A method and system for extreme precipitation area frequency analysis based on radar precipitation products

Abstract

The application relates to the technical field of precipitation detection, in particular to an extreme precipitation area frequency analysis method and system based on radar precipitation products, which comprises the following steps: carrying out grid division on a precipitation monitoring area to obtain a precipitation grid set; collecting and obtaining a precipitation echo signal according to radar precipitation products, and segmenting the precipitation grid set according to a preset echo intensity threshold to obtain a precipitation candidate area; carrying out feature extraction on the precipitation candidate area to obtain a precipitation spatial feature set, constructing a three-dimensional precipitation projection map according to the precipitation spatial feature set, and carrying out key point extraction on the three-dimensional precipitation projection map. The application can effectively identify the spatial distribution characteristics of precipitation by analyzing the precipitation echo signal, and realizes accurate spatial positioning and morphological identification of the precipitation area through the three-dimensional precipitation projection map construction and key point extraction technology. The accurate positioning can help to more effectively evaluate and manage the spatial distribution of precipitation.

Description

Technical Field

[0001] This invention relates to the field of precipitation detection technology, specifically to a method and system for frequency analysis of extreme precipitation areas based on radar precipitation products. Background Technology

[0002] Radar precipitation products are data acquired by meteorological radar. After processing and analysis, these products are used to describe and monitor various information about precipitation. They are mainly based on data such as the intensity and frequency changes of radar echo signals and can provide information such as the spatial distribution and intensity of precipitation.

[0003] Traditional methods typically rely on relatively simple precipitation observation data, failing to effectively distinguish the spatial distribution characteristics of precipitation. This is particularly true in identifying extreme precipitation events, where accuracy is low. Traditional methods are often insufficiently precise in locating and identifying the morphology of precipitation areas, lacking accurate 3D projection and key point extraction. Furthermore, they often rely solely on single precipitation intensities or values ​​for analysis, making it difficult to analyze the impacts of different types of precipitation in detail, especially in distinguishing the specific environmental impacts of different precipitation types. They also lack advanced techniques such as spatial clustering and temporal segmentation, resulting in insufficient analysis of precipitation intensity changes and duration, hindering the provision of sufficient evidence for disaster prevention and mitigation decisions. Moreover, traditional methods often fail to accurately identify the propagation characteristics and directions of precipitation in different regions, leading to imprecise regional divisions of precipitation intensity and impact, making it impossible to provide targeted prevention and control measures. Additionally, traditional methods lack automated regional clustering and segmentation capabilities, hindering the rapid identification of extreme precipitation areas and resulting in slow response times. Summary of the Invention

[0004] To achieve the above objectives, the present invention provides the following technical solution: a method for frequency analysis of extreme precipitation areas based on radar precipitation products, comprising:

[0005] The precipitation monitoring area is divided into grids to obtain a precipitation grid set; precipitation echo signals are acquired based on radar precipitation products, and the precipitation grid set is segmented according to a preset echo intensity threshold to obtain precipitation candidate areas;

[0006] Feature extraction is performed on the candidate precipitation region to obtain a precipitation spatial feature set. A three-dimensional precipitation projection map is constructed based on the precipitation spatial feature set. Key points are extracted from the three-dimensional precipitation projection map to obtain a precipitation key point coordinate sequence.

[0007] Precipitation hotspot areas are determined based on the coordinate sequence of key precipitation points; boundary detection is performed on the precipitation hotspot areas to obtain the boundaries of extreme precipitation areas; the precipitation hotspot areas are segmented based on the boundaries of extreme precipitation areas to obtain extreme precipitation event segments; spatial coordinate transformation is performed on the extreme precipitation event segments to obtain extreme precipitation location information.

[0008] The precipitation type information of the extreme precipitation event segment is determined based on the extreme precipitation location information; wherein, the precipitation type information includes a first precipitation event and a second precipitation event; precipitation intensity is detected for the first precipitation event and the second precipitation event based on the extreme precipitation location information to obtain precipitation intensity type information.

[0009] Preferably, constructing a three-dimensional precipitation projection map based on the set of precipitation spatial features includes:

[0010] The projection parameters are determined based on the set of spatial features of precipitation; wherein the set of spatial features of precipitation includes precipitation intensity, precipitation range, and precipitation height; and the projection parameters include horizontal projection boundary, vertical projection boundary, and projection resolution.

[0011] A three-dimensional precipitation projection map is constructed based on the projection parameters; wherein, the three-dimensional precipitation projection map is used to map the spatial distribution pattern of precipitation.

[0012] Preferably, determining the projection parameters based on the set of spatial characteristics of precipitation includes:

[0013] The horizontal projection boundary is determined based on the precipitation range and the preset range threshold.

[0014] The vertical projection boundary is determined based on the precipitation height and the preset height threshold.

[0015] The projection resolution is determined based on the precipitation intensity and a preset intensity threshold.

[0016] Constructing a three-dimensional precipitation projection map based on the projection parameters includes:

[0017] The precipitation projection space is determined based on the horizontal projection boundary, the vertical projection boundary, and the projection resolution.

[0018] The three-dimensional precipitation projection map is formed by mapping the distribution pattern of precipitation in three-dimensional space according to the precipitation projection space; wherein, the precipitation projection space represents the projection range of three-dimensional precipitation on the horizontal plane, the horizontal projection boundary represents the boundary of the precipitation projection space in the horizontal direction, and the vertical projection boundary represents the height boundary of the precipitation projection space in the vertical direction.

[0019] Preferably, key points are extracted from the three-dimensional precipitation projection map to obtain a sequence of precipitation key point coordinates, including:

[0020] The precipitation type is obtained, and the coding parameters are determined based on the precipitation type; wherein, the precipitation type includes convective precipitation, stratiform cloud precipitation, and mixed precipitation; the coding parameters include key point extraction threshold and key point density threshold, wherein the key point extraction threshold for convective precipitation is lower than that for stratiform cloud precipitation, and the key point density threshold for mixed precipitation is higher than that for convective precipitation.

[0021] Based on the matching results between the precipitation type and the preset type library, the corresponding coding parameter template is called; wherein, the preset type library includes coding parameter combinations corresponding to different precipitation types, and the coding parameter combinations include key point extraction threshold, key point density threshold and coding accuracy level;

[0022] Based on the encoded parameter template, key points are extracted from the three-dimensional precipitation projection map to obtain a sequence of precipitation key point coordinates.

[0023] In response to the number of key points in the precipitation key point coordinate sequence exceeding a preset threshold, it is determined that the current area has dense precipitation.

[0024] In response to the fact that the number of key points in the precipitation key point coordinate sequence does not exceed a preset number threshold, it is determined that the current area has sparse precipitation; wherein, the preset number threshold is determined based on the average number of key points in historical precipitation data.

[0025] Preferably, determining the precipitation type information of the extreme precipitation event segment based on the extreme precipitation location information includes:

[0026] In response to detecting that the precipitation range of the first precipitation event exceeds a preset first range threshold based on the extreme precipitation location information, the precipitation duration of the first precipitation event is determined;

[0027] In response to the precipitation duration exceeding a preset first time threshold, the first precipitation event is marked as a first precipitation type;

[0028] In response to detecting that the movement rate of the precipitation center of the second precipitation event exceeds a preset rate threshold based on the extreme precipitation location information, the precipitation intensity change rate of the second precipitation event is determined;

[0029] In response to the precipitation intensity change rate exceeding a preset intensity threshold, the second precipitation event is marked as a second precipitation type;

[0030] The precipitation type information is determined based on the first precipitation type and the second precipitation type.

[0031] Preferably, precipitation intensity is detected for the first and second precipitation events based on the extreme precipitation location information to obtain precipitation intensity type information, including:

[0032] Spatial clustering was performed on the coordinate sequence of key precipitation points of the first precipitation event to obtain the first precipitation core area;

[0033] The average precipitation intensity per unit time is determined based on the echo intensity time series of the first precipitation core area;

[0034] In response to the average precipitation intensity exceeding a preset first intensity threshold, first intensity type information is determined;

[0035] The precipitation hotspots of the second precipitation event are processed by time-series segmentation to obtain multiple precipitation sub-events;

[0036] The cumulative precipitation is determined based on the precipitation range and duration of each precipitation sub-event.

[0037] In response to the cumulative precipitation exceeding a preset second intensity threshold, second intensity type information is determined;

[0038] The precipitation intensity type information is determined based on the first intensity type information and the second intensity type information.

[0039] Preferably, the method of detecting precipitation intensity of the first precipitation event and the second precipitation event based on the extreme precipitation location information to obtain precipitation intensity type information further includes:

[0040] In response to detecting that the rate of change of precipitation intensity in the precipitation area is greater than a preset rate threshold based on the extreme precipitation location information, a warning message is issued to the precipitation area;

[0041] In response to the detection that the precipitation area is still greater than the preset rate threshold after the warning information is issued, the third intensity change information is determined;

[0042] Based on the first intensity change information, the second intensity change information, and the third intensity change information, the precipitation intensity type information is determined.

[0043] Preferably, the method further includes:

[0044] In the three-dimensional precipitation projection map, any point is taken as the origin, and the ray connecting the origin to other points within the preset spatiotemporal neighborhood is used as the precipitation propagation line.

[0045] The point intensity is determined based on the precipitation intensity type information at the same location and time point in the three-dimensional precipitation projection map; the propagation characteristic vector of each location point is determined based on the point intensity of other locations on each precipitation propagation line.

[0046] The total propagation vector at each location point is determined based on the changes in the propagation characteristic vector at different locations.

[0047] Based on the total propagation vector, the region is clustered to determine the clustering index of two adjacent locations. Based on the clustering index of all two adjacent locations, the region is divided to determine the clustered region. Based on the point intensity of each location within each clustered region, the extreme precipitation region is determined. The extreme precipitation region is extracted from the three-dimensional precipitation projection map to obtain the three-dimensional extreme region.

[0048] Preferably, the propagation characteristic vector of each location point is determined based on the point intensity at other locations along each precipitation propagation line, including:

[0049] For two adjacent points along the same precipitation propagation line, the maximum and minimum values ​​of the ratio of the point intensity of the earlier point to that of the later point are normalized to obtain the vector magnitude.

[0050] Along the precipitation propagation line, the direction corresponding to the propagation of point intensity from high to low is taken as the vector direction;

[0051] The intensity change vector along the corresponding precipitation propagation line is determined based on the vector magnitude and the vector direction.

[0052] The propagation characteristic vector of a location point is obtained by summing the intensity change vectors along all precipitation propagation lines.

[0053] An extreme precipitation area frequency analysis system based on radar precipitation products, applicable to the aforementioned extreme precipitation area frequency analysis method based on radar precipitation products, includes:

[0054] The data acquisition unit is used to divide the precipitation monitoring area into grids to obtain a precipitation grid set; to acquire precipitation echo signals based on radar precipitation products, and to segment the precipitation grid set according to a preset echo intensity threshold to obtain precipitation candidate areas;

[0055] A three-dimensional projection unit is used to extract features from the candidate precipitation region to obtain a precipitation spatial feature set, construct a three-dimensional precipitation projection map based on the precipitation spatial feature set, and extract key points from the three-dimensional precipitation projection map to obtain a precipitation key point coordinate sequence.

[0056] A precipitation location unit is used to determine precipitation hotspot areas based on the coordinate sequence of precipitation key points; perform boundary detection on the precipitation hotspot areas to obtain the boundary of extreme precipitation areas; segment the precipitation hotspot areas according to the boundary of extreme precipitation areas to obtain extreme precipitation event segments; and perform spatial coordinate transformation on the extreme precipitation event segments to obtain extreme precipitation location information.

[0057] An intensity detection unit is used to determine the precipitation type information of the extreme precipitation event segment based on the extreme precipitation location information; wherein the precipitation type information includes a first precipitation event and a second precipitation event; and to perform precipitation intensity detection on the first precipitation event and the second precipitation event based on the extreme precipitation location information to obtain precipitation intensity type information.

[0058] Compared with the prior art, the beneficial effects of the present invention are:

[0059] This invention analyzes precipitation echo signals to effectively identify the spatial distribution characteristics of precipitation, especially to accurately distinguish extreme precipitation events. This helps in early warning and the implementation of corresponding disaster prevention and mitigation measures. Furthermore, through the construction of three-dimensional precipitation projection maps and key point extraction technology, it achieves precise spatial positioning and morphological identification of precipitation areas. This precise positioning can help to more effectively assess and manage the spatial distribution of precipitation.

[0060] This invention classifies precipitation events by using precipitation type information and intensity detection, thereby more accurately predicting and analyzing the environmental impact of different types of precipitation; and by using spatial clustering, temporal segmentation and other technologies, it can analyze the intensity changes and duration of precipitation in detail. This analysis helps to determine the intensity of precipitation events and provides a basis for disaster prevention and mitigation decisions.

[0061] This invention analyzes precipitation propagation lines, enabling the method to identify the propagation characteristics and directions of precipitation in different regions. This facilitates the precise classification of precipitation intensity and impact in different areas, providing data support for targeted prevention and control. Furthermore, it can automatically cluster and divide regions based on precipitation propagation characteristic vectors, thereby quickly identifying extreme precipitation areas and providing data support for further emergency response and planning. By dynamically monitoring parameters such as precipitation intensity and rate of change, it can issue timely precipitation warnings and adjust the warning level according to preset thresholds, improving the timeliness and accuracy of precipitation warnings. Attached Figure Description

[0062] Figure 1 This is a schematic flowchart of the overall method in one embodiment of the present invention;

[0063] Figure 2 This is a schematic diagram of the overall system architecture in one embodiment of the present invention.

[0064] In the diagram: 1. Data acquisition unit; 2. 3D projection unit; 3. Precipitation location unit; 4. Intensity detection unit. Detailed Implementation

[0065] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0066] Example 1, please refer to Figure 1 This invention provides a technical solution: a method for frequency analysis of extreme precipitation areas based on radar precipitation products, comprising:

[0067] S1. Divide the precipitation monitoring area into grids to obtain a precipitation grid set; acquire precipitation echo signals based on radar precipitation products, and divide the precipitation grid set according to a preset echo intensity threshold to obtain precipitation candidate areas;

[0068] S2. Extract features from the candidate precipitation areas to obtain a set of precipitation spatial features. Construct a three-dimensional precipitation projection map based on the set of precipitation spatial features. Extract key points from the three-dimensional precipitation projection map to obtain a sequence of precipitation key point coordinates.

[0069] S3. Determine precipitation hotspot areas based on the coordinate sequence of key precipitation points; perform boundary detection on precipitation hotspot areas to obtain the boundaries of extreme precipitation areas; segment precipitation hotspot areas based on the boundaries of extreme precipitation areas to obtain extreme precipitation event segments; perform spatial coordinate transformation on extreme precipitation event segments to obtain extreme precipitation location information.

[0070] S4. Determine the precipitation type information of extreme precipitation event segments based on extreme precipitation location information; wherein, the precipitation type information includes the first precipitation event and the second precipitation event; perform precipitation intensity detection on the first precipitation event and the second precipitation event based on the extreme precipitation location information to obtain precipitation intensity type information.

[0071] It should be noted that the precipitation monitoring area is divided into multiple small grids, each representing a small region. This allows for refined processing and analysis of precipitation data. Precipitation echo signals are continuously monitored, reflecting the intensity and location of precipitation. Based on the collected echo signals and a preset echo intensity threshold, the precipitation grid set is segmented. This segmentation process aims to identify candidate regions from the overall precipitation data, regions where extreme precipitation may occur. These candidate regions are then analyzed in detail to extract spatial characteristics of precipitation. Based on these extracted spatial characteristics, a three-dimensional projection map is constructed. This projection map clearly displays the spatial distribution of precipitation, helping to identify key features of precipitation events. The three-dimensional projection map is analyzed to extract key point coordinates. These key points represent the main characteristics of precipitation, such as the precipitation center and points of abrupt changes in intensity. Based on the extracted key points… Key point coordinate sequences are used to identify precipitation hotspots, which typically exhibit strong precipitation signals. Boundary detection is then performed on these hotspots to obtain the specific boundaries of extreme precipitation areas, thus determining which regions have experienced extreme precipitation events. Based on the boundary detection results, the extreme precipitation areas are segmented, with each segment representing a specific precipitation event. These segments are then transformed into specific extreme precipitation location information for further analysis. Based on this location information, the type of each precipitation event is further determined, categorized into two main types: Type I and Type II precipitation events. For each precipitation event, location information is used to detect its precipitation intensity. Precipitation intensity type information is then used to further describe the strength of each precipitation event. This detection process helps identify which areas experience particularly heavy precipitation, potentially leading to disasters.

[0072] In an optional embodiment, constructing a three-dimensional precipitation projection map based on a set of spatial precipitation features includes:

[0073] The projection parameters are determined based on the spatial feature set of precipitation, which includes precipitation intensity, precipitation range, and precipitation height; the projection parameters include the horizontal projection boundary, the vertical projection boundary, and the projection resolution.

[0074] A three-dimensional precipitation projection map is constructed based on projection parameters; the three-dimensional precipitation projection map is used to map the spatial distribution of precipitation.

[0075] It should be noted that precipitation intensity represents the strength of precipitation, which can be reflected by the signal strength of radar echoes; the greater the intensity, the stronger the precipitation, and the more likely it is to cause disasters such as floods. Precipitation range refers to the spatial extent of precipitation coverage, usually indicating the size of the area affected by precipitation; in radar data, precipitation range can be determined by the spatial distribution of echo signals. Vertical distribution of precipitation refers to the altitude information of precipitation events; this can be determined by radar measurements of the height of precipitation clouds and the depth of precipitation layers. Based on the set of spatial characteristics of precipitation (precipitation intensity, range, and altitude), projection parameters need to be determined, which are the key parameters used to construct a three-dimensional precipitation projection map. The horizontal projection boundary refers to the boundary of the precipitation area defined on the horizontal plane, determining the horizontal extension of the precipitation's influence range; it is usually determined based on a threshold of precipitation intensity or the outer boundary of the precipitation area. The vertical projection boundary represents the boundary of the precipitation event in the vertical direction, usually defined by the altitude information of the precipitation; this reflects the distribution of precipitation at different altitude layers and helps to understand the depth of the precipitation event's extension in the atmosphere. Projection resolution refers to the resolution of each grid in the projection map. The spatial scale represented by the grid cell; high-resolution projection maps can display the distribution of precipitation in greater detail, while low-resolution maps simplify the display of precipitation areas and are suitable for analyzing precipitation events over a larger area; based on the above projection parameters (horizontal projection boundary, vertical projection boundary, projection resolution), a three-dimensional precipitation projection map is constructed. The function of this map is to: map the spatial distribution of precipitation; the three-dimensional precipitation projection map can intuitively display the distribution of precipitation in the horizontal and vertical directions; the horizontal projection shows the spatial extent of precipitation, while the vertical projection shows the height information of precipitation; by combining these two dimensions, the spatial distribution of precipitation can be fully understood; this projection map not only shows the intensity distribution of precipitation, but also helps to analyze the spatial morphology of precipitation events; for example, it can show information such as the central area of ​​precipitation, the outer influence range, and the height of the precipitation layer, thus helping to predict the impact of precipitation on the ground and atmosphere; through the three-dimensional projection map, precipitation hotspots can be identified, thus enabling event segmentation, grading, and classification; for example, identifying areas of heavy precipitation and areas of light precipitation, further providing a basis for disaster prevention and mitigation work.

[0076] In an optional embodiment, determining the projection parameters based on a set of spatial features of precipitation includes:

[0077] The horizontal projection boundary is determined based on the precipitation range and a preset range threshold.

[0078] The vertical projection boundary is determined based on the precipitation height and a preset height threshold.

[0079] The projection resolution is determined based on the precipitation intensity and a preset intensity threshold.

[0080] Constructing a three-dimensional precipitation projection map based on projection parameters, including:

[0081] The precipitation projection space is determined based on the horizontal projection boundary, the vertical projection boundary, and the projection resolution.

[0082] A three-dimensional precipitation projection map is formed by mapping the distribution pattern of precipitation in three-dimensional space based on the precipitation projection space. The precipitation projection space represents the projection range of three-dimensional precipitation on the horizontal plane, the horizontal projection boundary represents the boundary of the precipitation projection space in the horizontal direction, and the vertical projection boundary represents the height boundary of the precipitation projection space in the vertical direction.

[0083] In an optional embodiment, key points are extracted from the three-dimensional precipitation projection map to obtain a sequence of precipitation key point coordinates, including:

[0084] The precipitation type is obtained, and the coding parameters are determined based on the precipitation type. The precipitation type includes convective precipitation, stratiform cloud precipitation, and mixed precipitation. The coding parameters include key point extraction threshold and key point density threshold. The key point extraction threshold for convective precipitation is lower than that for stratiform cloud precipitation, and the key point density threshold for mixed precipitation is higher than that for convective precipitation.

[0085] Based on the matching results between precipitation type and the preset type library, the corresponding coding parameter template is called; the preset type library includes coding parameter combinations corresponding to different precipitation types, and the coding parameter combinations include key point extraction threshold, key point density threshold and coding accuracy level.

[0086] Key points are extracted from the 3D precipitation projection map based on the encoded parameter template to obtain the coordinate sequence of precipitation key points;

[0087] When the number of key points in the precipitation key point coordinate sequence exceeds a preset threshold, it is determined that the current area has dense precipitation.

[0088] If the number of key points in the precipitation key point coordinate sequence does not exceed a preset threshold, it is determined that the current area has sparse precipitation; the preset threshold is determined based on the average number of key points in historical precipitation data.

[0089] It should be noted that convective precipitation is usually formed by the rising of warm air, producing localized heavy precipitation; its characteristics are a small precipitation area, high intensity, and short duration. Stratigraphic precipitation is usually formed by the encounter of cold air and moist air over a large area; the precipitation intensity is usually lower, but the area is larger, and the duration is longer. Mixed precipitation is a combination of convective and stratigraphic precipitation, typically characterized by a combination of localized heavy precipitation and large-scale light precipitation. Based on different precipitation types, the system selects corresponding coding parameters, and the key point extraction threshold is used to define which points are considered key points. Key points are points in the precipitation space that have a significant impact on the intensity or variation of precipitation. Different types of precipitation have different spatial characteristics, and the selected thresholds vary accordingly. The keypoint extraction thresholds also differ; the threshold for convective precipitation is lower than that for stratiform cloud precipitation because convective precipitation typically manifests as intense, localized precipitation, thus a lower threshold helps capture precipitation features over a smaller area. The threshold for stratiform cloud precipitation is higher because it is usually widespread and uniform in intensity, requiring a higher threshold to extract more prominent features. The keypoint density threshold measures the density of keypoints within a unit area; different precipitation types require different density thresholds: convective precipitation has a lower density threshold because it typically presents as small-scale, intense precipitation with sparse keypoints; mixed precipitation has a higher density threshold because it combines large-scale and small-scale intense precipitation, requiring a higher threshold to extract more prominent features. A high density threshold is used to identify this complex spatial distribution; based on the precipitation type, corresponding coding parameter combinations can be matched from a preset type library; the preset type library includes different precipitation types and their corresponding coding parameters. Parameter combinations typically include: key point extraction threshold: defining which points are "key points"; key point density threshold: used to identify areas of dense precipitation; coding accuracy level: referring to the required level of accuracy when processing precipitation data, which may affect the resolution of key points or the accuracy of spatial feature extraction of precipitation; based on the above coding parameter template, key point extraction begins on the 3D precipitation projection map, obtaining a sequence of precipitation key point coordinates. In this step, the system filters out important precipitation areas or... "Key points" identify important points on the precipitation map. These points reflect areas with significant variations in precipitation intensity and may represent the core area of ​​precipitation or extreme weather phenomena. By analyzing the coordinate sequence of precipitation key points, the system can determine the precipitation density of the current area based on the number of key points. When the number of precipitation key points exceeds a preset threshold, the current area is considered to have dense precipitation. The threshold is determined based on the average number of key points in historical precipitation data, aiming to set a reasonable standard based on historical data. When the number of precipitation key points does not exceed the preset threshold, the current area is considered to have sparse precipitation. A relatively small number of key points indicates that the spatial distribution of precipitation is relatively sparse, the intensity is low, or the precipitation area is small.The preset threshold is determined based on the average number of key points in historical precipitation data. This means the system will set a reasonable standard based on past data to compare and analyze current precipitation events.

[0090] In an optional embodiment, determining precipitation type information for extreme precipitation event segments based on extreme precipitation location information includes:

[0091] In response to detecting that the precipitation range of the first precipitation event exceeds a preset first range threshold based on extreme precipitation location information, the duration of precipitation of the first precipitation event is determined;

[0092] In response to the precipitation duration exceeding a preset first time threshold, the first precipitation event is marked as the first precipitation type;

[0093] In response to the detection that the movement rate of the precipitation center of the second precipitation event exceeds a preset rate threshold based on the extreme precipitation location information, the precipitation intensity change rate of the second precipitation event is determined.

[0094] In response to the rate of change of precipitation intensity exceeding a preset intensity threshold, the second precipitation event is marked as the second precipitation type;

[0095] Precipitation type information is determined based on the first and second precipitation types.

[0096] It should be noted that the first precipitation event is detected using extreme precipitation location information, and its precipitation range (i.e., the size of the area covered by precipitation) is determined. This range is compared with a preset first range threshold. If the precipitation range of the first precipitation event exceeds the preset first range threshold, it indicates that the affected area of ​​the precipitation event is large, possibly a large-scale precipitation event. Once it is determined that the range of the first precipitation event exceeds the threshold, the system will further calculate the precipitation duration. The precipitation duration refers to the length of time from the start to the end of the precipitation event. If the duration of the first precipitation event exceeds a preset first time threshold, it indicates that the precipitation event is relatively long. If the duration of the first precipitation event exceeds the preset time threshold, the system will mark this precipitation event as the first precipitation type. The first precipitation type may represent a specific precipitation pattern (e.g., long-term, continuous precipitation). The movement rate of the precipitation center is similar to that of the first precipitation event. The system detects the second precipitation event using extreme precipitation location information and calculates the precipitation center based on the change in the center position of the precipitation event. Movement rate; the movement rate of the precipitation center represents the speed of the precipitation system, reflecting its spatial dynamics. If the movement rate of the precipitation center of the second precipitation event exceeds a preset rate threshold, it indicates that the precipitation system is moving rapidly, potentially manifesting as localized heavy rain or extreme weather phenomena. Based on the spatial characteristics and temporal evolution of the precipitation event, the system also calculates the rate of change of precipitation intensity, i.e., the magnitude of change in precipitation intensity per unit time. This reflects the trend of precipitation intensity changes (e.g., whether it suddenly increases or decreases). If the rate of change of precipitation intensity of the second precipitation event exceeds a preset intensity threshold, it indicates a significant change in precipitation intensity. At this point, the precipitation event will be labeled as the second precipitation type. The second precipitation type may represent short-duration heavy rainfall or extreme precipitation events (e.g., heavy rain, thunderstorms, etc.). Based on the type information of the first and second precipitation events, the system will ultimately integrate the characteristics of these two types of precipitation to determine the precipitation type information. This step typically involves a comprehensive assessment of the impact of different types of precipitation events on meteorological disasters, and the determination of appropriate early warning and response measures.

[0097] In an optional embodiment, precipitation intensity detection is performed on the first and second precipitation events based on extreme precipitation location information to obtain precipitation intensity type information, including:

[0098] Spatial clustering was performed on the coordinate sequence of key precipitation points of the first precipitation event to obtain the core area of ​​the first precipitation event;

[0099] The average precipitation intensity per unit time is determined based on the echo intensity time series of the first precipitation core area;

[0100] In response to the average precipitation intensity exceeding a preset first intensity threshold, first intensity type information is determined;

[0101] The precipitation hotspots of the second precipitation event were processed by time-series segmentation to obtain multiple precipitation sub-events;

[0102] The cumulative precipitation is determined based on the precipitation range and duration of each precipitation sub-event;

[0103] In response to the cumulative precipitation exceeding a preset second intensity threshold, the second intensity type information is determined;

[0104] The precipitation intensity type information is determined based on the first intensity type information and the second intensity type information.

[0105] It should be noted that for the first precipitation event, spatial clustering is performed on these coordinates by analyzing the key point coordinate sequence of precipitation. Spatial clustering uses a certain algorithm to group closely spaced precipitation coordinates into one class, and the clustering result forms the core area of ​​the first precipitation event. This core area represents the main area of ​​influence of the precipitation event, where the precipitation is most concentrated and intense. The coordinates of the key precipitation points usually represent changes in the location of precipitation, such as the center or boundary of the precipitation. Spatial clustering uses algorithms (such as K-means or DBSCAN) to aggregate precipitation data according to spatial location and identify the core area of ​​precipitation. Echo intensity usually represents the intensity of precipitation, which is determined by radar and other equipment. For the first precipitation core area, the average precipitation intensity per unit time is calculated based on the data of echo intensity variation over time in that area. Average precipitation intensity is the average precipitation intensity over a given time period. Echo intensity represents precipitation intensity, usually expressed by the intensity of radar echo signals. The precipitation intensity within a specific time period is measured by calculating the average of all precipitation intensities over that period. If the average precipitation intensity exceeds a preset first intensity threshold, it indicates that the precipitation intensity is strong and exceeds the normal range. Based on this threshold, the system will mark the precipitation event as a specific precipitation intensity type, referred to as the first intensity type information. This may indicate heavy rainfall. Extreme weather events such as heavy rain or torrential rain; for the second precipitation event, it is first necessary to identify the precipitation hotspots of the event, that is, the areas where precipitation is most concentrated; these hotspots can be determined by analyzing precipitation intensity data; the precipitation process of the second precipitation event is processed by time segmentation to generate multiple precipitation sub-events; each precipitation sub-event represents a specific time period of the precipitation process and usually has relatively independent precipitation characteristics; for each precipitation sub-event, the system calculates its precipitation range (i.e., the size of the covered area) and duration (i.e., the length of time the precipitation occurs); by weighting the precipitation range and duration of each precipitation sub-event, the precipitation intensity is determined. The cumulative precipitation is the total precipitation within the specified time period. If the cumulative precipitation exceeds a preset second intensity threshold, it indicates that the precipitation event is relatively strong and falls under the category of heavy precipitation. In this case, the system will label the second precipitation event as a specific precipitation intensity type, referred to as the second intensity type information. Finally, the system combines the intensity type information of the first and second precipitation events to determine the final precipitation intensity type information. This step may involve combining and prioritizing different intensity types to help determine the overall intensity level of the precipitation event (such as light, moderate, heavy, or torrential rain).

[0106] In an optional embodiment, precipitation intensity detection is performed on the first and second precipitation events based on extreme precipitation location information to obtain precipitation intensity type information, and the method further includes:

[0107] In response to the detection that the rate of change of precipitation intensity in the precipitation area exceeds a preset rate threshold based on extreme precipitation location information, a warning message is issued to the precipitation area;

[0108] In response to the detection that the precipitation area is still greater than the preset rate threshold after the warning information is issued, the third intensity change information is determined;

[0109] Based on the first intensity change information, the second intensity change information, and the third intensity change information, the precipitation intensity type information is determined.

[0110] It should be noted that extreme precipitation location information refers to the location information of precipitation events obtained through meteorological monitoring equipment (such as radar, satellites, etc.). This information helps identify and locate precipitation areas, especially areas where extreme precipitation events occur. The rate of change of precipitation intensity refers to the rate at which precipitation intensity changes over time, usually expressed as the amount of change in intensity per unit time. A large rate of change of precipitation intensity usually indicates drastic changes in precipitation intensity, which may be a sign of extreme weather events such as heavy rain. A rate threshold is set; when the rate of change of precipitation intensity exceeds this threshold, it indicates that a rapid change has occurred in the precipitation area (such as a sudden intensification of heavy rain). If the monitored rate of change of precipitation intensity is greater than this threshold, an alert mechanism is triggered. Once the rate of change of intensity in the precipitation area exceeds the preset threshold... If the precipitation event reaches a certain threshold, the system will issue a warning, notifying relevant personnel (such as meteorological departments, government agencies, or the public) that the precipitation event may have a significant impact and that appropriate countermeasures need to be taken. After issuing the warning, the meteorological monitoring system continues to track the intensity changes of the precipitation area. If the rate of change of precipitation intensity continues to exceed a preset threshold, it indicates that the precipitation event may be intensifying and may last for a long time. At this point, the system will analyze the further trend of precipitation intensity changes to determine the third intensity change information. The third intensity change information may indicate a further intensification of precipitation intensity changes or other important changes (e.g., expansion of the precipitation area, further enhancement of intensity, etc.). This information is usually used to determine whether the precipitation will further escalate into an extreme weather event (such as heavy rain, typhoon, etc.).

[0111] In an optional embodiment, the method further includes:

[0112] In a three-dimensional precipitation projection map, any point is taken as the origin, and the ray connecting the origin to other points within a preset spatiotemporal neighborhood is used as the precipitation propagation line.

[0113] The point intensity is determined based on the precipitation intensity type information at the same location and time point in the 3D precipitation projection map; the propagation characteristic vector of each location point is determined based on the point intensity of other locations along each precipitation propagation line.

[0114] The total propagation vector at each location point is determined based on the changes in the propagation characteristic vector at different locations.

[0115] Based on the total propagation vector, the region is clustered to determine the cluster index of two adjacent locations. Based on the cluster index of all two adjacent locations, the region is divided to determine the clustered regions. Based on the point intensity of each location within each clustered region, the extreme precipitation region is determined. The extreme precipitation region is extracted from the three-dimensional precipitation projection map to obtain the three-dimensional extreme region.

[0116] It should be noted that an arbitrary point in the 3D precipitation map is selected as the origin. From this point, a preset spatiotemporal neighborhood is defined, encompassing other points related to this point (other points within the precipitation region) within a certain spatial range and time period. The rays between the origin and these other points are considered precipitation propagation lines. These rays connect different precipitation points, reflecting how precipitation propagates from one location to another in space. Point intensity refers to the precipitation intensity information at any point in the 3D precipitation projection map at a certain time. Precipitation intensity type information reflects the precipitation intensity level at that point, such as light, moderate, or heavy. Based on the precipitation intensity type at the same location and time in the 3D precipitation projection map... The system uses data to determine the point intensity of precipitation at a given location, i.e., the specific intensity level of the precipitation. For each precipitation propagation line, there is a precipitation intensity at each location along the line. Based on these intensity data, a propagation characteristic vector can be calculated, which reflects the trend of precipitation intensity change from one location to another. The propagation characteristic vector describes how the precipitation intensity changes at a given location, including the direction and rate of increase or decrease in intensity. In this way, the precipitation propagation pattern can be transformed into vector information, helping to analyze the evolution of precipitation. Throughout the precipitation region, the propagation characteristic vector may vary between multiple locations. By analyzing these variations, the system can calculate the total propagation vector at each location. The total propagation vector, which comprehensively considers the changes in precipitation intensity in all directions at a given location, is a comprehensive propagation vector. This vector considers not only spatial variations in precipitation intensity but may also include temporal factors, thus providing a more comprehensive description of precipitation propagation at different locations. Using the propagation characteristic vector of each location, similar propagation characteristics can be clustered to form regions. Specifically, based on the total propagation vector, the algorithm performs cluster analysis on location points, grouping points with similar propagation characteristics into a single region. The clustering index is a measure of the similarity in propagation characteristics between two adjacent locations; it may be some kind of distance or similarity metric. Based on the clustering indices of all adjacent locations, the system can... The precipitation area is divided into multiple clusters; each cluster represents a precipitation area with similar propagation characteristics. By analyzing each cluster, the precipitation intensity within each cluster can be determined. If the precipitation intensity in a certain area exceeds a set threshold or exhibits particularly drastic precipitation changes, it will be considered an extreme precipitation area. Extreme precipitation areas are extracted from the 3D precipitation projection map: by analyzing each cluster, areas with extreme precipitation characteristics are identified, and these areas are extracted from the 3D precipitation projection map. Finally, the entire process extracts the 3D extreme precipitation areas. These areas are regions with particularly drastic precipitation intensity and rate of change, which may usually have a serious impact on the ground, such as floods and flash floods.

[0117] In an optional embodiment, determining the propagation characteristic vector of each location point based on the point intensity at other locations along each precipitation propagation line includes:

[0118] For two adjacent points along the same precipitation propagation line, the maximum and minimum values ​​of the ratio of the point intensity of the earlier point to that of the later point are normalized to obtain the vector magnitude.

[0119] Along the precipitation propagation line, the direction corresponding to the propagation of point intensity from high to low is taken as the vector direction;

[0120] The intensity change vector along the corresponding precipitation propagation line is determined based on the vector magnitude and vector direction;

[0121] The propagation characteristic vector of a location point is obtained by summing the intensity change vectors along all precipitation propagation lines.

[0122] It should be noted that on the precipitation propagation line, two adjacent points are selected: one is the earlier point (usually closer to the origin), and the other is the later point (a subsequent position). To make the ratio more comparable, it is usually normalized. The purpose of normalization is to adjust the ratio to a standard range (e.g., between 0 and 1). A specific method is to calculate the maximum and minimum values ​​and convert them to the standard range using a normalization formula. The normalized ratio is used as the magnitude of the vector. The magnitude of the vector describes the magnitude of the change in precipitation intensity from one location to another, reflecting the relative degree of change in precipitation intensity. Along the precipitation propagation line, precipitation intensity changes. Assuming that the point intensity propagates from higher to lower, then the vector direction is determined as the direction in which the point intensity changes from high to low. Based on the vector magnitude (the normalized ratio of point intensities) and direction (the direction of intensity change), the ratio is determined. This method can determine the intensity change vector along each precipitation propagation line. This vector contains both the magnitude (magnitude) and the direction (propagation from high to low). A long magnitude indicates drastic changes in precipitation intensity, while a short magnitude indicates relatively gentle changes. If the direction points to the origin or an adjacent point, it indicates the direction of precipitation intensity propagation. The intensity change vectors along all precipitation propagation lines are as follows: In a 3D precipitation projection map, there are multiple precipitation propagation lines; each line has its corresponding intensity change vector. The system performs vector summation on these vectors. By summing the intensity change vectors along each precipitation propagation line, the propagation characteristic vector for each location point is obtained. This propagation characteristic vector integrates the intensity change information in all propagation directions at that location point; it is a multi-dimensional vector that reflects the precipitation intensity change pattern and propagation characteristics at that location point.

[0123] Example 2, please refer to Figure 2This invention provides a technical solution: an extreme precipitation area frequency analysis system based on radar precipitation products, applicable to the aforementioned extreme precipitation area frequency analysis method based on radar precipitation products, comprising:

[0124] Data acquisition unit 1 is used to divide the precipitation monitoring area into grids to obtain a precipitation grid set; it acquires precipitation echo signals based on radar precipitation products, and divides the precipitation grid set according to a preset echo intensity threshold to obtain precipitation candidate areas.

[0125] The three-dimensional projection unit 2 is used to extract features from the candidate precipitation area to obtain a set of precipitation spatial features. Based on the set of precipitation spatial features, a three-dimensional precipitation projection map is constructed. Key points are extracted from the three-dimensional precipitation projection map to obtain a sequence of precipitation key point coordinates.

[0126] Precipitation location unit 3 is used to determine precipitation hotspot areas based on the coordinate sequence of precipitation key points; perform boundary detection on precipitation hotspot areas to obtain the boundary of extreme precipitation areas; segment precipitation hotspot areas based on the boundary of extreme precipitation areas to obtain extreme precipitation event segments; and perform spatial coordinate transformation on extreme precipitation event segments to obtain extreme precipitation location information.

[0127] The intensity detection unit 4 is used to determine the precipitation type information of the extreme precipitation event segment based on the extreme precipitation location information; wherein, the precipitation type information includes the first precipitation event and the second precipitation event; and to perform precipitation intensity detection on the first precipitation event and the second precipitation event based on the extreme precipitation location information to obtain the precipitation intensity type information.

[0128] The embodiments of the present invention have been described in detail above with reference to the accompanying drawings. However, the present invention is not limited thereto. Various changes can be made within the scope of knowledge possessed by those skilled in the art without departing from the spirit of the present invention.

Claims

1. A method for frequency analysis of extreme precipitation areas based on radar precipitation products, characterized in that, include: The precipitation monitoring area is divided into grids to obtain a precipitation grid set; Based on the precipitation echo signal acquired from radar precipitation products, the precipitation grid set is segmented according to a preset echo intensity threshold to obtain precipitation candidate areas; Feature extraction is performed on the candidate precipitation region to obtain a precipitation spatial feature set. A three-dimensional precipitation projection map is constructed based on the precipitation spatial feature set. Key points are extracted from the three-dimensional precipitation projection map to obtain a precipitation key point coordinate sequence. The precipitation hotspot areas were determined based on the coordinate sequence of the key precipitation points. Boundary detection is performed on the precipitation hotspot areas to obtain the boundaries of extreme precipitation areas. The precipitation hotspot areas are then segmented according to the boundaries of the extreme precipitation areas to obtain extreme precipitation event segments. Spatial coordinate transformation is performed on the extreme precipitation event segments to obtain extreme precipitation location information. The precipitation type information of the extreme precipitation event segment is determined based on the extreme precipitation location information; wherein, the precipitation type information includes a first precipitation event and a second precipitation event; precipitation intensity is detected for the first precipitation event and the second precipitation event based on the extreme precipitation location information to obtain precipitation intensity type information.

2. The method for frequency analysis of extreme precipitation areas based on radar precipitation products according to claim 1, characterized in that, A three-dimensional precipitation projection map is constructed based on the aforementioned set of spatial precipitation features, including: The projection parameters are determined based on the set of spatial features of precipitation; wherein the set of spatial features of precipitation includes precipitation intensity, precipitation range, and precipitation height; and the projection parameters include horizontal projection boundary, vertical projection boundary, and projection resolution. A three-dimensional precipitation projection map is constructed based on the projection parameters; wherein, the three-dimensional precipitation projection map is used to map the spatial distribution pattern of precipitation.

3. The method for frequency analysis of extreme precipitation areas based on radar precipitation products according to claim 2, characterized in that, The projection parameters are determined based on the aforementioned set of spatial features of precipitation, including: The horizontal projection boundary is determined based on the precipitation range and the preset range threshold. The vertical projection boundary is determined based on the precipitation height and the preset height threshold. The projection resolution is determined based on the precipitation intensity and a preset intensity threshold. Constructing a three-dimensional precipitation projection map based on the projection parameters includes: The precipitation projection space is determined based on the horizontal projection boundary, the vertical projection boundary, and the projection resolution. The three-dimensional precipitation projection map is formed by mapping the distribution pattern of precipitation in three-dimensional space according to the precipitation projection space; wherein, the precipitation projection space represents the projection range of three-dimensional precipitation on the horizontal plane, the horizontal projection boundary represents the boundary of the precipitation projection space in the horizontal direction, and the vertical projection boundary represents the height boundary of the precipitation projection space in the vertical direction.

4. The method for frequency analysis of extreme precipitation areas based on radar precipitation products according to claim 3, characterized in that, Key points are extracted from the three-dimensional precipitation projection map to obtain a sequence of precipitation key point coordinates, including: The precipitation type is obtained, and the coding parameters are determined based on the precipitation type; wherein, the precipitation type includes convective precipitation, stratiform cloud precipitation, and mixed precipitation; the coding parameters include key point extraction threshold and key point density threshold, wherein the key point extraction threshold for convective precipitation is lower than that for stratiform cloud precipitation, and the key point density threshold for mixed precipitation is higher than that for convective precipitation. Based on the matching results between the precipitation type and the preset type library, the corresponding coding parameter template is called; wherein, the preset type library includes coding parameter combinations corresponding to different precipitation types, and the coding parameter combinations include key point extraction threshold, key point density threshold and coding accuracy level; Based on the encoded parameter template, key points are extracted from the three-dimensional precipitation projection map to obtain a sequence of precipitation key point coordinates. In response to the number of key points in the precipitation key point coordinate sequence exceeding a preset threshold, it is determined that the current area has dense precipitation. In response to the fact that the number of key points in the precipitation key point coordinate sequence does not exceed a preset number threshold, it is determined that the current area has sparse precipitation; wherein, the preset number threshold is determined based on the average number of key points in historical precipitation data.

5. The method for extreme precipitation area frequency analysis based on radar precipitation products according to claim 4, characterized in that, Based on the extreme precipitation location information, the precipitation type information of the extreme precipitation event segment is determined, including: In response to detecting that the precipitation range of the first precipitation event exceeds a preset first range threshold based on the extreme precipitation location information, the precipitation duration of the first precipitation event is determined; In response to the precipitation duration exceeding a preset first time threshold, the first precipitation event is marked as a first precipitation type; In response to detecting that the movement rate of the precipitation center of the second precipitation event exceeds a preset rate threshold based on the extreme precipitation location information, the precipitation intensity change rate of the second precipitation event is determined; In response to the precipitation intensity change rate exceeding a preset intensity threshold, the second precipitation event is marked as a second precipitation type; The precipitation type information is determined based on the first precipitation type and the second precipitation type.

6. The method for extreme precipitation area frequency analysis based on radar precipitation products according to claim 5, characterized in that: Based on the extreme precipitation location information, precipitation intensity is detected for the first and second precipitation events to obtain precipitation intensity type information, including: Spatial clustering was performed on the coordinate sequence of key precipitation points of the first precipitation event to obtain the first precipitation core area; The average precipitation intensity per unit time is determined based on the echo intensity time series of the first precipitation core area; In response to the average precipitation intensity exceeding a preset first intensity threshold, first intensity type information is determined; The precipitation hotspots of the second precipitation event are processed by time-series segmentation to obtain multiple precipitation sub-events; The cumulative precipitation is determined based on the precipitation range and duration of each precipitation sub-event. In response to the cumulative precipitation exceeding a preset second intensity threshold, second intensity type information is determined; The precipitation intensity type information is determined based on the first intensity type information and the second intensity type information.

7. The method for frequency analysis of extreme precipitation areas based on radar precipitation products according to claim 6, characterized in that, Based on the extreme precipitation location information, precipitation intensity is detected for the first precipitation event and the second precipitation event to obtain precipitation intensity type information, and the method further includes: In response to detecting that the rate of change of precipitation intensity in the precipitation area is greater than a preset rate threshold based on the extreme precipitation location information, a warning message is issued to the precipitation area; In response to the detection that the precipitation area is still greater than the preset rate threshold after the warning information is issued, the third intensity type information is determined; Based on the first intensity type information, the second intensity type information, and the third intensity type information, the precipitation intensity type information is determined.

8. The method for frequency analysis of extreme precipitation areas based on radar precipitation products according to claim 7, characterized in that, The method further includes: In the three-dimensional precipitation projection map, any point is taken as the origin, and the ray connecting the origin to other points within the preset spatiotemporal neighborhood is used as the precipitation propagation line. The point intensity is determined based on the precipitation intensity type information at the same location and time point in the three-dimensional precipitation projection map; the propagation characteristic vector of each location point is determined based on the point intensity of other locations on each precipitation propagation line. The total propagation vector at each location point is determined based on the changes in the propagation characteristic vector at different locations. Based on the total propagation vector, the region is clustered to determine the clustering index of two adjacent locations. Based on the clustering index of all two adjacent locations, the region is divided to determine the clustered region. Based on the point intensity of each location within each clustered region, the extreme precipitation region is determined. The extreme precipitation region is extracted from the three-dimensional precipitation projection map to obtain the three-dimensional extreme region.

9. The method for frequency analysis of extreme precipitation areas based on radar precipitation products according to claim 8, characterized in that, Based on the point intensities at other points along each precipitation propagation line, determine the propagation characteristic vector at each point, including: For two adjacent points along the same precipitation propagation line, the maximum and minimum values ​​of the ratio of the point intensity of the earlier point to that of the later point are normalized to obtain the vector magnitude. Along the precipitation propagation line, the direction corresponding to the propagation of point intensity from high to low is taken as the vector direction; The intensity change vector along the corresponding precipitation propagation line is determined based on the vector magnitude and the vector direction. The propagation characteristic vector of a location point is obtained by summing the intensity change vectors along all precipitation propagation lines.

10. A frequency analysis system for extreme precipitation areas based on radar precipitation products, applicable to the frequency analysis method for extreme precipitation areas based on radar precipitation products as described in any one of claims 1-9, characterized in that, include: The data acquisition unit is used to divide the precipitation monitoring area into grids to obtain a precipitation grid set. Based on the precipitation echo signal acquired from radar precipitation products, the precipitation grid set is segmented according to a preset echo intensity threshold to obtain precipitation candidate areas; A three-dimensional projection unit is used to extract features from the candidate precipitation region to obtain a precipitation spatial feature set, construct a three-dimensional precipitation projection map based on the precipitation spatial feature set, and extract key points from the three-dimensional precipitation projection map to obtain a precipitation key point coordinate sequence. A precipitation location unit is used to determine precipitation hotspot areas based on the sequence of coordinates of key precipitation points. Boundary detection is performed on the precipitation hotspot areas to obtain the boundaries of extreme precipitation areas. The precipitation hotspot areas are then segmented according to the boundaries of the extreme precipitation areas to obtain extreme precipitation event segments. Spatial coordinate transformation is performed on the extreme precipitation event segments to obtain extreme precipitation location information. An intensity detection unit is used to determine the precipitation type information of the extreme precipitation event segment based on the extreme precipitation location information; wherein the precipitation type information includes a first precipitation event and a second precipitation event; and to perform precipitation intensity detection on the first precipitation event and the second precipitation event based on the extreme precipitation location information to obtain precipitation intensity type information.

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