A control method for artificial snowmaking operations based on meteorological radar data

Abstract

The present invention relates to the field of artificial weather modification operations and discloses a method for controlling artificial snow enhancement operations based on meteorological radar data, comprising: obtaining a farmland distribution map and location information of a target snow enhancement area; determining the target meteorological radar number and obtaining radar data; mapping the farmland distribution map to a radar echo map and dividing covered and uncovered areas; obtaining sounding balloon data; screening uncovered areas pointing toward farmland as secondary selected areas based on wind direction and radial velocity maps; forming a group of areas to be evaluated by combining the covered and secondary selected areas; evaluating the snow enhancement cloud layer and ground conditions in the area to be evaluated; determining an area that meets both cloud layer and ground conditions as a catalyst placement area; obtaining a catalyst placement plan and generating an artificial snow enhancement plan. Thus, a method for controlling artificial snow enhancement operations based on meteorological radar data is implemented.

Description

Technical Field

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

[0002] Weather modification, particularly snowmaking, involves artificially intervening in cloud microphysical processes using catalysts (such as silver iodide) at appropriate times and under appropriate cloud conditions to increase snowfall on the ground. This technology has important applications in agricultural production (such as replenishing farmland moisture and increasing crop yields), ecological and environmental protection (such as increasing snow cover in mountainous areas and conserving water resources), and drought relief. Weather radar is a crucial detection tool in snowmaking operations, providing information such as cloud location, intensity, and movement direction, informing operational decisions.

[0003] The existing snow enhancement operations, especially the decision-making and implementation of catalyst deployment based on weather radar data, often encounter the following technical problems:

[0004] First, existing technologies typically assess and make decisions about artificial snowmaking operations based on broad meteorological conditions. This lacks detailed analysis of the target snowmaking area, leading to inaccurate selection of catalyst deployment areas and a failure to fully consider the actual needs and ground conditions of the target area. This in turn leads to low catalyst utilization efficiency, unstable snowmaking results, and even potential adverse effects on agricultural production.

[0005] Second, existing technologies typically use a standardized catalyst application schedule for artificial snowmaking operations, lacking tailored adjustments for different crop growth stages. This can lead to catalyst application during periods when snowmaking is unnecessary or unsuitable, resulting in wasted resources and impacting crop growth. Furthermore, snowmaking evaluations lack an effective feedback mechanism tailored to the environment, preventing timely adjustments to catalyst application based on actual snowmaking results. This results in unstable snowmaking results and makes it difficult to achieve desired yield targets.

[0006] Third, in existing technologies, artificial snowmaking operations usually rely on a single radar station. When the radar station moves or the coverage area is insufficient, it is impossible to obtain effective data in a timely manner, which in turn affects the decision-making and implementation efficiency of artificial snowmaking operations. Summary of the Invention

[0007] This summary is intended to briefly introduce concepts that will be described in detail in the detailed description below. This summary is not intended to identify key features or essential features of the claimed technical solution, nor is it intended to limit the scope of the claimed technical solution.

[0008] The present invention proposes a method for controlling artificial snowmaking operations based on weather radar data to solve one or more of the technical problems mentioned in the above background technology section.

[0009] The present invention provides a method for controlling snowmaking operations based on weather radar data, comprising:

[0010] Obtaining a farmland distribution map and location information of the target snow-increasing area; determining a target weather radar number based on the location information of the target snow-increasing area; obtaining 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;

[0011] Mapping multiple farmland areas in the farmland distribution map of the target snow-increasing area to a 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;

[0012] Acquire sounding balloon data corresponding to the location information of the target snow-increasing area, the sounding balloon data including the temperature profile, humidity profile, and wind direction profile; determine the wind direction of each uncovered area in the uncovered area group based on the wind direction profile and the radial velocity map; based on the farmland distribution map of the target snow-increasing area and the wind direction of each uncovered area in the uncovered area group, screen out 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 from the farmland is less than or equal to a preset distance threshold, to obtain a secondary area group, and form an area group to be evaluated together with the covered area group;

[0013] Obtain the snow-enhancing cloud 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 determine the catalyst deployment area; generate an artificial snowmaking plan based on the catalyst deployment area and the catalyst deployment plan corresponding to the catalyst deployment area.

[0014] Optionally, the snow-enhancing cloud condition assessment results for each area to be assessed are determined by the following steps:

[0015] Obtain the 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;

[0016] 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 and cloud top heights corresponding to each area to be assessed are determined based on the radar echo map, radar vertical profile, and sounding balloon data. The cloud thickness corresponding to each area to be assessed is generated based on the cloud base and cloud top heights.

[0017] Determine the proportion of supercooled water areas in each target height interval of each area to be evaluated in multiple target height intervals; determine the target height interval in which the proportion of supercooled water areas is greater than or equal to the preset supercooled water area proportion threshold as the supercooled 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, the snow-enhancing cloud condition assessment result corresponding to the corresponding area to be evaluated is determined to be passed.

[0018] Optionally, the supercooled water area ratio is determined by the following steps:

[0019] Obtaining a meteorological radar polarization type corresponding to a 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 correspond to the radar detection data in a one-to-one manner;

[0020] For each radar detection unit, if the polarization type of the meteorological radar is a dual-polarization radar, the differential reflectivity and the 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 a supercooled water area exists 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 thicknesses of the multiple radar detection units with supercooled water areas are obtained; the ratio of the sum of the thicknesses of the 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;

[0021] If the meteorological radar polarization type is single polarization radar, obtain the echo intensity corresponding to each target altitude 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 the corresponding target altitude interval is determined to be a supercooled water area; obtain the ratio of the sum of the thickness of the target altitude intervals where the supercooled water area exists to the cloud thickness of the corresponding area to be evaluated, and obtain the proportion of the second supercooled water area;

[0022] The first supercooled water region proportion or the second supercooled water region proportion is determined as the supercooled water region proportion.

[0023] Optionally, the snow-enhancing ground condition assessment results corresponding to each area to be assessed are determined by the following steps:

[0024] 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; based on the multiple soil temperatures, a soil temperature average is obtained; based on the multiple soil moisture conditions, a soil moisture average is obtained; the soil temperature average and the preset soil temperature maximum threshold are compared with the 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 passed.

[0025] Optionally, the target weather radar data further includes a spectrum width diagram; the catalyst placement plan includes at least one catalyst placement sub-plan, and the catalyst placement sub-plan is determined by the following steps:

[0026] Determine the target placement location based on the catalyst placement area and spectrum width map;

[0027] 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 the crop type, sowing date, estimated harvest date and farmland terrain category; based on the crop type, the crop snow requirement level is obtained through the 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 based on the crop type and the preset crop information table; the catalyst placement method is determined based on the farmland terrain category and the preset catalyst placement method table; the catalyst placement sub-plan is determined through the target placement location, crop cold resistance level, the preset catalyst adjustment table and the catalyst placement method.

[0028] Optionally, the method for controlling snowmaking operations based on weather radar data of the present invention further includes:

[0029] Get 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 corresponding growing days for the crop type based on the current date and sowing date; determine the corresponding growth stage for the crop type based on the crop type, growing days, and the preset crop information table;

[0030] According to the crop type, 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 in 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.

[0031] Optionally, the method for controlling snowmaking operations based on weather radar data of the present invention further includes:

[0032] 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 based on the multiple soil moisture contents before snowing, obtain an average soil moisture content after snowing based on the multiple soil moisture contents after snowing; obtain an average snow depth based on the multiple snow depths; obtain a soil moisture increment based on the average soil moisture content before snowing and the average soil moisture content after snowing;

[0033] Obtain a soil moisture increment assessment result corresponding to the soil moisture increment, and obtain a snow depth assessment result corresponding to the mean snow depth; if the soil moisture increment assessment result indicates a low increment, or the snow depth assessment result indicates a shallow depth, generate first catalyst delivery amount feedback information; if the soil moisture increment assessment result indicates a high increment or a high increment, or the snow depth assessment result indicates a deep depth or a deep depth, generate second catalyst delivery amount feedback information; if the soil moisture increment assessment result indicates a low increment, or the snow depth assessment result indicates a shallow depth, generate third catalyst delivery amount feedback information; send the first catalyst delivery amount feedback information, the second catalyst delivery amount feedback information, or the third catalyst delivery amount feedback information to the corresponding feedback terminal.

[0034] Optionally, the soil moisture increment assessment result and the snow depth assessment result are determined by the following steps:

[0035] Comparing the soil moisture increment with a preset soil moisture increment critical value group, the preset soil moisture increment critical value group including 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;

[0036] If the soil moisture increment is less than the first soil moisture increment critical value, the increment is judged 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 judged 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 judged 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 judged to be high; if the soil moisture increment is greater than or equal to the fourth soil moisture increment critical value, the increment is judged to be high;

[0037] Comparing the snow depth with a preset snow depth increment critical value group, the preset snow depth increment critical value group 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;

[0038] If the snow depth increment is less than the first snow depth increment critical value, the increment is judged 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 judged 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 judged 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 judged to be deep; if the snow depth increment is greater than or equal to the fourth snow depth increment critical value, the increment is judged to be deep.

[0039] The present invention has the following beneficial effects:

[0040] 1. It achieves precise snowmaking in target snowmaking areas, significantly improving the pertinence and effectiveness of artificial snowmaking 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 cover, and ground conditions to screen the catalyst delivery area, it ensures effective delivery and targeted delivery of the catalyst. At the same time, differentiated delivery plans are formulated based on farmland information to maximize the needs of different crops, improve catalyst utilization and snowmaking effects, and enhance the overall efficiency of artificial snowmaking operations, making it more in line with the actual needs of agricultural production.

[0041] 2. It effectively overcomes the problems of the existing technology, such as the single catalyst placement scheme and insufficient feedback mechanism, and significantly improves the accuracy and effectiveness of snowmaking operations. Specifically, by differentiating catalyst placement according to the crop growth stage, it avoids unnecessary resource waste and negative impacts on crop growth. At the same time, by establishing a snowmaking effect feedback mechanism and conducting a comprehensive assessment based on meteorological and ground information, it achieves timely adjustment of catalyst placement, improves the stability and pertinence of the snowmaking effect, and provides good moisture conditions for crop growth.

[0042] 3. This method, which uses a backup radar selection method based on the percentage of overlap, effectively addresses the data loss problem associated with single radar station failure or insufficient coverage in existing snowmaking operations, thereby improving the reliability of these operations. Specifically, the optimal backup radar is selected by calculating the percentage of overlap between the target snowmaking area and the monitoring range of the backup radars. This method avoids the shortcomings of traditional methods that rely solely on distance or proximity to select backup radars. Furthermore, it employs an efficient coordinate transformation method, meeting the real-time requirements of snowmaking operations and improving both decision-making speed and implementation efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] The above and other features, advantages, and aspects of the various embodiments of the present invention will become more apparent with reference to the following detailed description in conjunction with the accompanying drawings. 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 that the elements are not necessarily drawn to scale.

[0044] Figure 1 The present invention is a flow chart of a method for controlling artificial snowmaking operations based on weather radar data. DETAILED DESCRIPTION

[0045] The present invention will be described in more detail below with reference to the accompanying drawings. Although certain embodiments of the present invention are shown in the accompanying 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. Rather, these embodiments are provided to provide a more thorough and complete understanding of the present invention. It should be understood that the drawings and embodiments of the present invention are for illustrative purposes only and are not intended to limit the scope of protection of the present invention.

[0046] It should also be noted that, for ease of description, only the parts related to the invention are shown in the drawings. In the absence of conflict, the embodiments and features of the embodiments of the present invention may be combined with each other.

[0047] It should be noted that the concepts of "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 of the functions performed by these devices, modules or units.

[0048] 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".

[0049] The names of the messages or information exchanged between multiple devices of the present invention are only used for illustrative purposes and are not used to limit the scope of these messages or information.

[0050] The present invention will be described in detail below with reference to the accompanying drawings and in conjunction with embodiments.

[0051] like Figure 1 FIG. 1 is a flow chart of a method for controlling snowmaking operations based on weather radar data according to the present invention, which specifically includes the following steps:

[0052] Step 101, obtain the farmland distribution map of the target snow-increasing area and the location information of the target snow-increasing area; determine the target weather radar number based on the location information of the target snow-increasing area; obtain the 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.

[0053] In some embodiments, the execution entity can be a server. The execution entity first retrieves target snow-enhancing area information from an agricultural resource database or a geographic information system database using the target snow-enhancing area's administrative division code. This target snow-enhancing area information includes a farmland distribution map and location information for the target snow-enhancing area. Subsequently, the target weather radar number corresponding to the target snow-enhancing area is determined using the target snow-enhancing area's administrative division code and GIS (Geographic Information System) information. The corresponding target weather radar data is then retrieved based on the target weather radar number. The target weather radar data includes a radar echo map and a radial velocity map.

[0054] In practice, the target snow-enhancing area can be an area demarcated by administrative division codes. A farmland distribution map of the target snow-enhancing area refers to the distribution of farmland within the target snow-enhancing area, presented in map or image format. The target snow-enhancing area location information describes the geographic location of the target snow-enhancing area on Earth. The target weather radar number is a code that uniquely identifies a weather radar. The administrative division code is a numerical code used to identify an administrative region. GIS, or geographic information system, is used to collect, store, manage, analyze, display, and apply geospatial data. A radar echo map is an image of the echo intensity received by the radar, used to display the location, intensity, and range of precipitation clouds and predict precipitation intensity. A radial velocity map is an image of the velocity of precipitation particles along the radar beam, measured using the Doppler effect, and used to analyze wind field distribution. A spectral width map is an image of the spectral width of the radar echo signal, used to reflect the variability of precipitation particle velocity and assist in identifying precipitation types and phenomena such as turbulence. Echo intensity is the power intensity of the electromagnetic wave received by the radar. The Doppler effect refers to the change in the frequency of waves received by a receiver when there is relative motion between the wave source and the receiver. If the wave source is close to the receiver, the received frequency becomes higher; if the wave source is far away, the received frequency becomes lower. Precipitation particles are various forms of precipitation in the atmosphere, such as raindrops, snowflakes, and hail. The wind field refers to the distribution of wind direction and speed at different locations within a certain area. Spectral width is the frequency range of the echo signal received by the radar. Turbulence is the irregular, random motion of a fluid.

[0055] Step 102: Map 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, which includes multiple mapped farmland areas; determine whether each echo area in the mapped radar echo map is covered by the mapped farmland area, and obtain a covered area group and an uncovered area group.

[0056] In some embodiments, the execution entity first maps multiple farmland areas within the farmland distribution map of the target snow-enhancing area to a radar echo map to obtain a mapped radar echo map, wherein the mapped radar echo map contains multiple mapped farmland areas. Subsequently, for each echo area within the mapped radar echo map, a method such as geometric figure or raster pixel comparison is used to determine whether each echo area is covered by the mapped farmland area. The multiple echo areas covered by the mapped farmland areas are determined as a covered area group, and the multiple echo areas not covered by the mapped farmland areas are determined as an uncovered area group.

[0057] In practice, a mapped radar echo map is a new radar echo map obtained by overlaying or projecting additional spatial information onto the original radar echo map. Mapped farmland areas are the representation of farmland areas in the target snow-enhancing farmland distribution map on the mapped radar echo map. This represents the farmland areas' appearance on the radar echo map after coordinate transformation and overlay or projection. GIS tools can be used to map multiple farmland areas in the target snow-enhancing farmland distribution map onto the radar echo map. ArcGIS can be the GIS tool, and the mapping method can be boundary comparison or region intersection. ArcGIS is a geographic information system software platform widely used for geographic data management, analysis, visualization, and sharing, particularly in map production and spatial analysis. Raster pixels, also known as raster pixels, are the basic building blocks of raster data. Boundary comparison involves comparing the boundaries of two or more geographic areas to determine their relative spatial locations, overlaps, and differences. Region intersection involves calculating the overlap between two or more geographic areas, typically analyzing the intersection of two areas in geographic space through spatial overlap. The intersection operation returns the portion of two regions that are common to each other and is often used to determine the area of overlap or common influence between the two regions.

[0058] Step 103: Acquire sounding balloon data corresponding to the location information of the target snow-enhancing area, where the sounding balloon data includes a temperature profile, a humidity profile, and a wind direction profile; determine the wind direction of each uncovered area in the uncovered area group based on the wind direction profile and the radial velocity map; and screen out uncovered areas from the uncovered area group whose wind direction points to any farmland in the farmland distribution map of the target snow-enhancing area and whose distance from the farmland is less than or equal to a preset distance threshold based on the farmland distribution map of the target snow-enhancing area, to obtain a secondary area group, and form an area group to be evaluated together with the covered area group.

[0059] In some embodiments, the executive body first locates the center point or boundary range of the target snow-enhancing area based on the geographical coordinates of the area. Then, a connection is established with the sounding balloon data source to determine the weather station to which the target snow-enhancing area belongs, and the sounding balloon data is obtained from the weather station. The acquired sounding balloon data includes temperature profiles, humidity profiles, and wind direction profiles. Subsequently, for the uncovered area group, the executive body determines the wind direction distribution at different heights through the wind direction profiles in the sounding balloon data, combined with the vertical meteorological conditions of the target snow-enhancing area. The radial velocity map provides the radial motion speed of atmospheric particles in different areas on the horizontal plane, thereby indirectly reflecting the horizontal distribution of the wind. By analyzing the wind direction, the wind field conditions of each uncovered area are determined. Then, using each farmland area in the target snow-increasing farmland distribution map as a marker, the uncovered area group was screened to find uncovered areas where the wind direction pointed toward any farmland in the target snow-increasing farmland distribution map. The latitude and longitude coordinates of the uncovered area and the farmland pointed toward the wind direction were obtained. The coordinate distance between the uncovered area and the farmland pointed toward the wind direction was calculated. If the distance was less than or equal to a preset distance threshold, the uncovered area was identified as a secondary selection area, and multiple secondary selection areas that met the screening criteria were identified as a secondary selection area group. Finally, the covered area group and the secondary selection area were merged to obtain the area group to be evaluated.

[0060] In practice, wind direction profiles and the wind direction of each uncovered area in the radar echo map can be used to screen uncovered areas within the uncovered area group whose wind direction points toward any farmland area. GIS tools can then be used to calculate the actual distance between the farmland area and the uncovered area. If the actual distance is less than or equal to a preset distance threshold, the corresponding uncovered area is designated as a secondary selected area. The GIS tool can be ArcGIS, and the preset distance threshold can be 5 kilometers. The secondary selected area group consists of uncovered areas that are located a certain distance from the target farmland area and whose wind direction points toward the target snow enhancement area, selected during the screening process based on wind direction and distance threshold. A wind direction profile refers to the distribution of wind speed and direction with altitude, recorded by a weather balloon. It is used to analyze atmospheric flow at different levels and predict the impact of wind fields on precipitation and snow enhancement. A radial velocity profile refers to the radial velocity distribution of precipitation particles, obtained by radar using the Doppler effect. It reflects the direction and speed of airflow and further helps determine the state of the wind field. A temperature profile is a curve or graph showing the variation of atmospheric temperature with altitude, describing the temperature distribution at different altitudes in the atmosphere. A humidity profile is a curve or graph showing how atmospheric humidity changes with altitude, describing the distribution of water vapor at different altitudes within the atmosphere. Vertical meteorological conditions refer to the distribution of meteorological characteristics in the vertical direction of the atmosphere, typically including how temperature, humidity, air pressure, wind speed, and wind direction vary with altitude.

[0061] Step 104: Obtain the snow-enhancing cloud 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 determine the catalyst placement area; generate an artificial snow-enhancing plan based on the catalyst placement area and the catalyst placement plan corresponding to the catalyst placement area.

[0062] In some embodiments, the execution entity first evaluates cloud conditions and ground conditions for snow enhancement in each of the groups of areas to be evaluated. The evaluation results are used to determine whether the areas meet the conditions for implementing snow enhancement. Areas that pass both the cloud condition evaluation and the ground condition evaluation are identified as catalyst deployment areas. Subsequently, a pre-configured catalyst deployment plan corresponding to the catalyst deployment area is obtained, and the catalyst deployment area and the catalyst deployment plan are integrated to obtain an artificial snow enhancement plan.

[0063] In practice, the catalyst can be silver iodide. A catalyst is a substance used to promote certain physical or chemical processes. In artificial snowmaking, the catalyst helps water vapor or water droplets in clouds form ice crystals, thereby accelerating the precipitation process. Silver iodide is a commonly used catalyst in artificial snowmaking operations. Silver iodide has unique physical properties. Its crystal structure is very similar to that of ice, effectively promoting the condensation of water in clouds into ice crystals.

[0064] These examples achieve precise snowmaking in targeted snowmaking areas, significantly improving the relevance and effectiveness of artificial snowmaking operations. Specifically, by mapping farmland distribution maps onto radar echo maps for refined regional division, catalyst placement areas are selected based on factors such as wind direction, distance, cloud cover, and ground conditions, ensuring effective catalyst delivery and targeted placement. Furthermore, differentiated placement plans are developed based on farmland information to maximize the needs of different crops, improve catalyst utilization and snowmaking effectiveness, and enhance the overall efficiency of artificial snowmaking operations, better meeting the actual needs of agricultural production.

[0065] In some embodiments, in order to further solve the second technical problem described in the background technology section, namely, "In the prior art, since artificial snowmaking operations usually adopt a unified catalyst placement scheme, there is a lack of targeted adjustments for different crop growth stages. Catalysts may be placed during the growth stage when crops do not need or are not suitable for snowmaking, resulting in waste of resources and affecting crop growth. In addition, the evaluation of snowmaking operations lacks an effective feedback mechanism combined with the environment, and the amount of catalyst placed cannot be adjusted in time according to the actual snowmaking effect, resulting in unstable snowmaking effects on farmland and difficulty in achieving the expected production increase target", in some embodiments of the present invention, a method for controlling artificial snowmaking operations based on meteorological radar data, the snowmaking cloud condition evaluation results corresponding to each area to be evaluated are determined by the following steps:

[0066] 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.

[0067] In some embodiments, the executing entity first obtains a radar vertical profile corresponding to the radar echo pattern and, using the radar echo pattern and radar vertical profile, determines the cloud type corresponding to each area to be assessed. Specifically, a communication connection is first established with the weather station corresponding to the target weather radar to obtain weather radar data monitored by the target weather radar at multiple azimuths. Subsequently, echo information at different altitudes is extracted and a radar vertical profile is generated through coordinate transformation and data interpolation. Finally, the cloud type corresponding to each area to be assessed is determined by jointly analyzing the radar echo pattern and radar vertical profile.

[0068] In practice, cloud types can be identified based on the characteristics of radar echograms and radar vertical profiles. For example, if the radar echogram displays large, uniform echoes and the radar vertical profile shows a bright band at the zero-degree layer, it can be identified as stratiform clouds. The radar vertical profile is an image that displays the echo intensity distribution within the radar detection area in a vertical cross-section, reflecting information such as the vertical structure, height, and intensity of precipitation clouds. Cloud types are classified based on characteristics such as cloud morphology, height, and formation. Common cloud types include stratiform, convective, and stratocumulus. Stratiform clouds typically appear as large sheets or layers, are evenly distributed, have blurred edges, are thin vertically, and have a low cloud base. Convective clouds typically appear as blocks or masses, have clear edges, exhibit strong vertical development, and have a high cloud base. Stratocumulus clouds combine the characteristics of both stratiform and convective clouds, with a more complex echo structure. They typically form when stratiform 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.

[0069] 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; and the cloud thickness corresponding to each area to be evaluated is generated based on the cloud base height and cloud top height.

[0070] In some embodiments, the execution entity first determines the cloud type. If the cloud type matches a preset snow-enhancing cloud type, it then analyzes the temperature profile to match multiple preset snow-enhancing temperature intervals, thereby obtaining multiple target altitude intervals. Subsequently, the cloud base and cloud top altitudes corresponding to each area to be assessed are determined using radar echograms, radar vertical profiles, and sounding balloon data. Finally, the cloud thickness corresponding to each area to be assessed is determined by performing a difference calculation between the cloud top and cloud base altitudes.

[0071] In practice, the preset snow-enhancing cloud type can be stratiform clouds. Multiple preset snow-enhancing temperature ranges include a near-zero temperature range, an optimal catalytic range, an effective catalytic range, and a limited catalytic range. The near-zero temperature range can be between 0°C and -5°C; the optimal catalytic range can be between -5°C and -10°C; the effective catalytic range can be between -10°C and -20°C; and the limited catalytic range can be -20°C or less. Using the temperature profile and multiple preset snow-enhancing temperature ranges, multiple target altitude ranges corresponding to these preset snow-enhancing temperature ranges can be obtained. In the radar vertical profile, the altitude at which the echo suddenly intensifies is determined as the cloud base altitude, while the altitude at which the echo suddenly weakens or disappears is determined as the cloud top altitude. Humidity profiles from sounding balloon data can assist in verification; the location where humidity increases sharply with altitude is close to the altitude at which the echo suddenly intensifies. Cloud base altitude refers to the vertical distance between the bottom of the cloud and the ground. Cloud top altitude refers to the vertical distance between the top of the cloud and the ground. Cloud thickness refers to the vertical distance between the cloud top and the cloud base, reflecting the vertical development of the cloud.

[0072] Step three, determine the proportion of supercooled water areas in each target height interval of each area to be evaluated in multiple target height intervals; determine the target height interval in which the proportion of supercooled water areas is greater than or equal to the preset supercooled water area proportion threshold as the supercooled 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, the snow-enhancing cloud condition assessment result corresponding to the corresponding area to be evaluated is determined to be passed.

[0073] In some embodiments, the execution entity first calculates the proportion of supercooled water areas in each target altitude interval of each area to be evaluated in multiple target altitude intervals, and compares the proportion of supercooled water areas with a preset supercooled water area proportion threshold. If the proportion of supercooled water areas is greater than or equal to the preset supercooled water area proportion threshold, the corresponding target altitude interval is determined to be a supercooled cloud interval. Subsequently, by performing a ratio operation on the supercooled cloud interval and the cloud thickness corresponding to each area to be evaluated, the proportion of supercooled cloud layers corresponding to each area to be evaluated is obtained. Finally, it is determined whether the proportion of supercooled cloud layers is greater than or equal to the preset supercooled cloud layer proportion threshold. If the proportion of supercooled cloud layers is greater than or equal to the preset supercooled cloud layer proportion threshold, the snow-enhancing cloud layer condition assessment result corresponding to the corresponding area to be evaluated is determined to be passed.

[0074] In practice, the preset supercooled water area percentage threshold can be 60%. The preset supercooled cloud layer percentage threshold can be 40%. The supercooled cloud layer interval refers to the target altitude interval where the supercooled water area percentage reaches or exceeds the preset supercooled water area percentage threshold. Supercooled water refers to water that is below 0°C but still liquid.

[0075] The proportion of supercooled water area is determined by the following steps:

[0076] Step 1: 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 correspond to the radar detection data one-to-one.

[0077] In some embodiments, the execution entity first establishes a communication connection with a database storing weather radar information, obtains target weather radar information corresponding to the target weather radar from the database storing weather radar information based on the target weather radar number, and extracts the weather radar polarization type corresponding to the target weather radar number from the target weather radar information, where the weather radar polarization type includes dual-polarization radar or single-polarization radar. The target weather radar data includes multiple radar detection data, which are obtained from multiple radar detection units, wherein the radar detection units and radar detection data correspond one-to-one.

[0078] In practice, radar detection units are range bins, which are discrete units formed by the radar receiver dividing the received echo signal in time. Single-polarization radars transmit and receive electromagnetic waves with only a single polarization state, usually horizontal, and can only provide echo intensity information. Dual-polarization radars transmit and receive electromagnetic waves with two orthogonal polarization states, usually horizontal and vertical, and can provide more information about precipitation particles. Polarization refers to the asymmetry of the shear wave's vibration direction relative to the propagation direction.

[0079] Step 2: For each radar detection unit, if the polarization type of the meteorological radar is a dual-polarization radar, the differential reflectivity and correlation coefficient are extracted 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, 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 the multiple radar detection units with supercooled water areas is obtained; the ratio of the sum of the thickness of the 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 ratio.

[0080] 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 the preset differential reflectivity threshold, and the correlation coefficient is judged against the 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 in the corresponding radar detection unit. Then, the radar detection unit with supercooled water area is screened out from the multiple radar detection units, and multiple radar detection units with supercooled water area are obtained, and the thickness of the multiple radar detection units with supercooled water area is obtained. Finally, the sum of the thicknesses of the multiple radar detection units with supercooled water area is ratioed to the cloud thickness of the corresponding area to be evaluated to obtain the first supercooled water area ratio.

[0081] In practice, using thickness for calculation can more accurately assess the total amount of supercooled water in the cloud layer. Among them, the preset differential reflectivity threshold can be 0.5dB. The preset correlation coefficient threshold can be 0.9. 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 degree of correlation between the horizontal polarization echo and the vertical polarization echo, and its value range is 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 shape, size and phase of the scatterer are more consistent; the lower the correlation coefficient, the worse the correlation, indicating that the type or state of the scatterer is more mixed. A scatterer refers to an object whose propagation direction changes when the wave encounters an inhomogeneous medium or obstacle during propagation.

[0082] Step 3: If the polarization type of the meteorological radar is a single polarization radar, obtain the echo intensity corresponding to each target altitude 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 the corresponding target altitude interval is determined to be a supercooled water area; obtain the ratio of the sum of the thickness of the target altitude intervals where the supercooled water area exists to the cloud thickness of the corresponding area to be evaluated, and obtain the proportion of the second supercooled water area.

[0083] 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 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 sounding balloon 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 to be a supercooled water area. Then, the thickness of each target altitude interval is counted, and only the target altitude intervals that have been determined to be supercooled water areas are selected. The thicknesses of these target altitude intervals are summed to obtain the sum of the thicknesses of the target altitude intervals where supercooled water areas exist. 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.

[0084] In practice, the preset echo intensity threshold can be 10 dBZ. The preset humidity threshold can be 80%. dBZ is a logarithmic unit used to represent the strength of the radar reflectivity factor. A larger dBZ value indicates a stronger echo power received by the radar. The radar reflectivity factor is the sum of the sixth power of the diameters of all precipitation particles per unit volume of air.

[0085] Step 4: Determine the first supercooled water area ratio or the second supercooled water area ratio as the supercooled water area ratio.

[0086] In some embodiments, the execution entity determines the determined first supercooled water region proportion or the second supercooled water region proportion as the supercooled water region proportion.

[0087] The snow-enhancing ground condition assessment results for each area to be assessed are determined through the following steps:

[0088] Step 1: Obtain a farmland coordinate group based on the farmland distribution map of the target snow-increasing area; obtain multiple soil temperatures and multiple soil moisture conditions corresponding to each farmland coordinate in the farmland coordinate group; obtain a soil temperature average based on the multiple soil temperatures; obtain a soil moisture average based on the multiple soil moisture conditions; compare the soil temperature average with the preset soil temperature maximum threshold and the 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 determine that the soil temperature assessment has passed; compare the soil moisture average with the preset soil moisture maximum threshold and 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 determine that the soil moisture assessment has passed; if the soil temperature assessment passes and the soil moisture assessment passes, the snow-increasing ground condition assessment result corresponding to the corresponding area to be assessed is determined to be assessed as passed.

[0089] In some embodiments, the execution entity first uses a GIS tool to obtain multiple boundary coordinates of each farmland area from the farmland distribution map of the target snow-increasing area to obtain a farmland coordinate group. For each farmland coordinate in the farmland coordinate group, multiple soil temperatures and multiple soil moisture conditions 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 up, and soil temperature and soil moisture conditions are monitored at the multiple edge monitoring points and the multiple non-edge monitoring points to obtain multiple soil temperatures and multiple soil moisture conditions. Subsequently, the multiple soil temperatures and the multiple soil moisture conditions are respectively averaged to obtain the soil temperature mean and the soil moisture mean. Finally, the soil temperature average and the preset soil temperature maximum threshold are compared with the 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, the soil temperature assessment result 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, the soil moisture assessment result is determined to be passed; if the soil temperature assessment result is passed and the soil moisture assessment result is passed, the corresponding snow-enhancing ground condition assessment result of the corresponding area to be assessed is determined to be assessed as passed.

[0090] In practice, the GIS tool can be ArcGIS. A thermistor sensor can be used to measure soil temperature, and a frequency domain reflectometry sensor can be used to measure soil moisture. The preset maximum soil temperature threshold can be 5°C, the preset minimum soil temperature threshold can be -5°C, the preset maximum soil moisture threshold can be 20%, and the preset minimum soil moisture threshold can be 15%. A thermistor is a sensitive element whose resistance changes significantly with temperature. In practice, the soil temperature is obtained by burying the thermistor in the soil and measuring its resistance. Frequency domain reflectometry is a technology that uses the differences in the propagation characteristics of electromagnetic waves in different media to measure material properties. In practice, soil moisture is inferred by measuring the dielectric constant of the soil.

[0091] The target weather radar data also includes a spectrum width diagram; the catalyst delivery plan includes at least one catalyst delivery sub-plan, and the catalyst delivery sub-plan is determined by the following steps:

[0092] Step 1: Determine the target placement location based on the catalyst placement area and spectrum width map.

[0093] In some embodiments, the executing entity determines the target placement location by jointly analyzing the catalyst placement area and the spectral width map. Specifically, the GIS tool is first used to import the vector data of the catalyst placement area and the raster data of the spectral width map, and align and project them under the same geographic coordinate system. Subsequently, the GIS tool superimposes the spatial range of the two types of data, extracts the corresponding spectral width value for each pixel in the superimposed area, and filters out areas with higher spectral width values in combination with the location range of the catalyst placement area. Finally, these areas are selected as target placement locations. In practice, the GIS tool can be ArcGIS. Vector data is a data format used to represent spatial features in a geographic information system. Pixels are the basic units of raster data, which are used to represent a small area in geographic space. Raster data is a spatial data format based on a grid structure, which is used to represent continuous geographic information.

[0094] Step 2: 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 crop type, sowing date, estimated harvest date and farmland terrain category; according to the crop type, obtain the crop snow requirement level through the 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, obtain the crop cold resistance level according to the crop type and the preset crop information table; determine the catalyst placement method according to the farmland terrain category and the preset catalyst placement method table; determine the catalyst placement sub-plan through the target placement location, crop cold resistance level, the preset catalyst adjustment table and the catalyst placement method.

[0095] In some embodiments, the target weather radar data also includes a spectrum width map. The execution entity extracts the coordinate information of each farmland area from the farmland distribution map of the target snow-increasing area using a GIS tool. Based on this coordinate information, the execution entity obtains the farmland information of each farmland area from a database storing farmland distribution information, thereby obtaining a farmland information group. The farmland information includes the crop type, sowing date, estimated harvest date, and farmland terrain category. Subsequently, based on the crop type, the crop snow requirement level is obtained from a preset crop information table. Crop snow requirement levels include low, medium, or high. Next, the crop snow requirement level is determined. If the crop snow requirement level is medium or high, the crop cold resistance level is obtained from the preset crop information table based on the crop type. Then, based on the crop terrain category, the corresponding catalyst delivery method is obtained from the preset catalyst delivery method table. Finally, based on the target delivery location, crop cold resistance level, and catalyst delivery method, combined with the preset catalyst adjustment table, a catalyst delivery sub-plan is obtained.

[0096] In practice, the crop type can be winter wheat. The farmland terrain type can be 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 by 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 by crop terrain type. The catalyst delivery method can be aircraft broadcasting, anti-aircraft gun broadcasting, or ground smoke burning. The preset catalyst adjustment table is a preset information table, including the snow requirement level for the growth stage, the cold resistance level for the growth stage, and the catalyst delivery amount adjustment amount. The catalyst delivery amount can be adjusted according to the different growth stages of different crops. Among them, aircraft broadcasting refers to a method of using an aircraft as a carrier to carry a catalyst broadcasting device to perform artificial snowmaking operations in the clouds. Anti-aircraft gun broadcasting refers to a method of using a ground launch device such as an anti-aircraft gun to launch catalyst-loaded projectiles into the clouds to perform 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.

[0097] A method for controlling snowmaking operations based on weather radar data further includes:

[0098] Step 1: Get 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 number of growing days corresponding to the crop type based on the current date and the sowing date. Determine the growth stage corresponding to the crop type based on the crop type, growing days, and the preset crop information table.

[0099] In some embodiments, the execution entity 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 earlier than the estimated harvest date, the execution entity performs a subtraction operation on the current date and the sowing date to obtain the number of growing days corresponding to the crop type. Subsequently, based on the crop type and the number of growing days, the execution entity queries the preset crop information table for the growth stage corresponding to the crop type.

[0100] In practice, the sowing date may be January 1, the current date may be January 5, and the harvest date may be July 10. The current date is later than the sowing date and earlier than the harvest date. By performing a difference operation between the current date and the sowing date, the number of growing days is 4 days, and the corresponding growth stage may be the emergence stage. The preset crop information table is a preset information table, including crop types, growth stages, and the range of growing days for each stage. The corresponding growth stage can be obtained from the preset crop information table through the crop type and growth days. Among them, the number of growing days refers to the number of days from the sowing or transplanting of crops to a specific date. The growth stage refers to the different developmental stages that crops go through in their 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.

[0101] Step 2: According to the crop type, growth stage and the preset crop growth stage information table, obtain the growth stage snow requirement level and growth stage cold resistance level corresponding to the crop type in the growth stage; according to the growth stage snow requirement level, growth stage cold resistance level and the preset catalyst adjustment table, generate a growth stage adjustment plan for the farmland area corresponding to the crop type; and send the growth stage adjustment plan to the corresponding processing terminal.

[0102] In some embodiments, the execution entity first searches a preset crop growth stage information table for the corresponding snow requirement and cold tolerance level for the crop type at the current growth stage based on the crop type and growth stage. Subsequently, based on the snow requirement and cold tolerance level, the execution entity searches a preset catalyst adjustment table for catalyst adjustment information. The retrieved catalyst adjustment information is determined as a growth stage adjustment plan, and the growth stage adjustment plan is transmitted to the corresponding processing terminal.

[0103] In practice, the snow requirement level during the growth stage can be high, medium or low. The cold resistance level during the growth stage can be high, medium or low. The cold resistance and snow requirement levels of crops are different at different growth stages. For example, during the wintering period of winter wheat, sufficient snow cover can significantly increase the ground temperature to ensure safe wintering. The corresponding snow requirement level during the growth stage is high, and the cold resistance level during the growth stage is high. During the jointing period of winter wheat, the cold resistance of the plant decreases, and the demand for snow is low. Excessive snow accumulation can cause disease. The corresponding snow requirement level during the growth stage is low, and the cold resistance 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 resistance level during the growth stage, and the catalyst dosage adjustment amount. The corresponding catalyst dosage adjustment amount can be determined by the snow requirement level during the growth stage and the cold resistance level during the growth stage. For example, when the snow requirement level during the growth stage is medium, and the cold resistance level during the growth stage is medium, the corresponding catalyst dosage adjustment amount can be reduced by 15%. The processing terminal can be a server. The overwintering period refers to the period when certain winter crops, under low temperatures, essentially cease growth and enter a dormant or semi-dormant state. The jointing period is the period during which the stems of grass crops begin to rapidly elongate. Grass crops, a very important category of herbaceous plants, are crops that produce grains or seeds that can be used as food or feed, such as rice, wheat, corn, sorghum, barley, oats, and millet.

[0104] A method for controlling snowmaking operations based on weather radar data further includes:

[0105] Step 1: Obtain multiple soil moisture contents before snowing, multiple soil moisture contents after snowing, and multiple snow depths corresponding to the farmland coordinate group; obtain the average soil moisture content before snowing based on the multiple soil moisture contents before snowing, and obtain the average soil moisture content after snowing based on the multiple soil moisture contents after snowing; obtain the average snow depth based on the multiple snow depths; obtain the soil moisture increment based on the average soil moisture content before snowing and the average soil moisture content after snowing.

[0106] In some embodiments, the execution entity first calculates multiple pre-snow soil moisture contents, multiple post-snow soil moisture contents, and multiple snow depths corresponding to the farmland coordinate group. Subsequently, the multiple pre-snow soil moisture contents are averaged to obtain a pre-snow soil moisture average; the multiple post-snow soil moisture contents are averaged to obtain a post-snow soil moisture average; and the multiple snow depths are averaged to obtain a snow depth average. Next, a difference calculation is performed between the post-snow soil moisture average and the pre-snow soil moisture average, and the result of the difference calculation is compared with the pre-snow soil moisture average to obtain a soil moisture increment.

[0107] In practice, soil moisture can be measured using a TDR sensor, while snow depth can be measured using an ultrasonic snow depth sensor. A TDR sensor uses time-domain reflectometry to measure dielectric properties. In soil moisture measurement, it measures the propagation time of an electromagnetic wave pulse in the soil and the reflected waveform to determine the soil's dielectric constant, thereby inferring the soil's moisture content. An ultrasonic snow depth sensor uses ultrasonic waves to measure the distance from the snow surface to the sensor. Time-domain reflectometry is a technique that measures the propagation characteristics of signals in transmission lines or other media. It analyzes the properties of a medium by emitting a fast-rising electrical pulse and measuring the reflected signal encountered during transmission. The dielectric constant is a physical quantity that measures a substance's ability to store electric field energy.

[0108] Step 2: Obtain the soil moisture increment assessment result corresponding to the soil moisture increment, and obtain the snow depth assessment result corresponding to the mean snow depth; if the soil moisture increment assessment result indicates a low increment, or the snow depth assessment result indicates a shallow depth, then generate first catalyst dosage feedback information; if the soil moisture increment assessment result indicates a high increment or a high increment, or the snow depth assessment result indicates a deep depth or a deep depth, then generate second catalyst dosage feedback information; if the soil moisture increment assessment result indicates a low increment, or the snow depth assessment result indicates a shallow depth, then generate third catalyst dosage feedback information; send the first catalyst dosage feedback information, the second catalyst dosage feedback information, or the third catalyst dosage feedback information to the corresponding feedback terminal.

[0109] In some embodiments, the execution entity first calculates the soil moisture increment assessment result corresponding to the soil moisture increment and the snow depth assessment result corresponding to the snow depth mean. If the soil moisture increment assessment result is a low increment, or the snow depth assessment result is a shallow depth, then first catalyst dosage feedback information is generated; if the soil moisture increment assessment result is a high increment or a high increment, or the snow depth assessment result is a deep depth or a deep depth, then second catalyst dosage feedback information is generated; if the soil moisture increment assessment result is a low increment, or the snow depth assessment result is a shallow depth, then third catalyst dosage feedback information is generated. Finally, the first catalyst dosage feedback information, the second catalyst dosage feedback information, or the third catalyst dosage feedback information is sent to the corresponding feedback terminal.

[0110] In practice, the first catalyst dosage feedback information may be that the catalyst dosage increases by 15%; the second catalyst dosage feedback information may be that the catalyst dosage decreases by 25%; and the third catalyst dosage feedback information may be that the catalyst dosage increases by 25%.

[0111] The soil moisture increment assessment results and snow depth assessment results are determined by the following steps:

[0112] Step 1: Compare the soil moisture increment with a preset soil moisture increment critical value group, which 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.

[0113] In some embodiments, the execution entity compares the soil moisture increment with each soil moisture increment threshold value in a preset soil moisture increment threshold value group, wherein the preset soil moisture increment threshold value group includes a first soil moisture increment threshold value, a second soil moisture increment threshold value, a third soil moisture increment threshold value, and a fourth soil moisture increment threshold value.

[0114] In practice, the first soil moisture increment critical value is the minimum soil moisture increment threshold, and the fourth soil moisture increment critical value is the maximum soil moisture increment threshold. The first soil moisture increment critical value may be 3%, the second soil moisture increment critical value may be 7%, the third soil moisture increment critical value may be 12%, and the fourth soil moisture increment critical value may be 15%.

[0115] Step 2: If the soil moisture increment is less than the first soil moisture increment critical value, the increment is judged 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 judged 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 judged 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 judged to be high; if the soil moisture increment is greater than or equal to the fourth soil moisture increment critical value, the increment is judged to be high.

[0116] In some embodiments, the execution entity compares the soil moisture increment with each soil moisture increment critical value in a preset soil moisture increment critical value group. If the soil moisture increment is less than the first soil moisture increment critical value, the soil moisture increment assessment result is determined to be a low increment; 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 soil moisture increment assessment result is determined to be a low increment; 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 soil moisture increment assessment result is determined to be a moderate increment; 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 soil moisture increment assessment result is determined to be a high increment; if the soil moisture increment is greater than or equal to the fourth soil moisture increment critical value, the soil moisture increment assessment result is determined to be a high increment.

[0117] In practice, using a multi-interval fuzzy matching method with a preset soil moisture increment critical value group, rather than conventional binary value determination, more precisely and accurately reflects actual changes in soil moisture increment. Fuzzy matching is a matching method that allows for a certain degree of difference between the input data and the target data. Unlike exact matching, which requires exact consistency, it determines whether a match is made based on a certain similarity or distance metric. Binary value matching requires exact consistency between the input data and the target data. A match is considered only when the input data and the target data are identical; otherwise, it is considered a mismatch.

[0118] Step three: compare the snow depth with a preset snow depth increment critical value group, which 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.

[0119] In some embodiments, the execution entity compares the snow depth with each snow depth increment threshold value in a preset snow depth increment threshold value set, which includes a first snow depth increment threshold value, a second snow depth increment threshold value, a third snow depth increment threshold value, and a fourth snow depth increment threshold value.

[0120] In practice, the first snow depth increment critical value is the minimum snow depth increment threshold, and the fourth snow depth increment critical value is the maximum snow depth increment critical value. The first snow depth increment critical value may be 2 cm, the second snow depth increment critical value may be 5 cm, the third snow depth increment critical value may be 10 cm, and the fourth snow depth increment critical value may be 15 cm.

[0121] Step 4: If the snow depth increment is less than the first snow depth increment critical value, the increment is judged 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 judged 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 judged 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 judged to be deep; if the snow depth increment is greater than or equal to the fourth snow depth increment critical value, the increment is judged to be deep.

[0122] In some embodiments, the execution entity compares the snow depth increment with each snow depth increment critical value in a preset snow depth increment critical value group. If the snow depth increment is less than the first snow depth increment critical value, the snow depth increment assessment result is determined to be a shallow increment; 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 snow depth increment assessment result is determined to be a relatively shallow increment; 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 snow depth increment assessment result is determined to be a moderate increment; 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 snow depth increment assessment result is determined to be a relatively deep increment; and if the snow depth increment is greater than or equal to the fourth snow depth increment critical value, the snow depth increment assessment result is determined to be a relatively deep increment.

[0123] These examples effectively overcome the existing challenges of single catalyst placement and insufficient feedback mechanisms, significantly improving the accuracy and effectiveness of snowmaking operations. Specifically, by tailoring catalyst placement to the crop growth stage, unnecessary resource waste and negative impacts on crop growth are avoided. Furthermore, by establishing a feedback mechanism for snowmaking effects and conducting a comprehensive assessment based on meteorological and ground-based information, timely adjustments to catalyst dosage are achieved, improving the stability and specificity of snowmaking effects and providing optimal moisture conditions for crop growth.

[0124] In some embodiments, to further address the third technical issue described in the background technology section, namely, "In the prior art, artificial snowmaking operations typically rely on a single radar station. When the radar station is relocated or its coverage area is insufficient, it is impossible to obtain effective data in a timely manner, which in turn affects the decision-making and implementation efficiency of artificial snowmaking operations," in some embodiments of the present invention, a method for controlling artificial snowmaking operations based on meteorological radar data further includes:

[0125] Step 1: Obtain multiple boundary coordinates corresponding to the target snow-increasing area location information to obtain the target snow-increasing area boundary coordinate group; convert each boundary coordinate in the target snow-increasing area boundary coordinate group to a radar echo map, and determine the proportion of overlapping areas in the radar echo map.

[0126] In some embodiments, the executing entity first obtains the corresponding administrative division code based on the location information of the target snow-enhancing area. Using this administrative division code, the executing entity retrieves boundary data corresponding to the target snow-enhancing area location information from a database storing geographic information data. Multiple boundary coordinates are extracted from the boundary data to obtain a target snow-enhancing area boundary coordinate set. Subsequently, each boundary coordinate in the target snow-enhancing area boundary coordinate set is transformed using a radar echo map to obtain a transformed radar echo map. Subsequently, the percentage of overlap in the transformed radar echo map is calculated, thereby obtaining the overlap percentage.

[0127] In practice, coordinate system conversion can be performed by converting the geographic coordinate system into the radar polar coordinate system. Specifically, the target snow enhancement area boundary coordinates are first converted to the geocentric coordinate system. Then, based on the latitude, longitude, and altitude of the target weather radar, the corresponding geocentric coordinates of the weather radar are calculated. The azimuth, elevation, and distance of the target snow enhancement area boundary coordinates relative to the radar station are calculated. Finally, the coordinate system conversion is completed using a Python library. The Python library can be Pyproj. The geographic coordinate system uses longitude and latitude to define the location of a point 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 uses the radar station as the origin and uses distance or distance library and azimuth to define the target's position. The geocentric coordinate system uses the Earth's center of mass as the origin and uses the X, Y, and Z axes to define the position of a point in space. The azimuth is the angle measured clockwise from a reference direction (usually due north) in the horizontal plane to the target direction. The elevation is the angle of the target relative to the horizontal plane. Pyproj is a Python library for map projections and coordinate transformations.

[0128] Step 2: If the overlapping area ratio is less than or equal to the preset overlapping area ratio threshold, obtain information on multiple adjacent areas adjacent to the target snow-increasing area; obtain multiple secondary meteorological radar numbers based on the multiple adjacent area information; obtain multiple secondary radar echo maps corresponding to the multiple secondary meteorological radar numbers; convert each boundary coordinate in the target snow-increasing area boundary coordinate group into multiple secondary radar echo maps, and screen out secondary radar echo maps with an overlapping area ratio greater than the preset overlapping area ratio threshold to obtain a secondary radar echo map group.

[0129] In some embodiments, the execution entity first compares the overlap ratio with a preset overlap ratio threshold. If the overlap ratio is less than or equal to the preset overlap ratio threshold, the execution entity then obtains the adjacent administrative division codes corresponding to multiple regions adjacent to the target snow-increasing region based on the administrative division code corresponding to the target snow-increasing region and a GIS tool. Based on the adjacent administrative division codes, multiple adjacent region information is obtained. Each adjacent region information in the multiple adjacent region information corresponds to a secondary weather radar number, resulting in multiple secondary weather radar numbers. Next, the execution entity establishes a communication connection with the weather station corresponding to each of the multiple secondary weather radar numbers and obtains the corresponding secondary weather radar data based on the corresponding secondary weather radar number. Data is extracted from the secondary weather radar data to obtain a secondary radar echo map. Subsequently, each boundary coordinate in the target snow-increasing region boundary coordinate group is converted to multiple secondary radar echo maps, resulting in multiple converted secondary radar echo maps. Secondary radar echo maps with an overlap ratio greater than the preset overlap ratio threshold are then selected to obtain a secondary radar echo map group. The GIS tool may be ArcGIS. The preset overlap ratio may be 90%. The secondary radar echo map refers to the echo map obtained from the secondary meteorological radar in the adjacent area because the overlapping area ratio of the currently used primary radar echo map does not reach the preset overlapping area ratio threshold within the target snow increase area.

[0130] Step three, obtain the secondary center coordinates corresponding to each secondary radar echo image in the secondary radar echo group; obtain the center coordinates of the target snow-increasing area corresponding to the target snow-increasing area location information; obtain multiple center distances based on the center coordinates of the target snow-increasing area and multiple secondary center coordinates; screen the multiple center distances, obtain the secondary meteorological radar number corresponding to the shortest center distance, and determine it as the secondary target meteorological radar.

[0131] In some embodiments, the executing entity first uses a GIS tool to obtain the secondary center coordinates corresponding to each secondary radar echo pattern in the secondary radar echo group. Furthermore, the executing entity also uses the GIS tool to obtain the target snow increase area center coordinates corresponding to the target snow increase area location information. Subsequently, the execution entity calculates the distances between the target snow increase area center coordinates and the multiple secondary center coordinates to obtain multiple center distances. Finally, the multiple center distances are screened, and the secondary weather radar number corresponding to the shortest center distance is determined as the secondary target weather radar. The GIS tool may be ArcGIS.

[0132] In these embodiments, a backup radar selection method based on the percentage of overlap effectively addresses the data loss problem caused by single radar station failure or insufficient coverage in existing snowmaking operations, thereby improving the reliability of these operations. Specifically, the optimal backup radar is selected by calculating the percentage of overlap between the target snowmaking area and the monitoring range of the backup radars. This avoids the shortcomings of traditional methods that rely solely on distance or proximity to select backup radars, and employs an efficient coordinate transformation method to meet the real-time requirements of snowmaking operations, thereby improving the decision-making speed and implementation efficiency of snowmaking operations.

[0133] The above descriptions are merely some preferred embodiments of the present invention and illustrate the underlying technical principles. Those skilled in the art should understand that the scope of the present invention is not limited to technical solutions formed by specific combinations of the aforementioned technical features. It also encompasses other technical solutions formed by any combination of the aforementioned technical features or their equivalents, without departing from the aforementioned inventive concept. For example, a technical solution formed by replacing the aforementioned features with (but not limited to) technical features with similar functions disclosed in this invention.

Claims

1. A method for controlling 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 based on 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 based on the wind direction profile and the radial velocity map; based on the farmland distribution map of the target snow-increasing area and the wind direction, screen from the uncovered area group uncovered areas whose wind direction points to any farmland in the farmland distribution map of the target snow-increasing area and whose distance from the farmland is less than or equal to a preset distance threshold, to obtain a secondary area group, and form an area group to be evaluated together with the covered area group; Obtaining snow-increasing cloud condition assessment results and snow-increasing 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; generating an artificial snowmaking plan according to the catalyst placement area and the catalyst placement plan corresponding to the catalyst placement area; The snow-enhancing cloud condition assessment results corresponding to each area to be assessed are determined by the following steps: Obtaining a radar vertical profile corresponding to the radar echo map; determining a cloud type corresponding to each area to be evaluated based on 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 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, the radar vertical profile, and the sounding balloon data; and the cloud thickness corresponding to each area to be evaluated is generated using the cloud base height and the cloud top height. Determine the proportion of supercooled water areas in each target height interval of each to-be-assessed area in 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 a supercooled cloud interval; obtain the proportion of supercooled cloud layers corresponding to each to-be-assessed area based on the supercooled cloud interval and the cloud thickness corresponding to each to-be-assessed area; if the proportion of supercooled cloud layers is greater than or equal to the preset supercooled cloud layer proportion threshold, determine the snow-enhancing cloud condition assessment result corresponding to the corresponding to-be-assessed area as passed.

2. The method for controlling snowmaking operations based on weather radar data according to claim 1, characterized in that: The proportion of the supercooled water area is determined by the following steps: Obtaining a 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 a plurality of radar detection data corresponding to a plurality of radar detection units, where the radar detection units correspond to the radar detection data in a one-to-one manner; 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 the preset correlation coefficient threshold, it is determined that a supercooled water area exists 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 thicknesses of the multiple radar detection units with supercooled water areas are obtained; the ratio of the sum of the thicknesses of the 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, obtain the echo intensity corresponding to each target altitude interval and the humidity corresponding to the humidity profile; 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, determine the corresponding target altitude interval as a supercooled water area; obtain the ratio of the sum of the thicknesses of the target altitude intervals where the supercooled water area exists to the cloud thickness of the corresponding area to be evaluated, and 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.

3. The method for controlling 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; based on the multiple soil temperatures, a soil temperature average is obtained; based on 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 passed.

4. The method for controlling snowmaking operations based on weather radar data according to claim 1, 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 placement location based on the catalyst placement area and the spectrum width map; 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 the 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.

5. The method for controlling snowmaking operations based on weather radar data according to claim 4, characterized in that: Also includes: Get the current date; If the current date is greater than or equal to the sowing date, and the current date is less than the estimated harvest date, obtaining the number of growing days corresponding to the crop type based on the current date and the sowing date; and determining the growth stage corresponding to the crop type based on 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.

6. The method for controlling snowmaking operations based on weather radar data according to claim 3, characterized in that: Also includes: Obtaining multiple pre-snowing soil moisture contents, multiple post-snowing soil moisture contents, and multiple snow depths corresponding to the farmland coordinate group; obtaining an average of the pre-snowing soil moisture contents based on the multiple pre-snowing soil moisture contents, obtaining an average of the post-snowing soil moisture contents based on the multiple post-snowing soil moisture contents; obtaining an average of the snow depths based on the multiple snow depths; and obtaining a soil moisture increment based on the average of the pre-snowing soil moisture contents and the average of the post-snowing soil moisture contents; 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 a low increment, or the snow depth assessment result indicates a shallow depth, generating first catalyst dosage feedback information; If the soil moisture increment assessment result indicates that the increment is too high or the increment is relatively high, or if the snow depth assessment result indicates that the depth is too deep or the depth is relatively deep, then second catalyst dosage 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.

7. The method for controlling snowmaking operations based on weather radar data according to claim 6, 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, it is determined that the increment is 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, it is determined that the increment is 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, it is determined that the increment is 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, it is determined that the increment is large; if the soil moisture increment is greater than or equal to the fourth soil moisture increment critical value, it is determined that the increment is large; 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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