A regional joint artificial weather influence drought operation method

Abstract

This invention discloses a regional joint artificial weather modification (AIM) method for drought relief, relating to the field of drought relief technology. The method includes the following steps: Based on meteorological and agricultural drought monitoring results, areas experiencing moderate to severe drought are identified as areas requiring drought relief operations; the conditions for artificial rain enhancement in these areas are determined using the China Meteorological Administration's CMA-GFS model and real-time weather data; for areas meeting the conditions for artificial rain enhancement, seedable cloud systems are identified based on a 6-hour forecast using the CPEFS model, combined with satellite and radar data, and 0-2 hour radar extrapolation forecasts are performed; using the 2-hour radar extrapolation forecast results, effective operation stations are determined based on ballistic parameters, and the effective firing parameters for seedable cloud systems at each operation station are calculated and pushed to relevant stations and administrative regions, achieving multi-regional joint operations in a seedable cloud system area. This method has the advantages of improving the efficiency of large-scale drought disaster response and enabling dynamic control of multi-regional collaborative operations.

Description

Technical Field

[0001] This invention relates to the field of drought relief operation technology, and in particular to a regional joint artificial weather modification operation method for drought relief. Background Technology

[0002] Traditional methods of artificial rain enhancement for drought relief have significant limitations. Each administrative unit operates independently, using artificial weather modification sites as basic units. They rely on subjective judgment of cloud systems, adjusting launch parameters based on experience, and seeding catalysts into the clouds using tools such as artillery and rockets. Droughts often exhibit regional characteristics, spanning multiple administrative regions. Furthermore, weather systems and rain clouds are dynamically evolving, moving across different administrative regions over time. Without anticipating the evolution of rain clouds and coordinating upstream and downstream efforts, it is difficult to guarantee the effectiveness of the operation.

[0003] In existing technologies, weather modification involves launching catalysts from the ground using anti-aircraft guns and rockets. These catalysts explode in the clouds, and the silver iodide inside the projectiles burns and disperses as smoke agents into the clouds, causing precipitation or increasing precipitation. Currently, the launch time and parameters of these anti-aircraft guns and rockets are manually adjusted. Operators determine the location of the guns and rockets and the launch parameters based on the cloud position. However, as time goes on, some stations in the area cannot effectively fire at the target cloud system. Furthermore, the launch parameters of the shells and rockets at some stations need to be adjusted accordingly as the target cloud system changes, resulting in a low accuracy rate for weather modification drought relief operations. Summary of the Invention

[0004] To overcome the shortcomings of existing technologies, this invention provides a regional joint artificial weather modification drought relief operation method, which aims to improve the accuracy of artificial weather modification drought relief operations.

[0005] This invention provides a method for regional joint weather modification for drought relief, comprising the following steps:

[0006] Based on meteorological and agricultural drought monitoring results, areas with moderate to severe drought were identified as areas requiring drought relief operations.

[0007] The conditions for artificial rain enhancement operations in areas requiring drought relief were determined using the China Meteorological Administration's CMA-GFS model and real-time weather conditions.

[0008] For drought relief operations that meet the conditions for artificial rain enhancement, based on the 6-hour forecast of the CPEFS model, combined with satellite and radar data, the sowable cloud systems are identified, and 0-2 hour radar extrapolation forecasts are made.

[0009] Using 2-hour radar extrapolation forecast results, effective operational sites are determined based on ballistic parameters, and effective firing parameters for each operational site against sowable cloud systems are calculated and pushed to relevant sites and administrative regions, enabling multi-area joint operations in a sowable cloud system area.

[0010] By utilizing the aforementioned technical solution and fusing radar 3D extrapolation products with the ballistic parameters of weather modification artillery and rocket projectiles, the effective firing parameters for different tools at weather modification operation sites to fire at cloud systems capable of being seeded are obtained. These parameters are then pushed to the operation sites and their respective administrative regions, enabling multi-regional joint operations on a single seedable cloud system. Existing technologies employ a fixed administrative unit operation mode, while this solution establishes a cross-regional joint operation mechanism that automatically matches the optimal combination of operation sites based on the real-time location of the cloud system. This dynamic collaborative mechanism effectively resolves the contradiction between the cross-regional movement of cloud systems and the static distribution of operation sites. Through cloud trajectory prediction and geographic information overlay, it ensures that operation commands cover the effective cloud area; through multi-site collaborative operation, it avoids redundant operations or coverage blind spots; and through automated command generation, it shortens the time delay from cloud system identification to operation implementation, achieving dynamic matching between drought-stricken areas and operational resources, and improving the spatiotemporal accuracy of artificial rain enhancement operations.

[0011] Optionally, the radar extrapolation method includes the following steps:

[0012] Read radar CAPPI product data and satellite infrared cloud image data, and convert image color values ​​into dBZ intensity values ​​and brightness temperature values;

[0013] Calculate the spatial gradient of the dBZ intensity value and brightness temperature value in the spatial dimension and their rate of change over a set time interval, respectively.

[0014] A model of the optical flow field is constructed, and the iteration error threshold ε = 0.1 and the maximum number of iterations is set to 1000.

[0015] The optical flow field is iteratively calculated to obtain the cloud system movement vector;

[0016] Based on the optical flow field obtained from the final iteration, extrapolation forecasts for seedable cloud systems are made for 0-2 hours and 0-30 minutes.

[0017] By employing the aforementioned technical solution, visual color codes are transformed into quantitative physical quantities through the reading of CAPPI reflectivity data and infrared cloud image brightness temperature data, establishing a spatial distribution model of cloud intensity and height. In the calculation of gradients in the x and y directions, the central difference method is used to extract the spatial variation characteristics of the cloud system, and the cloud movement rate is calculated in conjunction with time-series data. The optical flow iteration process sets an initial motion vector and performs multiple error corrections based on brightness conservation constraints. For example, iteration terminates when the difference between the optical flow fields of two iterations is less than 0.1 or after 1000 calculations, ultimately obtaining a vector prediction field of cloud system motion. This accurately captures the motion patterns and evolution trends of the cloud system, providing reliable motion trajectory prediction data for cross-regional collaborative operations. By establishing a mathematical optical flow calculation model, the objectivity and accuracy of cloud extrapolation are significantly improved, effectively solving the problem of delayed operational instructions caused by human experience-based judgment, and providing technical support for the spatiotemporal matching of multi-site collaborative operations.

[0018] Optionally, the optical flow field model is iteratively calculated to obtain the cloud system movement vector, specifically including:

[0019] The optical flow field model is iteratively calculated. When the optical flow error between two iterations is less than the iteration error threshold or the number of iterations reaches the maximum number of iterations, the iteration process is terminated and the target optical flow field model is obtained.

[0020] Post-processing is performed on the optical flow components u in the x-direction and v in the y-direction of the target optical flow field model to obtain the cloud system movement vector.

[0021] Optionally, the iterative calculation formula for the optical flow field is as follows:

[0022] ;

[0023] ;

[0024] in,

[0025] u: Optical flow component in the x-direction;

[0026] V: Optical flow component in the y direction;

[0027] n: Number of iterations;

[0028] : Velocity field u in the current iteration n The spatial average value within the local neighborhood;

[0029] : Velocity field v in the current iteration n The spatial average value within the local neighborhood;

[0030] This is the regularization parameter.

[0031] Optionally, the optical flow component u in the x-direction and the optical flow component v in the y-direction of the optical flow field are post-processed, and the post-processing formula is as follows:

[0032] ;

[0033] ;

[0034] in,

[0035] : The x-direction velocity component of the k-th field (such as the final optical flow field) at grid point (i, j);

[0036] , The x-direction velocity of the direct neighbors of the center point (i, j);

[0037] : The y-direction velocity component of the k-th field (such as the final optical flow field) at grid point (i, j);

[0038] , : The y-direction velocity of the direct neighbors of the center point (i, j);

[0039] k: Number of iterations.

[0040] The above technical solution solves the problem of cloud extrapolation error accumulation caused by optical flow field noise interference, and improves the reliability of short-term cloud movement trajectory prediction (0-2 hours). Post-processed optical flow data can more accurately reflect the true motion state of the cloud system, providing a reliable kinematic parameter basis for the precise delivery of multi-region joint operation instructions. Especially when dealing with complex cloud systems where stratiform and convective clouds are mixed, it can avoid misjudgment of the operation area due to local optical flow anomalies.

[0041] Optionally, using the 2-hour radar extrapolation forecast results, effective operational sites are determined based on ballistic parameters, and the effective firing parameters for each operational site against the seedable cloud system are calculated, specifically including:

[0042] Based on the 2-hour radar extrapolation forecast results, cloud base height and cloud top height information are obtained;

[0043] Valid operational sites are determined based on the location information and ballistic parameters of the operational sites.

[0044] The minimum operational elevation angle that allows the ballistic maximum to reach the cloud base height is determined by traversing the elevation angles of effective operational sites and cloud systems, and the firing azimuth angle is calculated using spherical trigonometric functions.

[0045] Optionally, obtaining cloud base and cloud top height information includes the following steps:

[0046] Read the radar 3D mosaic and radar echo top height data, and for each horizontal coordinate position, vertically scan the reflectivity value from low to high. The height at which the reflectivity first reaches or exceeds 18dBZ is determined as the cloud base height.

[0047] Continue scanning upwards, and determine the height at which the reflectance value falls back below the preset reflectance threshold as the cloud top height.

[0048] Optionally, the formula for calculating the firing azimuth angle is as follows:

[0049] ;

[0050] in,

[0051] F: firing azimuth;

[0052] The latitude of the firing point;

[0053] Latitude of the target point;

[0054] Target longitude minus the firing point longitude.

[0055] A second aspect of this application provides a regional joint weather modification drought relief operation system for implementing the aforementioned regional joint weather modification drought relief operation method, the system comprising:

[0056] The drought region delineation module, based on meteorological and agricultural drought monitoring results, identifies areas with moderate to severe drought as areas requiring drought relief operations.

[0057] The operational condition assessment module uses the China Meteorological Administration's CMA-GFS model and real-time weather conditions to determine the conditions for artificial rain enhancement operations in areas requiring drought relief.

[0058] The cloud identification module identifies sowable cloud systems for drought relief operations that meet the conditions for artificial rain enhancement, based on the 6-hour forecast of the CPEFS model and combined with satellite and radar data, and performs 0-2 hour radar extrapolation forecasts.

[0059] The coordinated operation module utilizes 2-hour radar extrapolation forecast results to determine effective operation sites based on ballistic parameters, calculates the effective firing parameters of each operation site for the seedable cloud system, and pushes them to relevant sites and administrative regions to achieve multi-area joint operation in a seedable cloud system area.

[0060] A third aspect of this application provides an electronic device, the device including at least one processor; and a memory communicatively connected to the processor; wherein the memory stores instructions executable by the processor, the instructions being executed by the processor to enable the processor to perform a regional joint artificial weather modification drought relief operation method as described above.

[0061] The beneficial effects of this invention are as follows: by establishing the operational demand area through comprehensive meteorological data analysis, by combining multi-source meteorological data to achieve dynamic tracking and parameter calculation of cloud systems, and by using GIS technology to achieve intelligent push of operational instructions, it solves the technical problems that traditional decentralized operation mode cannot cope with regional drought and that manual judgment is inefficient. It has the advantages of improving the efficiency of responding to large-scale drought disasters and realizing dynamic regulation of multi-regional collaborative operations. Attached Figure Description

[0062] Figure 1 This is a flowchart of a regional joint artificial weather modification drought relief operation method provided by an embodiment of the present invention;

[0063] Figure 2 This is a schematic diagram showing the area requiring artificial weather modification for drought relief operations according to an embodiment of the present invention;

[0064] Figure 3 This is an embodiment of the CPEFS cloud band forecast of the present invention;

[0065] Figure 4 This invention provides an embodiment of CPEFS (Cross-Planetary Accumulated Subcooled Water Forecasting).

[0066] Figure 5 This refers to the precipitation conditions in the work area before the operation of this invention.

[0067] Figure 6 This is a real-world example of radar composite reflectivity and operational site data superimposed in an embodiment of the present invention.

[0068] Figure 7 The superposition of radar combined reflectivity and operating site is extrapolated by the optical flow method in this embodiment of the invention;

[0069] Figure 8 These are the parameters for rocket drought relief and rain enhancement operations calculated by extrapolation using the radar optical flow method in an embodiment of the present invention.

[0070] Figure 9 This shows the precipitation situation in the work area after the operation of this invention. Detailed Implementation

[0071] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0072] Example 1: Figure 1 This is a flowchart of a regional joint artificial weather modification drought relief operation method provided by an embodiment of the present invention, such as... Figure 1 As shown, the method includes the following steps:

[0073] Based on the comprehensive monitoring results of meteorological drought and agricultural drought, areas with moderate to severe drought were identified as areas requiring artificial weather modification for drought relief operations.

[0074] Based on meteorological and agricultural drought monitoring results, areas experiencing moderate to severe drought were identified.

[0075] Determine the conditions for artificial rain enhancement operations using the China Meteorological Administration's CMA-GFS model and real-time weather conditions;

[0076] Based on the 6-hour forecast of the CPEFS model, satellite and radar data are combined to identify sowable cloud systems and perform 0-2 hour radar extrapolation forecasts.

[0077] By overlaying GIS data with 2-hour extrapolation of the sowable cloud system, administrative regions, and ground operation sites, effective operation sites are determined based on ballistic parameters, and operation preparation instructions are pushed out.

[0078] By combining the 0-30 minute radar three-dimensional extrapolation results with ballistic parameters, the effective firing parameters of each operational site for the sowable cloud system are calculated and pushed to relevant sites and administrative regions, realizing multi-area joint operations for a sowable cloud system.

[0079] The regional joint artificial weather modification drought relief operation method involved in this invention will be specifically described below with reference to specific embodiments:

[0080] Example

[0081] This example uses an artificial rain enhancement and drought relief operation in Hunan Province on April 18, 2025.

[0082] A method for regional joint weather modification for drought relief includes the following steps:

[0083] Based on the daily meteorological drought monitoring and agricultural drought comprehensive analysis by the China Meteorological Administration, areas experiencing moderate to severe drought are identified as areas requiring artificial weather modification for drought relief operations. Figure 1As shown; based on the China Meteorological Administration's CMA-GFS model and actual weather conditions, weather systems that meet the above conditions, such as 24-hour ground precipitation below 20 mm and total atmospheric precipitation below 50 mm, are considered suitable for artificial rain enhancement operations.

[0084] Using 6-hour forecast data from the CPEFS model, cloud areas with supercooled water content greater than 0.01 mm were selected as potential targets for operations. Real-time satellite and radar data were combined to determine sowable cloud systems. The optical flow method was used to extrapolate the movement trajectory of the identified sowable cloud systems from 0 to 2 hours, providing a time window for core operation decisions.

[0085] The radar extrapolation prediction method includes the following steps: reading radar product CAPPI data and infrared cloud image data, converting the image color scale values ​​into dBZ intensity values ​​and brightness temperature values ​​respectively; calculating the spatial gradient of the dBZ intensity values ​​and brightness temperature values ​​in the spatial dimension and their rate of change over a set time interval respectively; constructing an optical flow field model, setting the error threshold ε=0.1 for the optical flow iteration calculation, the maximum number of iterations n=1000, and providing an initial value for the optical flow field; calculating the local average value of the optical flow field in the (k-1)th iteration, and then solving for the optical flow value (u) in the kth iteration. k v k The process involves calculating the optical flow error of the two iterations. If the error is less than a given error threshold ε or the number of iterations reaches n, the iteration is terminated; otherwise, K+1 iterations are performed.

[0086] Assuming the work point moves from (t+δt) to (x+δx, y+δy), and the grayscale value remains constant within a certain time interval δt, the formulas for calculating the spatial gradient and the rate of change over time are as follows:

[0087] (1)

[0088] in,

[0089] The grayscale value of the image at time t;

[0090] Ix: The gradient of the image in the x-direction;

[0091] Iy: The gradient of the image in the y-direction;

[0092] It: The rate of change of the image over a set time interval;

[0093] δt: Change over time;

[0094] δx: The amount of movement in the x-direction within a time interval δt;

[0095] δy: The amount of movement in the y direction within a time interval δt.

[0096] The optical flow field model is iteratively calculated to obtain the cloud system movement vector. Specifically, the optical flow field model is iteratively calculated, and the iteration process is terminated when the optical flow error between two iterations is less than the iteration error threshold or the number of iterations reaches the maximum number of iterations, thus obtaining the target optical flow field model. The optical flow component u in the x-direction and the optical flow component v in the y-direction of the target optical flow field model are post-processed to obtain the cloud system movement vector.

[0097] The iterative calculation formula for the optical flow field model is as follows:

[0098] (2)

[0099] (3)

[0100] Where u: optical flow component in the x direction;

[0101] v: Optical flow component in the y direction;

[0102] n: Number of iterations;

[0103] : Velocity field u in the current iteration n The spatial average value within the local neighborhood;

[0104] : Velocity field v in the current iteration n The spatial average value within the local neighborhood;

[0105] This is the regularization parameter.

[0106] Next, the optical flow components u in the x-direction and v in the y-direction of the optical flow field are post-processed, and the resulting optical flow field is spatially smoothed using the following formula:

[0107] (4)

[0108] (5)

[0109] in, It is the x-direction velocity component of the k-th field (such as the final optical flow field) at grid point (i, j); , It is the x-direction velocity of the direct neighboring points of the center point (i, j); It is the y-direction velocity component of the k-th field (such as the final optical flow field) at grid point (i, j); , y is the y-direction velocity of the direct neighbors of the center point (i, j); k is the number of iterations.

[0110] Using 2-hour radar extrapolation forecast results, effective operational sites are determined based on ballistic parameters. Effective site information includes: site name, province / city / county, site number, site latitude / longitude, and altitude. The effective firing parameters for each operational site against seedable cloud systems are calculated, specifically including:

[0111] Based on the 2-hour radar extrapolation forecast results, cloud base height and cloud top height information are obtained; radar 3D mosaic grid data are read using a Python database; for each horizontal position, reflectivity values ​​are scanned from low to high, and the height at which the reflectivity value first exceeds a certain threshold is taken as the cloud base height; the scan continues upward, and the height at which the reflectivity value falls below the threshold again is taken as the cloud top height; the cloud base height, cloud top height, and corresponding latitude and longitude location information are saved as structured data.

[0112] Based on the location information and ballistic parameters of the operational sites, valid operational sites are determined; using Geographic Information System (GIS) technology, spatial overlay analysis is performed on the forecast coverage area of ​​sowable cloud systems two hours later, the administrative boundary layers of provinces, cities, and counties, and the layers of ground operational sites (including rockets and anti-aircraft artillery) across the province. Figure 5 As shown. By combining the ballistic parameters (such as maximum altitude and effective range) of different types of rockets and anti-aircraft shells, it is determined spatially which sites are within the effective range of the cloud system's future path. Operational preparation instructions are then sent in advance to the equipment units identified as effective operational sites, requiring them to enter a standby state.

[0113] By traversing the elevation angles of effective operational sites and cloud systems, the minimum operational elevation angle that allows the ballistic peak to reach the cloud base height is determined, and the firing azimuth angle is calculated using spherical trigonometric functions. 0-30 minutes before the operation, a higher time-resolution radar 3D extrapolation product is used to accurately determine the real-time location, altitude (cloud base, cloud top), and intensity of the seedable cloud system.

[0114] Based on the precise latitude, longitude, and altitude information of each effective operational site, the rocket trajectory parameters and real-time monitored cloud base and cloud top heights are input. By traversing radar reflectivity data layer by layer, the altitude layer with the first detected reflectivity greater than 18 dBZ is determined as the cloud base height. Based on the equipment's "Elevation-Trajectory Table," cubic spline interpolation is used to achieve continuous and high-precision acquisition of trajectory parameters corresponding to any elevation angle within the range of 45° to 85°, with an interpolation error of less than 0.5%. By traversing different elevation angles, the minimum angle at which the highest point of the trajectory reaches the cloud base height is determined, and this elevation angle is defined as the minimum operational elevation angle. Using the spherical trigonometric function method, the firing azimuth angle is accurately calculated based on the latitude and longitude coordinates of the effective operational sites and the aiming point, with a calculation accuracy of 0.1°. The calculation formula is as follows:

[0115] (6)

[0116] In the formula, F is the firing azimuth (angle measured from due north). The latitude of the firing point. The latitude of the target point =λB-λA, which is the target longitude minus the longitude of the shot point. The calculation result needs to be converted into an angle (0~360°) from due north.

[0117] The calculated firing parameters, such as minimum elevation angle, azimuth angle, and ammunition quantity, are pushed to the corresponding effective operational sites and their superior command units in real time. Based on unified instructions and parameters, each site conducts coordinated operations against the same sowable cloud system at the optimal time, forming a regional joint operational effect. During the operation, radar tracking and extrapolation are continuously performed. If the extrapolation results show that the cloud system has moved out of the effective range of the operational point or has significantly weakened and dissipated, an order to cancel or stop the operation is immediately sent to the relevant sites.

[0118] An example of the operational results is as follows: On April 18, 2025, the Hunan Provincial Meteorological Department applied this method, first conducting an analysis of operational needs and conditions (…). Figure 2-4 ( ), across the province, qualified artificial weather modification sites were organized to carry out unified command and joint operations for weather processes. Pre-operation status can be found in [link to relevant documentation]. Figure 5 A total of rockets were successfully launched from various city and county-level operational sites. Detailed operational statistics are shown in Table 1. Following the operations, the affected areas experienced widespread light to moderate rain, effectively alleviating localized drought conditions. Post-operation monitoring data is available in [link to table]. Figure 9 This study verified the effectiveness of the proposed method in improving operational efficiency and achieving regional collaboration.

[0119] To verify the technical effect of the present invention, the inventors conducted the following experiments:

[0120] Table 1. Statistical Table of Ground Operations in Hunan Province as of April 18, 2025

[0121]

[0122]

[0123] Example 2:

[0124] Example 2 provides a regional joint weather modification drought relief operation system, used to implement the regional joint weather modification drought relief operation method described in Example 1.

[0125] Specifically, the system includes:

[0126] The drought region delineation module, based on meteorological and agricultural drought monitoring results, identifies areas with moderate to severe drought as areas requiring drought relief operations.

[0127] The operational condition assessment module uses the China Meteorological Administration's CMA-GFS model and real-time weather conditions to determine the conditions for artificial rain enhancement operations in areas requiring drought relief.

[0128] The cloud identification module identifies sowable cloud systems for drought relief operations that meet the conditions for artificial rain enhancement, based on the 6-hour forecast of the CPEFS model and combined with satellite and radar data, and performs 0-2 hour radar extrapolation forecasts.

[0129] The coordinated operation module utilizes 2-hour radar extrapolation forecast results to determine effective operation sites based on ballistic parameters, calculates the effective firing parameters of each operation site for the seedable cloud system, and pushes them to relevant sites and administrative regions to achieve multi-area joint operation in a seedable cloud system area.

[0130] Example 3:

[0131] Embodiment 3 provides an electronic device, including at least one processor; and a memory communicatively connected to the processor; wherein the memory stores instructions that are executed by the processor, the instructions being executed by the processor to enable the processor to perform a regional joint artificial weather modification drought relief operation method as described in Embodiment 1.

[0132] Finally, it should be noted that the above descriptions are merely optional examples of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for regional joint artificial weather modification for drought relief, characterized in that, Includes the following steps: Based on meteorological and agricultural drought monitoring results, areas with moderate to severe drought were identified as areas requiring drought relief operations. The conditions for artificial rain enhancement operations in areas requiring drought relief were determined using the China Meteorological Administration's CMA-GFS model and real-time weather conditions. For drought relief operations that meet the conditions for artificial rain enhancement, based on the 6-hour forecast of the CPEFS model, combined with satellite and radar data, the sowable cloud systems are identified, and 0-2 hour radar extrapolation forecasts are made. Using 2-hour radar extrapolation forecast results, effective operational sites are determined based on ballistic parameters, and effective firing parameters for each operational site against sowable cloud systems are calculated and pushed to relevant sites and administrative regions, enabling multi-area joint operations in a sowable cloud system area.

2. The method for regional joint artificial weather modification drought relief operations according to claim 1, characterized in that, The radar extrapolation prediction method includes the following steps: Read radar CAPPI product data and satellite infrared cloud image data, and convert image color values ​​into dBZ intensity values ​​and brightness temperature values; Calculate the spatial gradient of the dBZ intensity value and brightness temperature value in the spatial dimension and their rate of change over a set time interval, respectively. Construct an optical flow field model; The optical flow field model is iteratively calculated to obtain the cloud system movement vector; Based on the optical flow field model obtained from the final iteration, extrapolation forecasts for seedable cloud systems are performed for 0 to 2 hours.

3. The method for regional joint artificial weather modification drought relief operations according to claim 2, characterized in that, The optical flow field model is iteratively calculated to obtain the cloud system movement vector, specifically including: The optical flow field model is iteratively calculated. When the optical flow error between two iterations is less than the iteration error threshold or the number of iterations reaches the maximum number of iterations, the iteration process is terminated and the target optical flow field model is obtained. Post-processing is performed on the optical flow components u in the x-direction and v in the y-direction of the target optical flow field model to obtain the cloud system movement vector.

4. The regional joint artificial weather modification drought relief operation method according to claim 3, characterized in that, The iterative calculation formula for the optical flow field model is as follows: ； ； in, u: Optical flow component in the x-direction; v: Optical flow component in the y direction; n: Number of iterations; : Velocity field in the current iteration The spatial average value within the local neighborhood; : Velocity field in the current iteration The spatial average value within the local neighborhood; This is the regularization parameter.

5. The regional joint artificial weather modification drought relief operation method according to claim 4, characterized in that, The optical flow components u in the x-direction and v in the y-direction of the optical flow field are post-processed, and the post-processing formula is as follows: in, : The x-direction velocity component of the k-th field (such as the final optical flow field) at grid point (i, j); , , The x-direction velocity of the direct neighbors of the center point (i, j); : The y-direction velocity component of the k-th field (such as the final optical flow field) at grid point (i, j); , , : The y-direction velocity of the direct neighbors of the center point (i, j); k: Number of iterations.

6. The method for regional joint artificial weather modification drought relief operations according to claim 1, characterized in that, Using 2-hour radar extrapolation forecast results, effective operational sites are determined based on ballistic parameters, and the effective firing parameters for each operational site against the seedable cloud system are calculated, specifically including: Based on the 2-hour radar extrapolation forecast results, cloud base height and cloud top height information are obtained; Valid operational sites are determined based on the location information and ballistic parameters of the operational sites. The minimum operational elevation angle that allows the ballistic maximum to reach the cloud base height is determined by traversing the elevation angles of effective operational sites and cloud systems, and the firing azimuth angle is calculated using spherical trigonometric functions.

7. A regional joint artificial weather modification drought relief operation method according to claim 6, characterized in that, Obtaining cloud base and cloud top height information includes the following steps: Read the radar 3D mosaic and radar echo top height data, and for each horizontal coordinate position, vertically scan the reflectivity value from low to high. The height at which the reflectivity first reaches or exceeds 18dBZ is determined as the cloud base height. Continue scanning upwards, and determine the height at which the reflectance value falls back below the preset reflectance threshold as the cloud top height.

8. A regional joint artificial weather modification drought relief operation method according to claim 7, characterized in that, The formula for calculating the firing azimuth angle is as follows: ； in, F: firing azimuth; The latitude of the firing point; The latitude of the target point; Target longitude minus the firing point longitude.

9. A regional joint weather modification drought relief operation system, used to implement the regional joint weather modification drought relief operation method described in any one of claims 1-8, characterized in that, The system includes: The drought region delineation module, based on meteorological and agricultural drought monitoring results, identifies areas with moderate to severe drought as areas requiring drought relief operations. The operational condition assessment module uses the China Meteorological Administration's CMA-GFS model and real-time weather conditions to determine the conditions for artificial rain enhancement operations in areas requiring drought relief. The cloud identification module identifies sowable cloud systems for drought relief operations that meet the conditions for artificial rain enhancement, based on the 6-hour forecast of the CPEFS model and combined with satellite and radar data, and performs 0-2 hour radar extrapolation forecasts. The coordinated operation module utilizes 2-hour radar extrapolation forecast results to determine effective operation sites based on ballistic parameters, calculates the effective firing parameters of each operation site for the seedable cloud system, and pushes them to relevant sites and administrative regions to achieve multi-area joint operation in a seedable cloud system area.

10. An electronic device, characterized in that, The device includes at least one processor; and a memory communicatively connected to the processor; wherein the memory stores instructions that are executed by the processor to enable the processor to perform a regional joint artificial weather modification drought relief operation method as described in any one of claims 1-8.

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