A millimeter-wave cloud radar observation method and related device based on multi-source data

Abstract

This application provides a millimeter-wave cloud radar observation method and related apparatus based on multi-source data. A fused dataset is formed by real-time acquisition and preprocessing of at least one of the following: weather radar mosaic data, meteorological satellite data, ground visibility observation data, and co-located or adjacent aerosol lidar data. A preset rule set is used to determine that the current weather scene at the cloud radar station includes at least weather echo approaching, weather echo receding, local weather processes, fog, and non-precipitating clouds. Based on the identified weather scene type, the corresponding combined scanning strategy (composed of a basic scanning mode consisting of vertical top-view scanning, distance-height scanning, and three-dimensional volume scanning, and a fine scanning mode consisting of local planar horizontal scanning and layered planar horizontal scanning, combined according to preset logic) is called from a preset strategy mapping table and executed. During execution, the parameters of the fine scanning mode are dynamically adjusted based on the position and intensity information of the real-time radar echo or changes in the detection mode.

Description

Technical Field

[0001] This application relates to the field of radar observation technology, and in particular to a millimeter-wave cloud radar observation method and related apparatus based on multi-source data. Background Technology

[0002] Millimeter-wave cloud radar, also known as cloud radar, is a core active microwave remote sensing device in the field of meteorological observation. It operates in the Ka band (about 35 GHz) or W band (about 94 GHz). With its high spatiotemporal resolution, all-weather continuous observation and strong cloud particle detection capabilities, it can penetrate cloud layers to obtain key information such as cloud vertical structure, cloud base / cloud top height and microphysical changes within the cloud. It is widely used in scenarios such as weather forecasting, weather modification, climate change research and aviation support.

[0003] Existing cloud radars are generally equipped with basic operating modes such as vertical top-scanning, range and height scanning, horizontal planar scanning, and three-dimensional volume scanning. Among them, the vertical top-scanning mode has the antenna fixed at a 90° elevation angle and has no mechanical scanning; the range and height scanning mode has a fixed azimuth and elevation angle that scans back and forth within a preset range to acquire vertical profile data; the horizontal planar scanning mode has a fixed elevation and azimuth angle that rotates 360° to acquire horizontal echo distribution; and the three-dimensional volume scanning mode consists of horizontal planar scanning at multiple elevation angles to construct a three-dimensional data volume.

[0004] Current mainstream cloud radar scanning strategies mostly involve periodically executing preset fixed programs. Examples include timed horizontal scanning at a fixed elevation angle, fixed azimuth distance and height scanning, or cyclical vertical top-view scanning or three-dimensional volumetric scanning. However, this traditional technology has significant limitations in practical applications and is difficult to adapt to the complex and ever-changing needs of meteorological observation.

[0005] The methods described in this section are not necessarily methods that had been previously conceived or adopted. Unless otherwise specified, no method described in this section should be assumed to be prior art simply because it is included in this section. Similarly, unless otherwise specified, the issues mentioned in this section should not be considered to be accepted in any prior art. Summary of the Invention

[0006] In view of this, embodiments of this application provide a millimeter-wave cloud radar observation method and related apparatus based on multi-source data.

[0007] In a first aspect, embodiments of this application provide a millimeter-wave cloud radar observation method based on multi-source data, the method comprising: Real-time acquisition and preprocessing of at least one of weather radar mosaic data, meteorological satellite data, ground visibility observation data, and co-located or adjacent aerosol lidar data to form a fused dataset; Based on the fused dataset, the weather scene type of the current weather at the cloud radar station is determined by a preset set of rules; the weather scene type includes at least weather echo approaching, weather echo moving away, local weather process, fog and non-precipitating clouds; According to the weather scene type, the corresponding combined scanning strategy is called from the preset strategy mapping table and executed; the combined scanning strategy is composed of a basic scanning mode and a fine scanning mode combined according to preset logic. The basic scanning mode includes vertical top scanning, distance and height scanning and three-dimensional volume scanning, and the fine scanning mode includes planar horizontal scanning. When executing the combined scanning strategy, the parameters of the fine scanning mode are dynamically adjusted based on the position and intensity information of the radar echo in real time or changes in the detection mode.

[0008] In one implementation, when the weather scene type is weather echo approaching or weather echo receding, the combined scanning strategy is distance-height scanning and horizontal scanning. The step of calling and executing the corresponding combined scanning strategy from the preset strategy mapping table includes: The echo region is scanned at preset azimuth intervals to obtain the vertical profile structure; Based on the scanning results of the distance and height scan, select N0 height layers with strong echoes, where the value of N0 ranges from 1 to 3; A horizontal scan with a limited azimuth range is performed at the altitude level; the azimuth range is set based on the echo region determined by the weather radar mosaic data. As the distance between the echo and the cloud radar station changes, the radar's pulse repetition frequency mode is adjusted synchronously.

[0009] In one implementation, when the weather scene type is a local weather process, the combined scanning strategy is vertical top-down scanning and low-elevation stereo volume scanning. The step of calling and executing the corresponding combined scanning strategy from the preset strategy mapping table includes: Perform continuous vertical top-view scanning observations for T0 minutes; the value of T0 ranges from 3 to 5 minutes. Based on the echo top height obtained from the vertical top-scan, a set of low elevation angles not exceeding 20° are set, and the low elevation angles include at least three of the following: 0.5°, 2.5°, 5°, 7.5°, 10° and 15°. Perform a stereo volume scan based on the low elevation angle.

[0010] In one implementation, when the weather scene type is fog, the combined scanning strategy is distance-height scanning and horizontal scanning. The step of calling and executing the corresponding combined scanning strategy from the preset strategy mapping table includes: Distance and altitude scanning are performed at azimuth intervals of K1 degrees; the value of K1 ranges from 20 to 30 degrees, and the elevation angle range of the distance and altitude scanning is 0 to 90 degrees. N1 fixed low elevation angles are selected to perform a horizontal plane scan; the value of N1 ranges from 2 to 3, and the low elevation angles include 0.5°, 1° and 2°; the azimuth range of the horizontal plane scan is set based on the fog zone boundary determined by satellite data and ground visibility data.

[0011] In one implementation, if the cloud radar station is located within a fog area, the combined scanning strategy is adjusted to vertical top-down scanning, range-height scanning, and horizontal planar scanning.

[0012] In one implementation, when the weather scene type is non-precipitating clouds, the combined scanning strategy is vertical top-down scanning and horizontal planar scanning; The step of calling and executing the corresponding combined scanning strategy from the preset strategy mapping table includes: Perform continuous vertical top-view scanning observations for T2 minutes; the value of T2 ranges from 3 to 5 minutes. The number of cloud layers, the height of the cloud base, the height of the cloud top, and the strong echo layer in the cloud are determined based on the scanning results of the vertical top scan. Perform a 0-360° omnidirectional horizontal scan on the cloud base, cloud top, and strong echo layer in the cloud for each cloud layer; If multiple layers of clouds exist, each layer is scanned sequentially from lowest to highest cloud height.

[0013] In one implementation, when the current weather at the cloud radar station is a weather type other than the weather scene type, a daily monitoring mode is adopted, and the combined scanning strategy is the vertical top-down scanning, distance and height scanning, and horizontal plane scanning.

[0014] The step of calling and executing the corresponding combined scanning strategy from the preset strategy mapping table includes: Perform continuous vertical top-view scanning observations for T3 minutes; the value of T3 ranges from 8 to 12 minutes. Distance and height scanning is performed at intervals of K2 degrees in the azimuth angle of 0-180°; the value of K2 is in the range of 25-35 degrees, and the elevation angle range of the distance and height scanning is 0-180 degrees; finally, a 360° all-round horizontal planar scan with a low elevation angle of 0.5° or 1° is performed.

[0015] Secondly, embodiments of this application provide a millimeter-wave cloud radar observation device based on multi-source data, the device comprising: The acquisition module is used to acquire and preprocess at least one of weather radar mosaic data, meteorological satellite data, ground visibility observation data, and co-located or adjacent aerosol lidar data in real time to form a fused dataset. The judgment module is used to determine the weather scene type of the current weather at the cloud radar station based on the fused dataset and a preset rule set; the weather scene type includes at least weather echo approaching, weather echo moving away, local weather process, fog and non-precipitating clouds; The calling module is used to call and execute the corresponding combined scanning strategy from the preset strategy mapping table according to the weather scene type. The combined scanning strategy is composed of a basic scanning mode and a fine scanning mode combined according to preset logic. The basic scanning mode includes vertical top scanning, distance and height scanning and three-dimensional volume scanning. The fine scanning mode includes local plane horizontal scanning and layered plane horizontal scanning. The adjustment module is used to dynamically adjust the parameters of the fine scanning mode based on the position and intensity information of the radar echo or changes in the detection mode when executing the combined scanning strategy.

[0016] In one implementation, when the weather scene type is weather echo approaching or weather echo receding, the combined scanning strategy is distance-height scanning and horizontal scanning. The module is specifically used to perform distance and height scanning on the echo region at preset azimuth intervals to obtain the vertical profile structure. Based on the scanning results of the distance and height scan, select N0 height layers with strong echoes, where the value of N0 ranges from 1 to 3; A horizontal scan with a limited azimuth range is performed at the altitude level; the azimuth range is set based on the echo region determined by the weather radar mosaic data. As the distance between the echo and the cloud radar station changes, the radar's pulse repetition frequency mode is adjusted synchronously.

[0017] In one implementation, when the weather scene type is a local weather process, the combined scanning strategy is vertical top-down scanning and low-elevation stereo volume scanning. The calling module is specifically used to perform continuous vertical top-scan observations for T0 minutes; the value of T0 ranges from 3 to 5 minutes. Based on the echo top height obtained from the vertical top-scan, a set of low elevation angles not exceeding 20° are set, and the low elevation angles include at least three of the following: 0.5°, 2.5°, 5°, 7.5°, 10° and 15°. Perform a stereo volume scan based on the low elevation angle.

[0018] In one implementation, when the weather scene type is fog, the combined scanning strategy is distance-height scanning and horizontal scanning. The calling module is specifically used to perform distance and height scanning at azimuth intervals of K1 degrees; the value of K1 ranges from 20 to 30 degrees, and the elevation angle range of the distance and height scanning is 0 to 90 degrees. N1 fixed low elevation angles are selected to perform a horizontal plane scan; the value of N1 ranges from 2 to 3, and the low elevation angles include 0.5°, 1° and 2°; the azimuth range of the horizontal plane scan is set based on the fog zone boundary determined by satellite data and ground visibility data.

[0019] In one implementation, if the cloud radar station is located within a fog area, the combined scanning strategy is adjusted to vertical top-down scanning, range-height scanning, and horizontal planar scanning.

[0020] In one implementation, when the weather scene type is non-precipitating clouds, the combined scanning strategy is vertical top-down scanning and horizontal planar scanning; The module is specifically used to perform continuous vertical top-scan observations for T2 minutes; the value of T2 ranges from 3 to 5 minutes. The number of cloud layers, the height of the cloud base, the height of the cloud top, and the strong echo layer in the cloud are determined based on the scanning results of the vertical top scan. Perform a 0-360° omnidirectional horizontal scan on the cloud base, cloud top, and strong echo layer in the cloud for each cloud layer; If multiple layers of clouds exist, each layer is scanned sequentially from lowest to highest cloud height.

[0021] In one implementation, when the current weather at the cloud radar station is a weather type other than the weather scene type, a daily monitoring mode is adopted, and the combined scanning strategy is the vertical top-down scanning, distance and height scanning, and horizontal plane scanning. The module is specifically used to perform continuous vertical top-scan observations for T3 minutes; the value of T3 ranges from 8 to 12 minutes. Distance and height scanning is performed at intervals of K2 degrees in the azimuth angle of 0-180°; the value of K2 is in the range of 25-35 degrees, and the elevation angle range of the distance and height scanning is 0-180 degrees; finally, a 360° all-round horizontal planar scan with a low elevation angle of 0.5° or 1° is performed.

[0022] Thirdly, embodiments of this application provide a device including a memory and a processor. The memory is used to store instructions or code, and the processor is used to execute the instructions or code to cause the device to perform the millimeter-wave cloud radar observation method based on multi-source data as described in any of the first aspects above.

[0023] Fourthly, embodiments of this application provide a computer storage medium storing code. When the code is executed, a device running the code implements the millimeter-wave cloud radar observation method based on multi-source data as described in any of the first aspects above.

[0024] This application embodiment acquires and preprocesses at least one of weather radar mosaic data, meteorological satellite data, ground visibility observation data, and co-located or adjacent aerosol lidar data in real time to form a fused dataset. Based on this fused dataset, a preset rule set is used to determine that the cloud radar station currently contains at least the following weather scene types: approaching weather echo, distant weather echo, local weather process, fog, and non-precipitating clouds. Then, according to the identified weather scene type, the corresponding combined scanning strategy (composed of a basic scanning mode consisting of vertical top scanning, distance and height scanning, and three-dimensional volume scanning, and a fine scanning mode consisting of local planar horizontal scanning and layered planar horizontal scanning, combined according to preset logic) is called from a preset strategy mapping table and executed. During the execution process, the parameters of the fine scanning mode are dynamically adjusted based on the position and intensity information of the radar echo in real time or changes in the detection mode.

[0025] This application embodiment achieves accurate weather scene identification through the fusion of multi-source meteorological data, avoiding the limitations of single data source judgment and providing a reliable basis for the adaptation of scanning strategies. By configuring corresponding combined scanning strategies for different weather scenes, it breaks the rigid limitations of traditional fixed scanning modes, making the scanning action more in line with the characteristics of weather targets. At the same time, the dynamic adjustment of fine scanning mode parameters during execution further improves the targeting and flexibility of observation, effectively reduces the waste of resources caused by invalid airspace scanning, and also reduces the risk of missing key meteorological data, significantly improving the intelligence and efficiency of cloud radar observation. Attached Figure Description

[0026] To more clearly illustrate the technical solutions in this embodiment or the prior art, the drawings used in the description of the embodiment or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0027] Figure 1 A flowchart illustrating a millimeter-wave cloud radar observation method based on multi-source data, provided in this application embodiment; Figure 2 This is a schematic diagram of the structure of a millimeter-wave cloud radar observation device based on multi-source data, provided in an embodiment of this application. Detailed Implementation

[0028] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. The terminology used in the following embodiments is for the purpose of describing specific embodiments only and is not intended to be a limitation of this application. As used in the specification of this application, the singular expressions "a," "an," "the," "the," "the," and "this" are intended to also include expressions such as "one or more," unless the context clearly indicates otherwise. It should also be understood that in the embodiments of this application, "one or more" refers to one, two, or more; "and / or" describes the relationship between related objects, indicating that three relationships can exist; for example, A and / or B can represent: A alone, A and B simultaneously, or B alone, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship.

[0029] like Figure 1 As shown, Figure 1 A flowchart illustrating a millimeter-wave cloud radar observation method based on multi-source data, provided in this application embodiment. The method includes: S101: Real-time acquisition and preprocessing of at least one of weather radar mosaic data, meteorological satellite data, ground visibility observation data, and co-located or adjacent aerosol lidar data to form a fused dataset.

[0030] Weather radar mosaic data refers to a dataset of global echo distribution formed by stitching together large-scale meteorological echo data collected by a new generation of S / C band weather radar networks. It can reflect the spatial distribution and movement trend of weather systems.

[0031] Meteorological satellite data refers to large-scale observational data acquired by meteorological satellites (such as the Himawari satellite and the Fengyun-4 satellite), including information such as cloud distribution, fog area range, and atmospheric temperature and humidity profiles.

[0032] Ground visibility observation data refers to the near-surface horizontal visibility data collected in real time by ground visibility observation equipment, which is used to determine low visibility weather phenomena such as fog and light fog.

[0033] Co-located or adjacent aerosol lidar data refers to data collected by aerosol lidar located at the same or adjacent sites as cloud lidar, which can accurately identify the presence of clouds, the number of layers, and information such as cloud base / cloud top height.

[0034] A fused dataset refers to a unified format dataset formed by integrating core information from multiple data sources after preprocessing, which can comprehensively reflect the weather and environmental characteristics of the detection area.

[0035] First, a standardized data interface is used to connect to a new generation of weather radar networks to receive S / C-band weather radar mosaic data in real time. The data update frequency is consistent with the radar scanning cycle, such as once every 6 minutes. Real-time observation data from the Himawari and Fengyun-4 satellites is acquired through a satellite data receiving terminal, focusing on extracting spatial feature information such as cloud outlines and fog boundaries. Ground visibility observation data is collected through the communication interface of ground meteorological observation stations, with a sampling frequency of once per minute. Observation data from co-located or nearby aerosol lidars are acquired through a local area network or wireless communication link, focusing on extracting parameters such as cloud identification results, cloud base height, and cloud top height. During the acquisition process, the timestamps and spatial coordinate information of each data source are recorded simultaneously to ensure data traceability.

[0036] Subsequently, the acquired multi-source data underwent preprocessing. The first step was spatiotemporal alignment. Using the cloud radar timestamp as a benchmark, linear interpolation was employed to synchronize data from different sampling frequencies, unifying all data to the same time point. Using the latitude and longitude of the cloud radar station as the origin, the spatial coordinates of satellite data and weather radar mosaic data were converted to local planar coordinates, achieving spatial alignment. The second step involved noise filtering. Median filtering was used to remove isolated noise points from the weather radar mosaic data, a moving average method was used to smooth random fluctuations in ground visibility data, and morphological filtering was used to eliminate image noise from the satellite data. The third step was format standardization. All data was uniformly converted to JSON format, and core feature fields from each data source were extracted, such as echo intensity from the weather radar mosaic data, fog area indicators from the satellite data, and cloud presence indicators from the lidar data. Finally, these were integrated to form a unified and complete fusion dataset.

[0037] Step S101, through real-time acquisition and standardized preprocessing of multi-source data, breaks through the information limitations of a single data source, integrating multi-dimensional information such as large-scale weather system trends, near-surface micro-meteorological conditions, and refined cloud characteristics. This provides a comprehensive and reliable data foundation for subsequent intelligent weather scene identification. The spatiotemporal alignment operation during preprocessing eliminates heterogeneity interference from different data sources, ensuring data consistency. Noise filtering improves data quality and reduces the impact of false information on subsequent judgments. The formation of the fused dataset avoids observation blind spots or errors that may exist with a single data source, significantly improving the accuracy and reliability of subsequent weather scene identification and laying a solid data foundation for the efficient operation of the entire adaptive observation scheme.

[0038] S102: Based on the fused dataset, determine the weather scene type of the current weather at the cloud radar station through a preset rule set.

[0039] Weather scene types include at least weather echo approaching, weather echo moving away, local weather process, fog and non-precipitating clouds.

[0040] The preset rule set refers to a set of pre-defined logical rules for judging weather scenarios based on the characteristics of multi-source data. It includes the judgment conditions, data thresholds and priority order corresponding to various weather scenarios, and is the core basis for scene recognition.

[0041] Weather scene type refers to the category of observation scene based on the characteristics and evolution of weather phenomena. Weather scene types include at least weather echo approaching (the state in which weather echoes move closer to the cloud radar station), weather echo moving away (the state in which weather echoes move away from the cloud radar station), local weather process (the state in which weather echoes exist in a small area around the cloud radar station), fog (the phenomenon of water vapor condensation with low visibility near the ground) and non-precipitating clouds (cloud systems that do not produce precipitation).

[0042] Weather echoes refer to the signals reflected back after electromagnetic waves emitted by radar encounter meteorological targets such as clouds and precipitation particles. Their intensity and distribution can reflect the location, range, and intensity characteristics of the meteorological targets.

[0043] First, a pre-defined rule set is constructed and stored in the cloud radar control system. The logic of the rule set is based on typical data characteristics of various weather scenarios. For weather echoes moving closer or farther away, the rule is set to compare consecutive frames of weather radar mosaic data to determine the change in the relative distance between the echo and the cloud radar station. When the echo enters or is within the maximum detection range of the low pulse repetition frequency (PRF) mode and gradually approaches, it is determined to be a weather echo moving closer; when the echo gradually moves away but does not leave the maximum detection range of the low PRF mode, it is determined to be a weather echo moving farther away. For local weather processes, the rule is set to determine whether the area around the cloud radar station (N0km, usually 0.5km) is fully covered by weather echoes using weather radar mosaic data; if so, it is determined to be that scenario. For fog, the rule is set to combine fog area markers from meteorological satellite data with ground visibility observation data. When low visibility (meeting the visibility standard for fog) occurs within the area around the cloud radar station (N1km, usually 5km) and the satellite data marks a fog area, it is determined to be that scenario. For non-precipitating clouds, the rule is set to identify the cloud's presence using co-located or nearby aerosol lidar data when none of the above conditions are met, and if there are no precipitation-related echo characteristics, then this scenario is identified. The rule set also sets a priority, prioritizing weather echo-related scenarios (approaching / distant, local weather processes) over fog and non-precipitating cloud scenarios to ensure that key weather processes are identified first.

[0044] Subsequently, the weather scene recognition process is executed. The cloud radar control system calls the fusion dataset generated by S101 and matches and judges it one by one according to the priority order of the preset rule set. First, the weather radar mosaic data in the fusion dataset is extracted, and the position, range and movement trend of the echo are analyzed to determine whether it meets the rule conditions of weather echo moving closer, weather echo moving farther away or local weather process. If none of them are met, satellite data and ground visibility data are extracted and matched with the judgment rules of fog scene; if it still does not meet the requirements, aerosol lidar data is extracted to determine whether it meets the rules of non-precipitation cloud scene. The entire recognition process is executed automatically and is repeated once at preset time intervals to ensure real-time tracking of weather changes and timely updates of scene type.

[0045] Step S102 constructs a standardized and executable scene recognition logic through a preset rule set, avoiding the limitations of subjective judgment or single-data judgment, and ensuring the consistency and accuracy of scene recognition. The priority setting and multi-source data cross-validation mechanism in the rule set not only ensure the priority recognition of key weather processes such as severe convection, but also accurately distinguish weak echo weather such as fog and non-precipitating clouds, solving the problem of the lack of specificity in traditional cloud radar observation. The scene recognition results provide the core basis for the accurate invocation of subsequent combined scanning strategies, enabling the scanning mode to dynamically adapt to weather characteristics, laying the decision-making foundation for the intelligent operation of the entire adaptive observation scheme. At the same time, the automated nature of the recognition process reduces manual intervention and improves the real-time performance of observation response.

[0046] S103: Based on the weather scenario type, retrieve the corresponding combined scanning strategy from the preset strategy mapping table and execute it.

[0047] The pre-configured strategy mapping table refers to the associated data table pre-stored in the cloud radar control system, which clearly records the mapping relationship between each weather scene type and the corresponding combined scanning strategy. Strategies can be directly invoked through the scene type index, ensuring efficient invocation. The pre-configured logic refers to the execution order and connection method between the basic scanning mode and the fine scanning mode in the combined scanning strategy.

[0048] The combined scanning strategy refers to a scanning scheme optimized for specific weather scenarios, composed of a basic scanning mode and a fine scanning mode combined according to preset logic, taking into account both overall coverage of weather targets and detailed local detection. The basic scanning mode refers to the scanning modes used to quickly acquire the overall characteristics of weather targets, including Vertical Top-Inspection (THI), Range-Height Inspection (RHI), and Volumetric Calculation (VCP), characterized by wide coverage and short processing time. The fine scanning mode refers to the scanning modes used to focus on key areas of weather targets, including Planar Horizontal Inspection (PPI), which can accurately capture the fine structure and microphysical parameters of the target.

[0049] First, a strategy mapping table is constructed and pre-configured. Based on the observation requirements of different weather scenarios, a one-to-one correspondence between scenario types and combined scanning strategies is established in the cloud radar control system. For example: weather echo approaching / receding scenarios correspond to RHI scanning and PPI scanning; local weather process scenarios correspond to THI scanning and VCP scanning; fog scenarios correspond to RHI scanning and specific low-elevation-angle PPI scanning; and non-precipitating cloud scenarios correspond to THI scanning and PPI scanning. Simultaneously, each combined strategy defines preset logic, uniformly adopting an execution order of first conducting a basic scanning mode for global survey, and then focusing on key areas using a refined scanning mode, ensuring that the scanning has both global coverage and local focus.

[0050] Subsequently, the combined scanning strategy invocation and execution process is implemented. The cloud radar control system receives the weather scene type result output by S102, and performs an index lookup in the preset strategy mapping table based on this result to quickly match the corresponding combined scanning strategy. After the lookup is completed, the system automatically parses the execution logic of the combined strategy and generates standardized scanning control commands, which include the start sequence and operating parameters of the basic scanning mode and the fine scanning mode. Finally, the control commands are sent to the cloud radar's actuators, driving the antenna to execute the corresponding scanning actions according to the commands. The entire invocation and execution process is completed automatically without manual intervention, ensuring real-time scanning response.

[0051] Step S103 enables rapid invocation of the combined scanning strategy through a pre-set strategy mapping table, avoiding response delays caused by complex calculations and ensuring that the cloud radar can adapt to changes in weather scenarios in a timely manner. The pre-set logic of the basic and fine scanning of the combined scanning strategy ensures global coverage of weather targets through the basic scanning mode, avoiding blind spots, while focusing on key areas through the fine scanning mode, improving the targeting and precision of observations. This breaks the rigid limitations of the fixed scanning mode of traditional cloud radar, enabling precise matching of scanning strategies with weather scenario characteristics, effectively reducing resource waste such as transmitter lifespan loss and power consumption caused by ineffective airspace scanning, and laying the foundation for subsequent dynamic optimization of scanning parameters, significantly improving the efficiency and adaptability of cloud radar observations.

[0052] S104: When executing the combined scanning strategy, the parameters of the fine scanning mode are dynamically adjusted based on the position and intensity information of the radar echo in real time or changes in the detection mode.

[0053] The location / intensity information of the radar real-time echo refers to the meteorological target reflection signal data received in real time during the scanning process of the cloud radar. The location information reflects the latitude, longitude and altitude coordinates of the target in space, and the intensity information is characterized by echo power (dBZ), which can reflect the density and energy characteristics of the target.

[0054] The change in detection mode refers to the switching of the pulse repetition frequency (PRF) mode of the cloud radar between low / medium / high. The switching is based on the relative distance between the weather echo and the radar station, aiming to balance the detection range and the accuracy of velocity measurement.

[0055] Dynamic adjustment refers to the adaptive operation of continuously optimizing parameters based on real-time feedback data during the execution of the combined scanning strategy. This differs from static scanning with preset fixed parameters, ensuring that the parameters match the weather target characteristics in real time.

[0056] Fine scanning mode parameters refer to the core operating parameters of planar horizontal scanning, including azimuth scanning range, target height layer, scanning interval, and scanning duration.

[0057] First, the triggering conditions and associated logic for parameter adjustment are clearly defined. When executing a combined scanning strategy, the cloud radar control system simultaneously collects real-time data on the echo position and intensity, while also monitoring the switching status of the Presence Recognition Function (PRF). Trigger rules are set so that the parameter adjustment process is automatically initiated when the echo position deviates from the coverage area of ​​the current fine scan, when the echo intensity exhibits a significant peak (e.g., exceeding a preset threshold), or when the PRF mode switches. The direction and magnitude of parameter adjustment are determined based on the principles of focusing on meteorologically valuable areas and improving sampling efficiency. For example, areas with peak echo intensity require a narrower scanning range and more frequent sampling; when the PRF switches to a high mode, parameter settings must be adapted to close-range detection.

[0058] Subsequently, specific parameter adjustments are performed according to the scenario type. For weather echo approaching / receding scenarios, when RHI scanning detects high-altitude layers with strong echoes (e.g., N0=2), the azimuth range of the PPI is reduced according to the distribution boundary of the echo in the weather radar mosaic data, such as reducing it from 360° to the 60° range covered by the echo. Furthermore, as the echo approaches and switches to medium / high PRF mode, the scanning step size of the local PPI is simultaneously reduced (e.g., adjusted from 1° / step to 0.5° / step) to improve the fine sampling density. For fog scenarios, based on the vertical distribution of the fog area obtained from RHI scanning, the scanning azimuth range of a specific low-elevation PPI is limited to within the boundary of the fog area identified by satellite and ground data (e.g., within 5km). If the fog concentration is uneven (echo intensity difference exceeds 10dBZ), the number of scanning repetitions is increased in high-intensity areas. For non-precipitating cloud scenarios, the PPI scanning parameters are dynamically adjusted according to the THI scanning results. If three cloud layers are identified, independent scanning heights are set for the bottom, top, and strong echo layers of each cloud layer. The scanning interval for the strong echo layers in the cloud is smaller than that for the bottom and top layers of the cloud to ensure data quality in key areas.

[0059] Step S104, through dynamic parameter adjustment based on real-time feedback data, compensates for the static limitations of the preset parameters of the combined scanning strategy, enabling the fine scanning mode to accurately adapt to the dynamic changes and spatial distribution characteristics of weather targets. Parameter adjustment focuses on areas with the highest meteorological value, avoiding redundant scanning of ineffective airspace and further reducing resource waste such as radar transmitter wear and power consumption. Simultaneously, parameter optimization for key scenarios such as areas with peak echo intensity and areas with uneven fog concentration improves the sampling density and accuracy of critical meteorological data, effectively reducing the risk of missing key data during rapidly evolving severe convective weather. This step, together with the preceding multi-source data fusion, scene recognition, and combined strategy invocation, forms a closed loop, upgrading cloud radar observation from scene-adaptive to real-time target feature-adaptive, significantly improving the intelligence, flexibility, and efficiency of observation, and providing higher-quality observation data support for applications such as weather forecasting and aviation support.

[0060] Below, embodiments of this application will introduce corresponding combined scanning strategies for different weather scenarios.

[0061] For scenarios where weather echoes are approaching or receding, it is necessary to balance tracking the movement trend of the weather system with refined detection of key areas. Therefore, when the weather scenario type is weather echoes approaching or receding, the combined scanning strategy is distance and height scanning and horizontal scanning.

[0062] In one implementation, the corresponding combined scanning strategy is retrieved from a pre-defined strategy mapping table and executed, including: The echo region is scanned at preset azimuth intervals to obtain the vertical profile structure; Based on the scanning results of the distance and height scan, select N0 height layers with strong echoes, where the value of N0 ranges from 1 to 3; A horizontal scan with a limited azimuth range is performed at the altitude level; the azimuth range is set based on the echo region determined by the weather radar mosaic data. As the distance between the echo and the cloud radar station changes, the radar's pulse repetition frequency mode is adjusted synchronously.

[0063] First, determine the core parameters of RHI. Perform RHI scanning on the echo area at preset azimuth intervals. The azimuth interval can be flexibly set according to the echo coverage area, while the scanning elevation angle is fixed at 0-90° to ensure complete coverage of the vertical profile of the echo. During the scanning process, record the echo intensity and height distribution data at different azimuth angles in real time to form an echo vertical structure dataset, providing a basis for subsequent focusing scans.

[0064] Subsequently, target altitude layers are selected and PPI (Programmable Point Injection) is performed. Altitude layers with echo intensity exceeding a preset threshold are extracted from the RHI (Radar Infrared Detection) results, and 1-3 altitude layers with the strongest echoes are selected as key observation targets according to the range of N0. At the same time, the azimuth boundary of the echo area is determined based on weather radar mosaic data, and the azimuth range of the PPI scan is limited to this boundary to avoid redundant detection in invalid airspace.

[0065] Finally, the PRF mode is adjusted synchronously. The straight-line distance between the echo and the cloud radar station is calculated in real time. When the echo is within the maximum detection range of the PRF mode, the low PRF mode is used to ensure the detection range; when the echo enters the medium range, the medium PRF mode is switched to balance the detection range and velocity measurement accuracy; when the echo approaches the near range, the high PRF mode is switched to improve the accuracy of echo velocity measurement, ensuring that high-quality observation data can be obtained at different distances.

[0066] In local weather scenarios, the weather system covers a small area around the radar station, requiring the simultaneous acquisition of high temporal resolution data on vertical variation and spatial distribution characteristics. Therefore, when the weather scenario is a local weather process, the combined scanning strategy is vertical top-down scanning and low-elevation-angle volumetric scanning.

[0067] In one implementation, the step of calling and executing the corresponding combined scanning strategy from a preset strategy mapping table includes: Perform continuous vertical top-view scanning observations for T0 minutes; the value of T0 ranges from 3 to 5 minutes. Based on the echo top height obtained from the vertical top-scan, a set of low elevation angles not exceeding 20° are set, and the low elevation angles include at least three of the following: 0.5°, 2.5°, 5°, 7.5°, 10° and 15°. Perform a stereo volume scan based on the low elevation angle.

[0068] First, perform continuous THI observation. Start the THI scanning mode, fix the radar antenna at a 90° elevation angle, and continuously observe for T0 minutes (T0 is 3-5 minutes, preferably 5 minutes). Record the echo intensity change curve and echo top height data in real time to accurately capture the rapid evolution characteristics of the weather process (such as echo top height rise, intensity abrupt change, etc.).

[0069] Subsequently, low elevation angle parameters were set. Based on the echo top height obtained from the THI scan, low elevation angle combinations not exceeding 20° were selected, with at least three values ​​chosen from 0.5°, 2.5°, 5°, 7.5°, 10°, and 15° to ensure coverage of the main vertical layers of the echo distribution while avoiding observation redundancy caused by high elevation angle scans.

[0070] Finally, VCP is executed, and 360° azimuth scanning is performed sequentially at each elevation angle according to the set low elevation angle combination. By stitching together multi-layer horizontal scan data, a three-dimensional data volume of the weather process at this station is constructed, which comprehensively reflects the spatial distribution and intensity characteristics of the weather system and provides complete three-dimensional observation data for meteorological analysis.

[0071] Fog scenes are characterized by weak echoes, so it is important to focus on capturing the horizontal distribution and vertical structure of the fog area near the ground. Therefore, when the weather scene type is fog, the combined scanning strategy is distance and height scanning and horizontal plane scanning.

[0072] In one implementation, the step of calling and executing the corresponding combined scanning strategy from a preset strategy mapping table includes: Distance and altitude scanning are performed at azimuth intervals of K1 degrees; the value of K1 ranges from 20 to 30 degrees, and the elevation angle range of the distance and altitude scanning is 0 to 90 degrees. N1 fixed low elevation angles are selected to perform a horizontal plane scan; the value of N1 ranges from 2 to 3, and the low elevation angles include 0.5°, 1° and 2°; the azimuth range of the horizontal plane scan is set based on the fog zone boundary determined by satellite data and ground visibility data.

[0073] First, perform RHI (Rapid Hierarchical Indication) scanning. Scan the detection area at azimuth intervals of K1 degrees (K1 ranges from 20-30 degrees, preferably 30 degrees). The scanning elevation range is 0-90°, ensuring global coverage of the vertical structure of the fog area while avoiding resource waste caused by overly dense scanning. During the scanning process, key parameters such as the vertical thickness and intensity distribution of the fog area are recorded to provide a basis for subsequent PPI (Potential Per Pixel) scanning.

[0074] Subsequently, the PPI parameters were determined, and N1 fixed low elevation angles were selected from 0.5°, 1°, and 2°. This combination of low elevation angles can accurately capture the horizontal distribution characteristics of near-ground fog areas. At the same time, based on the fog area boundaries marked by meteorological satellite data and the low visibility range determined by ground visibility data, the azimuth angle range for PPI scanning was defined to ensure targeted scanning.

[0075] Finally, a PPI scan is performed according to the set parameters. At the selected low elevation angle, the scan is performed at a constant speed along the defined azimuth range, and the echo intensity data of the fog area is collected in real time to form a horizontal distribution map of the fog area, providing accurate observational support for fog monitoring and early warning.

[0076] When the cloud radar station is located within a fog area, it is necessary to simultaneously acquire the vertical fine structure, horizontal distribution, and real-time changes near the ground of the fog area. Therefore, if the cloud radar station is located within a fog area, the combined scanning strategy will be adjusted to vertical top-down scanning, range and height scanning, and horizontal plane scanning.

[0077] First, THI is activated to fix the radar antenna at a 90° elevation angle and continuously perform THI scans to capture dynamic characteristics such as vertical intensity changes and droplet concentration fluctuations in the near-ground fog area in real time. This provides high temporal resolution data for real-time fog monitoring and compensates for the rapid vertical changes that are difficult to capture by RHI and PPI alone.

[0078] Subsequently, RHI was performed according to the RHI parameters, maintaining the scanning parameters of K1 degree azimuth interval and 0-90° elevation angle range. RHI scanning was performed on the fog area to obtain data such as vertical thickness and intensity stratification of the fog area under different azimuth angles. This data complemented the THI scanning data to form a complete understanding of the vertical structure of the fog area.

[0079] Finally, PPI (Programmable Point Identification) is performed. A PPI scan is conducted within the azimuth range of the fog area determined by satellite data and ground visibility data to accurately capture the horizontal distribution boundaries and concentration differences of the fog area. The coordinated execution of these three processes comprehensively covers the vertical dynamics, vertical stratification, and horizontal distribution characteristics of the fog area, improving the completeness and accuracy of fog scene observation.

[0080] For non-precipitating cloud scenarios, it is necessary to accurately identify the layered structure of the cloud and the microphysical characteristics of each layer. Therefore, when the weather scenario type is non-precipitating cloud, the combined scanning strategy is vertical top scanning and horizontal planar scanning.

[0081] In one implementation, the corresponding combined scanning strategy is retrieved from a pre-defined strategy mapping table and executed, including: Perform continuous vertical top-view scanning observations for T2 minutes; the value of T2 ranges from 3 to 5 minutes. The number of cloud layers, the height of the cloud base, the height of the cloud top, and the strong echo layer in the cloud are determined based on the scanning results of the vertical top scan. Perform a 0-360° omnidirectional horizontal scan on the cloud base, cloud top, and strong echo layer in the cloud for each cloud layer; If multiple layers of clouds exist, each layer is scanned sequentially from lowest to highest cloud height.

[0082] First, the THI scan mode is activated, and observations are continuously performed for T2 minutes. Through high temporal resolution vertical observation data, the number of cloud layers, such as single-layer, double-layer, or multi-layer clouds, is accurately identified. The height of the cloud base, cloud top, and the height of the strong echo layer in the cloud are determined for each layer, providing clear targets for subsequent layered scanning.

[0083] Subsequently, a layered PPI scheme was developed. For each cloud layer, three key altitude layers were selected: the cloud base, cloud top, and the strong echo layer in the cloud. A 0-360° omnidirectional PPI scan was performed at each altitude layer to ensure complete coverage of the horizontal distribution range of the cloud layer. During the scanning process, parameters such as echo intensity and uniformity at each altitude layer were recorded to reflect the microphysical characteristics of the cloud layer.

[0084] Finally, perform layered scanning in sequence. If multiple cloud layers are identified, such as low-level, mid-level, and high-level clouds, complete the PPI scan of each layer in order of cloud height from low to high. This avoids interference between data from different cloud layers and ensures that the observation data of each cloud layer is independent and accurate, providing complete layered observation data for the study and monitoring of non-precipitating clouds.

[0085] When the current weather at the cloud radar station does not fall under scenarios such as weather echoes moving closer / far away, local weather processes, fog, or non-precipitating clouds, the daily monitoring mode needs to be executed to balance global coverage and basic observation requirements. Therefore, a combination strategy of vertical top scanning, distance and height scanning, and horizontal scanning can be adopted.

[0086] In one implementation, the step of calling and executing the corresponding combined scanning strategy from a preset strategy mapping table includes: Perform continuous vertical top-view scanning observations for T3 minutes; the value of T3 ranges from 8 to 12 minutes. Distance and height scanning is performed at intervals of K2 degrees in the azimuth angle of 0-180°; the value of K2 is in the range of 25-35 degrees, and the elevation angle range of the distance and height scanning is 0-180 degrees; finally, a 360° all-round horizontal planar scan with a low elevation angle of 0.5° or 1° is performed.

[0087] First, perform basic THI observations, continuously observing for T3 minutes (T3 value is 8-12 minutes, preferably 10 minutes), to monitor basic information such as the vertical changes of upper-air cloud systems and the presence or absence of echoes in real time, providing a reference for judging daily weather conditions.

[0088] Subsequently, intervald RHI (Rapid Induction Hierarchy) is performed. Within the azimuth range of 0-180°, RHI scans are conducted at intervals of K2 degrees (K2 values ​​range from 25-35 degrees, preferably 30 degrees). The scanning elevation range is 0-180°, ensuring global vertical profile coverage of the detection area while avoiding resource consumption caused by overly dense scanning. During the scanning process, the presence of echo signals from potential weather systems is recorded to provide clues for subsequent early warning.

[0089] Finally, a low-elevation-angle omnidirectional PPI scan is performed. Selecting a low elevation angle of 0.5° or 1°, a 360° omnidirectional PPI scan is executed to comprehensively capture the horizontal echo distribution from near the ground to low altitudes, screening for potential weak echo weather signals. These three processes are executed in the order of "THI→RHI→PPI," forming a complete observation process for daily monitoring. This ensures both global coverage and basic data collection, providing support for the early identification of weather systems.

[0090] The above describes some specific implementations of the millimeter-wave cloud radar observation method based on multi-source data provided in this application. Based on this, this application also provides a corresponding device. The device provided in this application will be described below from the perspective of functional modularity.

[0091] See Figure 2 The diagram shows the structure of a millimeter-wave cloud radar observation device based on multi-source data. The device 200 includes an acquisition module 201, a judgment module 202, a calling module 203, and an adjustment module 204.

[0092] The acquisition module 201 is used to acquire and preprocess at least one of weather radar mosaic data, meteorological satellite data, ground visibility observation data, and co-located or adjacent aerosol lidar data in real time to form a fused dataset. The judgment module 202 is used to determine the weather scene type of the current weather at the cloud radar station based on the fused dataset and a preset rule set; the weather scene type includes at least weather echo approaching, weather echo moving away, local weather process, fog and non-precipitating clouds; The calling module 203 is used to call and execute the corresponding combined scanning strategy from the preset strategy mapping table according to the weather scene type; the combined scanning strategy is composed of a basic scanning mode and a fine scanning mode combined according to a preset logic; the basic scanning mode includes vertical top scanning, distance and height scanning and three-dimensional volume scanning; the fine scanning mode includes local plane horizontal scanning and layered plane horizontal scanning. The adjustment module 204 is used to dynamically adjust the parameters of the fine scanning mode based on the position and intensity information of the radar echo or changes in the detection mode when executing the combined scanning strategy.

[0093] In one implementation, when the weather scene type is weather echo approaching or weather echo receding, the combined scanning strategy is distance-height scanning and horizontal scanning. Module 203 is invoked, specifically to perform distance and height scanning on the echo region at preset azimuth intervals to obtain the vertical profile structure. Based on the scanning results of the distance and height scan, select N0 height layers with strong echoes, where the value of N0 ranges from 1 to 3; A horizontal scan with a limited azimuth range is performed at the altitude level; the azimuth range is set based on the echo region determined by the weather radar mosaic data. As the distance between the echo and the cloud radar station changes, the radar's pulse repetition frequency mode is adjusted synchronously.

[0094] In one implementation, when the weather scene type is a local weather process, the combined scanning strategy is vertical top-down scanning and low-elevation stereo volume scanning. Module 203 is invoked, specifically for performing continuous vertical top-scan observations for T0 minutes; the value of T0 ranges from 3 to 5 minutes. Based on the echo top height obtained from the vertical top-scan, a set of low elevation angles not exceeding 20° are set, and the low elevation angles include at least three of the following: 0.5°, 2.5°, 5°, 7.5°, 10° and 15°. Perform a stereo volume scan based on the low elevation angle.

[0095] In one implementation, when the weather scene type is fog, the combined scanning strategy is distance-height scanning and horizontal scanning. Module 203 is invoked, specifically for performing distance and height scanning at azimuth intervals of K1 degrees; the value of K1 ranges from 20 to 30 degrees, and the elevation angle range of the distance and height scanning is 0 to 90 degrees. N1 fixed low elevation angles are selected to perform a horizontal plane scan; the value of N1 ranges from 2 to 3, and the low elevation angles include 0.5°, 1° and 2°; the azimuth range of the horizontal plane scan is set based on the fog zone boundary determined by satellite data and ground visibility data.

[0096] In one implementation, if the cloud radar station is located within a fog area, the combined scanning strategy is adjusted to vertical top-down scanning, range-height scanning, and horizontal planar scanning.

[0097] In one implementation, when the weather scene type is non-precipitating clouds, the combined scanning strategy is vertical top-down scanning and horizontal planar scanning; Module 203 is invoked, specifically for performing continuous vertical top-scan observations for T2 minutes; the value of T2 ranges from 3 to 5 minutes. The number of cloud layers, the height of the cloud base, the height of the cloud top, and the strong echo layer in the cloud are determined based on the scanning results of the vertical top scan. Perform a 0-360° omnidirectional horizontal scan on the cloud base, cloud top, and strong echo layer in the cloud for each cloud layer; If multiple layers of clouds exist, each layer is scanned sequentially from lowest to highest cloud height.

[0098] In one implementation, when the current weather at the cloud radar station is a weather type other than the weather scene type, a daily monitoring mode is adopted, and the combined scanning strategy is the vertical top-down scanning, distance and height scanning, and horizontal plane scanning. Module 203 is invoked, specifically for performing continuous vertical top-scan observations for T3 minutes; the value of T3 ranges from 8 to 12 minutes. Distance and height scanning is performed at intervals of K2 degrees in the azimuth angle of 0-180°; the value of K2 is in the range of 25-35 degrees, and the elevation angle range of the distance and height scanning is 0-180 degrees; finally, a 360° all-round horizontal planar scan with a low elevation angle of 0.5° or 1° is performed.

[0099] This application also provides corresponding devices and computer storage media for implementing the solutions provided in this application.

[0100] The device includes a memory and a processor. The memory is used to store instructions or code, and the processor is used to execute the instructions or code so that the device performs the millimeter-wave cloud radar observation method based on multi-source data as described in any embodiment of this application.

[0101] The computer storage medium stores code. When the code is executed, the device running the code implements the millimeter-wave cloud radar observation method based on multi-source data as described in any embodiment of this application.

[0102] In the embodiments of this application, the terms "first" and "second" (if they exist) are used only as name identifiers and do not represent the order of first and second.

[0103] As can be seen from the above description of the embodiments, those skilled in the art can clearly understand that all or part of the steps in the methods of the above embodiments can be implemented by means of software plus a general-purpose hardware platform. Based on this understanding, the technical solution of this application can be embodied in the form of a software product. This computer software product can be stored in a storage medium, such as a read-only memory (ROM) / RAM, magnetic disk, optical disk, etc., including several instructions to cause a computer device (which may be a personal computer, a server, or a network communication device such as a router) to execute the methods described in various embodiments or some parts of the embodiments of this application.

[0104] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on its differences from other embodiments. In particular, the apparatus embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without creative effort.

[0105] The above description is merely an exemplary implementation of this application and is not intended to limit the scope of protection of this application.

Claims

1. A millimeter-wave cloud radar observation method based on multi-source data, characterized in that, Includes the following steps: Real-time acquisition and preprocessing of at least one of weather radar mosaic data, meteorological satellite data, ground visibility observation data, and co-located or adjacent aerosol lidar data to form a fused dataset; Based on the fused dataset, the weather scene type of the current weather at the cloud radar station is determined by a preset set of rules; The weather scene types include at least weather echo approaching, weather echo moving away, local weather process, fog and non-precipitating clouds; According to the weather scene type, the corresponding combined scanning strategy is called from the preset strategy mapping table and executed; the combined scanning strategy is composed of a basic scanning mode and a fine scanning mode combined according to preset logic. The basic scanning mode includes vertical top scanning, distance and height scanning and three-dimensional volume scanning, and the fine scanning mode includes planar horizontal scanning. When executing the combined scanning strategy, the parameters of the fine scanning mode are dynamically adjusted based on the position and intensity information of the radar echo in real time or changes in the detection mode. When the weather scene type is weather echo approaching or weather echo receding, the combined scanning strategy is distance and height scanning and horizontal plane scanning; The step of calling and executing the corresponding combined scanning strategy from the preset strategy mapping table includes: The echo region is scanned at preset azimuth intervals to obtain the vertical profile structure; Based on the scanning results of the distance and height scan, select N0 height layers with strong echoes, where the value of N0 ranges from 1 to 3; A horizontal scan with a limited azimuth range is performed at the altitude level; the azimuth range is set based on the echo region determined by the weather radar mosaic data. As the distance between the echo and the cloud radar station changes, the radar's pulse repetition frequency mode is adjusted synchronously.

2. The method according to claim 1, characterized in that, When the weather scene type is a local weather process, the combined scanning strategy is vertical top-down scanning and low elevation angle stereo volume scanning; The step of calling and executing the corresponding combined scanning strategy from the preset strategy mapping table includes: Perform continuous vertical top-view scanning observations for T0 minutes; the value of T0 ranges from 3 to 5 minutes. Based on the echo top height obtained from the vertical top-scan, a set of low elevation angles not exceeding 20° are set, and the low elevation angles include at least three of the following: 0.5°, 2.5°, 5°, 7.5°, 10° and 15°. Perform a stereo volume scan based on the low elevation angle.

3. The method according to claim 1, characterized in that, When the weather scene type is fog, the combined scanning strategy is distance and height scanning and horizontal plane scanning; The step of calling and executing the corresponding combined scanning strategy from the preset strategy mapping table includes: Distance and altitude scanning are performed at azimuth intervals of K1 degrees; the value of K1 ranges from 20 to 30 degrees, and the elevation angle range of the distance and altitude scanning is 0 to 90 degrees. N1 fixed low elevation angles are selected to perform a horizontal plane scan; the value of N1 ranges from 2 to 3, and the low elevation angles include 0.5°, 1° and 2°; the azimuth range of the horizontal plane scan is set based on the fog zone boundary determined by satellite data and ground visibility data.

4. The method according to claim 3, characterized in that, If the cloud radar station is located within the fog area, the combined scanning strategy will be adjusted to vertical top scanning, range and height scanning, and horizontal plane scanning.

5. The method according to claim 1, characterized in that, When the weather scene type is non-precipitating clouds, the combined scanning strategy is vertical top-down scanning and horizontal planar scanning; The step of calling and executing the corresponding combined scanning strategy from the preset strategy mapping table includes: Perform continuous vertical top-view scanning observations for T2 minutes; the value of T2 ranges from 3 to 5 minutes. The number of cloud layers, the height of the cloud base, the height of the cloud top, and the strong echo layer in the cloud are determined based on the scanning results of the vertical top scan. Perform a 0-360° omnidirectional horizontal scan on the cloud base, cloud top, and strong echo layer in the cloud for each cloud layer; If multiple layers of clouds exist, each layer is scanned sequentially from lowest to highest cloud height.

6. The method according to claim 1, characterized in that, When the current weather at the cloud radar station is a weather type other than the weather scene type, a routine monitoring mode is adopted, and the combined scanning strategy is the vertical top scanning, distance and height scanning, and horizontal plane scanning. The step of calling and executing the corresponding combined scanning strategy from the preset strategy mapping table includes: Perform continuous vertical top-view scanning observations for T3 minutes; the value of T3 ranges from 8 to 12 minutes. Distance and height scanning is performed at intervals of K2 degrees in the azimuth angle of 0-180°; the value of K2 is in the range of 25-35 degrees, and the elevation angle range of the distance and height scanning is 0-180 degrees; finally, a 360° all-round horizontal planar scan with a low elevation angle of 0.5° or 1° is performed.

7. A millimeter-wave cloud radar observation device based on multi-source data, characterized in that, include: The acquisition module is used to acquire and preprocess at least one of weather radar mosaic data, meteorological satellite data, ground visibility observation data, and co-located or adjacent aerosol lidar data in real time to form a fused dataset. The judgment module is used to determine the weather scene type of the current weather at the cloud radar station based on the fused dataset and a preset rule set; The weather scene types include at least weather echo approaching, weather echo moving away, local weather process, fog and non-precipitating clouds; The calling module is used to call and execute the corresponding combined scanning strategy from the preset strategy mapping table according to the weather scene type. The combined scanning strategy is composed of a basic scanning mode and a fine scanning mode combined according to preset logic. The basic scanning mode includes vertical top scanning, distance and height scanning and three-dimensional volume scanning. The fine scanning mode includes local plane horizontal scanning and layered plane horizontal scanning. The adjustment module is used to dynamically adjust the parameters of the fine scanning mode based on the position and intensity information of the radar echo or changes in the detection mode when executing the combined scanning strategy. When the weather scene type is weather echo approaching or weather echo receding, the combined scanning strategy is distance and height scanning and horizontal plane scanning; The step of calling and executing the corresponding combined scanning strategy from the preset strategy mapping table includes: The echo region is scanned at preset azimuth intervals to obtain the vertical profile structure; Based on the scanning results of the distance and height scan, select N0 height layers with strong echoes, where the value of N0 ranges from 1 to 3; A horizontal scan with a limited azimuth range is performed at the altitude level; the azimuth range is set based on the echo region determined by the weather radar mosaic data. As the distance between the echo and the cloud radar station changes, the radar's pulse repetition frequency mode is adjusted synchronously.

8. A computer device, characterized in that, include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, it implements the millimeter-wave cloud radar observation method based on multi-source data as described in any one of claims 1-6.

9. A computer storage medium, characterized in that, The computer storage medium stores instructions that, when executed on a terminal device, cause the terminal device to perform the millimeter-wave cloud radar observation method based on multi-source data as described in any one of claims 1-6.

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