Artificial influence snow increasing operation control method based on meteorological radar data

Abstract

The invention relates to the field of artificial influence weather operation, and discloses an artificial influence snow increasing operation control method based on meteorological radar data, and the method comprises the steps: obtaining a farmland distribution diagram of a target snow increasing region and the position information of the target snow increasing region; determining a target meteorological radar number and acquiring radar data; mapping the farmland distribution map to a radar echo map, and dividing a covered area and an uncovered area; acquiring sounding balloon data; screening an uncovered area pointing to the farmland as a secondary selection area according to the wind direction and the radial velocity diagram; forming a to-be-evaluated region group by the coverage region and the secondary selection region; evaluating a snow-increasing cloud layer and a ground condition of the to-be-evaluated area; determining an area which meets the cloud layer and ground conditions as a catalyst feeding area; and obtaining a catalyst feeding scheme and generating an artificial snow increasing scheme. Therefore, the artificial influence snow increasing operation control method based on the meteorological radar data is realized.

Description

Technical Field

[0001] The present invention relates to the field of weather modification operations, and particularly to a method for controlling artificial weather modification snow enhancement operations based on meteorological radar data. Background Art

[0002] Artificial weather modification, especially artificial snow enhancement operations, is a technology that artificially intervenes in the cloud microphysical process by using catalysts (such as silver iodide, etc.) at appropriate times and cloud conditions to increase the ground snowfall. This technology has important application values in agricultural production (such as supplementing farmland moisture and increasing crop yields), ecological environment protection (such as increasing mountain snow cover and conserving water sources), alleviating droughts, etc. Meteorological radar is an important detection tool in artificial snow enhancement operations, which can provide information such as the position, intensity, and moving direction of clouds, providing a basis for operation decisions.

[0003] In the existing artificial weather modification snow enhancement operation process, especially in the decision-making and implementation of catalyst delivery based on meteorological radar data, the following technical problems often exist: First, in the prior art, artificial snow enhancement operations usually evaluate and make decisions based on large-scale meteorological conditions, lacking refined analysis for the target snow enhancement area. As a result, the selection of the catalyst delivery area is not precise enough, and the actual needs and ground conditions of the target area cannot be fully considered, thus leading to low utilization efficiency of the catalyst, unstable snow enhancement effects, and even possible adverse impacts on agricultural production. Second, in the prior art, since artificial snow enhancement operations usually adopt a unified catalyst delivery plan, lacking targeted adjustments for different growth stages of crops, catalyst delivery may be carried out during the growth stages when crops do not need or are not suitable for snow enhancement, resulting in waste of resources and affecting crop growth. In addition, the evaluation of snow enhancement operations also lacks an effective feedback mechanism combined with the environment, and it is impossible to adjust the catalyst delivery amount in a timely manner according to the actual snow enhancement effect, resulting in unstable snow enhancement effects in farmland and being difficult to achieve the expected yield increase target. Third, in the prior art, artificial snow enhancement operations usually rely on a single radar station. When the radar station migrates or the coverage area is insufficient, effective data cannot be obtained in a timely manner, thus affecting the efficiency of artificial snow enhancement operation decision-making and implementation. Summary of the Invention

[0004] This part of the summary of the invention is used to briefly introduce the concepts, which will be described in detail in the following detailed implementation part. This part of the summary of the invention is not intended to identify the key features or essential features of the claimed technical solution, nor is it intended to limit the scope of the claimed technical solution.

[0005] The present invention provides a method for controlling artificial snow enhancement operations based on meteorological radar data to solve one or more of the technical problems mentioned in the above background art section.

[0006] The present invention provides a method for controlling artificial snow enhancement operations based on meteorological radar data, including: Obtain the farmland distribution map of the target snow enhancement area and the location information of the target snow enhancement area; according to the location information of the target snow enhancement area, determine the target meteorological radar number; obtain the target meteorological radar data corresponding to the target meteorological radar number; the target meteorological radar data includes a radar echo map and a radial velocity map; Map multiple farmland areas in the farmland distribution map of the target snow enhancement area to the radar echo map to obtain a mapped radar echo map, which includes multiple mapped farmland areas; determine whether each echo area in the mapped radar echo map is covered by a mapped farmland area to obtain a covered area group and an uncovered area group; Obtain the radiosonde data corresponding to the location information of the target snow enhancement area, where the radiosonde data includes a temperature profile, a humidity profile, and a wind direction profile; according to the wind direction profile and the radial velocity map, determine the wind direction of each uncovered area in the uncovered area group; according to the farmland distribution map of the target snow enhancement area and the wind direction of each uncovered area in the uncovered area group, screen out the uncovered areas in the uncovered area group whose wind directions point to any farmland in the farmland distribution map of the target snow enhancement area and whose distances from the farmland are less than or equal to a preset distance threshold to obtain a secondary selection area group, and form a group of areas to be evaluated with the covered area group; Obtain the evaluation results of the snow enhancement cloud conditions and the evaluation results of the snow enhancement ground conditions corresponding to each area to be evaluated in the group of areas to be evaluated and determine the catalyst injection area; generate an artificial snow enhancement plan according to the catalyst injection area and the catalyst injection plan corresponding to the catalyst injection area.

[0007] Optionally, the evaluation results of the snow enhancement cloud conditions corresponding to each area to be evaluated are determined through the following steps: Obtain the radar vertical profile corresponding to the radar echo map; according to the radar echo map and the radar vertical profile, determine the cloud type corresponding to each area to be evaluated; If the cloud type meets the preset snow enhancement cloud type, obtain multiple target height intervals according to the temperature profile and multiple preset snow enhancement temperature intervals; according to the radar echo map, the radar vertical profile, and the radiosonde data, determine the cloud base height and cloud top height corresponding to each area to be evaluated; generate the cloud thickness corresponding to each area to be evaluated through the cloud base height and the cloud top height; Determine the proportion of supercooled water regions in each target height interval for each region to be evaluated among multiple target height intervals; determine the target height intervals with the proportion of supercooled water regions greater than or equal to the preset supercooled water region proportion threshold as supercooled cloud intervals; obtain the proportion of supercooled clouds corresponding to each region to be evaluated based on the supercooled cloud intervals and the cloud thickness corresponding to each region to be evaluated; if the proportion of supercooled clouds is greater than or equal to the preset supercooled cloud proportion threshold, determine that the evaluation result of the snow enhancement cloud layer condition corresponding to the corresponding region to be evaluated passes the evaluation.

[0008] Optionally, the proportion of supercooled water regions is determined through the following steps: Obtain the meteorological radar polarization type corresponding to the target meteorological radar number, where the meteorological radar polarization type includes a dual-polarization radar or a single-polarization radar; the target meteorological radar data includes multiple radar detection data corresponding to multiple radar detection units, where the radar detection units and the radar detection data are in one-to-one correspondence; For each radar detection unit, if the meteorological radar polarization type is a dual-polarization radar, extract the differential reflectivity and correlation coefficient from the corresponding radar detection data; if the differential reflectivity is greater than or equal to the preset differential reflectivity threshold and the correlation coefficient is greater than or equal to the preset correlation coefficient threshold, determine that there is a supercooled water region within the corresponding radar detection unit; screen the radar detection units with supercooled water regions from multiple radar detection units to obtain multiple radar detection units with supercooled water regions; obtain the thicknesses of the multiple radar detection units with supercooled water regions; obtain the ratio of the sum of the thicknesses of the multiple radar detection units with supercooled water regions to the cloud thickness of the corresponding region to be evaluated to obtain the first proportion of supercooled water regions; If the meteorological radar polarization type is a single-polarization radar, obtain the echo intensity corresponding to each target height interval and the humidity corresponding to the humidity profile; if the echo intensity is greater than or equal to the preset echo intensity threshold and the humidity is greater than or equal to the preset humidity threshold, determine the corresponding target height interval as a supercooled water region; obtain the ratio of the sum of the thicknesses of the target height intervals with supercooled water regions to the cloud thickness of the corresponding region to be evaluated to obtain the second proportion of supercooled water regions; Determine the proportion of supercooled water regions as either the first proportion of supercooled water regions or the second proportion of supercooled water regions.

[0009] Optionally, the evaluation result of the snow enhancement ground condition corresponding to each region to be evaluated is determined through the following steps: According to the farmland distribution map of the target snow - increasing area, obtain the farmland coordinate group; obtain multiple soil temperatures and multiple soil moisture contents corresponding to each farmland coordinate in the farmland coordinate group; obtain the average soil temperature based on the multiple soil temperatures; obtain the average soil moisture content based on the multiple soil moisture contents; compare the average soil temperature with the preset maximum soil temperature threshold and the preset minimum soil temperature threshold; if the average soil temperature is greater than or equal to the preset minimum soil temperature threshold and less than the preset maximum soil temperature threshold, it is determined that the soil temperature assessment passes; compare the average soil moisture content with the preset maximum soil moisture threshold and the preset minimum soil moisture threshold; if the average soil moisture content is greater than or equal to the preset minimum soil moisture threshold and less than the preset maximum soil moisture threshold, it is determined that the soil moisture assessment passes; if the soil temperature assessment passes and the soil moisture assessment passes, then determine that the snow - increasing ground condition assessment result corresponding to the corresponding area to be evaluated passes.

[0010] Optionally, the target meteorological radar data further includes a spectrum width map; the catalyst delivery plan includes at least one catalyst delivery sub - plan, and the catalyst delivery sub - plan is determined through the following steps: Determine the target delivery location according to the catalyst delivery area and the spectrum width map; Obtain a farmland information group from the farmland distribution map of the target snow - increasing area; each farmland information in the farmland information group includes the crop type, sowing date, estimated harvest date, and farmland terrain category; according to the crop type, obtain the snow requirement level of the crop through a preset crop information table, and the snow requirement level of the crop includes low, medium, or high; if the snow requirement level of the crop is medium or high, obtain the cold tolerance level of the crop according to the crop type and the preset crop information table; determine the catalyst delivery method according to the farmland terrain category and the preset catalyst delivery method table; determine the catalyst delivery sub - plan through the target delivery location, the cold tolerance level of the crop, the preset catalyst adjustment table, and the catalyst delivery method.

[0011] Optionally, an artificial weather modification snow - increasing operation control method based on meteorological radar data of the present invention further includes: Obtain the current date; if the current date is later than or equal to the sowing date and earlier than the estimated harvest date, obtain the growth days corresponding to the crop type according to the current date and the sowing date; determine the growth stage corresponding to the crop type according to the crop type, the growth days, and the preset crop information table; Obtain the growth - stage snow requirement level and the growth - stage cold tolerance level corresponding to the crop type in the growth stage according to the crop type, the growth stage, and the preset crop growth - stage information table; generate a growth - stage adjustment plan for the farmland area corresponding to the crop type according to the growth - stage snow requirement level, the growth - stage cold tolerance level, and the preset catalyst adjustment table; send the growth - stage adjustment plan to the corresponding processing terminal.

[0012] Optionally, a method for controlling artificial weather modification snow enhancement operations based on weather radar data according to the present invention further includes: Obtaining a plurality of soil water contents before snow enhancement, a plurality of soil water contents after snow enhancement, and a plurality of snow depths corresponding to a farmland coordinate group; obtaining an average soil water content before snow enhancement based on the plurality of soil water contents before snow enhancement, and obtaining an average soil water content after snow enhancement based on the plurality of soil water contents after snow enhancement; obtaining an average snow depth based on the plurality of snow depths; and obtaining a soil water content increment based on the average soil water content before snow enhancement and the average soil water content after snow enhancement. Obtaining a soil water content increment evaluation result corresponding to the soil water content increment, and obtaining a snow depth evaluation result corresponding to the average snow depth; if the soil water content increment evaluation result indicates a low increment, or the snow depth evaluation result indicates a shallow depth, then generating first catalyst dosage feedback information; if the soil water content increment evaluation result indicates a high or relatively high increment, or the snow depth evaluation result indicates a deep or relatively deep depth, then generating second catalyst dosage feedback information; if the soil water content increment evaluation result indicates a low increment, or the snow depth evaluation result indicates a shallow depth, then generating third catalyst dosage feedback information; and sending the first catalyst dosage feedback information, the second catalyst dosage feedback information, or the third catalyst dosage feedback information to a corresponding feedback terminal.

[0013] Optionally, the soil water content increment evaluation result and the snow depth evaluation result are determined through the following steps: Comparing the soil water content increment with a preset group of soil water content increment critical values, the preset group of soil water content increment critical values including a first soil water content increment critical value, a second soil water content increment critical value, a third soil water content increment critical value, and a fourth soil water content increment critical value; If the soil water content increment is less than the first soil water content increment critical value, then determining that the increment is low; if the soil water content increment is greater than or equal to the first soil water content increment critical value and less than the second soil water content increment critical value, then determining that the increment is relatively low; if the soil water content increment is greater than or equal to the second soil water content increment critical value and less than the third soil water content increment critical value, then determining that the increment is moderate; if the soil water content increment is greater than or equal to the third soil water content increment critical value and less than the fourth soil water content increment critical value, then determining that the increment is relatively high; if the soil water content increment is greater than or equal to the fourth soil water content increment critical value, then determining that the increment is high; Comparing the snow depth with a preset group of snow depth increment critical values, the preset group of snow depth increment critical values including a first snow depth increment critical value, a second snow depth increment critical value, a third snow depth increment critical value, and a fourth snow depth increment critical value; If the snow depth increment is less than the first snow depth increment critical value, it is determined that the increment is relatively shallow; if the snow depth increment is greater than or equal to the first snow depth increment critical value and less than the second snow depth increment critical value, it is determined that the increment is relatively shallow; if the snow depth increment is greater than or equal to the second snow depth increment critical value and less than the third snow depth increment critical value, it is determined that the increment is moderate; if the snow depth increment is greater than or equal to the third snow depth increment critical value and less than the fourth snow depth increment critical value, it is determined that the increment is relatively deep; if the snow depth increment is greater than or equal to the fourth snow depth increment critical value, it is determined that the increment is relatively deep.

[0014] The present invention has the following beneficial effects: 1. Achieved precise snow augmentation for the target snow augmentation area, significantly improving the pertinence and effectiveness of artificial snow augmentation operations. Specifically, by mapping the farmland distribution map to the radar echo map for refined regional division, and combining factors such as wind direction, distance, cloud layer, and ground conditions to screen the catalyst injection area, ensuring the pertinence of effective catalyst delivery and injection. At the same time, formulating a differentiated injection plan according to farmland information to maximize the satisfaction of the needs of different crops, improving the catalyst utilization rate and snow augmentation effect, enhancing the overall efficiency of artificial snow augmentation operations, and better meeting the actual needs of agricultural production; 2. Effectively overcomes the problems of single catalyst injection plan and insufficient feedback mechanism in the prior art, significantly improving the precision and effectiveness of snow augmentation operations. Specifically, by carrying out differentiated catalyst injection according to the growth stage of crops, unnecessary resource waste and negative impacts on crop growth are avoided; at the same time, by establishing a snow augmentation effect feedback mechanism and comprehensively evaluating by combining meteorological and ground information, timely adjustment of the catalyst injection amount is realized, improving the stability and pertinence of the snow augmentation effect, and providing good moisture conditions for crop growth; 3. Through the backup radar selection method based on the overlapping area ratio, effectively solves the data loss problem caused by the failure or insufficient coverage of a single radar station in the prior art for artificial snow augmentation operations, improving the reliability of artificial snow augmentation operations. Specifically, by calculating the overlapping area ratio between the target snow augmentation area and the monitoring range of the alternative radar, the best backup radar is selected. Avoiding the deficiencies of the traditional method that only relies on distance or adjacency relationship to select the backup radar, and adopting an efficient coordinate transformation method to meet the real-time requirements of artificial snow augmentation operations, improving the decision-making speed and implementation efficiency of artificial snow augmentation operations. Description of the Drawings

[0015] Combined with the drawings and referring to the following specific embodiments, the above and other features, advantages, and aspects of the embodiments of the present invention will become more obvious. Throughout the drawings, the same or similar reference numerals represent the same or similar elements. It should be understood that the drawings are schematic, and the elements and elements are not necessarily drawn to scale.

[0016] Figure 1 It is a flowchart of a method for controlling artificial snow enhancement operations based on meteorological radar data according to the present invention. Specific embodiments

[0017] The present invention will be described in more detail below with reference to the accompanying drawings. Although some embodiments of the present invention are shown in the drawings, it should be understood that the present invention can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. On the contrary, these embodiments are provided to more thoroughly and completely understand the present invention. It should be understood that the drawings and embodiments of the present invention are only for exemplary purposes and are not used to limit the protection scope of the present invention.

[0018] In addition, it should be noted that for the sake of convenience of description, only the parts related to the relevant invention are shown in the drawings. Without conflict, the embodiments in the present invention and the features in the embodiments can be combined with each other.

[0019] It should be noted that the concepts such as "first" and "second" mentioned in the present invention are only used to distinguish different devices, modules or units, and are not used to limit the order or interdependence relationship of the functions performed by these devices, modules or units.

[0020] It should be noted that the modifications of "one" and "multiple" mentioned in the present invention are illustrative rather than restrictive. Those skilled in the art should understand that unless otherwise clearly indicated in the context, it should be understood as "one or more".

[0021] The names of the messages or information exchanged between multiple devices of the present invention are only for illustrative purposes and are not used to limit the scope of these messages or information.

[0022] The present invention will be described in detail below with reference to the drawings and in combination with embodiments.

[0023] As Figure 1 shown, it is a flowchart of a method for controlling artificial snow enhancement operations based on meteorological radar data according to the present invention, specifically including the following steps: Step 101, obtain the farmland distribution map of the target snow enhancement area and the location information of the target snow enhancement area; determine the target meteorological radar number according to the location information of the target snow enhancement area; obtain the target meteorological radar data corresponding to the target meteorological radar number; the target meteorological radar data includes a radar echo map and a radial velocity map.

[0024] In some embodiments, the execution entity may be a server. The execution entity first obtains target snow enhancement area information from an agricultural resources database or a geographic information system database through the administrative division code of the target snow enhancement area. The target snow enhancement area information includes a farmland distribution map of the target snow enhancement area and the location information of the target snow enhancement area. Subsequently, through the administrative division code of the target snow enhancement area and GIS (Geography Information System) information, the target meteorological radar number corresponding to the target snow enhancement area is determined, and the corresponding target meteorological radar data is obtained according to the target meteorological radar number. The target meteorological radar data includes a radar echo map and a radial velocity map.

[0025] In practice, the target snow enhancement area may be an area divided by an administrative division code. The farmland distribution map of the target snow enhancement area refers to the distribution of farmland within the target snow enhancement area presented in the form of a map or an image. The location information of the target snow enhancement area is used to describe the geographical location of the target snow enhancement area on the earth. The target meteorological radar number is a code used to uniquely identify a meteorological radar. Among them, the administrative division code is a digital code used to identify an administrative region. GIS is a geographic information system, which is used to collect, store, manage, analyze, display, and apply geospatial data. The radar echo map is an image of the echo intensity received by the radar, which is used to display the location, intensity, and range of precipitation cloud clusters and predict the precipitation intensity. The radial velocity map is an image of the velocity of precipitation particles along the radar beam direction measured using the Doppler effect, which is used to analyze the wind field distribution. The spectrum width map is an image of the spectrum width of the radar echo signal, which is used to reflect the variability of the precipitation particle velocity and assist in identifying precipitation types and phenomena such as turbulence. The echo intensity is the power intensity of the electromagnetic wave received by the radar. The Doppler effect refers to the phenomenon that when there is relative motion between the wave source and the receiver, the frequency of the wave received by the receiver will change. If the wave source approaches the receiver, the received frequency will increase; if the wave source moves away from the receiver, the received frequency will decrease. Precipitation particles are various forms of precipitation in the atmosphere, such as raindrops, snowflakes, and hailstones. The wind field refers to the distribution of wind direction and wind speed at different locations within a certain area. The spectrum width is the frequency range of the radar echo signal received. Turbulence is the irregular and random motion state of a fluid.

[0026] Step 102: Map multiple farmland areas in the farmland distribution map of the target snow enhancement area to the radar echo map to obtain a mapped radar echo map, which includes multiple mapped farmland areas; determine whether each echo area in the mapped radar echo map is covered by the mapped farmland areas to obtain a covered area group and an uncovered area group.

[0027] In some embodiments, the execution entity first maps multiple farmland areas in the farmland distribution map of the target snow augmentation area to the radar echo map to obtain a mapped radar echo map, which contains multiple mapped farmland areas. Subsequently, for each echo area in the mapped radar echo map, by methods such as geometric figure or grid cell comparison, it is judged one by one whether each echo area is covered by the mapped farmland areas. Multiple echo areas covered by the mapped farmland areas are determined as the covered area group, and multiple echo areas not covered by the mapped farmland areas are determined as the uncovered area group.

[0028] In practice, the mapped radar echo map refers to a new radar echo map obtained by superimposing or projecting other spatial information onto the original radar echo map. The mapped farmland area refers to the representation of the farmland area in the farmland distribution map of the target snow augmentation area on the mapped radar echo map. It is the form presented by the farmland area on the radar echo map after coordinate transformation and superposition or projection. Multiple farmland areas in the farmland distribution map of the target snow augmentation area can be mapped to the radar echo map using GIS tools. Among them, the GIS tool can be ArcGIS, and the mapping method can be boundary comparison or area intersection. ArcGIS is a geographic information system software platform, which is widely used in the management, analysis, visualization and sharing of geographic data, especially in the fields of map making and spatial analysis. The grid cell is also called a pixel, which is the basic unit of raster data. Boundary comparison refers to comparing the boundary lines of two or more geographic regions, aiming to determine their relative positions, overlapping parts and differences in space. Area intersection refers to calculating the overlapping parts between two or more geographic regions, usually by spatial overlap to analyze the intersecting parts of the two regions in the geographical space. The intersection operation will return the common part of the two regions, which is usually used to determine the overlapping area or the common influence area between the two.

[0029] Step 103, obtain the radiosonde data corresponding to the position information of the target snow augmentation area. The radiosonde data includes temperature profile, humidity profile and wind direction profile; according to the wind direction profile and the radial velocity map, determine the wind direction of each uncovered area in the uncovered area group; according to the farmland distribution map of the target snow augmentation area and the wind direction of each uncovered area in the uncovered area group, screen out the uncovered areas in the uncovered area group whose wind direction points to any farmland in the farmland distribution map of the target snow augmentation area and the distance from the farmland is less than or equal to the preset distance threshold to obtain the secondary selection area group, and form the to-be-evaluated area group with the covered area group.

[0030] In some embodiments, the executing entity first locates the center point or boundary range of the target snow augmentation area based on the geographical coordinates of the target snow augmentation area. Then, it establishes contact with the radiosonde data source, determines the weather station to which the target snow augmentation area belongs, and obtains radiosonde data from the weather station. The obtained radiosonde data includes temperature profiles, humidity profiles, and wind direction profiles. Subsequently, for the uncovered area group, the executing entity determines the wind direction distribution at different heights through the wind direction profile in the radiosonde data, in combination with the vertical meteorological conditions of the target snow augmentation area. The radial velocity map provides the radial movement velocities of atmospheric particles in different regions on the horizontal plane, thus indirectly reflecting the horizontal distribution of the wind. By analyzing the wind direction, the wind field situation of each uncovered area is determined. Then, each farmland area in the farmland distribution map of the target snow augmentation area is used as an identification point, and screening is carried out in the uncovered area group to find the uncovered area whose wind direction points to any farmland in the farmland distribution map of the target snow augmentation area. The longitude and latitude coordinates of the uncovered area and the farmland pointed by the wind direction are obtained, and the coordinate distance between the uncovered area and the farmland pointed by the wind direction is calculated. If the distance is less than or equal to the preset distance threshold, the uncovered area is determined as a candidate area, and multiple candidate areas that meet the screening conditions are determined as the candidate area group. Finally, the covered area group and the candidate areas are merged to obtain the area group to be evaluated.

[0031] In practice, the uncovered areas whose wind directions point to any farmland area can be screened from the uncovered area group through the wind direction profile and the wind direction in each uncovered area in the radar echo map, and the actual distance between the farmland area and the uncovered area can be calculated by using a GIS tool. If the actual distance is less than or equal to the preset distance threshold, the corresponding uncovered area is determined as a candidate area. Among them, the GIS tool can be ArcGIS; the preset distance threshold can be 5 kilometers. Among them, the candidate area group is the uncovered areas that are at a certain distance from the farmland in the target snow augmentation area and whose wind directions point to the target snow augmentation area selected during the screening process based on the wind direction and the distance threshold. The wind direction profile refers to the distribution of wind speed and wind direction recorded by the radiosonde with height, which is used to analyze the atmospheric flow at different levels and predict the influence of the wind field on the precipitation and snow augmentation processes. The radial velocity map refers to the distribution map of the radial velocities of precipitation particles obtained by the radar through the Doppler effect, which is used to reflect the moving direction and wind speed of the air flow and further help determine the state of the wind field. The temperature profile is a curve or graph of the change of atmospheric temperature with height, which describes the temperature distribution at different heights in the atmosphere. The humidity profile is a curve or graph of the change of atmospheric humidity with height, which describes the water vapor content distribution at different heights in the atmosphere. The vertical meteorological conditions refer to the distribution of meteorological characteristics in the vertical direction of the atmosphere, usually including the characteristics of the change of elements such as temperature, humidity, air pressure, wind speed, and wind direction with height.

[0032] Step 104: Obtain the snow enhancement cloud condition evaluation results and snow enhancement ground condition evaluation results corresponding to each area to be evaluated in the area group to be evaluated, and determine the catalyst injection area; generate an artificial snow enhancement plan according to the catalyst injection area and the corresponding catalyst injection plan.

[0033] In some embodiments, the execution entity first conducts a snow enhancement cloud condition evaluation and a snow enhancement ground condition evaluation on each area to be evaluated in the area group to be evaluated. The evaluation results are used to determine whether the area to be evaluated meets the conditions for snow enhancement implementation. The areas to be evaluated that pass the snow enhancement cloud condition evaluation and the snow enhancement ground condition evaluation are determined as the catalyst injection areas. Subsequently, obtain the pre-configured catalyst injection plan corresponding to the catalyst injection area, and integrate the catalyst injection area and the catalyst injection plan to obtain an artificial snow enhancement plan.

[0034] In practice, the catalyst can be silver iodide. Herein, a catalyst refers to a substance used to promote certain physical or chemical processes. In the process of artificial snow enhancement, the role of the catalyst is to help water vapor or water droplets in the cloud form ice crystals, thereby accelerating the precipitation process. Silver iodide is one of the commonly used catalysts in artificial snow enhancement operations. Silver iodide has special physical properties, and its crystal structure is very similar to that of ice, which can effectively promote the condensation of water in the cloud into ice crystals.

[0035] In these embodiments, precise snow enhancement for the target snow enhancement area is achieved, significantly improving the pertinence and effectiveness of artificial snow enhancement operations. Specifically, by mapping the farmland distribution map to the radar echo map for refined area division, and combining factors such as wind direction, distance, cloud layer and ground conditions to screen the catalyst injection area, it ensures the pertinence of the effective delivery and injection of the catalyst. At the same time, formulate a differentiated injection plan according to the farmland information to meet the needs of different crops to the greatest extent, improve the catalyst utilization rate and snow enhancement effect, enhance the overall efficiency of artificial snow enhancement operations, and better meet the actual needs of agricultural production.

[0036] In some embodiments, in order to further solve Technical Problem 2 described in the background art part, that is, "in the prior art, since the artificial snow enhancement operation usually adopts a unified catalyst injection plan, lacking targeted adjustment for different growth stages of crops, it may inject the catalyst in the growth stage when the crops do not need or are not suitable for snow enhancement, resulting in waste of resources and affecting the growth of crops. In addition, the evaluation of the snow enhancement operation lacks an effective feedback mechanism combined with the environment, and it is impossible to adjust the catalyst injection amount in a timely manner according to the actual snow enhancement effect, resulting in unstable snow enhancement effect on farmland and difficult to achieve the expected yield increase target". In some embodiments of the present invention, for a method for controlling artificial weather modification snow enhancement operation based on meteorological radar data, the snow enhancement cloud condition evaluation result corresponding to each area to be evaluated is determined through the following steps: Step 1: Obtain a radar vertical profile corresponding to the radar echo map; determine the cloud type corresponding to each area to be evaluated based on the radar echo map and the radar vertical profile map.

[0037] In some embodiments, the execution subject first obtains the radar vertical profile corresponding to the radar echo map, and determines the cloud type corresponding to each area to be evaluated through the radar echo map and the radar vertical profile. Specifically, first establish a communication connection with the meteorological station corresponding to the target meteorological radar, obtain the meteorological radar data monitored by the target meteorological radar at multiple azimuths, then extract the echo information at different heights, and generate the radar vertical profile through coordinate transformation and data interpolation. Finally, the cloud type corresponding to each area to be evaluated is determined through the joint analysis of the radar echo map and the radar vertical profile.

[0038] In practice, the cloud type can be judged by the characteristics of the radar echo map and the radar vertical profile map. For example, if the radar echo map shows a large uniform echo, and the radar vertical profile map shows the existence of a bright band at the zero-degree layer, it can be judged as a layered cloud. Among them, the radar vertical profile map is an image that displays the echo intensity distribution in the radar detection area in the form of a vertical profile, reflecting the vertical structure, height, intensity and other information of the precipitation cloud group. The cloud type is a classification of clouds based on the characteristics of the cloud shape, height, and cause. Common cloud types include layered clouds, convective clouds, and stratocumulus mixed clouds. Among them, layered clouds are usually large sheets or layers, evenly distributed, with blurred edges, thin vertical thickness, and low cloud base height. Convective clouds are usually blocky or clustered, with clear edges, vigorous vertical development, and high cloud base height. Straticum mixed clouds have the characteristics of both layered clouds and convective clouds, and the echo structure is relatively complex. They are usually formed when layered clouds develop under certain conditions or when convective clouds weaken. The bright band in the zero-degree layer usually appears near the 0℃ isotherm. As water film forms on the surface of ice crystals during the melting process, the echo intensity is enhanced, forming an obvious bright band.

[0039] Step 2: If the cloud type meets the preset snow-increasing cloud type, multiple target height intervals are obtained based on the temperature profile and multiple preset snow-increasing temperature intervals; the cloud base height and cloud top height corresponding to each area to be evaluated are determined based on the radar echo map, radar vertical profile map and sounding balloon data; the cloud thickness corresponding to each area to be evaluated is generated through the cloud base height and cloud top height.

[0040] In some embodiments, the execution subject first determines the cloud type. If the cloud type meets the preset snow-increasing cloud type, multiple preset snow-increasing temperature intervals are matched by analyzing the temperature profile, thereby obtaining multiple target height intervals. Subsequently, the cloud base height and cloud top height corresponding to each area to be evaluated are obtained through radar echo map, radar vertical profile map and sounding balloon data. Finally, the cloud thickness corresponding to each area to be evaluated is obtained by performing a difference operation on the cloud top height and cloud base height.

[0041] In practice, the preset snow - increasing cloud layer type can be stratus clouds. The multiple preset snow - increasing temperature ranges include a near - zero degree range, an optimal catalysis range, a catalytic effective action range, and a catalytic limited action range. Among them, the temperature range of the near - zero degree range can be less than or equal to 0°C and greater than - 5°C; the temperature range of the optimal catalysis range can be less than or equal to - 5°C and greater than - 10°C; the temperature range of the catalytic effective action range can be less than or equal to - 10°C and greater than - 20°C; the temperature range of the catalytic limited action range can be less than or equal to - 20°C. Through the temperature profile and the multiple preset snow - increasing temperature ranges, multiple target height ranges corresponding to the multiple preset snow - increasing temperature ranges can be obtained. In the radar vertical profile diagram, the height at which the echo suddenly increases is determined as the cloud - base height, and the height at which the echo suddenly weakens or disappears is determined as the cloud - top height. The humidity profile in the radiosonde data can be used for auxiliary verification, and the position where the humidity rises sharply with height is close to the height at which the echo suddenly increases. The cloud - base height refers to the vertical distance from the bottom of the cloud to the ground. The cloud - top height refers to the vertical distance from the top of the cloud to the ground. The cloud layer thickness refers to the vertical distance between the cloud - top height and the cloud - base height, reflecting the vertical development degree of the cloud body.

[0042] Step 3: Determine the proportion of the super - cooled water area in each target height range among the multiple target height ranges for each area to be evaluated; determine the target height range with the proportion of the super - cooled water area greater than or equal to the preset super - cooled water area proportion threshold as the super - cooled cloud layer range; according to the super - cooled cloud layer range and the cloud layer thickness corresponding to each area to be evaluated, obtain the proportion of the super - cooled cloud layer corresponding to each area to be evaluated; if the proportion of the super - cooled cloud layer is greater than or equal to the preset super - cooled cloud layer proportion threshold, then determine the evaluation result of the snow - increasing cloud layer condition corresponding to the corresponding area to be evaluated as passing the evaluation.

[0043] In some embodiments, the execution subject first calculates the proportion of the super - cooled water area in each target height range among the multiple target height ranges for each area to be evaluated, and compares the proportion of the super - cooled water area with the preset super - cooled water area proportion threshold. If the proportion of the super - cooled water area is greater than or equal to the preset super - cooled water area proportion threshold, then determine the corresponding target height range as the super - cooled cloud layer range. Subsequently, by performing a ratio operation on the super - cooled cloud layer range and the cloud layer thickness corresponding to each area to be evaluated, obtain the proportion of the super - cooled cloud layer corresponding to each area to be evaluated. Finally, determine whether the proportion of the super - cooled cloud layer is greater than or equal to the preset super - cooled cloud layer proportion threshold. If the proportion of the super - cooled cloud layer is greater than or equal to the preset super - cooled cloud layer proportion threshold, then determine the evaluation result of the snow - increasing cloud layer condition corresponding to the corresponding area to be evaluated as passing the evaluation.

[0044] In practice, the preset proportion threshold of the supercooled water region can be 60%. The preset proportion threshold of the supercooled cloud layer can be 40%. The supercooled cloud layer interval refers to the target height interval where the proportion of the supercooled water region reaches or exceeds the preset proportion threshold of the supercooled water region. Supercooled water refers to water with a temperature below 0°C but still in a liquid state.

[0045] The proportion of the supercooled water region is determined through the following steps: Step 1: Obtain the polarization type of the meteorological radar corresponding to the target meteorological radar number. The polarization type of the meteorological radar includes a dual-polarization radar or a single-polarization radar; the target meteorological radar data includes multiple radar detection data corresponding to multiple radar detection units, where the radar detection units and the radar detection data are in one-to-one correspondence.

[0046] In some embodiments, the execution entity first establishes a communication connection with the database storing meteorological radar information, obtains the target meteorological radar information corresponding to the target meteorological radar number from the database storing meteorological radar information, and extracts the polarization type of the meteorological radar corresponding to the target meteorological radar number from the target meteorological radar information. The polarization type of the meteorological radar includes a dual-polarization radar or a single-polarization radar. The target meteorological radar data includes multiple radar detection data, and the multiple radar detection data are obtained from multiple radar detection units, where the radar detection units and the radar detection data are in one-to-one correspondence.

[0047] In practice, the radar detection unit is a range bin. A range bin is a discrete unit formed by the radar receiver dividing the received echo signal in time. A single-polarization radar only emits and receives electromagnetic waves in a single polarization state, usually horizontal polarization, and a single-polarization radar can only provide echo intensity information. A dual-polarization radar emits and receives electromagnetic waves in two orthogonal polarization states, usually horizontal polarization and vertical polarization, and a dual-polarization radar can provide more information about precipitation particles. Polarization refers to the asymmetry of the vibration direction of a transverse wave relative to the propagation direction.

[0048] Step 2: For each radar detection unit, if the polarization type of the meteorological radar is a dual-polarization radar, extract the differential reflectivity and the correlation coefficient from the corresponding radar detection data; if the differential reflectivity is greater than or equal to the preset differential reflectivity threshold and the correlation coefficient is greater than or equal to the preset correlation coefficient threshold, determine that there is a supercooled water region in the corresponding radar detection unit; screen the radar detection units with a supercooled water region from the multiple radar detection units to obtain multiple radar detection units with a supercooled water region; obtain the thicknesses of the multiple radar detection units with a supercooled water region; obtain the ratio of the sum of the thicknesses of the multiple radar detection units with a supercooled water region to the cloud thickness of the corresponding area to be evaluated to obtain the first proportion of the supercooled water region.

[0049] In some embodiments, the execution entity first determines the polarization type of the weather radar. If the polarization type of the weather radar is a dual-polarization radar, the differential reflectivity and the correlation coefficient are extracted from the corresponding radar detection data. Subsequently, the differential reflectivity is judged against a preset differential reflectivity threshold, and the correlation coefficient is judged against a preset correlation coefficient threshold. If the differential reflectivity is greater than or equal to the preset differential reflectivity threshold and the correlation coefficient is greater than or equal to the preset correlation coefficient threshold, it is determined that there is a supercooled water area within the corresponding radar detection unit. Then, the radar detection units with supercooled water areas are screened out from multiple radar detection units to obtain multiple radar detection units with supercooled water areas, and the thicknesses of the multiple radar detection units with supercooled water areas are obtained. Finally, the sum of the thicknesses of the multiple radar detection units with supercooled water areas is divided by the cloud thickness of the corresponding area to be evaluated to obtain the proportion of the first supercooled water area.

[0050] In practice, using the thickness for calculation can more accurately evaluate the total amount of supercooled water in the cloud. Among them, the preset differential reflectivity threshold can be 0.5 dB. The preset correlation coefficient threshold can be 0.9. The differential reflectivity is the ratio of the horizontal polarization echo intensity to the vertical polarization echo intensity, usually expressed in dB. The correlation coefficient reflects the correlation degree between the horizontal polarization echo and the vertical polarization echo, and its value range is from 0 to 1. The higher the correlation coefficient, the better the correlation between the horizontal polarization echo and the vertical polarization echo, indicating that the shapes, sizes and phases of the scatterers are more consistent; the lower the correlation coefficient, the worse the correlation, indicating that the types or states of the scatterers are more mixed. A scatterer refers to an object whose propagation direction changes when a wave encounters an inhomogeneous medium or an obstacle during wave propagation.

[0051] Step 3, if the polarization type of the weather radar is a single-polarization radar, obtain the echo intensity corresponding to each target height interval and the humidity corresponding to the humidity profile; if the echo intensity is greater than or equal to the preset echo intensity threshold and the humidity is greater than or equal to the preset humidity threshold, then determine the corresponding target height interval as the supercooled water area; obtain the ratio of the sum of the thicknesses of the target height intervals with supercooled water areas to the cloud thickness of the corresponding area to be evaluated to obtain the proportion of the second supercooled water area.

[0052] In some embodiments, the executing entity first determines the polarization type of the weather radar. If the polarization type of the weather radar is a single-polarization radar, the echo intensity corresponding to each target altitude interval is extracted from the weather radar data, and the humidity corresponding to each target altitude interval is extracted from the humidity profile of the radiosonde data. Subsequently, the echo intensity is compared with a preset echo intensity threshold, and the humidity is compared with a preset humidity threshold. If the echo intensity is greater than or equal to the preset echo intensity threshold and the humidity is greater than or equal to the preset humidity threshold, the corresponding target altitude interval is determined as the supercooled water area. Then, the thickness of each target altitude interval is statistically analyzed. Only the target altitude intervals that have been determined as the supercooled water area are selected, and the thicknesses of these target altitude intervals are summed to obtain the sum of the thicknesses of the target altitude intervals with the supercooled water area. Finally, a ratio operation is performed with the cloud thickness of the corresponding area to be evaluated to obtain the proportion of the second supercooled water area.

[0053] In practice, the preset echo intensity threshold can be 10 dBZ. The preset humidity threshold can be 80%. Here, dBZ is a logarithmic unit used to represent the intensity of the radar reflectivity factor. The larger the dBZ value, the stronger the echo power received by the radar. The radar reflectivity factor is the sum of the sixth powers of the diameters of all precipitation particles in a unit volume of air.

[0054] Step four, determine the proportion of the supercooled water area as the proportion of the first supercooled water area or the proportion of the second supercooled water area.

[0055] In some embodiments, the executing entity determines the proportion of the supercooled water area as the proportion of the first supercooled water area or the proportion of the second supercooled water area after determination.

[0056] The evaluation result of the snow enhancement ground conditions corresponding to each area to be evaluated is determined through the following steps: Step one, according to the farmland distribution map of the target snow enhancement area, obtain the set of farmland coordinates; obtain multiple soil temperatures and multiple soil moisture contents corresponding to each farmland coordinate in the set of farmland coordinates; obtain the average soil temperature based on the multiple soil temperatures; obtain the average soil moisture content based on the multiple soil moisture contents; compare the average soil temperature with the preset maximum soil temperature threshold and the preset minimum soil temperature threshold; if the average soil temperature is greater than or equal to the preset minimum soil temperature threshold and the average soil temperature is less than the preset maximum soil temperature threshold, it is determined that the soil temperature evaluation passes; compare the average soil moisture content with the preset maximum soil moisture threshold and the preset minimum soil moisture threshold; if the average soil moisture content is greater than or equal to the preset minimum soil moisture threshold and the average soil moisture content is less than the preset maximum soil moisture threshold, it is determined that the soil moisture evaluation passes; if the soil temperature evaluation passes and the soil moisture evaluation passes, the evaluation result of the snow enhancement ground conditions corresponding to the corresponding area to be evaluated is determined as passing.

[0057] In some embodiments, the executing entity first uses a GIS tool to obtain a group of farmland coordinates, which are multiple boundary coordinates of each farmland area, from the farmland distribution map of the target snow augmentation area. For each farmland coordinate in the group of farmland coordinates, multiple soil temperatures and multiple soil moisture contents corresponding to each farmland coordinate are obtained. Specifically, in the farmland area corresponding to each farmland coordinate, multiple edge monitoring points and multiple non-edge monitoring points are set, and soil temperature and soil moisture content are monitored at the multiple edge monitoring points and the multiple non-edge monitoring points to obtain multiple soil temperatures and multiple soil moisture contents. Subsequently, mean operations are respectively performed on the multiple soil temperatures and the multiple soil moisture contents to obtain a mean soil temperature and a mean soil moisture content. Finally, the mean soil temperature is compared with a preset maximum soil temperature threshold value and a preset minimum soil temperature threshold value; if the mean soil temperature is greater than or equal to the preset minimum soil temperature threshold value and less than the preset maximum soil temperature threshold value, it is determined that the soil temperature evaluation result passes; the mean soil moisture content is compared with a preset maximum soil moisture content threshold value and a preset minimum soil moisture content threshold value; if the mean soil moisture content is greater than or equal to the preset minimum soil moisture content threshold value and less than the preset maximum soil moisture content threshold value, it is determined that the soil moisture content evaluation result passes; if the soil temperature evaluation result passes and the soil moisture content evaluation result passes, the snow augmentation ground condition evaluation result corresponding to the corresponding area to be evaluated is determined to pass the evaluation.

[0058] In practice, the GIS tool can be ArcGIS. A thermistor sensor can be used to measure the soil temperature, and a frequency domain reflectometry sensor can be used to measure the soil moisture content. The preset maximum soil temperature threshold value can be 5°C, the preset minimum soil temperature threshold value can be -5°C, the preset maximum soil moisture content threshold value can be 20%, and the preset minimum soil moisture content threshold value can be 15%. Among them, a thermistor is a sensitive element whose resistance value changes significantly with temperature. In practice, by burying the thermistor in the soil, the soil temperature is obtained by measuring its resistance value. Frequency domain reflectometry is a technique that uses the difference in the propagation characteristics of electromagnetic waves in different media to measure the characteristics of substances. In practice, the soil moisture content is deduced by measuring the dielectric constant of the soil.

[0059] The target meteorological radar data also includes a spectrum width map; the catalyst delivery plan includes at least one catalyst delivery sub-plan, and the catalyst delivery sub-plan is determined through the following steps: Step 1, determine the target delivery location according to the catalyst delivery area and the spectrum width map.

[0060] In some embodiments, the execution entity determines the target delivery location by jointly analyzing the catalyst delivery area and the spectral width map. Specifically, first, the vector data of the catalyst delivery area and the raster data of the spectral width map are imported using a GIS tool, and alignment and projection processing are performed under the same geographic coordinate system. Subsequently, the GIS tool superimposes the spatial ranges of the two types of data. For each pixel in the superimposed area, the corresponding spectral width value is extracted, and the areas with higher spectral width values are selected by combining the position range of the catalyst delivery area. Finally, these areas are selected as the target delivery locations. In practice, the GIS tool can be ArcGIS. Vector data is a data format used in geographic information systems to represent spatial features. A pixel is the basic unit of raster data and is used to represent a small area in the geographic space. Raster data is a spatial data format based on a grid structure and is used to represent continuous geographic information.

[0061] Step 2: Obtain a group of farmland information from the farmland distribution map of the target snow enhancement area; each piece of farmland information in the group of farmland information includes the type of crop, sowing date, estimated harvest date, and farmland terrain category; according to the type of crop, obtain the snow requirement level of the crop through a preset crop information table, and the snow requirement level of the crop includes low, medium, or high; if the snow requirement level of the crop is medium or high, then obtain the cold tolerance level of the crop according to the type of crop and the preset crop information table; determine the catalyst delivery method according to the farmland terrain category and the preset catalyst delivery method table; determine the catalyst delivery sub-scheme through the target delivery location, the cold tolerance level of the crop, the preset catalyst adjustment table, and the catalyst delivery method.

[0062] In some embodiments, the target meteorological radar data also includes a spectral width map. The execution entity extracts the coordinate information of each farmland area from the farmland distribution map of the target snow enhancement area through a GIS tool, and according to this coordinate information, obtains the farmland information of each farmland area from the database storing farmland distribution information, thus obtaining a group of farmland information. The farmland information includes the type of crop, sowing date, estimated harvest date, and farmland terrain category. Subsequently, according to the type of crop, obtain the snow requirement level of the crop from the preset crop information table. The snow requirement level of the crop includes low, medium, or high. Then, judge the snow requirement level of the crop. If the snow requirement level of the crop is medium or high, then obtain the cold tolerance level of the crop from the preset crop information table according to the type of crop. Then, obtain the corresponding catalyst delivery method from the preset catalyst delivery method table according to the crop terrain category. Finally, obtain the catalyst delivery sub-scheme through the target delivery location, the cold tolerance level of the crop, and the catalyst delivery method in combination with the preset catalyst adjustment table.

[0063] In practice, the crop type may be winter wheat. The farmland terrain category may be a plain. The preset crop information table is a preset information table, and the corresponding crop snow requirement level and crop cold resistance level can be obtained through the crop type. The crop snow requirement level includes low, medium or high. The crop cold resistance level includes low, medium or high. The preset catalyst delivery method table is a preset information table, and the corresponding catalyst delivery method can be obtained through the crop terrain category. The catalyst delivery method may be aircraft seeding, anti-aircraft gun seeding or ground smoke burning. The preset catalyst adjustment table is a preset information table, including the snow requirement level in the growth stage, the cold resistance level in the growth stage and the catalyst delivery amount adjustment amount, and the catalyst delivery amount can be adjusted according to the different growth stages of different crops. Among them, aircraft seeding refers to a method of using an aircraft as a carrier, carrying a catalyst seeding device, and performing artificial snowmaking operations in the cloud layer. Anti-aircraft gun seeding refers to a method of using a ground launch device such as an anti-aircraft gun to launch a projectile loaded with a catalyst into the cloud layer for artificial snowmaking operations. Ground smoke burning refers to a method of setting up a combustion furnace or combustion device on the ground to transport the smoke produced by catalyst combustion into the clouds for artificial snowmaking operations.

[0064] Among them, a method for controlling artificial snowmaking operations based on meteorological radar data also includes: Step 1, obtain the current date; if the current date is later than or equal to the sowing date, and the current date is earlier than the estimated harvest date, then according to the current date and the sowing date, obtain the corresponding growing days of the crop type; according to the crop type, growing days and the preset crop information table, determine the corresponding growth stage of the crop type.

[0065] In some embodiments, the execution subject first obtains the current date by calling the system's time service, and compares the current date with the sowing date. If the current date is later than or equal to the sowing date, and the current date is earlier than the estimated harvest date, the current date and the sowing date are subtracted to obtain the number of growing days corresponding to the crop type. Subsequently, according to the crop type and the number of growing days, the growth stage corresponding to the crop type is queried from the preset crop information table.

[0066] In practice, the sowing date can be January 1st, the current date can be January 5th, and the harvest date can be July 10th. The current date is later than the sowing date and earlier than the harvest date. By calculating the difference between the current date and the sowing date, the number of growing days is obtained as 4 days, and the corresponding growth stage can be the emergence stage. The preset crop information table is a preset information table, including crop types, growth stages, and the range of growth days for each stage. The corresponding growth stage can be obtained from the preset crop information table based on the crop type and the number of growth days. Among them, the number of growth days refers to the number of days elapsed from the sowing or transplanting of the crop to a specific date. The growth stage refers to the different developmental periods experienced by the crop during its life cycle, and each period has specific morphological characteristics and physiological activities. The emergence stage is the stage when the crop seedlings break through the soil.

[0067] Step 2: According to the crop type, growth stage, and the preset crop growth stage information table, obtain the snow requirement level and cold tolerance level corresponding to the growth stage of the crop type; generate an adjustment plan for the growth stage of the farmland area corresponding to the crop type based on the snow requirement level and cold tolerance level of the growth stage and the preset catalyst adjustment table; send the growth stage adjustment plan to the corresponding processing terminal.

[0068] In some embodiments, the execution entity first queries the snow requirement level and cold tolerance level corresponding to the current growth stage of the crop type from the preset crop growth stage information table through the crop type and growth stage. Subsequently, according to the snow requirement level and cold tolerance level of the growth stage, query the catalyst adjustment information from the preset catalyst adjustment table, determine the queried catalyst adjustment information as the growth stage adjustment plan, and send the growth stage adjustment plan to the corresponding processing terminal.

[0069] In practice, the snow requirement level during the growth stage can be high, medium, or low. The cold tolerance level during the growth stage can be high, medium, or low. Crops have different cold tolerance capabilities and snow requirement levels at different growth stages. For example, during the overwintering period of winter wheat, sufficient snow cover can significantly increase the ground temperature and ensure safe overwintering, so the corresponding snow requirement level during the growth stage is high, and the cold tolerance level during the growth stage is high; during the jointing stage of winter wheat, the cold resistance of the plants decreases, and the demand for snow is relatively low. Excessive snow will cause diseases, so the corresponding snow requirement level during the growth stage is low, and the cold tolerance level during the growth stage is medium. The preset catalyst adjustment table is a preset information table, including the snow requirement level during the growth stage, the cold tolerance level during the growth stage, and the adjustment amount of catalyst dosage. The corresponding adjustment amount of catalyst dosage can be determined by the snow requirement level during the growth stage and the cold tolerance level during the growth stage. For example, when the snow requirement level during the growth stage is medium and the cold tolerance level during the growth stage is medium, the corresponding adjustment amount of catalyst dosage can be a 15% reduction. The processing terminal can be a server. Among them, the overwintering period refers to the period when some winter crops basically stop growing and enter a dormant or semi-dormant state under low winter temperatures. The jointing stage refers to the period when the stems of gramineous crops begin to elongate rapidly during the growth process. Gramineous crops are an important category of herbaceous plants, referring to crops whose fruits are grains or seeds that can be used as food or feed, such as rice, wheat, corn, sorghum, barley, oats, millet, etc.

[0070] Among them, an artificial weather modification snow enhancement operation control method based on meteorological radar data further includes: Step 1, obtain multiple soil water contents before snow enhancement, multiple soil water contents after snow enhancement, and multiple snow depths corresponding to the farmland coordinate group; obtain the average soil water content before snow enhancement according to the multiple soil water contents before snow enhancement, and obtain the average soil water content after snow enhancement according to the multiple soil water contents after snow enhancement; obtain the average snow depth according to the multiple snow depths; obtain the soil water content increment according to the average soil water content before snow enhancement and the average soil water content after snow enhancement.

[0071] In some embodiments, the execution entity first calculates multiple soil water contents before snow enhancement, multiple soil water contents after snow enhancement, and multiple snow depths corresponding to the farmland coordinate group. Subsequently, perform an average operation on the multiple soil water contents before snow enhancement to obtain the average soil water content before snow enhancement; perform an average operation on the multiple soil water contents after snow enhancement to obtain the average soil water content after snow enhancement; perform an average operation on the multiple snow depths to obtain the average snow depth. Then, perform a difference operation on the average soil water content after snow enhancement and the average soil water content before snow enhancement, and perform a ratio operation on the result of the difference operation and the average soil water content before snow enhancement to obtain the soil water content increment.

[0072] In practice, the soil water content can be measured by using a TDR sensor, and the snow depth can be measured by using an ultrasonic snow depth sensor. Among them, the TDR sensor is a sensor that measures the characteristics of a medium using time domain reflectometry technology. In soil moisture measurement, it determines the dielectric constant of the soil by measuring the time for an electromagnetic wave pulse to propagate in the soil and the reflected waveform, and then calculates the soil water content. The ultrasonic snow depth sensor is a device that measures the distance from the snow surface to the sensor using ultrasonic waves. Time domain reflectometry is a technology for measuring the propagation characteristics of a signal in a transmission line or other medium. It analyzes the characteristics of the medium by transmitting a rapidly rising electrical pulse and measuring the reflected signal encountered by the pulse during transmission. The dielectric constant is a physical quantity that measures the ability of a substance to store electric field energy.

[0073] Step 2: Obtain the soil water content increment evaluation result corresponding to the soil water content increment and the snow depth evaluation result corresponding to the average snow depth; if the soil water content increment evaluation result indicates a low increment or the snow depth evaluation result indicates a shallow depth, generate the first catalyst dosage feedback information; if the soil water content increment evaluation result indicates a high or relatively high increment or the snow depth evaluation result indicates a deep or relatively deep depth, generate the second catalyst dosage feedback information; if the soil water content increment evaluation result indicates a low increment or the snow depth evaluation result indicates a shallow depth, generate the third catalyst dosage feedback information; send the first catalyst dosage feedback information or the second catalyst dosage feedback information or the third catalyst dosage feedback information to the corresponding feedback terminal.

[0074] In some embodiments, the execution entity first calculates the soil water content increment evaluation result corresponding to the soil water content increment and the snow depth evaluation result corresponding to the average snow depth. If the soil water content increment evaluation result is a low increment or the snow depth evaluation result is a shallow depth, generate the first catalyst dosage feedback information; if the soil water content increment evaluation result is a high or relatively high increment or the snow depth evaluation result is a deep or relatively deep depth, generate the second catalyst dosage feedback information; if the soil water content increment evaluation result is a low increment or the snow depth evaluation result is a shallow depth, generate the third catalyst dosage feedback information. Finally, send the first catalyst dosage feedback information or the second catalyst dosage feedback information or the third catalyst dosage feedback information to the corresponding feedback terminal.

[0075] In practice, the first catalyst dosage feedback information can be an increase in the catalyst dosage by 15%; the second catalyst dosage feedback information can be a decrease in the catalyst dosage by 25%; the third catalyst dosage feedback information can be an increase in the catalyst dosage by 25%.

[0076] The evaluation results of soil water content increment and snow depth are determined through the following steps: Step 1: Compare the soil water content increment with a preset group of critical values of soil water content increment. The preset group of critical values of soil water content increment includes a first critical value of soil water content increment, a second critical value of soil water content increment, a third critical value of soil water content increment, and a fourth critical value of soil water content increment.

[0077] In some embodiments, the execution subject compares the soil water content increment with each critical value of soil water content increment in the preset group of critical values of soil water content increment. The preset group of critical values of soil water content increment includes a first critical value of soil water content increment, a second critical value of soil water content increment, a third critical value of soil water content increment, and a fourth critical value of soil water content increment.

[0078] In practice, the first critical value of soil water content increment is the minimum threshold of soil water content increment, and the fourth critical value of soil water content increment is the maximum threshold of soil water content increment. The first critical value of soil water content increment can be 3%, the second critical value of soil water content increment can be 7%, the third critical value of soil water content increment can be 12%, and the fourth critical value of soil water content increment can be 15%.

[0079] Step 2: If the soil water content increment is less than the first critical value of soil water content increment, it is determined that the increment is low; if the soil water content increment is greater than or equal to the first critical value of soil water content increment and less than the second critical value of soil water content increment, it is determined that the increment is relatively low; if the soil water content increment is greater than or equal to the second critical value of soil water content increment and less than the third critical value of soil water content increment, it is determined that the increment is moderate; if the soil water content increment is greater than or equal to the third critical value of soil water content increment and less than the fourth critical value of soil water content increment, it is determined that the increment is relatively high; if the soil water content increment is greater than or equal to the fourth critical value of soil water content increment, it is determined that the increment is high.

[0080] In some embodiments, the executing entity compares the soil water content increment with each soil water content increment critical value in the preset soil water content increment critical value group. If the soil water content increment is less than the first soil water content increment critical value, it is determined that the evaluation result of the soil water content increment is low; if the soil water content increment is greater than or equal to the first soil water content increment critical value and less than the second soil water content increment critical value, it is determined that the evaluation result of the soil water content increment is relatively low; if the soil water content increment is greater than or equal to the second soil water content increment critical value and less than the third soil water content increment critical value, it is determined that the evaluation result of the soil water content increment is moderate; if the soil water content increment is greater than or equal to the third soil water content increment critical value and less than the fourth soil water content increment critical value, it is determined that the evaluation result of the soil water content increment is relatively high; if the soil water content increment is greater than or equal to the fourth soil water content increment critical value, it is determined that the evaluation result of the soil water content increment is high.

[0081] In practice, the use of the preset soil water content increment critical value group for multi-interval fuzzy matching determination, rather than conventional binary value determination, can more precisely and accurately reflect the actual change of the soil water content increment. Among them, fuzzy matching is a matching method that allows a certain degree of difference between the input data and the target data. Unlike exact matching, it does not require complete consistency, but judges whether to match according to a certain similarity or distance metric. Binary value matching is a matching method that requires the input data to be exactly the same as the target data. Only when the input data is exactly the same as the target data is it considered a match, otherwise it is considered a mismatch.

[0082] Step 3: Compare the snow depth with the preset snow depth increment critical value group, which includes the first snow depth increment critical value, the second snow depth increment critical value, the third snow depth increment critical value, and the fourth snow depth increment critical value.

[0083] In some embodiments, the executing entity compares the snow depth with each snow depth increment critical value in the preset snow depth increment critical value group. The preset snow depth increment critical value group includes the first snow depth increment critical value, the second snow depth increment critical value, the third snow depth increment critical value, and the fourth snow depth increment critical value.

[0084] In practice, the first snow depth increment critical value is the minimum threshold of the snow depth increment, and the fourth snow depth increment critical value is the maximum threshold of the snow depth increment critical value. The first snow depth increment critical value can be 2 cm, the second snow depth increment critical value can be 5 cm, the third snow depth increment critical value can be 10 cm, and the fourth snow depth increment critical value can be 15 cm.

[0085] Step 4: If the snow depth increment is less than the first snow depth increment critical value, it is determined that the increment is relatively shallow; if the snow depth increment is greater than or equal to the first snow depth increment critical value and less than the second snow depth increment critical value, it is determined that the increment is moderately shallow; if the snow depth increment is greater than or equal to the second snow depth increment critical value and less than the third snow depth increment critical value, it is determined that the increment is moderate; if the snow depth increment is greater than or equal to the third snow depth increment critical value and less than the fourth snow depth increment critical value, it is determined that the increment is relatively deep; if the snow depth increment is greater than or equal to the fourth snow depth increment critical value, it is determined that the increment is extremely deep.

[0086] In some embodiments, the execution entity compares the snow depth increment with each snow depth increment critical value in the preset snow depth increment critical value group. If the snow depth increment is less than the first snow depth increment critical value, it is determined that the evaluation result of the snow depth increment is relatively shallow; if the snow depth increment is greater than or equal to the first snow depth increment critical value and less than the second snow depth increment critical value, it is determined that the evaluation result of the snow depth increment is moderately shallow; if the snow depth increment is greater than or equal to the second snow depth increment critical value and less than the third snow depth increment critical value, it is determined that the evaluation result of the snow depth increment is moderate; if the snow depth increment is greater than or equal to the third snow depth increment critical value and less than the fourth snow depth increment critical value, it is determined that the evaluation result of the snow depth increment is relatively deep; if the snow depth increment is greater than or equal to the fourth snow depth increment critical value, it is determined that the evaluation result of the snow depth increment is extremely deep.

[0087] In these embodiments, the problems of single catalyst delivery scheme and insufficient feedback mechanism in the prior art are effectively overcome, and the accuracy and effectiveness of snow enhancement operations are significantly improved. Specifically, by performing differential catalyst delivery according to the growth stage of crops, unnecessary resource waste and negative impacts on crop growth are avoided; at the same time, by establishing a feedback mechanism for snow enhancement effects and comprehensively evaluating in combination with meteorological and ground information, timely adjustment of the catalyst delivery amount is achieved, the stability and pertinence of snow enhancement effects are improved, and good moisture conditions are provided for crop growth.

[0088] In some embodiments, in order to further solve Technical Problem 3 described in the background art section, that is, "in the prior art, artificial snow enhancement operations usually rely on a single radar station. When the radar station migrates or the coverage area is insufficient, effective data cannot be obtained in time, which in turn affects the decision-making and implementation efficiency of artificial snow enhancement operations", in some embodiments of the present invention, a method for controlling artificial weather modification snow enhancement operations based on meteorological radar data further includes: Step 1, obtain multiple boundary coordinates corresponding to the position information of the target snow enhancement area to obtain a target snow enhancement area boundary coordinate group; convert each boundary coordinate in the target snow enhancement area boundary coordinate group to a radar echo map, and determine the proportion of the overlapping area in the radar echo map.

[0089] In some embodiments, the execution entity first obtains the corresponding administrative division code according to the position information of the target snow enhancement area, and queries the boundary data corresponding to the position information of the target snow enhancement area from the database storing geographic information data through the administrative division code, and extracts multiple boundary coordinates from the boundary data to obtain a target snow enhancement area boundary coordinate group. Subsequently, for each boundary coordinate in the target snow enhancement area boundary coordinate group, perform coordinate system conversion in combination with the radar echo map to obtain the converted radar echo map. Subsequently, calculate the proportion of the overlapping area of the area formed by the boundary coordinates in the converted radar echo map to obtain the proportion of the overlapping area.

[0090] In practice, the coordinate system conversion method can be to convert the geographic coordinate system to the radar polar coordinate system. Specifically, first convert the boundary coordinates of the target snow enhancement area to the geocentric coordinate system, then calculate the corresponding geocentric coordinates of the meteorological radar according to the longitude, latitude and altitude of the target meteorological radar, then calculate the azimuth, elevation angle and distance of the boundary coordinates of the target snow enhancement area relative to the radar station, and finally complete the coordinate system conversion in combination with the Python library. Among them, the Python library can be Pyproj. The geographic coordinate system uses longitude and latitude to define the position of points on the earth's surface. Longitude is the angular distance relative to the prime meridian, and latitude is the angular distance relative to the equator. The radar polar coordinate system is a polar coordinate system with the radar station as the origin, and uses distance or distance library and azimuth to define the position of the target. The geocentric coordinate system is a rectangular coordinate system with the earth's centroid as the origin, and uses the three coordinate axes X, Y, and Z to define the position of points in space. The azimuth angle is the angle rotated clockwise from the reference direction (usually the due north direction) to the target direction on the horizontal plane. The elevation angle is the angle of the target relative to the horizontal plane. Pyproj is a Python library for map projection and coordinate conversion.

[0091] Step 2, if the proportion of the overlapping area is less than or equal to the preset overlapping area proportion threshold, obtain multiple adjacent area information adjacent to the target snow enhancement area; obtain multiple candidate meteorological radar numbers according to the multiple adjacent area information; obtain multiple candidate radar echo maps corresponding to the multiple candidate meteorological radar numbers; convert each boundary coordinate in the target snow enhancement area boundary coordinate group to the multiple candidate radar echo maps, and screen out the candidate radar echo maps with the proportion of the overlapping area greater than the preset overlapping area proportion threshold to obtain a candidate radar echo map group.

[0092] In some embodiments, the executing entity first compares the overlapping area ratio with a preset overlapping area ratio threshold. If the overlapping area ratio is less than or equal to the preset overlapping area ratio threshold, it obtains the adjacent administrative division codes corresponding to multiple areas adjacent to the target snow enhancement area according to the administrative division code corresponding to the target snow enhancement area and the GIS tool, and obtains multiple adjacent area information based on the adjacent administrative division codes. Each piece of adjacent area information in the multiple adjacent area information corresponds to a secondary selected weather radar number, obtaining multiple secondary selected weather radar numbers. Then, the executing entity establishes a communication connection with the weather station corresponding to each secondary selected weather radar number among the multiple secondary selected weather radar numbers, and obtains the corresponding secondary selected weather radar data according to the corresponding secondary selected weather radar number, and extracts data from the secondary selected weather radar data to obtain a secondary selected radar echo map. Subsequently, each boundary coordinate in the target snow enhancement area boundary coordinate group is converted to the multiple secondary selected radar echo maps, obtaining multiple converted secondary selected radar echo maps, and screening the secondary selected radar echo maps with an overlapping area ratio greater than the preset overlapping area ratio threshold from them, obtaining a secondary selected radar echo map group. Among them, the GIS tool can be ArcGIS. The preset overlapping area ratio can be 90%. The secondary selected radar echo map refers to the echo map obtained from the secondary selected weather radar in the adjacent area because the overlapping area ratio of the currently used main radar echo map in the target snow enhancement area does not reach the preset overlapping area ratio threshold.

[0093] Step 3: Obtain the secondary selected center coordinates corresponding to each secondary selected radar echo map in the secondary selected radar echo group; obtain the target snow enhancement area center coordinates corresponding to the target snow enhancement area location information; obtain multiple center distances according to the target snow enhancement area center coordinates and the multiple secondary selected center coordinates; screen the multiple center distances, obtain the secondary selected weather radar number corresponding to the shortest center distance, and determine it as the secondary selected target weather radar.

[0094] In some embodiments, the executing entity first obtains the secondary selected center coordinates corresponding to each secondary selected radar echo map in the secondary selected radar echo group through the GIS tool, and obtains the target snow enhancement area center coordinates corresponding to the target snow enhancement area location information through the GIS tool. Subsequently, calculate the distances between the target snow enhancement area center coordinates and the multiple secondary selected center coordinates, obtaining multiple center distances. Finally, screen the multiple center distances, and determine the secondary selected weather radar number corresponding to the shortest center distance as the secondary selected target weather radar. Among them, the GIS tool can be ArcGIS.

[0095] In these embodiments, through the method of selecting backup radars based on the proportion of overlapping areas, the problem of data loss in existing artificial snow enhancement operations caused by the failure or insufficient coverage of a single radar station is effectively solved, and the reliability of artificial snow enhancement operations is improved. Specifically, by calculating the proportion of the overlapping area between the target snow enhancement area and the monitoring range of the alternative radars, the best backup radar is selected. This avoids the deficiencies of traditional methods that only rely on distance or adjacency relationships to select backup radars, and adopts an efficient coordinate conversion method to meet the real-time requirements of artificial snow enhancement operations, improving the decision-making speed and implementation efficiency of artificial snow enhancement operations.

[0096] The above description is only some preferred embodiments of the present invention and an explanation of the technical principles applied. Those skilled in the art should understand that the scope of the invention involved in the present invention is not limited to the technical solutions formed by the specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the above inventive concept. For example, the technical solutions formed by mutually replacing the above features with the (but not limited to) technical features with similar functions disclosed in the present invention.

Claims

1. A method for controlling artificial snowmaking operations based on weather radar data, characterized in that: include: Obtain the farmland distribution map and location information of the target snow-increasing area; Determine the target weather radar number according to the target snow-increasing area location information; Acquire target weather radar data corresponding to the target weather radar number; the target weather radar data includes a radar echo map and a radial velocity map; Mapping multiple farmland areas in the farmland distribution map of the target snow-increasing area to the radar echo map to obtain a mapped radar echo map, wherein the mapped radar echo map includes multiple mapped farmland areas; determining whether each echo area in the mapped radar echo map is covered by the mapped farmland area to obtain a covered area group and an uncovered area group; Acquire sounding balloon data corresponding to the location information of the target snow-increasing area, the sounding balloon data including a temperature profile, a humidity profile and a wind direction profile; determine the wind direction of each uncovered area in the uncovered area group according to the wind direction profile and the radial velocity map; according to the farmland distribution map of the target snow-increasing area and the wind direction, screen the uncovered areas from the uncovered area group whose wind direction points to any farmland in the farmland distribution map of the target snow-increasing area and whose distance to the farmland is less than or equal to a preset distance threshold, to obtain a secondary selected area group, and form an area group to be evaluated together with the covered area group; Obtaining snow-enhancing cloud layer condition assessment results and snow-enhancing ground condition assessment results corresponding to each area to be assessed in the group of areas to be assessed and determining a catalyst placement area; An artificial snowmaking plan is generated according to the catalyst placement area and the catalyst placement plan corresponding to the catalyst placement area.

2. The method for controlling artificial snowmaking operations based on weather radar data according to claim 1 is characterized in that: The snow-enhancing cloud condition assessment result corresponding to each area to be assessed is determined by the following steps: Obtaining a radar vertical profile corresponding to the radar echo map; determining the cloud type corresponding to each area to be evaluated according to the radar echo map and the radar vertical profile map; If the cloud type meets the preset snow-increasing cloud type, multiple target height intervals are obtained according to the temperature profile and multiple preset snow-increasing temperature intervals; the cloud base height and cloud top height corresponding to each area to be evaluated are determined according to the radar echo map, the radar vertical profile map and the sounding balloon data; and the cloud thickness corresponding to each area to be evaluated is generated through the cloud base height and the cloud top height; Determine the proportion of supercooled water areas in each target height interval of each area to be evaluated among the multiple target height intervals; determine the target height interval in which the proportion of supercooled water areas is greater than or equal to a preset supercooled water area proportion threshold as an overcooled cloud interval; obtain the proportion of supercooled cloud layers corresponding to each area to be evaluated based on the supercooled cloud interval and the cloud thickness corresponding to each area to be evaluated; if the proportion of supercooled cloud layers is greater than or equal to the preset supercooled cloud layer proportion threshold, determine the snow enhancement cloud condition assessment result corresponding to the corresponding area to be evaluated as passed.

3. The method for controlling artificial snowmaking operations based on weather radar data according to claim 2 is characterized in that: The supercooled water area ratio is determined by the following steps: Acquire a meteorological radar polarization type corresponding to the target meteorological radar number, wherein the meteorological radar polarization type includes a dual polarization radar or a single polarization radar; the target meteorological radar data includes a plurality of radar detection data corresponding to a plurality of radar detection units, wherein the radar detection units correspond to the radar detection data one by one; For each radar detection unit, if the polarization type of the meteorological radar is a dual-polarization radar, a differential reflectivity and a correlation coefficient are extracted from the corresponding radar detection data; if the differential reflectivity is greater than or equal to a preset differential reflectivity threshold, and the correlation coefficient is greater than or equal to a preset correlation coefficient threshold, it is determined that there is a supercooled water area in the corresponding radar detection unit; radar detection units with supercooled water areas are screened from multiple radar detection units to obtain multiple radar detection units with supercooled water areas; the thickness of multiple radar detection units with supercooled water areas is obtained; the ratio of the sum of the thickness of multiple radar detection units with supercooled water areas to the cloud thickness of the corresponding area to be evaluated is obtained to obtain the first supercooled water area proportion; If the polarization type of the meteorological radar is a single polarization radar, the echo intensity corresponding to each target height interval and the humidity corresponding to the humidity profile are obtained; if the echo intensity is greater than or equal to a preset echo intensity threshold, and the humidity is greater than or equal to a preset humidity threshold, the corresponding target height interval is determined as a supercooled water area; the ratio of the sum of the thickness of the target height interval where the supercooled water area exists to the cloud thickness of the corresponding area to be evaluated is obtained to obtain the proportion of the second supercooled water area; The first supercooled water region proportion or the second supercooled water region proportion is determined as the supercooled water region proportion.

4. The method for controlling artificial snowmaking operations based on weather radar data according to claim 1, characterized in that: The snow-increasing ground condition assessment result corresponding to each area to be assessed is determined by the following steps: According to the farmland distribution map of the target snow-increasing area, a farmland coordinate group is obtained; multiple soil temperatures and multiple soil moisture conditions corresponding to each farmland coordinate in the farmland coordinate group are obtained; according to the multiple soil temperatures, a soil temperature average is obtained; according to the multiple soil moisture conditions, a soil moisture average is obtained; the soil temperature average and a preset soil temperature maximum threshold are compared with a preset soil temperature minimum threshold; if the soil temperature average is greater than or equal to the preset soil temperature minimum threshold, and the soil temperature average is less than the preset soil temperature maximum threshold, then the soil temperature assessment is determined to be passed; the soil moisture average and the preset soil moisture maximum threshold are compared with the preset soil moisture minimum threshold; if the soil moisture average is greater than or equal to the preset soil moisture minimum threshold, and the soil moisture average is less than the preset soil moisture maximum threshold, then the soil moisture assessment is determined to be passed; if the soil temperature assessment is passed and the soil moisture assessment is passed, the snow-increasing ground condition assessment result corresponding to the corresponding area to be assessed is determined to be assessed as passed.

5. The method for controlling artificial snowmaking operations based on weather radar data according to claim 2 is characterized in that: The target weather radar data also includes a spectrum width diagram; the catalyst placement scheme includes at least one catalyst placement sub-scheme, and the catalyst placement sub-scheme is determined by the following steps: Determining a target delivery location according to the catalyst delivery area and the spectrum width graph; A farmland information group is obtained from the farmland distribution map of the target snow-increasing area; each farmland information in the farmland information group includes crop type, sowing date, estimated harvest date and farmland terrain category; according to the crop type, the crop snow requirement level is obtained through a preset crop information table, and the crop snow requirement level includes low, medium or high; if the crop snow requirement level is medium or high, the crop cold resistance level is obtained according to the crop type and the preset crop information table; the catalyst placement method is determined according to the farmland terrain category and the preset catalyst placement method table; the catalyst placement sub-scheme is determined through the target placement location, the crop cold resistance level, the preset catalyst adjustment table and the catalyst placement method.

6. The method for controlling artificial snowmaking operations based on weather radar data according to claim 5 is characterized in that: Also includes: Obtain the current date; if the current date is later than or equal to the sowing date, and the current date is earlier than the estimated harvest date, obtain the number of growing days corresponding to the crop type according to the current date and the sowing date; determine the growth stage corresponding to the crop type according to the crop type, the number of growing days and the preset crop information table; According to the crop type, the growth stage and the preset crop growth stage information table, the growth stage snow requirement level and the growth stage cold resistance level corresponding to the crop type at the growth stage are obtained; according to the growth stage snow requirement level, the growth stage cold resistance level and the preset catalyst adjustment table, a growth stage adjustment plan for the farmland area corresponding to the crop type is generated; and the growth stage adjustment plan is sent to the corresponding processing terminal.

7. The method for controlling artificial snowmaking operations based on weather radar data according to claim 4, characterized in that: Also includes: Obtain multiple soil moisture contents before snowing, multiple soil moisture contents after snowing, and multiple snow depths corresponding to the farmland coordinate group; obtain an average soil moisture content before snowing according to the multiple soil moisture contents before snowing, and obtain an average soil moisture content after snowing according to the multiple soil moisture contents after snowing; obtain an average snow depth according to the multiple snow depths; obtain a soil moisture increment according to the average soil moisture content before snowing and the average soil moisture content after snowing; Obtaining a soil moisture increment assessment result corresponding to the soil moisture increment, and obtaining a snow depth assessment result corresponding to the snow depth mean; If the soil moisture increment assessment result indicates that the increment is low, or the snow depth assessment result indicates that the depth is shallow, then first catalyst delivery amount feedback information is generated; If the soil moisture increment assessment result indicates that the increment is too high or the increment is relatively high, or the snow depth assessment result indicates that the depth is too deep or the depth is relatively deep, then second catalyst delivery amount feedback information is generated; If the soil moisture increment assessment result indicates that the increment is too low, or the snow depth assessment result indicates that the depth is too shallow, a third catalyst dosage feedback information is generated; the first catalyst dosage feedback information or the second catalyst dosage feedback information or the third catalyst dosage feedback information is sent to the corresponding feedback terminal.

8. The method for controlling artificial snowmaking operations based on weather radar data according to claim 7 is characterized in that: The soil moisture increment assessment result and the snow depth assessment result are determined by the following steps: Comparing the soil moisture increment with a preset soil moisture increment critical value group, wherein the preset soil moisture increment critical value group includes a first soil moisture increment critical value, a second soil moisture increment critical value, a third soil moisture increment critical value, and a fourth soil moisture increment critical value; If the soil moisture increment is less than the first soil moisture increment critical value, the increment is determined to be low; if the soil moisture increment is greater than or equal to the first soil moisture increment critical value and the soil moisture increment is less than the second soil moisture increment critical value, the increment is determined to be low; if the soil moisture increment is greater than or equal to the second soil moisture increment critical value and the soil moisture increment is less than the third soil moisture increment critical value, the increment is determined to be moderate; if the soil moisture increment is greater than or equal to the third soil moisture increment critical value and the soil moisture increment is less than the fourth soil moisture increment critical value, the increment is determined to be high; if the soil moisture increment is greater than or equal to the fourth soil moisture increment critical value, the increment is determined to be high; Comparing the snow depth with a preset snow depth increment critical value group, wherein the preset snow depth increment critical value group includes a first snow depth increment critical value, a second snow depth increment critical value, a third snow depth increment critical value, and a fourth snow depth increment critical value; If the snow depth increment is less than the first snow depth increment critical value, the increment is determined to be shallow; if the snow depth increment is greater than or equal to the first snow depth increment critical value and the snow depth increment is less than the second snow depth increment critical value, the increment is determined to be shallow; if the snow depth increment is greater than or equal to the second snow depth increment critical value and the snow depth increment is less than the third snow depth increment critical value, the increment is determined to be moderate; if the snow depth increment is greater than or equal to the third snow depth increment critical value and the snow depth increment is less than the fourth snow depth increment critical value, the increment is determined to be deep; if the snow depth increment is greater than or equal to the fourth snow depth increment critical value, the increment is determined to be deep.

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