points that are set to black to form a wind speed influence mask mask, and obtain the wind speed influence mask mask data;

S402. Obtain the minimum circumscribed circle of the wind speed influence mask by using an image contour processing method based on the wind speed influence mask data, and use the coverage of the minimum circumscribed circle as the influence range of the tropical disturbance at a specified moment.

As a preferred implementation of this embodiment, the method also includes the following steps:

S500. According to the shp data of China's administrative divisions and the shp data of the impact range of tropical disturbances, use the superposition analysis of spatial distribution to determine whether there is surface intersection, so as to determine whether the predicted tropical disturbances will affect my country's land areas. According to wind speed, air pressure, time and other information , analyze the areas affected by tropical disturbances, and propose relevant defense measures.

Based on the above embodiments, the present invention automatically predicts the impact of future tropical disturbances based on meteorological data processing and image processing, can automatically identify the location of tropical disturbances, analyze the development trend of tropical disturbances, and the possible impact on designated areas , It can carry out 24-hour uninterrupted automatic monitoring, which is more time-sensitive than manual analysis, and can prevent possible disasters in advance.

Embodiment two:

This embodiment proposes a tropical disturbance impact prediction system, including:

The historical data acquisition module is used to determine the target sea area and obtain the historical tropical disturbance data of the target sea area; this module is used to realize the function of step S100 in the first embodiment, and will not be repeated here;

The characteristic value selection module is used to obtain the numerical distribution of historical tropical disturbance data, select the value corresponding to the characteristic point in the numerical distribution of sea level air pressure from the numerical distribution of historical tropical disturbance data as the sea level air pressure threshold, and select the value in the numerical distribution of wind speed The value corresponding to the feature point is used as the wind speed threshold; this module is used to realize the function of step S200 in the first embodiment, and will not be repeated here;

The tropical disturbance area prediction module is used to obtain weather forecast data, obtain the pressure field data within the target sea area at a specified time in the future from the weather forecast data, and traverse the sea level pressure values in the obtained pressure field data that are less than or equal to the sea level pressure threshold Corresponding grid points, the acquired grid points are linked together to form the tropical disturbance range area at a specified moment; this module is used to realize the function of step S300 in the first embodiment, and will not be repeated here;

The impact prediction module is used to obtain the wind speed data of each grid point in the tropical disturbance range area at a specified time from the weather forecast data, and judge the influence range of the tropical disturbance at a specified time based on the wind speed threshold and the wind speed data of the obtained grid points; This module is used to realize the function of step S400 in the first embodiment, which will not be repeated here.

As a preferred implementation of this embodiment, the feature value selection module specifically includes:

The sea level pressure threshold selection unit is used to obtain the historical sea level pressure data from the historical tropical disturbance data, and analyze the Gaussian distribution of the historical sea level pressure data, and take the μ+2σ endpoint of the Gaussian distribution of the historical sea level pressure data as the sea level barometric pressure threshold;

The wind speed threshold selection unit is used to extract the historical tropical disturbance wind force and wind circle radius data from the historical tropical disturbance data and obtain the Gaussian distribution of the historical wind speed within the wind circle range, and take the μ-2σ endpoint of the Gaussian distribution of the historical wind speed within the wind circle range as the wind speed threshold;

Among them, μ represents the mean value and σ represents the standard deviation.

As a preferred implementation of this embodiment, the impact prediction module includes a mask generation unit and an influence range determination unit, wherein:

The mask generation unit is used to compare the acquired wind speed data of any grid point with the wind speed threshold, and perform binarization processing on the image based on the comparison result, specifically: if the wind speed data of the grid point is greater than the threshold, then Set the pixel value of the corresponding grid point to black. If the wind speed data of the grid point is less than or equal to the threshold value, set the pixel value of the corresponding grid point to white; link the grid points set to black to form the wind speed Affect mask masks;

The influence range determination unit is used to obtain the minimum circumscribed circle of the wind speed influence mask, and use the coverage range of the minimum circumscribed circle as the influence range of the tropical disturbance at a specified moment.

As a preferred implementation of this embodiment, the system also includes a designated area impact judgment unit, configured to:

Obtain the terrain shp data of the specified area and the terrain shp data of the range affected by the tropical disturbance, and use the method of spatial distribution superposition analysis to determine whether there is a surface intersection, so as to determine whether the predicted tropical disturbance will affect the specified area.

Embodiment three:

This embodiment proposes an electronic device, including a memory, a processor, and a computer program stored on the memory and operable on the processor. When the processor executes the program, the computer program described in any embodiment of the present invention is implemented. A method for predicting the effects of tropical disturbances.

Embodiment four:

This embodiment proposes a computer-readable storage medium on which a computer program is stored, and when the program is executed by a processor, the method for predicting the impact of a tropical disturbance as described in any embodiment of the present invention is implemented.

In the embodiments of the present application, "at least one" means one or more, and "multiple" means two or more. "And/or" describes the association relationship of associated objects, indicating that there may be three kinds of relationships, for example, A and/or B may indicate that A exists alone, A and B exist simultaneously, or B exists alone. Among them, A and B can be singular or plural. The character "/" generally indicates that the contextual objects are an "or" relationship. "At least one of the following" and similar expressions refer to any combination of these items, including any combination of single items or plural items. For example, at least one of a, b, and c can represent: a, b, c, a and b, a and c, b and c or a and b and c, where a, b, c can be single, or Can be multiple.

Those of ordinary skill in the art can appreciate that each unit and algorithm steps described in the embodiments disclosed herein can be realized by a combination of electronic hardware, computer software and electronic hardware. Whether these functions are executed by hardware or software depends on the specific application and design constraints of the technical solution. Skilled artisans may use different methods to implement the described functions for each specific application, but such implementation should not be regarded as exceeding the scope of the present application.

Those skilled in the art can clearly understand that for the convenience and brevity of the description, the specific working process of the above-described system, device and unit can refer to the corresponding process in the foregoing method embodiment, which will not be repeated here.

In several embodiments provided in this application, if any function is realized in the form of a software function unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or the part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including Several instructions are used to make a computer device (which may be a personal computer, a server, or a network device, etc.) execute all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage media include: U disk, mobile hard disk, read-only memory (Read-Only Memory; hereinafter referred to as: ROM), random access memory (Random Access Memory; hereinafter referred to as: RAM), magnetic disk or optical disc, etc. A medium on which program code can be stored.

The above is only an embodiment of the present invention, and does not limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made by using the description of the present invention and the contents of the accompanying drawings, or directly or indirectly used in other related technologies fields, all of which are equally included in the scope of patent protection of the present invention.

Claims (10)

1. A method for predicting the impact of tropical disturbances, comprising the following steps: Determine the target sea area and obtain historical tropical disturbance data in the target sea area; Obtain the numerical distribution of historical tropical disturbance data, select the value corresponding to the characteristic point in the sea level pressure numerical distribution from the numerical distribution of historical tropical disturbance data as the sea level pressure threshold, and select the value corresponding to the characteristic point in the wind speed numerical distribution as wind speed threshold; Obtain the weather forecast data, obtain the pressure field data within the target sea area at a specified time in the future from the weather forecast data, and traverse the grid points corresponding to the sea level pressure values that meet the sea level pressure threshold less than or equal to the sea level pressure threshold in the obtained pressure field data, and will get The grid points are linked to form the tropical disturbance range area at a specified moment; The wind speed data of each grid point in the tropical disturbance range area at the specified time is obtained from the weather forecast data, and the influence range of the tropical disturbance at the specified time is judged based on the wind speed threshold and the wind speed data of the obtained grid points. 2. the impact prediction method of a kind of tropical disturbance according to claim 1, it is characterized in that, described from the numerical distribution of historical tropical disturbance data, select the value corresponding to the feature point in the sea level air pressure numerical distribution as sea level air pressure Threshold value, and the method of selecting the value corresponding to the characteristic point in the wind speed numerical distribution as the wind speed threshold value is as follows: Obtain historical sea level pressure data from historical tropical disturbance data, and analyze the Gaussian distribution of historical sea level pressure data, and use the μ+2σ endpoint of the Gaussian distribution of historical sea level pressure data as the sea level pressure threshold; Extract historical tropical disturbance wind force and wind circle radius data from historical tropical disturbance data and obtain the Gaussian distribution of historical wind speed within the wind circle range, and take the μ-2σ endpoint of the Gaussian distribution of historical wind speed within the wind circle range as the wind speed threshold; Among them, μ represents the mean value and σ represents the standard deviation. 3. The impact prediction method of a kind of tropical disturbance according to claim 1, it is characterized in that, the method for judging the scope of influence of tropical disturbance at a specified time based on the wind speed threshold and the wind speed data of the grid points obtained is specifically: Compare the wind speed data obtained at any grid point with the wind speed threshold, and perform binarization on the image based on the comparison result, specifically: If the wind speed data of the grid point is greater than the threshold value, then the pixel value of the corresponding grid point is set to black, and if the wind speed data of the grid point is less than or equal to the threshold value, then the pixel value of the corresponding grid point is set to white; Connect the grid points set to black to form a wind speed influence mask mask; Obtain the minimum circumscribed circle of the wind speed influence mask, and use the coverage of the minimum circumscribed circle as the influence range of the tropical disturbance at a specified moment. 4. the impact prediction method of a kind of tropical disturbance according to claim 1, is characterized in that, this method also comprises the following steps: Obtain the topographic shp data of the specified area and the topographic shp data of the affected range of tropical disturbances, and use the method of spatial distribution superposition analysis to determine whether there is surface intersection, so as to determine whether the predicted tropical disturbances will affect the specified area. 5. A system for predicting the impact of tropical disturbances, comprising: The historical data acquisition module is used to determine the target sea area and obtain the historical tropical disturbance data of the target sea area; The characteristic value selection module is used to obtain the numerical distribution of historical tropical disturbance data, select the value corresponding to the characteristic point in the numerical distribution of sea level air pressure from the numerical distribution of historical tropical disturbance data as the sea level air pressure threshold, and select the value in the numerical distribution of wind speed The value corresponding to the characteristic point of is used as the wind speed threshold; The tropical disturbance area prediction module is used to obtain weather forecast data, obtain the pressure field data within the target sea area at a specified time in the future from the weather forecast data, and traverse the sea level pressure values in the obtained pressure field data that are less than or equal to the sea level pressure threshold Corresponding grid points, linking the obtained grid points to form the tropical disturbance range area at a specified moment; The impact prediction module is used to obtain the wind speed data of each grid point in the tropical disturbance range area at a specified time from the weather forecast data, and judge the influence range of the tropical disturbance at a specified time based on the wind speed threshold and the wind speed data of the obtained grid points. 6. The impact prediction system of a kind of tropical disturbance according to claim 5, is characterized in that, described characteristic value selection module specifically comprises: The sea level pressure threshold selection unit is used to obtain the historical sea level pressure data from the historical tropical disturbance data, and analyze the Gaussian distribution of the historical sea level pressure data, and take the μ+2σ endpoint of the Gaussian distribution of the historical sea level pressure data as the sea level barometric pressure threshold; The wind speed threshold selection unit is used to extract the historical tropical disturbance wind force and wind circle radius data from the historical tropical disturbance data and obtain the Gaussian distribution of the historical wind speed within the wind circle range, and take the μ-2σ endpoint of the Gaussian distribution of the historical wind speed within the wind circle range as the wind speed threshold; Among them, μ represents the mean value and σ represents the standard deviation. 7. The impact prediction system of a kind of tropical disturbance according to claim 5, wherein the impact prediction module includes a mask generation unit and an influence range determination unit, wherein: The mask generation unit is used to compare the acquired wind speed data of any grid point with a wind speed threshold, and perform binarization processing on the image based on the comparison result, specifically: if the wind speed data of the grid point is greater than the threshold, then Set the pixel value of the corresponding grid point to black, if the wind speed data of the grid point is less than or equal to the threshold value, set the pixel value of the corresponding grid point to white; link the grid points set to black to form the wind speed Affect mask masks; The influence range determination unit is used to obtain the minimum circumscribed circle of the wind speed influence mask, and use the coverage range of the minimum circumscribed circle as the influence range of the tropical disturbance at a specified moment. 8. The impact prediction system of a kind of tropical disturbance according to claim 1, characterized in that, the system also includes a designated area impact judgment unit for: Obtain the terrain shp data of the specified area and the terrain shp data of the range affected by the tropical disturbance, and use the method of spatial distribution superposition analysis to determine whether there is a surface intersection, so as to determine whether the predicted tropical disturbance will affect the specified area. 9. An electronic device, comprising a memory, a processor, and a computer program stored on the memory and operable on the processor, characterized in that, when the processor executes the program, any one of claims 1 to 4 is realized. The method for predicting the impact of tropical disturbances described in the item. 10. A computer-readable storage medium, on which a computer program is stored, wherein when the program is executed by a processor, the method for predicting the impact of tropical disturbances according to any one of claims 1 to 4 is implemented.

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