Quantitative method and device for silver iodide artificial precipitation snow catalytic potential based on cloud physical parameters

Abstract

This invention discloses a quantitative method and apparatus for assessing the catalytic potential of silver iodide in artificial rain and snow enhancement based on cloud physics parameters, belonging to the field of atmospheric science and technology. The method includes: calculating and normalizing the total nucleation ratio of silver iodide particles to obtain a normalized nucleation conversion rate score; calculating the ice crystal potential ratio and supersaturation relaxation timescale that can effectively participate in the bergiron process after catalysis; calculating and normalizing the effective conversion time based on the ice crystal potential ratio and supersaturation relaxation timescale to obtain a normalized conversion rate score; calculating and normalizing the effective liquid water pathway to obtain a normalized liquid water content score; and weighted summing the normalized nucleation conversion rate score, normalized conversion rate score, and normalized liquid water content score to obtain a comprehensive catalytic potential score characterizing the quantitative results of the catalytic potential. This invention enables the quantitative assessment of the catalytic potential of cold clouds.

Description

Technical Field

[0001] This invention relates to the field of atmospheric science and technology, and in particular to a quantitative method and apparatus for assessing the catalytic potential of silver iodide for artificial rain and snow enhancement based on cloud physics parameters. Background Technology

[0002] Weather modification is a technological approach that involves artificially intervening in the physical and chemical processes of the local atmosphere to achieve objectives such as increasing rainfall and snowfall, preventing hail, and suppressing rain. Among these, artificial rain enhancement and artificial snowfall are the most widely used types of operations. Seeding cold clouds with silver iodide is the most commonly used catalytic method for artificial rain and snow enhancement, and its scientific basis has been confirmed by numerous indoor experiments, numerical simulations, and field tests.

[0003] The timing of operations and the assessment of operational conditions are crucial to the effectiveness of artificial rain and snow enhancement. Currently, the assessment of operational conditions for artificial rain and snow enhancement largely relies on single-indicator thresholds such as radar echo intensity, cloud top temperature, and supercooled layer thickness, or simple empirical summaries of multiple indicators. However, the catalytic effect of artificial rain and snow enhancement is influenced by a combination of multiple microphysical processes: the nucleation efficiency of silver iodide particles determines how much catalyst can actually be converted into ice crystals; the conversion rate of the Wegener-Bergeron-Findeisen (WBF) process determines the speed at which liquid water transforms into ice crystals; and the total amount of liquid water in the cloud determines the upper limit of available water resources for conversion. These processes vary significantly between different cloud clusters and different parts of the same cloud cluster, and existing methods cannot incorporate these key factors into a unified quantitative assessment framework.

[0004] Furthermore, recent observational and simulation studies have shown that the spatial distribution of liquid water and ice crystals in mixed-phase clouds is often non-uniform, exhibiting significant liquid-ice mixing inhomogeneity. This inhomogeneity inhibits the efficiency of the WBF process by reducing the liquid-ice contact volume, thereby affecting the ice crystal growth rate. However, existing operational condition assessment methods do not consider this important physical process, leading to significant deviations between the assessed WBF conversion rate and the actual cloud environment, and thus failing to accurately predict the catalytic effect.

[0005] In summary, existing technologies mostly focus on single indicators or empirical judgments, lacking a comprehensive quantitative evaluation method that can integrate multiple key cloud physics parameters such as nucleation efficiency, conversion rate, total liquid water volume, and liquid ice mixing uniformity. This results in highly subjective and low-precision assessments of operational conditions, making it difficult to meet the scientific and precise decision-making requirements of weather modification operations. Summary of the Invention

[0006] The purpose of this invention is to overcome the shortcomings of the prior art and provide a quantitative method and device for the catalytic potential of silver iodide artificial rain and snow enhancement based on cloud physical parameters. This method can achieve a quantitative assessment of the catalytic potential of cold clouds and provide a scientific basis for operational decisions.

[0007] To achieve the above objectives, the present invention is implemented using the following technical solution:

[0008] On the one hand, this invention provides a quantitative method for the catalytic potential of silver iodide for artificial rain and snow enhancement based on cloud physics parameters, comprising:

[0009] Obtain the physical parameters of the target cloud layer;

[0010] Based on the physical parameters of the target cloud layer, the total nucleation ratio of silver iodide particles is calculated, and the total nucleation ratio of silver iodide particles is normalized to obtain the normalized nucleation conversion rate score.

[0011] Based on the physical parameters of the target cloud, the proportion of ice crystals that can effectively participate in the berberine process after catalysis and the oversaturation relaxation time scale are calculated. Based on the proportion of ice crystals that can effectively participate in the berberine process and the oversaturation relaxation time scale, the effective conversion time is calculated. The effective conversion time is normalized to obtain the normalized conversion rate score.

[0012] Based on the physical parameters of the target cloud layer, the effective liquid water path within the effective catalytic temperature window of silver iodide and after correction for nucleation efficiency is calculated. The effective liquid water path is then normalized to obtain a normalized liquid water content score.

[0013] Based on the weight combination set according to the operation scenario, the normalized nucleation conversion rate score, normalized conversion rate score, and normalized liquid water content score are weighted and summed to obtain a comprehensive catalytic potential score that characterizes the quantitative results of catalytic potential.

[0014] Optionally, the target cloud physical parameters include cloud temperature, cloud pressure, cloud saturation ratio relative to ice surface, cloud saturation ratio relative to water surface, cloud liquid water content, cloud total condensate content, cloud liquid water path, cloud liquid water proportion, cloud number concentration of silver iodide particles to be seeded in the cloud, and cloud droplet spectrum distribution characteristics.

[0015] Optionally, the calculation of the normalized nucleation conversion rate score includes:

[0016] ;

[0017] when hour, ;

[0018] when hour, ;

[0019] in, This indicates the total nucleation ratio of silver iodide particles; Indicates the first fitted parameter; Indicates the second fitting parameter; Indicates the temperature inside the cloud; Indicates reference temperature; Represents the natural exponential function; This represents the normalized nucleation conversion rate score; This indicates the maximum proportion of nucleation.

[0020] Optionally, the formula for calculating the proportion of ice crystals that can effectively participate in the bergiron process after catalysis is as follows:

[0021] ;

[0022] ;

[0023] ;

[0024] in, Indicates the uniformity of liquid ice mixing; , , , , , Both represent the fitting coefficients for the uniformity of liquid ice mixing; The logarithm commonly used to express total condensate content; Indicates the temperature inside the cloud; Indicates the total condensate water content within the cloud; This indicates the proportion of ice crystals that can effectively participate in the bergiron process after catalysis; Indicates the proportion of liquid water within the cloud; , , , , , , , , , , , , , , , , , , , , All of these represent the fitting coefficients of the proportion of ice crystals that can effectively participate in the bergiron process after catalysis.

[0025] Optionally, the formula for calculating the oversaturation relaxation timescale is:

[0026] ;

[0027] ;

[0028] ;

[0029] ;

[0030] ;

[0031] ;

[0032] ;

[0033] ;

[0034] in, Indicates the timescale of oversaturation relaxation; This indicates the water vapor mixing ratio within the cloud when the relative water surface is saturated. This indicates the water vapor mixing ratio within the cloud when the ice surface is relatively saturated; This represents the correction term for supersaturation caused by latent heat release; This represents the total sublimation growth rate of ice crystal clusters during the Bergieron process; Indicates cloud temperature The saturated vapor pressure at the water surface below; Indicates cloud temperature The saturated water vapor pressure on the ice surface below; This indicates the triple point temperature of water; Represents the natural exponential function; This indicates the latent heat of water vapor sublimation; Indicates specific heat at constant pressure; Indicates the air pressure inside the cloud; This represents a specific gas constant for water vapor; Indicates the concentration of ice crystals produced by catalysis; Indicates the capacitance parameters of the ice crystals; This indicates the saturation ratio within the cloud relative to the ice surface. Indicates ventilation factor; Indicates the thermal conductivity of air; This represents the diffusion coefficient of water vapor; This represents the density of saturated water vapor.

[0035] Optionally, the calculation of the normalized transformation rate score includes:

[0036] ;

[0037] when hour, ;

[0038] when hour, ,when hour, ;

[0039] in, Indicates the effective conversion time; Indicates the timescale of oversaturation relaxation; This indicates the proportion of ice crystals that can effectively participate in the bergiron process after catalysis; This represents the score for the normalized transformation rate; , These represent the lower and upper limits of the conversion time, respectively.

[0040] Optionally, the formula for calculating the normalized liquid water content score is:

[0041] ;

[0042] ;

[0043] ;

[0044] in, Indicates the effective liquid water path; , These represent the lowest and highest altitudes of the vertical profile of the cloud layer, respectively. Indicates the height of the vertical profile of the cloud layer. The content of liquid water within the cloud; Indicates the height of the vertical profile of the cloud layer. Cloud temperature The normalized mapping function to nucleation efficiency; Indicates the height of the vertical profile of the cloud layer. Cloud temperature Falling within the effective catalytic temperature window of silver iodide Indicator functions within; Indicates the unit of temperature; Indicates the height of the vertical profile of the cloud layer. Cloud temperature The total nucleation ratio of silver iodide particles; Indicates the maximum proportion of nucleation; This represents the score for normalized liquid water content; Indicates the reference threshold for effective liquid water; This indicates taking the minimum value.

[0045] Optionally, weight combinations can be set according to the task scenario, including:

[0046] The operational scenarios include rain enhancement scenarios in target areas and rain enhancement scenarios in non-target areas;

[0047] Based on the operational scenarios, a historical operational training dataset was constructed, which includes historical target cloud physical parameters, historical normalized nucleation conversion rate scores, historical normalized conversion rate scores, historical normalized liquid water content scores, and historical rain enhancement efficiency.

[0048] Initialize the weight combination;

[0049] Using the historical homework training dataset, multiple linear regression was used to fit the weight coefficients to obtain the first candidate weight combination;

[0050] Using the historical homework training dataset, the random forest algorithm is used to calculate the feature importance ranking and obtain the second candidate weight combination;

[0051] The arithmetic mean of the first candidate weight combination and the second candidate weight combination is taken as the final weight combination.

[0052] Optionally, the formula for calculating the comprehensive catalytic potential score is as follows:

[0053] ;

[0054] in, This indicates the overall score for catalytic potential; , , These represent the normalized nucleation conversion rate score, the normalized conversion rate score, and the normalized liquid water content score, respectively. , , These represent the weighting coefficients for the normalized nucleation conversion rate score, the normalized conversion rate score, and the normalized liquid water content score, respectively.

[0055] On the other hand, the present invention provides a quantitative device for assessing the catalytic potential of silver iodide for artificial rain and snow enhancement based on cloud physics parameters, comprising:

[0056] The parameter acquisition module is used to: acquire the physical parameters of the cloud layer of the target operation;

[0057] The first score calculation module is used to: calculate the total nucleation ratio of silver iodide particles based on the physical parameters of the target cloud layer, normalize the total nucleation ratio of silver iodide particles, and obtain the normalized nucleation conversion rate score.

[0058] The second scoring module is used to: calculate the proportion of ice crystals that can effectively participate in the berberine process after catalysis and the oversaturation relaxation time scale based on the physical parameters of the target cloud layer; calculate the effective conversion time based on the proportion of ice crystals that can effectively participate in the berberine process and the oversaturation relaxation time scale; normalize the effective conversion time to obtain a normalized conversion rate score.

[0059] The third scoring module is used to: calculate the effective liquid water path within the effective catalytic temperature window of silver iodide and after nucleation efficiency correction based on the physical parameters of the target cloud layer; normalize the effective liquid water path to obtain the normalized liquid water content score.

[0060] The comprehensive scoring calculation module is used to: set weight combinations according to the operation scenario, and perform weighted summation on the normalized nucleation conversion rate score, normalized conversion rate score, and normalized liquid water content score to obtain a comprehensive catalytic potential score that characterizes the quantitative results of catalytic potential.

[0061] Compared with the prior art, the beneficial effects achieved by the present invention are as follows:

[0062] This invention provides a reliable quantitative input for catalytic potential assessment by calculating the nucleation conversion rate score. It designs a conversion rate calculation scheme for the Bergieron process with liquid ice mixing uniformity correction, converting supersaturation relaxation time into a conversion rate score. This corrects the ideal assumption of uniform ice-water mixing in traditional Bergieron process assessments, making the conversion rate assessment more accurate. It employs a weighted integral method based on the effective catalytic temperature window of silver iodide to calculate the effective liquid water path, eliminating the ineffective contribution of supercooled water within the nucleation ineffective temperature range and solving the problem of overestimation of catalytic cloud water resources in existing technologies. It determines differentiated weight combinations for different operational scenarios, enabling the same set of physical quantity assessments to flexibly adapt to different operational objectives such as rapid rainfall enhancement and reservoir water replenishment, overcoming the deficiency of existing technologies where a fixed standard cannot meet the needs of precise decision-making in multiple scenarios. By integrating the above multi-parameter physical models with scenario-based weight configurations, it outputs standardized quantitative scores, filling the gap in the current field of weather modification where a standardized assessment system for catalytic operational potential is lacking. The results have high credibility and practicality, providing scientific support for weather modification operational decision-making. Attached Figure Description

[0063] Figure 1 A schematic flowchart illustrating the quantitative method for the catalytic potential of silver iodide artificial rain and snow enhancement based on cloud physics parameters provided in this embodiment of the invention.

[0064] Figure 2 This is a schematic diagram showing the correspondence between the uniformity of liquid ice mixing, the proportion of liquid water in the cloud, and the proportion of ice crystals that can effectively participate in the bergiron process after catalysis under different liquid ice mixing scenarios provided in this embodiment of the invention.

[0065] Figure 3 A schematic diagram of the three-dimensional scatter distribution of the comprehensive catalytic potential score and the cloud temperature, cloud liquid water content, and cloud pressure provided for embodiments of the present invention;

[0066] Figure 4 This is a time-series diagram of cloud temperature and cloud liquid water content under operational scenario A provided in an embodiment of the present invention;

[0067] Figure 5 This is a time-series diagram illustrating the normalized scores and the comprehensive catalytic potential score under operation scenario A provided in this embodiment of the invention.

[0068] Figure 6 This is a time-series diagram of cloud temperature and cloud liquid water content under operational scenario B provided in an embodiment of the present invention.

[0069] Figure 7 This is a time-series diagram of the normalized scores and the comprehensive score of catalytic potential under operation scenario B provided in this embodiment of the invention. Detailed Implementation

[0070] The technical solution of the present invention will be described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the embodiments of the present invention and the specific features in the embodiments are detailed descriptions of the technical solution of the present invention, rather than limitations thereof. In the absence of conflict, the embodiments of the present invention and the technical features in the embodiments can be combined with each other.

[0071] The term "and / or" simply describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone. Additionally, the character " / " generally indicates that the preceding and following related objects have an "or" relationship.

[0072] Example 1

[0073] like Figure 1 As shown in this embodiment, a quantitative method for the catalytic potential of silver iodide for artificial rain and snow enhancement based on cloud physics parameters is introduced, including:

[0074] Obtain the physical parameters of the target cloud layer;

[0075] Based on the physical parameters of the target cloud layer, the total nucleation ratio of silver iodide particles is calculated, and the total nucleation ratio of silver iodide particles is normalized to obtain the normalized nucleation conversion rate score.

[0076] Based on the physical parameters of the target cloud, the proportion of ice crystals that can effectively participate in the berberine process after catalysis and the oversaturation relaxation time scale are calculated. Based on the proportion of ice crystals that can effectively participate in the berberine process and the oversaturation relaxation time scale, the effective conversion time is calculated. The effective conversion time is normalized to obtain the normalized conversion rate score.

[0077] Based on the physical parameters of the target cloud layer, the effective liquid water path within the effective catalytic temperature window of silver iodide and after correction for nucleation efficiency is calculated. The effective liquid water path is then normalized to obtain a normalized liquid water content score.

[0078] Based on the weight combination set according to the operation scenario, the normalized nucleation conversion rate score, normalized conversion rate score, and normalized liquid water content score are weighted and summed to obtain a comprehensive catalytic potential score that characterizes the quantitative results of catalytic potential.

[0079] like Figure 1 As shown in this embodiment, a quantitative method for the catalytic potential of silver iodide for artificial rain and snow enhancement based on cloud physics parameters includes the following steps:

[0080] Step 1: Obtain the physical parameters of the target cloud layer, specifically:

[0081] The target cloud physical parameters refer to the real-time physical characteristics of the cloud layer obtained through radar and other detection methods before silver iodide seeding operations. These parameters specifically include: cloud temperature. Intra-cloud air pressure The saturation ratio of the cloud relative to the ice surface , The saturation ratio of the cloud relative to the water surface Liquid water content in clouds Total condensate content in clouds Cloud liquid water pathway The proportion of liquid water in the cloud The number concentration of silver iodide (AgI) particles to be seeded in the cloud And the characteristic parameters of cloud droplet spectral distribution within the cloud.

[0082] In this embodiment, the target cloud physical parameters do not include the seeding data already implemented, ensuring that the catalytic potential score is based solely on the cloud's own physical properties and is completely decoupled from subsequent seeding schemes.

[0083] Step 2: Calculate the normalized nucleation conversion rate score, specifically:

[0084] First, the nucleation ratio parameterization scheme of the Gumbel bi-exponential distribution is based on the cloud temperature in the cloud physical parameters of the target cloud. Calculate the total nucleation ratio of silver iodide particles. The formula is:

[0085] ;

[0086] in, Indicates the first fitted parameter; Indicates the second fitting parameter; Indicates reference temperature; This represents the natural exponential function.

[0087] In this embodiment, , , The dataset used for this formula is a comprehensive database containing over 1000 sets of mixed-phase cloud observation samples, and the goodness of fit is... It is applicable to the range of 237K-268K.

[0088] Then, the total nucleation ratio of silver iodide particles was normalized to obtain the normalized nucleation conversion rate score. To achieve the highest nucleation ratio The corresponding score is 100 points, and the score is 0 points when the nucleation ratio is 0. The score calculation formula is as follows:

[0089] when hour, ;

[0090] when hour, ;

[0091] in, This indicates the maximum nucleation ratio, defined as the upper limit of the effective nucleation ratio that can be achieved under current silver iodide catalyst technology conditions and within the applicable temperature range. The method for determining the optimal nucleation temperature is as follows: Within the optimal nucleation temperature window for silver iodide (-6℃ to -15℃), an outdoor comparative experiment is conducted to measure the ratio of the number concentration of ice crystals in the cloud after catalysis to the theoretical number concentration of silver iodide particles. The average value of multiple experiments is taken as the nucleation temperature. Calibration value, in this embodiment The calibration value is 0.90.

[0092] Step 3: Calculate the normalized transformation rate score, specifically:

[0093] Based on the cloud physical parameters of the target operation, the proportion of ice crystals that can effectively participate in the bergiron process after catalysis and the supersaturation relaxation timescale are calculated.

[0094] First, calculate the uniformity of liquid ice mixing. , The turbulent mixing capacity of the target cloud before catalysis is used to predict the spatial mixing uniformity of newly formed ice crystals and supercooled water after catalysis. The value ranges from 0 to 1, where 0 represents that ice and water tend to be completely separated after catalysis, and 1 represents that completely uniform mixing can be achieved after catalysis. The parameterization is based on the physical parameters of the target cloud layer, and the formula is as follows:

[0095] ;

[0096] ;

[0097] in, , , , , , Both represent the fitting coefficients for the uniformity of liquid ice mixing; The logarithm is a commonly used representation of total condensate content. , , , , , .

[0098] Secondly, based on the uniformity of liquid ice mixing The proportion of liquid water within the cloud in the target cloud physical parameters Calculate the proportion of ice crystals that can effectively participate in the bergiron process after catalysis. Oversaturation relaxation timescale Liquid ice mixing uniformity under different liquid ice mixing scenarios The proportion of liquid water in the cloud The proportion of ice crystals that can effectively participate in the bergiron process after catalysis. The correspondence and the diagrams of water droplets and ice crystals are as follows: Figure 2 As shown, where:

[0099] The proportion of ice crystals that can effectively participate in the bergiron process after catalysis The calculation formula is:

[0100] ;

[0101] in, , , , , , , , , , , , , , , , , , , , , All of these represent the fitting coefficients of the proportion of ice crystals that can effectively participate in the bergiron process after catalysis. , , , , , , , , , , , , , , , , , , , , .

[0102] Oversaturation relaxation timescale The formula represents the characteristic time scale required for ice crystal clusters catalyzed by silver iodide to completely convert supercooled water into ice crystals via the Bergieron process, under the assumption of homogeneous mixing.

[0103] ;

[0104] in, This indicates the water vapor mixing ratio within the cloud when the relative water surface is saturated. This indicates the water vapor mixing ratio within the cloud when the ice surface is relatively saturated; This represents the correction term for supersaturation caused by latent heat release; This represents the total sublimation growth rate of ice crystal clusters during the Bergieron process.

[0105] ;

[0106] ;

[0107] in, Indicates cloud temperature The saturated vapor pressure of water surface below, in hPa; Indicates cloud temperature The saturated water vapor pressure on the ice surface.

[0108] The cloud temperature can be obtained using Bolton's formula. The saturated water vapor pressure at the water surface below :

[0109] .

[0110] The cloud temperature can be obtained from the Goff-Gratch formula for saturated vapor pressure over ice. The saturated water vapor pressure on the ice surface :

[0111] .

[0112] in, This indicates the triple point temperature of water. .

[0113] ;

[0114] in, This indicates the latent heat of water vapor sublimation; This represents the specific heat at constant pressure. (Take...) , .

[0115] Rate of change of water vapor mixing ratio in clouds with cloud temperature when relative ice surface saturation The formula is:

[0116] ;

[0117] in, This represents a specific gas constant for water vapor. (Take...) .

[0118] The total sublimation growth rate of ice crystal clusters during the Bergieron process was calculated using the Maxwell-Mason equation. The formula is:

[0119] ;

[0120] in, The concentration of ice crystals produced by catalysis is expressed as the total nucleation ratio of silver iodide particles. The number concentration of silver iodide particles to be seeded within the cloud The product is obtained; The capacitance parameter represents the capacitance of the ice crystal, initially assumed to be approximately spherical. , Indicates the initial average radius of newly formed ice crystals; This indicates the saturation ratio within the cloud relative to the ice surface. This represents the ventilation factor, initially set to 1.0; Indicates the thermal conductivity of air; This represents the diffusion coefficient of water vapor; This represents the density of saturated water vapor.

[0121] Based on ice crystal potential ratio Oversaturation relaxation timescale Calculate the effective conversion time That is, taking into account the uneven mixing of liquid ice in actual clouds, the theoretical oversaturation relaxation timescale is adjusted. Corrected to effective conversion time The formula is:

[0122] ;

[0123] Finally, regarding the effective conversion time Normalization is performed to obtain the normalized transformation rate score. Set a conversion time limit and lower limit of conversion time , The case with the slowest conversion rate, For the case with the fastest conversion rate, the effective conversion time will be... Map to 0-100 points using the following formula:

[0124] when hour, ;

[0125] when hour, ,when hour, ;

[0126] Maximum conversion time and lower limit of conversion time The value is set differently according to the different work scenarios.

[0127] Step 4: Calculate the normalized liquid water content score, specifically:

[0128] First, based on the physical parameters of the target cloud layer, the effective liquid water path, after nucleation efficiency correction and located within the effective catalytic temperature window of silver iodide, is calculated. Effective liquid water pathway Defined as the nucleation efficiency-corrected liquid water path within the optimal catalytic temperature window of silver iodide, this calculation excludes the invalid contribution of supercooled water outside the optimal nucleation temperature window of silver iodide to the score. The formula is:

[0129] ;

[0130] in, , These represent the lowest and highest altitudes of the vertical profile of the cloud layer, respectively. Indicates the height of the vertical profile of the cloud layer. The content of liquid water within the cloud; Indicates the height of the vertical profile of the cloud layer. Cloud temperature Falling within the effective catalytic temperature window of silver iodide Indicator functions within, when Falling within the effective catalytic temperature window of silver iodide The value is 1 if it falls within the interval, and 0 otherwise. Indicates the unit of temperature; Indicates the height of the vertical profile of the cloud layer. Cloud temperature The normalized mapping function to the nucleation efficiency has the following value:

[0131] ;

[0132] in, Indicates the height of the vertical profile of the cloud layer. Cloud temperature The total nucleation ratio of silver iodide particles.

[0133] For effective liquid water pathways Normalization was performed to obtain the normalized liquid water content score. The formula is:

[0134] ;

[0135] in, Indicates the reference threshold for effective liquid water; This indicates taking the minimum value. The reference threshold for effective liquid water. Based on cloud type and regional differences, the following values ​​are set: 0.8 kg / m2 for summer convective clouds, 0.2 kg / m2 for winter stratiform clouds, 1.2 kg / m2 for convective clouds in humid southern regions, and 0.5 kg / m2 for convective clouds in semi-arid northern regions.

[0136] Step 5: Calculate the comprehensive catalytic potential score, which characterizes the quantitative results of catalytic potential. Specifically:

[0137] Weight combinations are set according to the work scenario, including:

[0138] First, this embodiment covers two main business scenarios of cold cloud silver iodide catalysis: target area rain enhancement scenario and non-target area rain enhancement scenario. Scenario A is the target area rain enhancement scenario: it refers to the operational needs to generate precipitation as soon as possible in a specific target area, focusing on the efficient and rapid action of the catalyst. Scenario B is the non-target area rain enhancement scenario: it refers to the operational needs to increase the total precipitation in a specific catchment area or reservoir area, focusing more on the total amount of cloud water resources.

[0139] Secondly, weight combinations are set according to the work scenario:

[0140] Based on the operational scenarios, a historical operational training dataset was constructed, which includes historical target cloud physical parameters, historical normalized nucleation conversion rate scores, historical normalized conversion rate scores, historical normalized liquid water content scores, and historical rain enhancement efficiency. Complete records of silver iodide cold cloud catalytic operational cases were collected and classified into scenarios A and B, with no less than 100 cases in each category.

[0141] Before model training, the three normalized scores and rainfall efficiency in the historical task training dataset are standardized. The three normalized scores for each historical task case (…) are then used as the basis for the standardization process. , , An optimized dataset is constructed with as the independent variable and the rain enhancement efficiency, which has been confirmed by statistical testing, as the dependent variable.

[0142] Initialize the weight combination. The initial weights serve as the starting point for iterative weight optimization, used in the initial calculation of the comprehensive score, and are subsequently updated after regression and feature importance evaluation; among them, , , These represent the weighting coefficients for the normalized nucleation conversion rate score, the normalized conversion rate score, and the normalized liquid water content score, respectively.

[0143] Using the historical homework training dataset, we first fit the weight coefficients using multiple linear regression. After normalization, the standardized regression coefficients of each independent variable are used to obtain the first candidate weight combination. , , ).

[0144] Using a historical assignment training dataset, and then employing a random forest algorithm to calculate feature importance ranking as cross-validation, a second candidate weight combination is obtained:

[0145] Multiple training subsets are obtained by randomly sampling the original dataset. The accuracy and stability of the model are then improved by combining the multiple decision tree models trained on these subsets. The specific parameter configuration is as follows: number of decision trees. Set to 500 to ensure the stability of feature importance evaluation; maximum number of features. Set as Because there are only 3 features in total, having all of them participate in each split ensures that each decision tree can fully evaluate all features; node split evaluation criteria. Set to mean square error There is no limit to the maximum depth of the decision tree. Minimum number of samples for leaf nodes To fully capture the potential nonlinear interaction between the three scores and the actual rainfall enhancement efficiency and effectively prevent overfitting; Each decision tree is trained by sampling, and out-of-bag samples are used to evaluate each feature. , , The importance of each feature is considered. After training, the reduction in the mean squared error of each node caused by each feature is calculated. The cumulative values ​​of all 500 decision trees are weighted and averaged to output the feature importance score of the three scores. After normalization, this score is used as the second candidate weight combination. , , ).

[0146] Finally, the arithmetic mean of the first candidate weight combination and the second candidate weight combination is taken as the final weight combination, i.e.:

[0147] , ,

[0148] Validation was performed using a 7:3 training:test set split, requiring a comprehensive score for catalytic potential. The Pearson correlation coefficient R with the actual results of the operation is ≥0.75. The weights are subjected to perturbation tests within a range of ±0.1, and the relative fluctuation of the correlation coefficient after perturbation is required to not exceed 5%.

[0149] Finally, the normalized nucleation conversion rate score was calculated. Normalized transformation rate score Normalized liquid water content score A weighted summation is performed to obtain a comprehensive catalytic potential score, which characterizes the quantitative results of catalytic potential. The formula is:

[0150] ;

[0151] in, The catalytic potential score is calculated on a scale of 0-100, with higher scores indicating greater catalytic performance potential in that scenario. With cloud temperature Liquid water content in clouds Intra-cloud air pressure The three-dimensional scatter distribution is as follows Figure 3 As shown. Based on the decision-making needs of weather modification operations, the catalytic potential levels and corresponding decision thresholds are defined as follows:

[0152] Excellent level: It has excellent catalytic potential and possesses optimal conditions for rapid rain enhancement operations, allowing for immediate implementation of catalytic operations;

[0153] Good grade: It has good catalytic potential and meets the conditions for regional water enhancement operations, so catalytic operations can be carried out as appropriate.

[0154] Poor grade: The catalytic potential is insufficient, and the conditions for effective regional water enhancement operations are not met; therefore, catalytic operations are not recommended. This level did not appear in this embodiment.

[0155] The weighting coefficients for each scenario determined by the above method are as follows:

[0156] Scenario A: Weighting coefficients for normalized nucleation conversion rate score Weighting coefficients of normalized transformation rate score Weighting coefficients for normalized liquid water content scores Scenario A refers to rain enhancement in the target area;

[0157] Scenario B: Weighting coefficients for normalized nucleation conversion rate score Weighting coefficients of normalized transformation rate score Weighting coefficients for normalized liquid water content scores Scenario B refers to rain enhancement in non-target areas;

[0158] The above weighting coefficients satisfy the normalization condition: .

[0159] Each scenario uses a matching parameter threshold, and a lower limit for conversion time. Maximum conversion time Reference threshold for effective liquid water Differentiated settings based on scenario:

[0160] Scenario A: Lower limit of conversion time Maximum conversion time Reference threshold for effective liquid water ;

[0161] Scenario B: Lower limit of conversion time Maximum conversion time Reference threshold for effective liquid water .

[0162] This embodiment integrates the above-mentioned multi-parameter physical model with scenario-based weight configuration to output a standardized quantitative score, filling the gap in the current field of weather modification where there is a lack of a standardized evaluation system for the potential of weather modification operations. The results have high credibility and practicality, providing scientific support for weather modification operation decision-making.

[0163] Example 2

[0164] Based on Example 1, this example introduces an experimental case study of a quantitative method for assessing the catalytic potential of silver iodide for artificial rainmaking and snow enhancement based on cloud physics parameters:

[0165] In the scenario of rapid rain enhancement in the target area:

[0166] Taking a silver iodide artificial rain enhancement operation in an arid region during the summer as an example, the objective was to generate precipitation as quickly as possible within the target area. An airborne cloud microphysics probe continuously sampled the target cloud at a frequency of 1Hz for 600 seconds. After quality control, the moving average value every 60 seconds was used as a set of valid input parameters, resulting in 10 sets of data. Taking the first set of data as an example:

[0167] Step 1: Obtain the physical parameters of the target cloud layer. Cloud temperature. Intra-cloud air pressure The saturation ratio of the cloud relative to the ice surface Liquid water content in clouds Total condensate content in clouds Cloud liquid water pathway The proportion of liquid water in the cloud The number concentration of silver iodide (AgI) particles to be seeded in the cloud The initial average radius of newly formed ice crystals in the characteristic parameters of cloud droplet spectral distribution within clouds. .

[0168] Step 2: Calculate the normalized nucleation conversion rate score. This is based on the cloud temperature. Calculate the total nucleation ratio of silver iodide particles. Take the maximum nucleation ratio. The normalized nucleation conversion rate score was obtained. ,because , .

[0169] Step 3: Calculate the normalized conversion rate score. Liquid ice mixing uniformity. If the value exceeds the [0,1] range, the uniformity of liquid ice mixing is taken. Ice crystal potential ratio Oversaturation relaxation timescale Thus, the effective conversion time is obtained. Scenario A sets a lower limit for conversion time. Maximum conversion time . Normalized transformation rate score .

[0170] Step 4: Calculate the normalized liquid water content score. Within the effective catalytic temperature window of silver iodide. The effective liquid water pathway is obtained by vertically integrating the liquid water content and then weighting it using the temperature-nucleation efficiency function. Scenario A sets an effective liquid water reference threshold. Then the normalized liquid water content score .

[0171] Step 5: Calculate the comprehensive catalytic potential score, which represents the quantitative results of the catalytic potential. Select the weight corresponding to scenario A: the weight coefficient of the normalized nucleation conversion rate score. Weighting coefficients of normalized transformation rate score Weighting coefficients for normalized liquid water content scores The weighted sum of the three scores yields the overall score. This is considered excellent and recommended for implementation. A comprehensive score of ≥80 is considered excellent.

[0172] Repeat the above calculation process for the remaining 9 sets of data. Figure 4 As shown, the temperatures of each group fluctuated between -15.3℃ and -14.8℃, and the liquid water content within the clouds... Between 0.47 and 0.54 g / m 3 Between. For example Figure 5 As shown, the normalized nucleation conversion rate score Between 97.9 and 100 points, minor temperature fluctuations had minimal impact. The effective conversion time was between 1.2 and 1.8 minutes, both significantly shorter than the lower limit of conversion time for scenario A. Normalized transformation rate score The score ranged from 73.0 to 86.7, mainly influenced by the liquid water content within the clouds. Effects of changes. Normalized liquid water content score. The score fluctuated the most among the three categories, ranging from 58.8 to 67.5. The overall score for the 10 groups ranged from 74.4 to 83.3, with an average of 78.7. Groups 4 and 8 had the highest scores due to the low liquid water content within the clouds. The level is slightly high, with an overall score exceeding 80 points, reaching the excellent level. (Group 4: Cloud liquid water content) It is 0.53g / m 3 Group 8: Liquid water content within clouds The value was 0.54; the liquid water content within the clouds in Group 5 was... The lowest overall score was 74.4, which is considered good. The fifth group had the lowest liquid water content within the clouds. It is 0.47 g / m 3 The score fluctuations mainly stemmed from natural variations in liquid water content. During the observation period, the cloud's catalytic potential remained stable in the good to excellent range, making it suitable for timely implementation of rapid rain enhancement operations.

[0173] Example 3

[0174] Based on Example 1, this example introduces an experimental case study of a quantitative method for assessing the catalytic potential of silver iodide for artificial rainmaking and snow enhancement based on cloud physics parameters:

[0175] In the scenario of rain enhancement in non-target areas (reservoir water increase):

[0176] Taking the autumn layered mixed-phase clouds in the catchment area of ​​a reservoir in southern China as an example, 10 consecutive sets of vertical profile data were obtained through microwave radiometer and radiosonde data inversion. The objective of the operation was to increase the inflow of water into the reservoir. Taking the first set of data as an example:

[0177] Step 1: Obtain the physical parameters of the target cloud layer. Cloud temperature. Intra-cloud air pressure The saturation ratio of the cloud relative to the ice surface Liquid water content in clouds Total condensate content in clouds Cloud liquid water pathway The proportion of liquid water in the cloud The number concentration of silver iodide (AgI) particles to be seeded in the cloud The initial average radius of newly formed ice crystals in the characteristic parameters of cloud droplet spectral distribution within clouds. .

[0178] Step 2: Calculate the normalized nucleation conversion rate score. This is based on the cloud temperature. Calculate the total nucleation ratio of silver iodide particles. Take the maximum nucleation ratio. The normalized nucleation conversion rate score was obtained. .

[0179] Step 3: Calculate the normalized conversion rate score. Liquid ice mixing uniformity. If the value exceeds the [0,1] range, the uniformity of liquid ice mixing is taken. Ice crystal potential ratio Oversaturation relaxation timescale Thus, the effective conversion time is obtained. Scenario B sets a lower limit for conversion time. Maximum conversion time . Normalized transformation rate score .

[0180] Step 4: Calculate the normalized liquid water content score. Within the effective catalytic temperature window of silver iodide. The effective liquid water pathway is obtained by vertically integrating the liquid water content and then weighting it using the temperature-nucleation efficiency function. Scenario B sets an effective liquid water reference threshold. Then the normalized liquid water content score .

[0181] Step 5: Calculate the comprehensive catalytic potential score, which represents the quantitative results of the catalytic potential. Select the weight corresponding to scenario A: the weight coefficient of the normalized nucleation conversion rate score. Weighting coefficients of normalized transformation rate score Weighting coefficients for normalized liquid water content scores The weighted sum of the three scores yields the overall score. This is considered excellent and is recommended for implementation.

[0182] Repeat the above calculation process for the remaining 9 sets of data. Figure 6 As shown, the temperatures of each group fluctuated between -8.4℃ and -7.9℃, and the liquid water content within the clouds... Between 0.52 and 0.68 g / m 3 Between these, the corresponding total condensate water content within each group of clouds All are equal to or slightly greater than the liquid water content within the same cloud group. .like Figure 7 As shown, the normalized nucleation conversion rate score Between 25.9 and 35.3 minutes, slight temperature fluctuations had minimal impact. The effective conversion time ranged from 3.6 to 4.3 minutes, both significantly shorter than the lower limit of conversion time for scenario B. Normalized transformation rate score All scores are 100. Cloud liquid water pathway. The levels are between 0.55 and 0.75 kg / m², all exceeding the scenario B reference threshold of 0.5 kg / m², resulting in a normalized liquid water content score. All scores were 100. The overall scores for the 10 groups ranged from 88.9 to 90.3, with an average of 89.5, all reaching the excellent level. The latter two scores for this cloud body were consistently full marks, with only the nucleation score fluctuating slightly with a low weight of 0.15. The overall score was almost unaffected, indicating excellent and stable catalytic potential. It is very suitable for rain enhancement operations in non-target areas aimed at increasing reservoir storage.

[0183] Example 4

[0184] This embodiment introduces a quantitative device for the catalytic potential of silver iodide for artificial rain and snow enhancement based on cloud physics parameters, including:

[0185] The parameter acquisition module is used to: acquire the physical parameters of the cloud layer of the target operation;

[0186] The first score calculation module is used to: calculate the total nucleation ratio of silver iodide particles based on the physical parameters of the target cloud layer, normalize the total nucleation ratio of silver iodide particles, and obtain the normalized nucleation conversion rate score.

[0187] The second scoring module is used to: calculate the proportion of ice crystals that can effectively participate in the berberine process after catalysis and the oversaturation relaxation time scale based on the physical parameters of the target cloud layer; calculate the effective conversion time based on the proportion of ice crystals that can effectively participate in the berberine process and the oversaturation relaxation time scale; normalize the effective conversion time to obtain a normalized conversion rate score.

[0188] The third scoring module is used to: calculate the effective liquid water path within the effective catalytic temperature window of silver iodide and after nucleation efficiency correction based on the physical parameters of the target cloud layer; normalize the effective liquid water path to obtain the normalized liquid water content score.

[0189] The comprehensive scoring calculation module is used to: set weight combinations according to the operation scenario, and perform weighted summation on the normalized nucleation conversion rate score, normalized conversion rate score, and normalized liquid water content score to obtain a comprehensive catalytic potential score that characterizes the quantitative results of catalytic potential.

[0190] The specific functions of each module described above are explained in the relevant content of the method in Embodiment 1, and will not be repeated here.

[0191] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0192] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0193] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0194] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0195] The embodiments of the present invention have been described above with reference to the accompanying drawings. However, the present invention is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of the present invention without departing from the spirit and scope of the claims. All of these forms are within the protection scope of the present invention.

Claims

1. A quantitative method for assessing the catalytic potential of silver iodide for artificial rain and snow enhancement based on cloud physical parameters, characterized in that, include: Obtain the physical parameters of the target cloud layer; Based on the physical parameters of the target cloud layer, the total nucleation ratio of silver iodide particles is calculated, and the total nucleation ratio of silver iodide particles is normalized to obtain the normalized nucleation conversion rate score. Based on the physical parameters of the target cloud, the proportion of ice crystals that can effectively participate in the berberine process after catalysis and the oversaturation relaxation time scale are calculated. Based on the proportion of ice crystals that can effectively participate in the berberine process and the oversaturation relaxation time scale, the effective conversion time is calculated. The effective conversion time is normalized to obtain the normalized conversion rate score. Based on the physical parameters of the target cloud layer, the effective liquid water path within the effective catalytic temperature window of silver iodide and after correction for nucleation efficiency is calculated. The effective liquid water path is then normalized to obtain a normalized liquid water content score. Based on the weight combination set according to the operation scenario, the normalized nucleation conversion rate score, normalized conversion rate score, and normalized liquid water content score are weighted and summed to obtain a comprehensive catalytic potential score that characterizes the quantitative results of catalytic potential.

2. The method for quantitatively analyzing the catalytic potential of silver iodide for artificial rain and snow enhancement based on cloud physics parameters according to claim 1, characterized in that, The target cloud physical parameters include cloud temperature, cloud pressure, cloud saturation ratio relative to ice surface, cloud saturation ratio relative to water surface, cloud liquid water content, cloud total condensate content, cloud liquid water path, cloud liquid water proportion, cloud number concentration of silver iodide particles to be seeded in the cloud, and cloud droplet spectrum distribution characteristics.

3. The method for quantitatively analyzing the catalytic potential of silver iodide for artificial rain and snow enhancement based on cloud physics parameters according to claim 1, characterized in that, The calculation of the normalized nucleation conversion rate score includes: ； when hour, ; when hour, ; in, Indicates the total nucleation ratio of silver iodide particles; Indicates the first fitted parameter; Indicates the second fitting parameter; Indicates the temperature inside the cloud; Indicates reference temperature; Represents the natural exponential function; This represents the normalized nucleation conversion rate score; This indicates the maximum proportion of nucleation.

4. The method for quantitatively analyzing the catalytic potential of silver iodide for artificial rain and snow enhancement based on cloud physics parameters according to claim 1, characterized in that, The formula for calculating the proportion of ice crystals that can effectively participate in the bergiron process after catalysis is as follows: ； ； ； in, Indicates the uniformity of liquid ice mixing; , , , , , Both represent the fitting coefficients for the uniformity of liquid ice mixing; The logarithm commonly used to express total condensate content; Indicates the temperature inside the cloud; Indicates the total condensate water content within the cloud; This indicates the proportion of ice crystals that can effectively participate in the bergiron process after catalysis; Indicates the proportion of liquid water within the cloud; , , , , , , , , , , , , , , , , , , , , All of these represent the fitting coefficients of the proportion of ice crystals that can effectively participate in the bergiron process after catalysis.

5. The method for quantitatively analyzing the catalytic potential of silver iodide for artificial rain and snow enhancement based on cloud physics parameters according to claim 1, characterized in that, The formula for calculating the oversaturation relaxation timescale is as follows: ； ； ； ； ； ； ； ； in, Indicates the timescale of oversaturation relaxation; This indicates the water vapor mixing ratio within the cloud when the relative water surface is saturated. This indicates the water vapor mixing ratio within the cloud when the ice surface is relatively saturated; This represents the correction term for supersaturation caused by latent heat release; This represents the total sublimation growth rate of ice crystal clusters during the Bergieron process; Indicates cloud temperature The saturated vapor pressure at the water surface below; Indicates cloud temperature The saturated water vapor pressure on the ice surface below; This indicates the triple point temperature of water; Represents the natural exponential function; This indicates the latent heat of water vapor sublimation; Indicates specific heat at constant pressure; Indicates the air pressure inside the cloud; This represents a specific gas constant for water vapor; Indicates the concentration of ice crystals produced by catalysis; Indicates the capacitance parameters of the ice crystals; This indicates the saturation ratio within the cloud relative to the ice surface. Indicates ventilation factor; Indicates the thermal conductivity of air; This represents the diffusion coefficient of water vapor; This represents the density of saturated water vapor.

6. The method for quantitatively analyzing the catalytic potential of silver iodide for artificial rain and snow enhancement based on cloud physics parameters according to claim 1, characterized in that, The calculation of the normalized conversion rate score includes: ； when hour, ; when hour, ,when hour, ; in, Indicates the effective conversion time; Indicates the timescale of oversaturation relaxation; This indicates the proportion of ice crystals that can effectively participate in the bergiron process after catalysis; This represents the score for the normalized transformation rate; , These represent the lower and upper limits of the conversion time, respectively.

7. The method for quantitatively analyzing the catalytic potential of silver iodide for artificial rain and snow enhancement based on cloud physics parameters according to claim 1, characterized in that, The formula for calculating the normalized liquid water content score is as follows: ； ； ； in, Indicates the effective liquid water path; , These represent the lowest and highest altitudes of the vertical profile of the cloud layer, respectively. Indicates the height of the vertical profile of the cloud layer. The content of liquid water within the cloud; Indicates the height of the vertical profile of the cloud layer. Cloud temperature The normalized mapping function to nucleation efficiency; Indicates the height of the vertical profile of the cloud layer. Cloud temperature Falling within the effective catalytic temperature window of silver iodide Indicator functions within; Indicates the unit of temperature; Indicates the height of the vertical profile of the cloud layer. Cloud temperature The total nucleation ratio of silver iodide particles; Indicates the maximum proportion of nucleation; This represents the score for normalized liquid water content; Indicates the reference threshold for effective liquid water; This indicates taking the minimum value.

8. The method for quantitatively analyzing the catalytic potential of silver iodide for artificial rain and snow enhancement based on cloud physics parameters according to claim 1, characterized in that, Weight combinations are set according to the work scenario, including: The operational scenarios include rain enhancement scenarios in target areas and rain enhancement scenarios in non-target areas; Based on the operational scenarios, a historical operational training dataset was constructed, which includes historical target cloud physical parameters, historical normalized nucleation conversion rate scores, historical normalized conversion rate scores, historical normalized liquid water content scores, and historical rain enhancement efficiency. Initialize the weight combination; Using the historical homework training dataset, multiple linear regression was used to fit the weight coefficients to obtain the first candidate weight combination; Using a historical assignment training dataset, the random forest algorithm is employed to calculate the feature importance ranking and obtain the second candidate weight combination; The arithmetic mean of the first candidate weight combination and the second candidate weight combination is taken as the final weight combination.

9. The method for quantitatively analyzing the catalytic potential of silver iodide for artificial rain and snow enhancement based on cloud physics parameters according to claim 1, characterized in that, The formula for calculating the comprehensive score of catalytic potential is as follows: ； in, This indicates the overall score for catalytic potential; , , These represent the normalized nucleation conversion rate score, the normalized conversion rate score, and the normalized liquid water content score, respectively. , , These represent the weighting coefficients for the normalized nucleation conversion rate score, the normalized conversion rate score, and the normalized liquid water content score, respectively.

10. A quantitative device for assessing the catalytic potential of silver iodide for artificial rain and snow enhancement based on cloud physics parameters, characterized in that, include: The parameter acquisition module is used to: acquire the physical parameters of the target cloud layer; The first score calculation module is used to: calculate the total nucleation ratio of silver iodide particles based on the physical parameters of the target cloud layer, normalize the total nucleation ratio of silver iodide particles, and obtain the normalized nucleation conversion rate score. The second scoring module is used to: calculate the proportion of ice crystals that can effectively participate in the berberine process after catalysis and the oversaturation relaxation time scale based on the physical parameters of the target cloud layer; calculate the effective conversion time based on the proportion of ice crystals that can effectively participate in the berberine process and the oversaturation relaxation time scale; normalize the effective conversion time to obtain a normalized conversion rate score. The third scoring module is used to: calculate the effective liquid water path within the effective catalytic temperature window of silver iodide and after nucleation efficiency correction based on the physical parameters of the target cloud layer; normalize the effective liquid water path to obtain the normalized liquid water content score. The comprehensive scoring calculation module is used to: set weight combinations according to the operation scenario, and perform weighted summation on the normalized nucleation conversion rate score, normalized conversion rate score, and normalized liquid water content score to obtain a comprehensive catalytic potential score that characterizes the quantitative results of catalytic potential.

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