Weather data processing method and system

Abstract

The present invention provides a weather data processing method and system. Accurate weather data can provide people with a reliable basis for decision-making. Therefore, it is of great significance to improve the accuracy of weather data. The real-time cloud area is processed for regional changes based on the regional change rate to obtain the splitting level of the broadcast area; the broadcast area is divided according to the division direction and the geographical information in the broadcast area to obtain multiple attenuation areas, and the real-time wind speed is attenuated based on the attenuation area to obtain the predicted wind speed; the cloud path trajectory of the real-time cloud area is determined based on the real-time wind direction and the real-time wind speed, and the broadcast area is updated according to the splitting level, the predicted wind speed and the cloud path trajectory to obtain a cloud path display map. The area can be dynamically divided and broadcasted according to the actual change trend of the cloud layer, thereby better improving the accuracy of weather data.

Description

Technical Field

[0001] The invention relates to data processing technology, and in particular to a weather data processing method. Background Art

[0002] With the rapid development of society and the continuous advancement of science and technology, people are increasingly dependent on weather information. Accurate weather data can not only provide a reliable basis for decision-making in daily travel, agricultural production, aviation and navigation, but also play a key role in disaster warning and environmental protection. Therefore, improving the accuracy of weather data is of great significance.

[0003] At present, the prediction and broadcasting of weather data usually adopts a relatively simple regional division method and then broadcasts it. For example, the region is divided and broadcasted according to the direction or fixed longitude and latitude grid. For example, heavy rain in the eastern region fails to fully consider the actual changing trend of the clouds and the relationship between regional division, which often leads to large deviations from the actual situation.

[0004] Therefore, how to dynamically divide and broadcast regions based on the actual changing trends of clouds, so as to better improve the accuracy of weather data, has become an urgent problem to be solved. Summary of the invention

[0005] The embodiment of the present invention provides a weather data processing method, which can dynamically divide and broadcast regions according to the actual change trend of clouds, thereby improving the accuracy of weather data.

[0006] A first aspect of an embodiment of the present invention provides a weather data processing method, comprising:

[0007] Based on the regional change rate, the real-time cloud area is processed for regional changes to obtain the split level of the broadcast area;

[0008] The broadcast area is divided according to the division direction and the geographical information in the broadcast area to obtain multiple attenuation areas, and the real-time wind speed is attenuated based on the attenuation areas to obtain the predicted wind speed;

[0009] The cloud path trajectory of the real-time cloud area is determined based on the real-time wind direction and real-time wind speed. The broadcast area is updated according to the split level, predicted wind speed and cloud path trajectory to obtain a cloud path display map.

[0010] Optionally, in a possible implementation manner of the first aspect, performing regional change processing on the real-time cloud layer area based on the regional change rate to obtain a sub-splitting level of the broadcast area includes:

[0011] The changed area is obtained by multiplying the predicted duration and the regional change rate, and the predicted area is obtained based on the difference between the real-time area and the changed area of ​​the real-time cloud area;

[0012] The split level of the reporting area is determined based on a level comparison table of the predicted area and the reporting area, wherein the level comparison table includes a one-to-one correspondence between the area intervals and the split levels.

[0013] Optionally, in a possible implementation manner of the first aspect, dividing the broadcast area according to the division direction and the geographical information in the broadcast area to obtain a plurality of attenuation areas includes:

[0014] Determine the division direction according to the orthogonal direction of the real-time wind direction;

[0015] Merge adjacent and similar geographic information in the reporting area to obtain multiple merged terrain areas, and construct a division coordinate system in the reporting area with the real-time wind direction as the positive direction of the longitudinal coordinate axis;

[0016] Determine a coordinate point corresponding to an extreme value of the ordinate of the merged terrain area in the primary division coordinate system as a first division point, construct a first division line at the first division point based on the division direction, and divide the broadcast area according to the first division line to obtain a plurality of division areas;

[0017] Taking the division direction as the positive direction of the longitudinal coordinate axis, a secondary division coordinate system is constructed in the broadcast area, and the coordinate point corresponding to the longitudinal coordinate extreme value of each merged terrain area in each division area in the secondary division coordinate system is determined as the second division point;

[0018] A second dividing line is constructed at the second dividing point based on the real-time wind direction, and the broadcast area is divided twice according to the second dividing line to obtain a plurality of attenuation areas.

[0019] Optionally, in a possible implementation manner of the first aspect, the merging of adjacent and same type of geographic information in the broadcast area to obtain multiple merged terrain areas includes:

[0020] Acquire areas corresponding to the same type of geographic information in the broadcast area as similar areas, and determine the center points of the similar areas as similar midpoints;

[0021] Determine the farthest distance between the regional point and the midpoint of the same category in each similar area as the construction radius, and generate the parcel location area corresponding to the similar area based on the construction radius and the midpoint of the same category;

[0022] The package location area is magnified based on a preset search multiple to obtain a search area, and the package location areas corresponding to the intersecting search areas are used as areas to be merged;

[0023] Connect the centers of adjacent areas to be merged to obtain a center connection line, and select the smallest radius of two adjacent areas to be merged as the translation distance;

[0024] The circle center connection line is translated and copied to both sides according to the translation distance to obtain a merged line, and adjacent areas to be merged are merged based on the merged line to obtain a plurality of merged terrain areas.

[0025] Optionally, in a possible implementation manner of the first aspect, performing attenuation processing on the real-time wind speed based on the attenuation area to obtain the predicted wind speed includes:

[0026] Attenuation areas adjacent to the real-time wind direction are counted sequentially, and multiple rows of regional attenuation sequences are obtained;

[0027] The real-time wind speed is attenuated according to the pixel distribution ratio of the geographical information of the corresponding attenuation area in the regional attenuation sequence to obtain the predicted wind speed.

[0028] Optionally, in a possible implementation manner of the first aspect, the attenuation processing is performed on the real-time wind speed according to the pixel distribution ratio of the geographic information of the corresponding attenuation area in the regional attenuation sequence to obtain the predicted wind speed, including:

[0029] The first attenuation region in the region attenuation sequence is obtained as the first region, and the number of pixel points corresponding to each type of geographic information in the first region is counted as the number of type pixel points;

[0030] Counting the number of pixels in the first area to obtain the number of regional pixels, and obtaining the type number ratio according to the ratio of the number of pixels of each type to the number of pixels of the area;

[0031] Retrieving the attenuation weight value corresponding to the corresponding type of geographic information, obtaining the sub-attenuation coefficient of the first area according to the product of the type quantity ratio and the attenuation weight value, and summing the sub-attenuation coefficients to obtain the comprehensive attenuation coefficient of the first area;

[0032] Based on the product of the comprehensive attenuation coefficient and the preset attenuation wind speed, an actual attenuation wind speed is obtained;

[0033] According to the difference between the real-time wind speed and the actual attenuation wind speed, the predicted wind speed of the first area is obtained, the first attenuation area in the attenuation sequence is deleted and updated, and the predicted wind speed is used as the current real-time wind speed. The above steps of obtaining the predicted wind speed are repeated until there is no attenuation area in the attenuation sequence, and the predicted wind speed corresponding to each attenuation area is obtained.

[0034] Optionally, in a possible implementation manner of the first aspect, determining a cloud path trajectory of a real-time cloud layer area based on the real-time wind direction and the real-time wind speed includes:

[0035] Get the real-time position of the real-time cloud area, and generate the initial cloud path trajectory based on the real-time position and real-time wind direction;

[0036] Based on the difference between the real-time area and the minimum value in the smallest area interval, a total changed area is obtained;

[0037] Obtaining a total change duration according to the ratio of the total change area to the regional change rate;

[0038] Obtaining a change distance based on the product of the real-time wind speed and the total change duration;

[0039] Taking the real-time position as the starting point, the initial cloud path trajectory is intercepted and processed according to the change distance to obtain the cloud path trajectory of the real-time cloud layer area.

[0040] Optionally, in a possible implementation manner of the first aspect, updating the broadcast area according to the split level, the predicted wind speed, and the cloud path trajectory to obtain the cloud path display map includes:

[0041] The level areas in the broadcast area are split according to the split level, and the predicted wind speed and cloud path trajectory are updated to the corresponding positions in the broadcast area, and the cloud path display map is obtained and sent to the management end for display.

[0042] Optionally, in a possible implementation of the first aspect, the method further includes:

[0043] The area passed by the cloud path in the cloud path display diagram is obtained as the affected area, and the remaining area is taken as the unaffected area;

[0044] Determine the terrain height in the affected area, determine the terrain height in the affected area, and regard the area in the affected area with a terrain height greater than a preset height as a non-waterlogging area, and regard the rest of the area in the affected area as a waterlogging area;

[0045] Obtaining the predicted wind speed in the non-waterlogged area and the duration of the predicted wind speed, and retrieving a dryness weight value corresponding to the predicted wind speed;

[0046] Based on the product of the dryness weight value and the corresponding predicted wind speed, a unit dryness coefficient is obtained, and according to the product of the unit dryness coefficient and the duration, a dryness value corresponding to the non-waterlogged area is obtained;

[0047] When it is determined that the dryness value is greater than the preset dryness value, the corresponding non-water accumulation area is used as a selection area, and a dry area is obtained according to the selection area and the unaffected area;

[0048] The camping area in the broadcast area is retrieved, and the push area is obtained according to the intersection of the dry area and the camping area.

[0049] A second aspect of an embodiment of the present invention provides a weather data processing system, comprising:

[0050] The splitting module is used to process the regional changes of the real-time cloud area based on the regional change rate and obtain the splitting level of the broadcast area;

[0051] A division module is used to divide the broadcast area according to the division direction and the geographical information in the broadcast area to obtain multiple attenuation areas, and perform attenuation processing on the real-time wind speed based on the attenuation areas to obtain the predicted wind speed;

[0052] The update module is used to determine the cloud path trajectory of the real-time cloud area based on the real-time wind direction and real-time wind speed, and update the broadcast area according to the split level, predicted wind speed and cloud path trajectory to obtain a cloud path display map.

[0053] According to a third aspect of an embodiment of the present invention, there is provided an electronic device, comprising: a memory, a processor and a computer program, wherein the computer program is stored in the memory, and the processor runs the computer program to execute the first aspect of the present invention and various methods that may be involved in the first aspect.

[0054] According to a fourth aspect of an embodiment of the present invention, a storage medium is provided, in which a computer program is stored. When the computer program is executed by a processor, it is used to implement the first aspect of the present invention and various methods that may be involved in the first aspect.

[0055] The beneficial effects of the present invention are as follows:

[0056] 1. The present invention determines the splitting level of the broadcast area by performing regional change processing on the real-time cloud area based on the regional change rate, divides the attenuation area according to the division direction and geographical information to process the real-time wind speed to obtain the predicted wind speed, and then determines the cloud path trajectory in combination with the real-time wind direction and wind speed, and then updates the broadcast area to obtain the cloud path display map. This series of operations dynamically divides and broadcasts the area according to the actual change trend of the cloud layer, breaking the limitations of traditional simple regional division broadcasting, fully considering the dynamic changes of the cloud layer, the impact of geographical factors on wind speed, etc., so that the weather data can be more in line with the actual situation, greatly improving the accuracy of the weather data.

[0057] 2. The present invention calculates the change area according to the prediction duration and the regional change rate, obtains the predicted area in combination with the real-time area, and then uses the grade comparison table to determine the split level. This method uses scientific calculation methods and historical data experience to more accurately determine the split level of the broadcast area based on the real-time cloud area changes, making the broadcast area division more reasonable and detailed, and can provide users with forecast content that is more in line with actual weather conditions, meet users' needs for refined weather services, determine the division direction according to the orthogonal direction of the real-time wind direction, merge the geographic information of the broadcast area, construct a coordinate system, determine the division points and division lines, and finely divide the broadcast area into multiple attenuation areas. This division method fully considers the impact of geographic information on wind speed, makes the geographical features in each attenuation area relatively uniform, lays the foundation for accurate wind speed attenuation processing, greatly improves the accuracy of wind speed prediction, provides more reliable wind speed information for related industries and users, and reduces the risks and losses caused by inaccurate wind speed prediction.

[0058] 3. The present invention splits the reporting area level area according to the split level, updates the predicted wind speed and cloud path trajectory to the corresponding position and displays them on the management end. This method makes the display of meteorological information more detailed, and can be adaptively split as the cloud area changes, allowing users to intuitively understand the wind speed changes and cloud movement paths in different areas, and through the analysis of the cloud path display map, divide the affected area and the unaffected area, and then determine the waterlogged area and non-waterlogged area according to the terrain height, and calculate the dryness value based on the predicted wind speed, duration and dryness weight value of the non-waterlogged area, screen out the dry area, and finally take the intersection with the camping area to get the push area. This series of operations comprehensively considers meteorological and topographical factors, and more accurately recommends suitable areas for users with camping needs. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] Figure 1 A flow chart of a weather data processing method provided by the present invention;

[0060] Figure 2 A schematic diagram of a package positioning area provided by the present invention;

[0061] Figure 3 A schematic diagram of determining a region to be merged provided by the present invention;

[0062] Figure 4 A schematic diagram of a combined terrain area provided by the present invention;

[0063] Figure 5 A structural schematic diagram of a weather data processing system provided by the present invention;

[0064] Figure 6 A schematic diagram of the hardware structure of an electronic device provided by the present invention. DETAILED DESCRIPTION

[0065] The technical solution of the present invention is described in detail with specific embodiments below. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described in detail in some embodiments.

[0066] The present invention provides a weather data processing method, such as Figure 1 As shown, steps S1-S3 are included:

[0067] S1, based on the regional change rate, the real-time cloud area is processed for regional changes to obtain the split level of the broadcast area.

[0068] At present, the forecast of weather data is relatively rough. Usually, the entire area is taken as the weather impact area. For example, the weather in city-level area A is heavy rain. Or it is reported based on the distribution in the area. For example, there is heavy rain in the eastern part of city-level area A and light rain in the western part. However, the above impact forecast is relatively rough and cannot make adaptive changes to the region based on the actual changes in the clouds. As a result, when heavy rain is predicted in the eastern region, some areas in the east do not rain and are not affected.

[0069] It should be noted that in weather data processing, changes in cloud areas have a significant impact on weather conditions. For example, in rainy weather, the cloud area will gradually decrease over time, and the corresponding affected area will also become smaller. In order to make weather reports more accurately, it is necessary to reasonably divide the reporting area according to the changes in the real-time cloud area. By processing the real-time cloud area based on the regional change rate to determine the split level of the reporting area, the forecast division can be made more scientific and detailed, thereby providing users with more accurate and targeted weather information.

[0070] The regional change rate refers to the change ratio or rate of the area of ​​the real-time cloud area per unit time. It can be calculated by comparing the cloud area data at different times, reflecting the dynamic change degree of the cloud area. The data can be obtained by automatically processing and calculating the remote sensing data collected by the server.

[0071] The real-time cloud area refers to the area corresponding to the actual clouds at the current moment, and its location and range information can be obtained through satellite cloud images, weather radar and other means.

[0072] The broadcast area is the geographical scope where weather information broadcast is required, which is usually a larger administrative area or a specific geographical area, such as a city-level area, A city-level area.

[0073] Split level: indicates the degree of segmentation of the broadcast area, for example, towns and streets. The more sub-areas the broadcast area is divided into, the more detailed they are.

[0074] Specifically, we first analyze the regional change rate of the real-time cloud area, which reflects the dynamic changes of the cloud area within a certain period of time. Based on the change rate, we process the real-time cloud area to obtain the changes in the area corresponding to the cloud. Finally, we determine the split level of the broadcast area based on the changed area. The smaller the area of ​​the cloud, the smaller the corresponding split level, such as towns and streets, which means that the broadcast area is divided more finely.

[0075] In some embodiments, step S1 (performing regional change processing on the real-time cloud layer area based on the regional change rate to obtain the sub-division level of the broadcast area) includes S11-S12:

[0076] S11, obtaining the changed area according to the product of the predicted time and the regional change rate, and obtaining the predicted area based on the difference between the real-time area and the changed area of ​​the real-time cloud area.

[0077] Among them, the prediction duration is a pre-set time length used to predict real-time cloud area changes. It can be adjusted according to different weather conditions and forecast requirements. For example, a shorter prediction duration can be set when the weather changes rapidly.

[0078] The real-time area refers to the area actually occupied by the real-time cloud area at the current moment, which can be obtained through technical means such as satellite cloud images.

[0079] Specifically, we first obtain the two key parameters of forecast duration and regional change rate, and multiply them to get the change area, which reflects the area change of the real-time cloud area during the forecast duration. Then we subtract the change area from the real-time area to get the forecast area, which reflects the possible size of the cloud area in the future.

[0080] S12, determining the split level of the broadcast area based on a level comparison table of the predicted area and the broadcast area, wherein the level comparison table includes a one-to-one correspondence between the area intervals and the split levels.

[0081] Among them, the level comparison table is a table that records the one-to-one correspondence between area intervals and split levels. It is formulated based on a large amount of historical meteorological data and actual weather forecasting experience. It is mainly used to determine the split level of the broadcast area based on the predicted area. For example, the larger the predicted area, the larger the corresponding split level, in units of cities or districts, and the smaller the predicted area, the smaller the corresponding split level, in units of towns and streets, etc.

[0082] The split level refers to the degree to which the broadcast area is subdivided.

[0083] It is understandable that after the predicted area is obtained, it is matched with a pre-defined level comparison table. The level comparison table clearly specifies the split levels corresponding to different area intervals. By finding the area interval where the predicted area is located, the corresponding split level of the broadcast area can be determined.

[0084] Through the above method, the split level of the broadcast area can be determined more accurately according to the changes in the real-time cloud area. This makes the division of weather broadcast areas more reasonable and refined, helps to improve the accuracy and pertinence of weather information, and can provide users with forecast content that is more in line with actual weather conditions, meeting users' needs for refined weather services.

[0085] S2, dividing the broadcast area according to the division direction and the geographical information in the broadcast area to obtain a plurality of attenuation areas, performing attenuation processing on the real-time wind speed based on the attenuation areas to obtain a predicted wind speed.

[0086] It should be noted that traditional weather data processing often ignores the geographical information in the broadcast area and the differences in the impact of different regions on wind speed when predicting wind speed. In most cases, the wind speed is simply inferred based on the overall meteorological data, without considering that geographical factors such as topography will have different effects on wind speed, such as attenuation or enhancement. For example, different environments such as mountains and buildings will cause wind speed to show significantly different changes in different regions. If these factors are not accurately considered, the wind speed forecast results will deviate greatly from the actual situation, resulting in the wind speed part of the weather information being inaccurate and unable to meet the user's demand for accurate wind speed prediction.

[0087] Among them, the division direction is the specific direction for dividing the broadcast area, which is related to the real-time wind direction factor. By reasonably determining the division direction, the broadcast area can be better divided in a targeted manner in combination with geographic information to analyze the impact of different areas on wind speed.

[0088] Geographic information refers to various geographical features within the broadcast area, including but not limited to buildings, mountains, etc. These geographical information will have different degrees of impact on wind speed and are an important basis for dividing attenuation areas.

[0089] The attenuation area is a multiple sub-area obtained by dividing the broadcast area according to the division direction and geographical information. Each sub-area has different attenuation characteristics for real-time wind speed due to different geographical information. In these areas, the wind speed will change due to factors such as geographical obstruction and friction.

[0090] Real-time wind speed is the wind speed value actually measured by meteorological monitoring equipment (such as anemometers, etc.) at the current moment. It reflects the current flow speed of the atmosphere and is the basic data for wind speed attenuation processing.

[0091] The predicted wind speed is the value obtained after the real-time wind speed is attenuated in different attenuation areas. This value is closer to the future wind speed conditions in different areas under actual conditions, providing users with more accurate wind speed prediction information.

[0092] In some embodiments, step S2 (dividing the broadcast area according to the division direction and the geographical information in the broadcast area to obtain multiple attenuation areas) includes S21-S25:

[0093] S21, determining a division direction according to an orthogonal direction of the real-time wind direction.

[0094] Among them, the real-time wind direction is the direction of atmospheric flow obtained by meteorological monitoring equipment at the current moment. It is an important reference for determining the division direction. The real-time wind direction affects the flow path of the air and the direction in which the wind speed is affected by geographical factors.

[0095] The orthogonal direction is the direction that forms a 90-degree angle with the real-time wind direction. In this scheme, the orthogonal direction of the real-time wind direction is selected as the division direction in order to divide the area according to the horizontal direction of the wind direction, because buildings or terrain in the horizontal direction will have an impact on the wind force, so as to better analyze the differences in the impact of different geographical areas on wind speed.

[0096] S22, merging adjacent and similar geographic information in the reporting area to obtain a plurality of merged terrain areas, and constructing a division coordinate system in the reporting area with the real-time wind direction as the positive direction of the longitudinal coordinate axis.

[0097] Among them, geographical features will have different degrees of impact on wind speed through blocking and other means.

[0098] The merged terrain area is an area formed by merging adjacent areas with the same geographic information type in the broadcast area.

[0099] Specifically, the server processes the geographic information and merges adjacent geographic information of the same type into merged terrain areas. For example, several adjacent forest areas are merged into one forest merged terrain area, and multiple urban buildings are merged into one merged terrain area, thereby obtaining multiple merged terrain areas.

[0100] Subsequently, a division coordinate system will be constructed with the real-time wind direction as the positive longitudinal axis to provide a coordinate reference frame for the subsequent determination of division points and division lines. The origin of the coordinates can be any point selected. That is, the coordinate system for the initial division is constructed in the broadcast area with the real-time wind direction as the positive longitudinal axis.

[0101] In some embodiments, step S22 (merging adjacent and similar geographic information in the broadcast area to obtain multiple merged terrain areas) includes S221-S225:

[0102] S221, obtaining areas corresponding to the same type of geographic information in the broadcast area as similar areas, and determining the center points of the similar areas as similar midpoints.

[0103] It is worth mentioning that, generally speaking, terrain areas such as buildings and forests are close to each other and usually exist in concentrated areas. Therefore, adjacent and close areas of the same type can be merged.

[0104] It should be noted that in order to process geographic information more finely and improve the accuracy of wind speed prediction, a series of operations are performed on the same type of geographic information areas, including determining the center point, generating package positioning areas, searching for intersecting areas, and constructing merge lines, so that adjacent and potentially related geographic information areas of the same type are merged to form a more representative merged terrain area, so as to more accurately analyze the impact of different geographic areas on wind speed.

[0105] The same type of geographic information refers to information with the same geographic features in the broadcast area, such as forests, buildings, etc. The same type of geographic information has similar characteristics in affecting wind speed.

[0106] The same type of area is composed of areas corresponding to the same type of geographic information in the broadcast area. These areas are consistent in geographical features and are the basic units for subsequent processing.

[0107] The same type midpoint is the center point of the same type area, which is the geometric center position of the area. By determining the same type midpoint, a reference point can be provided for the subsequent generation of the package positioning area. The center point can be obtained by obtaining the average value of the sum of the horizontal and vertical coordinates.

[0108] Specifically, firstly, the areas corresponding to the same type of geographic information are extracted from the broadcast area as the same type of areas, and their center points, i.e., the same type of midpoints, are determined to provide a basic location reference for subsequent operations.

[0109] S222, determining the farthest distance between the regional point in each similar region and the similar midpoint as a construction radius, and generating a package location area corresponding to the similar region based on the construction radius and the similar midpoint.

[0110] Among them, the regional point is any point in the same region. When determining the construction radius, it is necessary to consider the distance between all regional points in the same region and the same midpoint.

[0111] The construction radius is the farthest distance between the regional point and the midpoint of the same type of area. It is used to describe the size of the same type of area and is a key parameter for generating a parcel location area.

[0112] The parcel location area is an area generated based on the construction radius and the midpoint of the same category. It can usually be understood as a circular area with the midpoint of the same category as the center and the construction radius as the radius. This area can completely wrap the same category area, so that the area can be used to represent the same category area.

[0113] The construction radius is obtained by calculating the farthest distance between the regional point and the midpoint of the same type in the same area, and then the package positioning area is generated by combining the midpoint of the same type. The package positioning area can be used to represent the same type of area, which is convenient for subsequent merging of areas. For example, see Figure 2 For a relatively irregular building area, the center point of the area can be obtained, and finally the radius is determined according to the farthest area point to construct the package positioning area that wraps it.

[0114] S223, the package location area is magnified based on a preset search multiple to obtain a search area, and the package location areas corresponding to the intersecting search areas are used as areas to be merged.

[0115] The preset search multiple is a pre-set value used to magnify the parcel location area. By magnifying the parcel location area, the search range can be expanded to find adjacent areas that may be associated. For example, it can be 1.1, 1.2, etc., which is set according to actual conditions.

[0116] The search area is the area obtained by magnifying the package location area according to the preset search multiple. Search is performed within this area to find the intersecting package location areas.

[0117] The area to be merged is the parcel location area corresponding to the intersecting search area. These areas have a certain overlap or adjacent relationship in space and have the possibility of being merged, so they are marked as the area to be merged.

[0118] It can be understood that the package location area is magnified by using a preset search multiple to obtain a search area, and the package location areas corresponding to the directly or indirectly intersecting search areas are used as the area to be merged, so as to facilitate the subsequent merging of the same type of adjacent geographic information, see Figure 3 ,This scheme will treat the package location areas within the directly and indirectly intersecting search areas as the ,areas to be merged to facilitate the subsequent merging process.

[0119] S224, connecting the centers of adjacent areas to be merged to obtain a center connection line, and selecting the smallest radius between two adjacent areas to be merged as the translation distance.

[0120] The center of the circle is the center of the package location area, that is, the midpoint of the same type. When merging adjacent areas to be merged, the center of the circle needs to be used as a reference point for operation.

[0121] The center connecting line is a line segment obtained by connecting the centers of adjacent areas to be merged. It provides position information for the subsequent construction of the merge line.

[0122] The translation distance is the smallest radius of two adjacent areas to be merged. When constructing the merge line, the center connecting line needs to be translated according to this translation distance.

[0123] It can be understood that the centers of adjacent areas to be merged are connected to obtain a center connection line, and the smallest radius of two adjacent areas to be merged is selected as the translation distance to prepare for constructing the merge line.

[0124] S225, performing translation and copying processing on the circle center connection line to both sides according to the translation distance to obtain a merged line, and merging adjacent areas to be merged based on the merged line to obtain multiple merged terrain areas.

[0125] Specifically, the circle center connection line is translated and copied according to the translation distance to obtain a merged line, and finally the adjacent areas to be merged are merged based on the merged line to form multiple merged terrain areas, thereby completing the merging process of the same type of geographic information areas.

[0126] It is worth mentioning that after copying and translating to obtain the merged line, there will be redundant line segments in the area to be merged. You can directly eliminate them, so that the merged line connects and merges the adjacent areas to be merged to obtain multiple merged areas. See Figure 4 , the adjacent areas to be merged are merged through the merging line to obtain the merged terrain area.

[0127] S23, determining the coordinate point of the merged terrain area corresponding to the extreme value of the vertical coordinate in the first division coordinate system as the first division point, constructing a first division line at the first division point based on the division direction, and dividing the broadcast area according to the first division line to obtain multiple division areas.

[0128] Specifically, in a primary division coordinate system, find the coordinate points corresponding to the extreme values ​​of the ordinate in the merged terrain area as the first division points, that is, the coordinate points corresponding to the maximum and minimum values ​​of the merged terrain area in the ordinate direction. These coordinate points can reflect the boundary position of the merged terrain area in the real-time wind direction and are the key basis for determining the first division point. Based on the division direction, the first division line is constructed at these points, thereby performing the initial division of the broadcast area and obtaining multiple division areas containing different combinations of merged terrain areas.

[0129] It should be noted that even if the areas of the same type are close to each other, there are still the same type of terrain across different divided areas, resulting in multiple types of terrain in the divided areas. Therefore, it is necessary to combine the real-time wind direction and subsequently divide the divided areas for a second time.

[0130] S24, constructing a secondary division coordinate system in the broadcast area with the division direction as the positive direction of the longitudinal coordinate axis, and determining the coordinate point corresponding to the longitudinal coordinate extreme value of each merged terrain area in each division area in the secondary division coordinate system as the second division point.

[0131] It can be understood that a secondary division coordinate system is constructed on the basis that the division direction is the positive direction of the longitudinal coordinate axis. Similarly, the origin can be an arbitrarily selected point. Subsequently, a secondary division can be performed on each divided area after the first division, and the coordinate point corresponding to the extreme value of the longitudinal coordinate of each merged terrain area is determined as the second division point, providing a basis for the secondary division.

[0132] S25, constructing a second dividing line at the second dividing point based on the real-time wind direction, and dividing the broadcast area for a second time according to the second dividing line to obtain a plurality of attenuation areas.

[0133] It can be understood that, based on the real-time wind direction, a second dividing line is constructed at the second dividing point, and the divided area obtained by the first division is divided twice, and finally multiple attenuation areas are obtained. These attenuation areas have a consistent attenuation effect on wind speed due to relatively uniform internal geographical features, which lays the foundation for accurate wind speed attenuation processing.

[0134] Through the above implementation, the broadcast area can be finely divided into multiple attenuation areas according to the similarity of geographic information and the consistency of the impact on wind speed. This allows the prediction of wind speed to fully consider the impact of different geographical environments, greatly improving the accuracy of wind speed prediction. Providing more reliable wind speed information to related industries and users will help to arrange production and life activities more reasonably and reduce the risks and losses caused by inaccurate wind speed predictions.

[0135] In some embodiments, step S2 (attenuating the real-time wind speed based on the attenuation area to obtain the predicted wind speed) includes S26-S27:

[0136] S26, sequentially counting the attenuation areas adjacent to each other in the real-time wind direction, and obtaining multiple rows of area attenuation sequences.

[0137] It is not difficult to understand that this solution divides the broadcast area twice, so that the geographical information in each attenuation area obtained by the division is consistent, so that it can be determined later that a row of attenuation areas have been passed in sequence in this wind direction, and different degrees of attenuation processing are performed according to the different attenuation areas passed in this wind direction, so as to obtain the predicted wind speed.

[0138] Specifically, the real-time wind direction is first determined, and then the adjacent attenuation areas are counted in sequence according to the real-time wind direction, and they are combined into multiple rows of regional attenuation sequences. The purpose of this is to sort out the order in which the wind speed passes through different attenuation areas in the real-time wind direction, providing a clear path for subsequent wind speed attenuation processing.

[0139] S27, performing attenuation processing on the real-time wind speed according to the pixel point distribution ratio of the geographical information of the corresponding attenuation area in the regional attenuation sequence, to obtain a predicted wind speed.

[0140] Specifically, after obtaining the regional attenuation sequence, for each attenuation area in the sequence, the pixel distribution ratio of its geographic information is analyzed. Different geographic information has different attenuation degrees on wind speed. The influence weight of various geographic information in each attenuation area can be quantified by the pixel distribution ratio. Then, the real-time wind speed is attenuated in turn according to these weights, and finally the predicted wind speed is obtained. The weight is pre-set based on the geographic information.

[0141] In some embodiments, step S27 (attenuating the real-time wind speed according to the pixel distribution ratio of the geographic information of the corresponding attenuation area in the regional attenuation sequence to obtain the predicted wind speed) includes S271-S275:

[0142] S271, obtaining the first attenuation area in the area attenuation sequence as the first area, and counting the number of pixel points corresponding to each type of geographic information in the first area as the number of type pixels.

[0143] Specifically, the first attenuation region is accurately extracted from the region attenuation sequence and is determined as the first region. Next, for each type of geographic information in the first region, the number of pixels corresponding to each type of geographic information is counted in detail, that is, the number of pixels corresponding to the geographic information in the attenuation region.

[0144] S272, counting the number of pixels in the first area to obtain the number of regional pixels, and obtaining the type number ratio according to the ratio of the number of pixels of each type to the number of regional pixels.

[0145] Specifically, the number of all pixels in the first area is counted to obtain the number of regional pixels, and the type quantity ratio, that is, the distribution ratio of the geographical feature, is obtained according to the ratio of the number of pixels of each type to the number of regional pixels.

[0146] S273, retrieve the attenuation weight value corresponding to the corresponding type of geographic information, obtain the sub-attenuation coefficient of the first area according to the product of the type quantity ratio and the attenuation weight value, sum the sub-attenuation coefficients, and obtain the comprehensive attenuation coefficient of the first area.

[0147] It is not difficult to understand that there may still be multiple geographical types within the first region.

[0148] Therefore, according to the preset attenuation weight values ​​corresponding to different types of geographic information, the corresponding attenuation weight values ​​are multiplied by the proportion of the types of geographic information calculated previously to obtain the sub-attenuation coefficient of each type of geographic information in the first area. Finally, the sub-attenuation coefficients of all types of geographic information are summed to obtain a comprehensive attenuation coefficient that can fully reflect the overall attenuation effect of the geographic information in the first area on the wind speed.

[0149] S274, obtaining the actual attenuation wind speed based on the product of the comprehensive attenuation coefficient and the preset attenuation wind speed.

[0150] Specifically, the calculated comprehensive attenuation coefficient is multiplied by a preset attenuation wind speed to obtain a specific value of the actual attenuation of the wind speed in the first area due to the influence of geographic information, that is, the actual attenuation wind speed, wherein the preset attenuation wind speed is an attenuation wind speed set artificially in advance, for example, it can be the speed of wind attenuation corresponding to passing through a plain area, or it can be set artificially according to actual conditions.

[0151] S275, based on the difference between the real-time wind speed and the actual attenuation wind speed, obtain the predicted wind speed of the first area, delete and update the first attenuation area in the attenuation sequence, and use the predicted wind speed as the current real-time wind speed, repeat the above steps of obtaining the predicted wind speed until there is no attenuation area in the row attenuation sequence, and obtain the predicted wind speed corresponding to each attenuation area.

[0152] Specifically, the actual attenuation wind speed calculated previously is subtracted from the real-time wind speed to obtain the predicted wind speed of the first area. After completing this step, the regional attenuation sequence is updated, the first attenuation area (i.e., the first area) in the sequence is deleted, and the predicted wind speed just calculated is used as the new real-time wind speed. Then, the entire process from S271 to S275 is repeated, and the same calculation is performed on the next attenuation area, and this cycle is repeated until there is no longer any attenuation area in the regional attenuation sequence, and finally the predicted wind speed corresponding to each attenuation area is obtained.

[0153] S3, based on the real-time wind direction and real-time wind speed, determine the cloud path trajectory of the real-time cloud area, update the broadcast area according to the split level, predicted wind speed and cloud path trajectory, and obtain a cloud path display map.

[0154] In some embodiments, step S3 (determining the cloud path trajectory of the real-time cloud layer area based on the real-time wind direction and the real-time wind speed) includes S31-S35:

[0155] S31, obtaining the real-time position of the real-time cloud area, and generating an initial cloud path trajectory based on the real-time position and the real-time wind direction.

[0156] Specifically, the real-time position and real-time wind direction of the real-time cloud area are first obtained. Taking the real-time position as the starting point, a preliminary path ray is generated according to the direction of the real-time wind direction, namely, the initial cloud path trajectory, which provides a basic direction for subsequent trajectory determination.

[0157] S32, obtaining a total changed area based on a difference between the real-time area and the minimum value in the minimum area interval.

[0158] It can be understood that by comparing the real-time area of ​​the real-time cloud zone with the minimum value in the minimum area interval, the difference between the two is calculated to obtain the total changed area, thereby quantifying the change in cloud area, that is, the area required to change when the clouds gradually decrease to have no effect.

[0159] S33, obtaining a total change duration according to the ratio of the total change area to the area change rate.

[0160] S34, obtaining a change distance based on the product of the real-time wind speed and the total change duration.

[0161] Specifically, the distance that the cloud layer moves to have no effect is calculated.

[0162] S35, taking the real-time position as the starting point, intercepting the initial cloud path trajectory according to the change distance to obtain the cloud path trajectory of the real-time cloud layer area.

[0163] Specifically, taking the real-time position as the starting point, the initial cloud path trajectory is intercepted according to the change distance obtained in step S34, and the redundant part is removed to obtain an accurate real-time cloud path trajectory of the cloud area, which comprehensively considers factors such as the cloud position, area change, wind direction and wind speed.

[0164] In some embodiments, step S3 (updating the broadcast area according to the split level, predicted wind speed and cloud path trajectory to obtain a cloud path display map) includes:

[0165] The level areas in the broadcast area are split according to the split level, and the predicted wind speed and cloud path trajectory are updated to the corresponding positions in the broadcast area, and the cloud path display map is obtained and sent to the management end for display.

[0166] It can be understood that, first, the level area in the broadcast area is split according to the determined split level. This step is to divide the broadcast area according to different levels of precision, so that each sub-area can more accurately reflect its unique meteorological characteristics, the more detailed the display of meteorological information, and it will be adaptively split as the cloud area changes, so that subsequent predictions are more accurate, for example, predicting towns, streets, etc.

[0167] Then, the predicted wind speed and cloud path are updated to the corresponding position in the broadcast area. The predicted wind speed reflects the future wind speed conditions in each area. Updating it to the corresponding position allows users to intuitively understand the wind speed changes in different areas. The cloud path shows the movement path of the clouds. Updating it to the corresponding position can clearly show the movement direction and range of the clouds.

[0168] Finally, the cloud road display map obtained through the above processing is sent to the management end for display. As a receiving and display terminal, the management end enables relevant personnel to view meteorological information intuitively and provide support for meteorological analysis, decision-making and services.

[0169] In actual applications, people have the need to camp in some special areas such as scenic spots. Therefore, it is necessary to further refine the affected area based on the actual terrain in the area to determine possible dry areas to facilitate camping.

[0170] Based on the above embodiment, it also includes:

[0171] The area passed by the cloud path in the cloud path display image is obtained as the affected area, and the remaining area is taken as the unaffected area.

[0172] Specifically, the areas where the cloud path passes are determined as affected areas, because these areas will be affected by various meteorological factors brought about by the movement of clouds; while the remaining areas that are not passed by the cloud path are determined as unaffected areas, which are relatively less affected by the movement of clouds. Through this division method, a preliminary classification of the areas covered by the cloud path display map is achieved.

[0173] Determine the terrain height in the affected area, determine the terrain height in the affected area, and regard the area in the affected area with a terrain height greater than a preset height as a non-waterlogging area, and regard the rest of the area in the affected area as a waterlogging area.

[0174] Specifically, the terrain height of each location is compared with the preset height. When the terrain height of a location is greater than the preset height, the area where the location is located is determined as a non-waterlogging area, because from the perspective of terrain conditions, it is not easy for water to accumulate here; and when the terrain height of a location is less than or equal to the preset height, the area where the location is located is determined as a waterlogging area, indicating that these areas may have the possibility of waterlogging during precipitation. Through such a comparison and division process, the classification of the possibility of waterlogging in the affected area based on the terrain height is achieved.

[0175] The predicted wind speed of the non-waterlogged area and the duration of the predicted wind speed are obtained, and a dryness weight value corresponding to the predicted wind speed is retrieved.

[0176] It is clear that the target area is the non-waterlogged area determined previously. Then, the predicted wind speed of the non-waterlogged area is obtained. This step is based on the previous meteorological analysis and calculation results, such as the wind speed prediction value calculated based on factors such as real-time wind direction, real-time wind speed and geographical information. Next, determine the duration of the predicted wind speed in the area to understand the time range of the wind speed effect. Finally, according to the predicted wind speed obtained, the corresponding dry weight value is retrieved from the pre-set corresponding relationship. Through this series of operations, the size of the wind speed, the action time and the degree of its influence on the dryness are quantitatively associated, which provides the necessary data support for the subsequent calculation of the dryness of the non-waterlogged area, so as to more accurately evaluate the dryness of the area. Among them, the dry weight value can be a weight value pre-set by humans, and the weight value can be set according to the terrain of the area. For example, although the terrain is high, the location is in a shaded place without sunlight, which can be set manually according to the situation.

[0177] Based on the product of the dryness weight value and the corresponding predicted wind speed, a unit dryness coefficient is obtained, and according to the product of the unit dryness coefficient and the duration, a dryness value corresponding to the non-waterlogged area is obtained.

[0178] It can be understood that the dryness value is obtained by multiplying the obtained unit dryness coefficient by the duration. The unit dryness coefficient represents the drying capacity per unit time, while the duration represents the time of wind speed action. The multiplication of the two can obtain the quantitative value of the comprehensive dryness degree of the non-waterlogged area during the entire predicted wind speed duration, that is, the dryness value.

[0179] When it is determined that the dryness value is greater than the preset dryness value, the corresponding non-water accumulation area is used as a selected area, and a dry area is obtained according to the selected area and the unaffected area.

[0180] It is understandable that when the dryness value is greater than the preset dryness value, the corresponding non-waterlogged area is determined as the selected area. These selected areas meet the set standard in terms of dryness and have good drying conditions, so the selected areas and the unaffected areas are used as dry areas.

[0181] The camping area in the broadcast area is retrieved, and the push area is obtained according to the intersection of the dry area and the camping area.

[0182] It is understandable that the dry areas are compared and analyzed with the retrieved camping areas to find their intersection. The intersection means finding those areas that have both dry conditions and are suitable for camping. The dry areas are determined based on meteorological conditions, while the camping areas are determined based on the needs of camping activities. The intersection of the two combines these two factors.

[0183] Finally, the intersection is determined as the push area, which is the area that will be recommended to users in the end. It meets the user's dual needs for dry environment and suitable for camping, and provides users with more accurate and valuable information.

[0184] See also Figure 5 , is a schematic diagram of the structure of a weather data processing system provided by an embodiment of the present invention, the weather data processing system comprising:

[0185] The splitting module is used to process the regional changes of the real-time cloud area based on the regional change rate and obtain the splitting level of the broadcast area;

[0186] A division module is used to divide the broadcast area according to the division direction and the geographical information in the broadcast area to obtain multiple attenuation areas, and perform attenuation processing on the real-time wind speed based on the attenuation areas to obtain the predicted wind speed;

[0187] The update module is used to determine the cloud path trajectory of the real-time cloud area based on the real-time wind direction and real-time wind speed, and update the broadcast area according to the split level, predicted wind speed and cloud path trajectory to obtain a cloud path display map.

[0188] See also Figure 6 , is a schematic diagram of the hardware structure of an electronic device provided in an embodiment of the present invention, the electronic device 60 includes: a processor 61, a memory 62 and a computer program; wherein

[0189] The memory 62 is used to store the computer program, which may also be a flash memory. The computer program is, for example, an application program, a functional module, etc. for implementing the above method.

[0190] The processor 61 is used to execute the computer program stored in the memory to implement each step performed by the device in the above method. For details, please refer to the relevant description in the above method embodiment.

[0191] Optionally, the memory 62 may be independent or integrated with the processor 61 .

[0192] When the memory 62 is a device independent of the processor 61, the device may further include:

[0193] The bus 63 is used to connect the memory 62 and the processor 61 .

[0194] The present invention also provides a readable storage medium, in which a computer program is stored. When the computer program is executed by a processor, it is used to implement the methods provided by the various embodiments described above.

[0195] Among them, the readable storage medium can be a computer storage medium or a communication medium. The communication medium includes any medium that facilitates the transmission of a computer program from one place to another. The computer storage medium can be any available medium that can be accessed by a general-purpose or special-purpose computer. For example, a readable storage medium is coupled to a processor so that the processor can read information from the readable storage medium and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can be located in an application-specific integrated circuit (Application Specific Integrated Circuits, referred to as: ASIC). In addition, the ASIC can be located in a user device. Of course, the processor and the readable storage medium can also exist in a communication device as discrete components. The readable storage medium can be a read-only memory (ROM), a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, and an optical data storage device, etc.

[0196] The present invention also provides a program product, which includes an execution instruction, which is stored in a readable storage medium. At least one processor of a device can read the execution instruction from the readable storage medium, and at least one processor executes the execution instruction so that the device implements the methods provided in the above various embodiments.

[0197] In the embodiments of the above-mentioned devices, it should be understood that the processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), etc. The general-purpose processor may be a microprocessor or any conventional processor. The steps of the method disclosed in the present invention may be directly implemented as being executed by a hardware processor, or may be executed by a combination of hardware and software modules in the processor.

[0198] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A weather data processing method, characterized in that: include: Based on the regional change rate, the real-time cloud area is processed for regional changes to obtain the split level of the broadcast area, including: The changed area is obtained by multiplying the predicted duration and the regional change rate, and the predicted area is obtained based on the difference between the real-time area and the changed area of ​​the real-time cloud area; Determine the split level of the broadcast area based on a level comparison table of the predicted area and the broadcast area, wherein the level comparison table includes a one-to-one correspondence between the area interval and the split level; The broadcast area is divided according to the division direction and the geographical information in the broadcast area to obtain multiple attenuation areas, including: Determine the division direction according to the orthogonal direction of the real-time wind direction; Merge adjacent and similar geographic information in the reporting area to obtain multiple merged terrain areas, and construct a division coordinate system in the reporting area with the real-time wind direction as the positive direction of the longitudinal coordinate axis; Determine a coordinate point corresponding to an extreme value of the ordinate of the merged terrain area in the primary division coordinate system as a first division point, construct a first division line at the first division point based on the division direction, and divide the broadcast area according to the first division line to obtain a plurality of division areas; Taking the division direction as the positive direction of the longitudinal coordinate axis, a secondary division coordinate system is constructed in the broadcast area, and the coordinate point corresponding to the longitudinal coordinate extreme value of each merged terrain area in each division area in the secondary division coordinate system is determined as the second division point; Based on the real-time wind direction, a second dividing line is constructed at the second dividing point, and the broadcast area is divided twice according to the second dividing line to obtain multiple attenuation areas; The real-time wind speed is attenuated based on the attenuation area to obtain the predicted wind speed; The cloud path trajectory of the real-time cloud area is determined based on the real-time wind direction and real-time wind speed. The broadcast area is updated according to the split level, predicted wind speed and cloud path trajectory to obtain a cloud path display map.

2. The method according to claim 1, characterized in that The adjacent and same type of geographical information in the broadcast area is merged to obtain multiple merged terrain areas, including: Acquire areas corresponding to the same type of geographic information in the broadcast area as similar areas, and determine the center points of the similar areas as similar midpoints; Determine the farthest distance between the regional point and the midpoint of the same category in each similar area as the construction radius, and generate the parcel location area corresponding to the similar area based on the construction radius and the midpoint of the same category; The package location area is magnified based on a preset search multiple to obtain a search area, and the package location areas corresponding to the intersecting search areas are used as areas to be merged; Connect the centers of adjacent areas to be merged to obtain a center connection line, and select the smallest radius of two adjacent areas to be merged as the translation distance; The circle center connection line is translated and copied to both sides according to the translation distance to obtain a merged line, and adjacent areas to be merged are merged based on the merged line to obtain a plurality of merged terrain areas.

3. The method according to claim 1, characterized in that The attenuation processing of the real-time wind speed based on the attenuation area to obtain the predicted wind speed includes: Attenuation areas adjacent to the real-time wind direction are counted sequentially, and multiple rows of regional attenuation sequences are obtained; The real-time wind speed is attenuated according to the pixel distribution ratio of the geographical information of the corresponding attenuation area in the regional attenuation sequence to obtain the predicted wind speed.

4. The method according to claim 3, characterized in that: The attenuation processing is performed on the real-time wind speed according to the pixel distribution ratio of the geographical information of the corresponding attenuation area in the regional attenuation sequence to obtain the predicted wind speed, including: The first attenuation region in the region attenuation sequence is obtained as the first region, and the number of pixel points corresponding to each type of geographic information in the first region is counted as the number of type pixel points; Counting the number of pixels in the first area to obtain the number of regional pixels, and obtaining the type number ratio according to the ratio of the number of pixels of each type to the number of pixels of the area; Retrieving the attenuation weight value corresponding to the corresponding type of geographic information, obtaining the sub-attenuation coefficient of the first area according to the product of the type quantity ratio and the attenuation weight value, and summing the sub-attenuation coefficients to obtain the comprehensive attenuation coefficient of the first area; Based on the product of the comprehensive attenuation coefficient and the preset attenuation wind speed, an actual attenuation wind speed is obtained; According to the difference between the real-time wind speed and the actual attenuation wind speed, the predicted wind speed of the first area is obtained, the first attenuation area in the attenuation sequence is deleted and updated, and the predicted wind speed is used as the current real-time wind speed. The above steps of obtaining the predicted wind speed are repeated until there is no attenuation area in the attenuation sequence, and the predicted wind speed corresponding to each attenuation area is obtained.

5. The method according to claim 1, characterized in that The method of determining the cloud path trajectory of the real-time cloud layer area based on the real-time wind direction and the real-time wind speed includes: Get the real-time position of the real-time cloud area, and generate the initial cloud path trajectory based on the real-time position and real-time wind direction; Based on the difference between the real-time area and the minimum value in the smallest area interval, a total changed area is obtained; Obtaining a total change duration according to the ratio of the total change area to the regional change rate; Obtaining a change distance based on the product of the real-time wind speed and the total change duration; Taking the real-time position as the starting point, the initial cloud path trajectory is intercepted and processed according to the change distance to obtain the cloud path trajectory of the real-time cloud layer area.

6. The method according to claim 1, characterized in that The broadcast area is updated according to the split level, predicted wind speed and cloud path trajectory to obtain a cloud path display map, including: The level areas in the broadcast area are split according to the split level, and the predicted wind speed and cloud path trajectory are updated to the corresponding positions in the broadcast area, and the cloud path display map is obtained and sent to the management end for display.

7. The method according to claim 1, characterized in that Also includes: The area passed by the cloud path in the cloud path display diagram is obtained as the affected area, and the remaining area is taken as the unaffected area; Determine the terrain height in the affected area, determine the terrain height in the affected area, and regard the area in the affected area with a terrain height greater than a preset height as a non-waterlogging area, and regard the rest of the area in the affected area as a waterlogging area; Obtaining the predicted wind speed in the non-waterlogged area and the duration of the predicted wind speed, and retrieving a dryness weight value corresponding to the predicted wind speed; Based on the product of the dryness weight value and the corresponding predicted wind speed, a unit dryness coefficient is obtained, and according to the product of the unit dryness coefficient and the duration, a dryness value corresponding to the non-waterlogged area is obtained; When it is determined that the dryness value is greater than the preset dryness value, the corresponding non-water accumulation area is used as a selection area, and a dry area is obtained according to the selection area and the unaffected area; The camping area in the broadcast area is retrieved, and the push area is obtained according to the intersection of the dry area and the camping area.

8. A weather data processing system according to any one of the methods of claims 1-7, characterized in that: include: The splitting module is used to process the regional changes of the real-time cloud area based on the regional change rate and obtain the splitting level of the broadcast area; A division module is used to divide the broadcast area according to the division direction and the geographical information in the broadcast area to obtain multiple attenuation areas, and perform attenuation processing on the real-time wind speed based on the attenuation areas to obtain the predicted wind speed; The update module is used to determine the cloud path trajectory of the real-time cloud area based on the real-time wind direction and real-time wind speed, and update the broadcast area according to the split level, predicted wind speed and cloud path trajectory to obtain a cloud path display map.

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