An intelligent integrated monitoring and display system and method for weather radar

Abstract

The present invention relates to the technical field of meteorological display, and discloses a weather radar intelligent integrated monitoring and display system and method, including a tornado monitoring and prediction system. The tornado monitoring and prediction system includes: an environmental factor monitoring module, which uses the environmental factor monitoring module to monitor and collect data on temperature, air pressure, dryness and humidity, cumulonimbus clouds and wind fields in the monitoring area; an environmental factor data processing module, which predicts the flow direction of air currents based on the monitored and collected temperature and air pressure data and in combination with the wind field data. This weather radar intelligent integrated monitoring and display system and method, through the tornado monitoring and prediction system, uses the environmental factor monitoring module to collect data on temperature, air pressure, dryness and humidity, cumulonimbus clouds and wind fields in the monitoring area, and predicts the flow direction of wind field air currents in the cumulonimbus cloud area and the dry-wet intersection area where tornadoes are likely to occur. According to the height, rotation diameter and wind speed of the predicted wind field air currents, tornadoes can be predicted.

Description

Technical Field

[0001] The present invention relates to the technical field of meteorological display, and specifically to a weather radar intelligent integrated monitoring and display system and method. Background Art

[0002] A tornado is one of the most violent and destructive types of severe convective weather, capable of causing heavy casualties and property losses in a short period of time. By monitoring and forecasting tornadoes, the harm caused to people by tornadoes can be reduced and property losses can be minimized.

[0003] Currently, using the PUP software for single-station radar product analysis is one of the important ways to monitor tornadoes. However, this technology can only monitor tornadoes that have already formed and predict the path of tornadoes. It is very difficult to predict in advance the areas where tornadoes may occur. In the areas where tornadoes may occur, corresponding measures cannot be taken in a timely manner when a tornado appears. In addition, the existing integrated monitoring and display system based on a multi-radar stereo monitoring network can improve the monitoring and early warning effects of tornadoes, but it requires installing professional software and downloading data to the local area to display and use, and at the same time does not support the display function of multiple types of radar products. Summary of the Invention

[0004] To solve the problems that it is very difficult to predict in advance the areas where tornadoes may occur in the current existing technologies, and in addition, the existing integrated monitoring and display system based on a multi-radar stereo monitoring network requires installing professional software and downloading data to the local area to display and use, and at the same time does not support the display function of multiple types of radar products, the present invention is achieved through the following technical solutions: A weather radar intelligent integrated monitoring and display system includes a tornado monitoring and prediction system, and the tornado monitoring and prediction system includes:

[0005] An environmental factor monitoring module, which uses the environmental factor monitoring module to monitor and collect data on temperature, air pressure, dryness and humidity, cumulonimbus clouds and wind fields in the monitoring area. The environmental factor monitoring module includes weather radars such as Doppler radars and wind profilers. The data sources of the weather radars include the China Meteorological Administration Satellite Broadcast System, the National Integrated Meteorological Information Sharing System and the local Primary User Processor (PUP). The PUP product data is obtained through the data sources of the weather radars and sent to the PUP product storage server. The PUP product data includes data on temperature, air pressure, dryness and humidity, cumulonimbus clouds and wind fields in the monitoring area;

[0006] An environmental factor data processing module, which predicts the flow direction of airflows based on the monitored and collected temperature and air pressure data and in combination with the wind field data. In the atmospheric environment, the higher the temperature, the lower the air pressure, and the airflows will flow in the direction of lower pressure. The dry and wet intersection area in the monitoring area is determined based on the monitored and collected dryness and humidity data. The dry and wet intersection area is convectively unstable and prone to tornadoes;

[0007] A wind field air flow direction prediction module predicts the air flow direction of the wind field in the area below the cumulonimbus cloud where the monitoring and collection is carried out or in the dry-wet intersection area of the monitoring area according to the air flow direction predicted by the environmental factor data processing module. When a large amount of energy is contained in the cumulonimbus cloud, a part of the energy is released in a very small area, and the concentrated release of energy is likely to form a tornado. By predicting the air flow direction of the wind field in these two geographical areas prone to tornadoes, namely the area below the cumulonimbus cloud and the dry-wet intersection area of the monitoring area, the probability of a tornado occurring in the above two geographical areas can be further predicted.

[0008] A tornado prediction module determines the rotation diameter of the wind field air flow according to the predicted air flow direction of the wind field. At the same time, in combination with the height where the wind field air flow is located, the rotation diameter and the wind speed of the wind field air flow, it predicts the probability of a tornado occurring in the area below the cumulonimbus cloud or in the dry-wet intersection area of the monitoring area.

[0009] When the height of the wind field air flow is below 2 km, if the rotation diameter of the wind field air flow does not exceed 1000 m and the wind speed is not lower than 25 m / s, there is a possibility of a tornado occurring. The smaller the rotation diameter and / or the higher the wind speed, the higher the probability of a tornado occurring. When the height of the wind field air flow is between 2 km and 4 km, if the rotation diameter of the wind field air flow does not exceed 10 km and the wind speed is not lower than 30 m / s, there is a possibility of a tornado occurring. The smaller the rotation diameter and / or the higher the wind speed, the higher the probability of a tornado occurring. Therefore, according to the height where the wind field air flow is located, the rotation diameter and the wind speed of the wind field air flow, the probability of a tornado occurring in the area below the cumulonimbus cloud or in the dry-wet intersection area of the monitoring area can be predicted.

[0010] Furthermore, using the wind field data collected by the environmental factor monitoring module, it is determined whether a tornado already exists in the monitoring area. When the air flow height in the wind field data is below 2 km, the air flow rotation diameter is within 1000 m, and the speed reaches 25 m / s, or when the air flow height in the wind field data is above 2 km, the air flow rotation diameter is within 10 km, and the speed reaches 30 m / s, it is determined that a tornado has occurred at this monitoring point.

[0011] Furthermore, it further includes a tornado monitoring and display system. The tornado monitoring and display system converts the data of environmental factors collected in the tornado monitoring and prediction system into a GIS vector data layer and displays it in combination with the national geodetic coordinate system. At the same time, it displays the probability of a tornado occurring in the predicted monitoring area. The tornado monitoring and display system includes:

[0012] A data acquisition module uses the data acquisition module to collect the environmental factor data monitored and collected in the tornado monitoring and prediction system and the data of the wind field air flow for predicting the probability of a tornado occurring in the area below the cumulonimbus cloud or in the dry-wet intersection area of the monitoring area.

[0013] A data vectorization processing module, which uses JAVA technology to convert the data collected by the data collection module into an OpenGIS geometric object model, obtains a GIS vector data layer, and stores it in a PostGIS database;

[0014] A data service publishing module, which configures GeoServer to connect to the PostGIS database as a data source, and provides an invocation interface for the GIS vector data layer as a Web map service;

[0015] A data display module, where the WebGIS client invokes the GIS vector data layer of the Web map service interface through the HTTP protocol and overlays it with the geographic base map provided by the national geodetic coordinate system server for display.

[0016] The WMS interface standard defined by OpenGIS is a set of simple HTTP interfaces for transferring geographically located map image data from one or more geographic information databases. The radar product WMS interface is published externally by using the GeoServer WMS function. After configuring corresponding parameters such as layer name, projection coordinate system, and map style for each type of PUP product data, the client can call the interface through the GetMap operation of the WMS specification. After receiving the request, the Web map server automatically reads the radar product vector data and the map style file, realizes data rendering and picture drawing, and returns it to the user. The WMS interfaces of the products provided by the system include basic reflectivity, basic velocity, mesocyclone, and tornado characteristics.

[0017] Furthermore, the data of temperature, air pressure, dryness / humidity, cumulonimbus cloud, and wind field in the monitoring area are acquired by monitoring and collecting with weather radars.

[0018] Furthermore, the specific processing steps of the data vectorization processing module include:

[0019] Abstract the data of environmental factors at a monitoring point in the monitoring area collected by the weather radar into an OpenGIS polygon geometric object model. For the processing of PUP product data, the Kafka message system is introduced, and the data processing is divided into two parts: PUP product message publishing and PUP product message subscription processing according to the distributed architecture to improve the reliability and scalability of the tornado monitoring and display system. The PUP product message publishing function deploys an application in the PUP product storage server to call the monitoring service interface provided by JAVA, uses the underlying file system function to monitor the changes in the file system, and publishes the newly added PUP product file message to the radar product message category of the Kafka message system;

[0020] The PUP product message subscription processing is to deploy the message subscription processing program through 2 microprocessors to form a Kafka consumer group, so as to realize the real-time load balancing processing of the PUP product data of multiple S-band radars and multiple X-band radars, and improve the concurrent processing ability of radar product messages;

[0021] The polar coordinates of the radial radar data of the environmental factors at a monitoring point in the monitoring area collected by the weather radar are converted into double standard parallel equal-area conic projection. A radial product consists of several radial data, and each radial data is composed of multiple distance-color pairs. Each distance-color pair encloses a fan-shaped ring. When performing data vectorization processing, the fan-shaped ring is simplified into an isosceles trapezoid for processing, that is, each distance-color pair is abstracted into a polygon of OpenGIS, and finally the polygon sets of the same color level are jointly analyzed and combined into a polygon geometric object model.

[0022] The conversion formula for converting the polar coordinates of the radial radar data into double standard parallel equal-area conic projection is:

[0023] albX = rsin(θ);

[0024] albY = rcos(θ);

[0025] Among them, albX is the Albers equal-area conic projection X-axis, albY is the Albers equal-area conic projection Y-axis, r is the distance from the vertex of the isosceles trapezoid to the display center of the weather radar, and θ is the polar coordinate azimuth angle of the vertex of the isosceles trapezoid with the display center of the weather radar as the origin;

[0026] Use the Geotools library to project the double standard parallel equal-area conic projection coordinates of the monitoring point into the national geodetic coordinate system to obtain the GIS vector data layer and store it in the PostGIS database.

[0027] Furthermore, the specific call of the service interface in the data service publishing module specifically includes:

[0028] Configure the data source, configure the IP, port, access account and password of the PostGIS database, and use the PostGIS database to store data;

[0029] Define the Web map service layer, create a new layer in the GeoServer service application, and set the GIS vector data layer;

[0030] Configure the SLD map style to control the display of each layer of the Web map service through the SLD standard;

[0031] The Web map service layer of the GIS vector data layer is called, and the Web map service interface of the GIS vector data layer is called through the HTTP protocol.

[0032] Furthermore, the WebGIS client adopts a three-layer design. The bottom layer is the geographic base map in the national geodetic coordinate system, the middle layer is the GIS vector data layer, and the top layer is the layer that displays the boundaries and distance ranges of the monitoring area.

[0033] The WebGIS client calls the geographic information service platform (national geodetic coordinate system) of the monitoring area as the geographic base map, and both the middle layer and the top layer call the radar product WMS interface through the HTTP protocol to obtain the real-time rendered layer and overlay it on the geographic base map for comprehensive display.

[0034] A weather radar intelligent comprehensive monitoring and display method includes the following specific methods:

[0035] Use a weather radar to monitor and collect data on temperature, air pressure, dryness and humidity, cumulonimbus clouds and wind fields in the monitoring area, and determine whether a tornado already exists in the monitoring area according to the wind field data collected by the monitoring.

[0036] Predict the flow direction of the air current according to the temperature and air pressure data collected by the monitoring and combined with the wind field data, and determine the dry-wet intersection area of the monitoring area according to the dryness and humidity data collected by the monitoring.

[0037] According to the predicted flow direction of the air current, predict the flow direction of the wind field air current below the area where the cumulonimbus cloud is located in the monitoring and collection or in the dry-wet intersection area of the monitoring area.

[0038] Determine the rotation diameter of the wind field air current according to the predicted flow direction of the wind field air current, and at the same time combine the height where the wind field air current is located, the rotation diameter and the wind speed of the wind field air current to predict the probability of a tornado occurring below the area where the cumulonimbus cloud is located in the monitoring and collection or in the dry-wet intersection area of the monitoring area.

[0039] Furthermore, it also includes:

[0040] Collect the environmental factor data collected by the tornado monitoring and prediction system and the data of the wind field air current with the probability of a tornado occurring below the area where the cumulonimbus cloud is located in the monitoring and collection or in the dry-wet intersection area of the monitoring area.

[0041] Use JAVA technology to convert the data collected by the data collection module into an OpenGIS geometric object model, obtain the GIS vector data layer, and store it in the PostGIS database.

[0042] Configure GeoServer to connect to the PostGIS database as the data source, and provide an external call interface for the GIS vector data layer as a Web map service.

[0043] The WebGIS client calls the Web map service interface GIS vector data layer through the HTTP protocol and overlays and displays it with the geographic base map provided by the national geodetic coordinate system server.

[0044] Compared with the prior art, the present invention has the following beneficial effects:

[0045] 1. For the weather radar intelligent integrated monitoring and display system and method, through the environmental factor monitoring module in the tornado monitoring and prediction system, the temperature, air pressure, dry and humidity, cumulonimbus cloud and wind field data of the monitoring area are collected, and the flow direction of the wind field air flow is predicted in the cumulonimbus cloud area and the dry-wet intersection area where tornadoes are likely to occur. According to the height, rotation diameter and wind speed of the predicted wind field air flow, tornadoes can be predicted in the areas where tornadoes are likely to occur, so as to take corresponding measures in time for the possible tornadoes.

[0046] 2. For the weather radar intelligent integrated monitoring and display system and method, through the combined design of the data acquisition module, data vectorization processing module, data service publishing module and data display module in the tornado monitoring and display system, the data of environmental factors collected by different types of radar products are vectorized. Users can directly obtain the display layer of the GIS vector data layer overlaid with the geographic base map provided by the national geodetic coordinate system server through the WebGIS client, and then intuitively obtain the tornado monitoring and early warning information. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 It is a schematic structural diagram of the weather radar intelligent integrated monitoring and display system of the present invention;

[0048] Figure 2 It is a flow chart of the weather radar intelligent integrated monitoring and display system of the present invention;

[0049] Figure 3 It is a schematic diagram of the radial radar data of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0050] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0051] Embodiments of the weather radar intelligent integrated monitoring and display system and method are as follows:

[0052] Please refer to Figures 1 - 3, a weather radar intelligent integrated monitoring and display system, including a tornado monitoring and prediction system and a tornado monitoring and display system. The tornado monitoring and prediction system includes:

[0053] An environmental factor monitoring module that monitors and collects data on temperature, air pressure, dryness and humidity, cumulonimbus clouds, and wind fields in the monitoring area. Using the wind field data collected by the environmental factor monitoring module, it determines whether a tornado already exists in the monitoring area. When the air flow height in the wind field data is below 2 km, the air flow rotation diameter is within 1000 m, and the speed reaches 25 m / s, or when the air flow height in the wind field data is above 2 km, the air flow rotation diameter is within 10 km, and the speed reaches 30 m / s, it is determined that a tornado has occurred at the monitoring point.

[0054] Data on temperature, air pressure, dryness and humidity, cumulonimbus clouds, and wind fields in the monitoring area are obtained through monitoring and collection by weather radars. The environmental factor monitoring module includes weather radars such as Doppler radars and wind profilers. The data sources of the weather radars include the China Meteorological Administration Satellite Broadcast System, the National Integrated Meteorological Information Sharing System, and the local Primary User Processor (PUP). The PUP product data is obtained through the data sources of the weather radars and sent to the PUP product storage server. The PUP product data includes data on temperature, air pressure, dryness and humidity, cumulonimbus clouds, and wind fields in the monitoring area. The data sources of the weather radars of the China Meteorological Administration Satellite Broadcast System and the local Primary User Processor (PUP) are sent to the PUP product storage server through the FTP protocol, and the data sources of the weather radars of the National Integrated Meteorological Information Sharing System are sent to the PUP product storage server through the HTTP protocol.

[0055] An environmental factor data processing module that predicts the flow direction of the air flow based on the monitored and collected temperature and air pressure data in combination with the wind field data. In the atmospheric environment, the higher the temperature, the lower the air pressure, and the air flow will flow towards the low-pressure direction. The dry-wet intersection area in the monitoring area is determined based on the monitored and collected dryness and humidity data. The dry-wet intersection area is convectively unstable and prone to tornadoes.

[0056] A wind field air flow direction prediction module that predicts the flow direction of the wind field air flow in the area below the cumulonimbus clouds in the monitored and collected area or in the dry-wet intersection area of the monitoring area based on the flow direction of the air flow predicted by the environmental factor data processing module. When a huge amount of energy is contained in the cumulonimbus clouds, a part of the energy is released in a very small area, and the concentrated release of energy is likely to form a tornado. By predicting the flow direction of the wind field air flow in the two geographical areas prone to tornadoes, namely the area below the cumulonimbus clouds in the monitored area and the dry-wet intersection area of the monitoring area, the probability of a tornado occurring in the above two geographical areas can be further predicted.

[0057] The tornado prediction module determines the rotation diameter of the wind field airflow according to the flow direction of the predicted wind field airflow. At the same time, combining the height where the wind field airflow is located, the rotation diameter of the wind field airflow, and the wind speed, it predicts the probability of a tornado occurring below the area where the cumulonimbus cloud is located or in the dry-wet intersection area of the monitoring area.

[0058] When the height of the wind field airflow is below 2 km, the rotation diameter of the wind field airflow does not exceed 1000 m, and the wind speed is not lower than 25 m / s, there is a possibility of a tornado occurring. The smaller the rotation diameter and / or the higher the wind speed, the higher the probability of a tornado occurring. When the height of the wind field airflow is between 2 km and 4 km, the rotation diameter of the wind field airflow does not exceed 10 km, and the wind speed is not lower than 30 m / s, there is a possibility of a tornado occurring. The smaller the rotation diameter and / or the higher the wind speed, the higher the probability of a tornado occurring. Therefore, according to the height where the wind field airflow is located, the rotation diameter of the wind field airflow, and the wind speed, the probability of a tornado occurring below the area where the cumulonimbus cloud is located or in the dry-wet intersection area of the monitoring area can be predicted.

[0059] The tornado monitoring and display system converts the data of environmental factors collected in the tornado monitoring and prediction system into a GIS vector data layer and displays it in combination with the national geodetic coordinate system. At the same time, it displays the probability of a tornado occurring in the predicted monitoring area. The tornado monitoring and display system includes:

[0060] The data acquisition module uses the data acquisition module to collect the data of environmental factors monitored and collected in the tornado monitoring and prediction system and the data of the wind field airflow that predicts the probability of a tornado occurring below the area where the cumulonimbus cloud is located or in the dry-wet intersection area of the monitoring area.

[0061] The data vectorization processing module uses JAVA technology to convert the data collected by the data acquisition module into an OpenGIS geometric object model, obtains a GIS vector data layer, and stores it in the PostGIS database.

[0062] The specific processing steps of the data vectorization processing module include:

[0063] Abstract the data of environmental factors of a monitoring point in the monitoring area collected by weather radar into an OpenGIS polygon geometric object model. The processing of PUP product data is to introduce the Kafka message system, and divide the data processing into two parts: PUP product message publishing and PUP product message subscription processing according to the distributed architecture, so as to improve the reliability and scalability of the tornado monitoring and display system. The PUP product message publishing function deploys an application program in the PUP product storage server to call the monitoring service interface provided by JAVA, uses the underlying file system function to monitor the changes of the file system, and publishes the new PUP product file message to the radar product message category of the Kafka message system.

[0064] The PUP product message subscription processing is to deploy the message subscription processing program through 2 microprocessors to form a Kafka consumer group, so as to realize the real-time load balancing processing of the PUP product data of multiple S-band radars and multiple X-band radars, and improve the concurrent processing ability of radar product messages.

[0065] The polar coordinates of the radial radar data of the environmental factors at a monitoring point in the monitoring area collected by the weather radar are converted into double standard parallel equal-area conic projection. A radial product consists of several radial data, and each radial data is composed of multiple distance-color pairs. Each distance-color pair encloses a fan-shaped ring. When performing data vectorization processing, the fan-shaped ring is simplified into an isosceles trapezoid for processing. As Figure 3 shown, the isosceles trapezoid is composed of four vertices A, B, C, and D, that is, each distance-color pair is abstracted into a polygon of OpenGIS, and finally the polygon set of the same color level is analyzed jointly and combined into a polygon geometric object model.

[0066] The conversion formula for converting the polar coordinates of the radial radar data into double standard parallel equal-area conic projection is:

[0067] albX = rsin(θ);

[0068] albY = rcos(θ);

[0069] Among them, albX is the Albers equal-area conic projection X-axis, albY is the Albers equal-area conic projection Y-axis, r is the distance from the vertex of the isosceles trapezoid to the display center of the weather radar, and θ is the polar coordinate azimuth angle of the vertex of the isosceles trapezoid with the display center of the weather radar as the origin.

[0070] Use the Geotools library to project the double standard parallel equal-area conic projection coordinates of the monitoring point into the national geodetic coordinate system to obtain the GIS vector data layer and store it in the PostGIS database.

[0071] The data service publishing module configures GeoServer to connect to the PostGIS database as the data source and provides a call interface for the GIS vector data layer as a Web map service.

[0072] The specific calls of the service interface in the data service publishing module specifically include:

[0073] Configure the data source, configure the IP, port, access account, and password of the PostGIS database, and use the PostGIS database to store data.

[0074] Define the Web map service layer, create a new layer in the GeoServer service application, and set the GIS vector data layer.

[0075] Configure the SLD map style to control the display of each layer of the Web map service through the SLD standard.

[0076] Invoke the Web map service layer of the GIS vector data layer, and call the Web map service interface of the GIS vector data layer through the HTTP protocol.

[0077] Data display module. The WebGIS client calls the Web map service interface of the GIS vector data layer through the HTTP protocol and overlays it with the geographic base map provided by the national geodetic coordinate system server for display.

[0078] The WebGIS client adopts a three-layer design. The bottom layer is the national geodetic coordinate system geographic base map, the middle layer is the GIS vector data layer, and the top layer is the layer that displays the boundaries and distance ranges of the monitoring area.

[0079] The WebGIS client calls the sliced map Web service (WMTS) of the geographic information service platform (national geodetic coordinate system server) of the monitoring area as the geographic base map. Both the middle layer and the top layer call the radar product WMS interface through the HTTP protocol to obtain the real-time rendered layer and overlay it on the geographic base map for comprehensive display.

[0080] The WMS interface standard defined by OpenGIS is a set of simple HTTP interfaces for transferring geographically located map image data from one or more geographic information databases. The radar product WMS interface is published externally through the GeoServer WMS function. After configuring parameters such as the corresponding layer name, projection coordinate system, and map style for each type of PUP product data, the client can call the interface through the GetMap operation of the WMS specification. After receiving the request, the Web map server automatically reads the radar product vector data and map style files, realizes the rendering of the data and the drawing of the picture, and returns it to the user. The WMS interfaces provided by the system for the products include basic reflectivity, basic velocity, mesocyclone, and tornado characteristics.

[0081] A weather radar intelligent integrated monitoring and display method includes the following specific methods:

[0082] Use the weather radar to monitor and collect data on temperature, air pressure, dryness, humidity, cumulonimbus clouds, and wind fields in the monitoring area. Based on the wind field data collected by the monitoring, determine whether there is a tornado in the monitoring area;

[0083] Predict the flow direction of the air current based on the temperature and air pressure data collected by the monitoring and combined with the wind field data, and determine the dry-wet intersection area in the monitoring area based on the dryness and humidity data collected by the monitoring;

[0084] According to the predicted flow direction of the air current, predict the flow direction of the wind field air current in the area below the cumulonimbus cloud where the monitoring and collection are carried out or in the dry-wet intersection area of the monitoring area;

[0085] Determine the rotation diameter of the wind field air current according to the predicted flow direction of the wind field air current. At the same time, combine the height where the wind field air current is located, the rotation diameter of the wind field air current, and the wind speed to predict the probability of a tornado occurring in the area below the cumulonimbus cloud where the monitoring and collection are carried out or in the dry-wet intersection area of the monitoring area;

[0086] Collect the environmental factor data monitored and collected in the tornado monitoring and prediction system and the data of the wind field air current with the probability of a tornado occurring in the area below the cumulonimbus cloud where the monitoring and collection are carried out or in the dry-wet intersection area of the monitoring area;

[0087] Use JAVA technology to convert the data collected by the data collection module into an OpenGIS geometric object model, obtain a GIS vector data layer, and store it in the PostGIS database;

[0088] By configuring GeoServer to connect to the PostGIS database as a data source, provide a call interface for the GIS vector data layer as a Web map service;

[0089] The WebGIS client calls the GIS vector data layer of the Web map service interface through the HTTP protocol and overlays and displays it with the geographical base map provided by the national geodetic coordinate system server.

[0090] Working process of the weather radar intelligent integrated monitoring and display system:

[0091] First, use the weather radar to monitor and collect the data of temperature, air pressure, dryness and humidity, cumulonimbus cloud and wind field in the monitoring area. Use the wind field data collected by the environmental factor monitoring module to determine whether there is already a tornado in the monitoring area. Use the environmental factor data processing module in the tornado monitoring and prediction system to simulate and predict the flow direction of the air current according to the monitored and collected temperature and air pressure data and combine with the wind field data, and determine the dry-wet intersection area of the monitoring area according to the monitored and collected dryness and humidity data.

[0092] The wind field air current flow direction prediction module predicts the flow direction of the wind field air current in the area below the cumulonimbus cloud where the monitoring and collection are carried out or in the dry-wet intersection area of the monitoring area according to the flow direction of the air current simulated and predicted by the environmental factor data processing module. The tornado prediction module determines the rotation diameter of the wind field air current according to the predicted flow direction of the wind field air current. At the same time, combine the height where the wind field air current is located, the rotation diameter of the wind field air current, and the wind speed to predict the probability of a tornado occurring in the area below the cumulonimbus cloud where the monitoring and collection are carried out or in the dry-wet intersection area of the determined monitoring area.

[0093] When the height of the wind field airflow is below 2 km, the rotation diameter of the wind field airflow does not exceed 1000 m, and when the wind speed is not less than 25 m / s, there is a possibility of a tornado occurring. The smaller the rotation diameter and / or the higher the wind speed, the higher the probability of a tornado occurring. When the height of the wind field airflow is between 2 km and 4 km, the rotation diameter of the wind field airflow does not exceed 10 km, and when the wind speed is not less than 30 m / s, there is a possibility of a tornado occurring. The smaller the rotation diameter and / or the higher the wind speed, the higher the probability of a tornado occurring.

[0094] After the tornado monitoring and prediction system completes the monitoring and collection of environmental factor data, the data acquisition module in the tornado monitoring display system acquires the environmental factor data monitored and collected by the tornado monitoring and prediction system, as well as the data of the wind field airflow where the probability of a tornado occurring in the area below the predicted cumulonimbus cloud or in the dry-wet intersection area of the monitoring area.

[0095] The data vectorization processing module uses JAVA technology to convert the data collected by the data acquisition module into an OpenGIS geometric object model, obtains a GIS vector data layer, and stores it in the PostGIS database; the data service publishing module configures GeoServer to connect to the PostGIS database as a data source, and provides an invocation interface for the GIS vector data layer as a Web map service.

[0096] The WebGIS client calls the GIS vector data layer of the Web map service interface through the HTTP protocol and overlays it with the geographic base map provided by the national geodetic coordinate system server for display.

[0097] Although the embodiments of the present invention have been shown and described, for those of ordinary skill in the art, it can be understood that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A weather radar intelligent integrated monitoring and display system, including a tornado monitoring and prediction system, characterized in that: The tornado monitoring and prediction system comprises: An environmental factor monitoring module is used to monitor and collect data on temperature, air pressure, dryness and humidity, cumulonimbus clouds and wind field in the monitoring area; The environmental factor data processing module predicts the direction of airflow based on the monitored and collected temperature and air pressure data combined with the wind field data, and determines the dry and wet intersection area of ​​the monitored area based on the monitored and collected dry and wet data; A wind field airflow direction prediction module predicts the direction of the wind field airflow below the area where the monitored and collected cumulonimbus clouds are located or in the dry and wet intersection area of ​​the monitored area according to the direction of the airflow predicted by the environmental factor data processing module; The tornado prediction module determines the rotation diameter of the wind field airflow according to the predicted flow direction of the wind field airflow, and predicts the probability of a tornado occurring below the cumulonimbus cloud area or in the dry-wet intersection area of ​​the monitoring area in combination with the height of the wind field airflow, the rotation diameter of the wind field airflow and the wind speed.

2. The weather radar intelligent comprehensive monitoring and display system according to claim 1 is characterized in that: The wind field data collected by the environmental factor monitoring module is used to determine whether a tornado already exists in the monitoring area.

3. The weather radar intelligent comprehensive monitoring and display system according to claim 2 is characterized in that: Also included is a tornado monitoring and display system, the tornado monitoring and display system comprising: A data acquisition module is used to collect environmental factor data monitored and collected in the tornado monitoring and prediction system and wind field and airflow data for predicting the probability of a tornado occurring below the area where the cumulonimbus clouds are located or in the dry-wet intersection area of ​​the monitoring area; A data vectorization processing module uses JAVA technology to convert the data collected by the data collection module into an OpenGIS geometric object model, obtain a GIS vector data layer, and store it in a PostGIS database; The data service publishing module configures GeoServer to connect to the PostGIS database as a data source and provides a calling interface to the outside world as a Web map service; In the data display module, the WebGIS client calls the Web map service interface GIS vector data layer through the HTTP protocol, and overlays and displays it with the geographic base map provided by the national geodetic coordinate system server.

4. The weather radar intelligent comprehensive monitoring and display system according to claim 3 is characterized by: The data of temperature, air pressure, humidity, cumulonimbus clouds and wind field in the monitoring area are acquired by weather radar monitoring.

5. The weather radar intelligent comprehensive monitoring and display system according to claim 4 is characterized in that: The specific processing steps of the data vectorization processing module include: Abstracting the data of environmental factors of a certain monitoring point in the monitoring area collected by the weather radar monitoring into a polygonal geometric object model of OpenGIS; The polar coordinates of the radial radar data of the environmental factors of a certain monitoring point in the monitoring area collected by the weather radar monitoring are converted into a double standard latitude equal area conic projection, and the conversion formula is: albX = rsin(θ); albY=rcos(θ); Wherein, albX is the X-axis of the Albers equal-area conic projection, albY is the Y-axis of the Albers equal-area conic projection, r is the distance between the vertex of the isosceles trapezoid and the display center of the weather radar, and θ is the polar coordinate azimuth of the vertex of the isosceles trapezoid with the display center of the weather radar as the origin; The double standard parallel equal-area conic projection coordinates of the monitoring points were projected into the national geodetic coordinate system using the Geotools library to obtain a GIS vector data layer and stored in a PostGIS database.

6. The weather radar intelligent comprehensive monitoring and display system according to claim 5 is characterized in that: The specific call of the service interface in the data service publishing module specifically includes: Configure the data source, configure the IP, port, access account and password of the PostGIS database, and use the PostGIS database to store data; Define the Web map service layer, create a new layer in the GeoServer service application, and set the GIS vector data layer; Configure the SLD map style and control the display of each layer of the Web map service through the SLD standard; The Web map service layer call of the GIS vector data layer calls the Web map service interface of the GIS vector data layer through the HTTP protocol.

7. The weather radar intelligent comprehensive monitoring and display system according to claim 6 is characterized by: The WebGIS client adopts a three-layer design, the bottom layer is the national geodetic coordinate system geographic base map, the middle layer is the GIS vector data layer, and the top layer is a layer showing the boundary and distance range of the monitoring area.

8. A weather radar intelligent comprehensive monitoring and display method, using the weather radar intelligent comprehensive monitoring and display system according to claim 6 or 7, characterized in that: The following specific methods are included: Using weather radar to monitor and collect data on temperature, air pressure, dryness and humidity, cumulonimbus clouds and wind field in the monitoring area, and determining whether a tornado already exists in the monitoring area based on the wind field data collected by monitoring; Predict the direction of airflow based on the temperature and air pressure data collected by monitoring and combined with wind field data, and determine the dry-wet intersection area of ​​the monitoring area based on the dry-wet data collected by monitoring; According to the predicted airflow direction, predict the airflow direction of the wind field below the area where the cumulonimbus clouds collected by monitoring are located or in the dry-wet intersection area of ​​the monitoring area; The rotation diameter of the wind field airflow is determined according to the predicted flow direction of the wind field airflow. At the same time, the probability of a tornado occurring below the cumulonimbus cloud area or in the dry and wet intersection area of ​​the monitoring area is predicted in combination with the height of the wind field airflow and the rotation diameter and wind speed of the wind field airflow.

9. The weather radar intelligent comprehensive monitoring and display method according to claim 8, characterized in that: Also includes: Collecting environmental factor data monitored and collected in the tornado monitoring and prediction system and wind field and airflow data of the probability of a tornado occurring below the area where the cumulonimbus clouds are located or in the dry-wet intersection area of ​​the monitoring area; The data collected by the data collection module is converted into an OpenGIS geometric object model using JAVA technology to obtain a GIS vector data layer and store it in a PostGIS database; By configuring GeoServer to connect to the PostGIS database as a data source, the GIS vector data layer is provided as a Web map service to the outside world with a calling interface; The WebGIS client calls the Web map service interface GIS vector data layer through the HTTP protocol, and overlays and displays it with the geographic base map provided by the national geodetic coordinate system server.

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