Artificial rain and snow enhancement effect quantitative analysis method based on fine calculation of influence zone

Abstract

The invention discloses a quantitative analysis method for an artificial rain and snow enhancement effect based on fine calculation of an influence zone, which comprises the following steps: acquiring the influence zone in an artificial spreading catalyst diffusion zone according to artificial ice crystal concentration or silver iodide concentration; carrying out extraction and qualitative analysis on the radar products in the influence area; performing space-time matching on the influence area and the radar product, and calculating a mean value and distribution of radar parameters in the influence area; performing spatial distribution and time sequence change analysis on the radar parameters, and calculating parameter change and change rate of the radar product in the influence area; and quantitatively analyzing the parameter change and the change rate, and giving a rainfall enhancement operation effect. The method not only can improve the precision of quantitative analysis of the artificial rain and snow enhancement effect based on fine calculation of the influence area, but also has good interpretability, and can be directly applied to a quantitative analysis system of the artificial rain and snow enhancement effect.

Description

Technical Field

[0001] The present invention relates to the field of atmospheric coupling, and in particular to a quantitative analysis method for artificial rain and snow enhancement effects based on refined calculation of impact areas. Background Art

[0002] Statistical testing, physical testing, and numerical model testing are the three main technical means for evaluating the effectiveness of weather modification. Numerical model testing involves adding parameterized cloud seeding schemes to numerical models describing cloud and precipitation processes. This involves quantitatively forecasting macro- and microscopic cloud parameters and surface precipitation under both seeding and non-seeding conditions, and comparing these with actual observations to assess the effectiveness of weather modification. However, current numerical simulations still have uncertainties, and their results cannot fully represent the complex physical information of cloud and precipitation.

[0003] Physical verification is the process of obtaining evidence for the various physical changes that should occur after artificial induction through a series of observations of the physical parameters of the cloud-seeding process. Among them, radar observations are widely used in the physical verification of weather modification. Compared with statistical tests and model tests, physical verification based on remote sensing data such as radar makes it difficult to quantitatively evaluate the effects of artificial cloud seeding. Previous studies have tended to analyze changes in macro- and micro-parameters of cloud precipitation from a qualitative perspective. Furthermore, which of the changed physical quantities are caused by natural variations and which are caused by artificial cloud seeding has always been a major issue plaguing physical verification. Therefore, accurate and precise selection of the operational impact zone is an important prerequisite for conducting quantitative and accurate physical verification and evaluation.

[0004] At present, quantitative evaluation of the effects of artificial rainmaking operations at home and abroad generally adopts a single statistical test, numerical test or physical test method, which combines objective, quantitative and refined quantitative physical effect test methods in the operation impact area. There is a lack of artificial rainmaking operation effect evaluation methods that combine numerical model simulation and radar network observation.

[0005] Therefore, a new and feasible method for quantitatively analyzing the physical effects of rain enhancement operations, based on the quantitative analysis of radar products after rain enhancement operations using refined numerical model impact areas, has been proposed. This method leverages the advantages of numerical model simulation and remote sensing observations. Addressing the existing issues of uncertainty in cloud physics in numerical simulations and difficulty in determining the impact area in radar observations, a refined impact area is obtained using numerical model simulations. Combined with physical parameters measured by radar, radar parameter products are calculated for the impact area of ​​the rain enhancement operation, which are then used to analyze the physical changes in the target cloud after the catalytic operation. This provides support for refined quantitative physical testing and has valuable reference value for evaluating the effectiveness of rain enhancement. Summary of the Invention

[0006] The purpose of the present invention is to provide a quantitative analysis method of artificial rain and snow enhancement effects based on refined calculation of the impact area.

[0007] To achieve the above object, the present invention is implemented according to the following technical solutions:

[0008] The present invention comprises the following steps:

[0009] In the diffusion area of ​​artificially spread catalyst, the affected area is obtained based on the concentration of artificial ice crystals or silver iodide;

[0010] Extract and qualitatively analyze radar products within the affected area; radar products refer to radar observation data and derived parameters used for quantitative analysis of the effects of artificial rain and snow enhancement operations;

[0011] Performing spatiotemporal matching on the impact area and the radar product, and calculating the mean and distribution of radar parameters within the impact area; the radar parameters include reflectivity factor, differential reflectivity factor, and differential propagation phase shift rate;

[0012] Performing spatial distribution and temporal variation analysis on the radar parameters, and calculating parameter changes and rates of change of the radar products within the impact area;

[0013] Quantitatively analyze the parameter changes and the variability to provide the effect of the rain enhancement operation.

[0014] Furthermore, the method for obtaining the impact area includes:

[0015] The artificial seeding catalyst data were formatted; based on numerical models or diffusion transmission models, the artificial seeding catalyst information and meteorological reanalysis data were input into the cloud and precipitation explicit forecast system of the Meteorological Bureau to simulate and calculate the concentration of artificial seeding catalyst and the temporal and spatial distribution of artificial ice crystals; the areas with artificial ice crystal concentration ≥ 0.1 / L or silver iodide concentration ≥ 0.1 / L were regarded as the affected areas.

[0016] Furthermore, the method for extracting and qualitatively analyzing radar products within the impact area includes:

[0017] Based on the spatiotemporal information of the three-dimensional impact area, radar mosaic product data within a time interval of 3 minutes and a spatial distance of 500 meters from the impact area are extracted;

[0018] Through visual interpretation, the temporal and spatial evolution characteristics of radar echoes in the impact area are qualitatively analyzed.

[0019] Furthermore, the method for performing spatiotemporal matching between the impact area and the radar product includes:

[0020] The impact area and radar product monitoring area are spatially divided according to the latitude and longitude ranges, divided into grid tiles of different levels, and a spatial code set is obtained. The time is divided according to the time granularity to obtain a time code subset. The higher the level, the finer the grid.

[0021] Establish a hierarchical structure. When the level is 0, it represents the coarsest granularity level. As the level increases, the spatiotemporal granularity becomes finer. At the coarsest granularity level, a preliminary large-scale matching is performed between the impact area and the radar product monitoring area; at the fine-grained level, an accurate matching is performed.

[0022] For layer c, calculate the time-coded intersection of the impact area and the radar product:

[0023]

[0024] The time code set of the i-th influence area in the c-th layer is The time code set of the zth radar product in the cth layer is The time code intersection of the c-th layer impact area and the radar product is

[0025] If the time code intersection is an empty set, then there is no intersection in the time dimension of this layer, and the number of matching points is 0; if the time code intersection is not an empty set, calculate the spatial similarity:

[0026]

[0027] Among them, the spatial level weight of layer c in level a tile coding is In the level a tile coding, the number of locations where the impact area and the radar product have the same time code w is E a (w), the number of sub-region points of the impact area on time code w is Z(w), the number of sub-region points of the product radar on time code w is R(w), and the spatial similarity between the impact area and the radar product at the cth layer is H c ;

[0028] Introduce time level weights, calculate the matching degree between the impact area and radar products at different levels, and calculate the overall similarity:

[0029]

[0030] The matching degree between the impact area and the radar product at layer c is B c , the time level weight of the cth layer is The number of levels is M1;

[0031] Output the spatiotemporal matching results whose similarity is higher than the similarity threshold.

[0032] Furthermore, the method for calculating the mean and distribution of radar parameters in the influence area includes:

[0033] In the impact area after time and space matching, the zero-degree layer height is obtained according to the sounding information of the day, and the mean value and intensity distribution of the reflectivity factor above the zero-degree layer in the impact area are calculated; the zero-degree layer height is obtained according to the sounding information of the day, and the mean value and intensity distribution of the reflectivity factor below the zero-degree layer in the impact area are calculated; the mean value and intensity distribution of the radar parameters in the three-dimensional catalytic impact area are calculated; the mean value and intensity distribution of the radar parameters in the sowing height layer are calculated; the mean value and intensity distribution of the combined reflectivity factor in the two-dimensional impact area are calculated; the mean value and intensity distribution of the vertically integrated liquid water content in the two-dimensional impact area are calculated; the mean value and intensity distribution of the hourly rainfall intensity in the two-dimensional impact area are calculated; among them, "mean" is the average value of the radar parameters in the operation impact area; "distribution" is the spatial volume occupied by different intensity intervals of the radar parameters in the operation impact area, and the proportion of the spatial volume.

[0034] Furthermore, the method for analyzing the spatial distribution and temporal variation of the radar parameters includes:

[0035] Construct multidimensional feature vectors for multiple radar parameters according to the spatial coding layer, calculate the feature distances of different spatial coding units, and spatially annotate the radar parameters based on the feature distances;

[0036] Obtain the time series data of radar parameters, liquid water content, and catalytic operation time, use the cumulative sum control chart to scan the time series data, and identify significant mutation points. The expression is:

[0037] U(t)=max(0,U(t-1)+(V(t)-θ o ))

[0038] The radar parameter at time t is V(t), and the mean value before the catalyst is θ o , the cumulative statistics of radar parameters at time t is U(t), and the cumulative statistics of radar parameters at time t-1 is U(t-1);

[0039] According to the catalysis, the time-varying stages are divided into three categories: the natural development stage of autonomous evolution of cloud system before catalysis, the catalytic response stage dominated by the catalyst, and the precipitation attenuation stage of natural dissipation of precipitation.

[0040] An exclusive dimension analysis was conducted on the three types of time-varying stages to obtain stage characteristics. The natural development stage characteristics are cloud expansion speed and parameter baseline trend. The catalytic response stage characteristics are parameter jump amplitude and spatial response synchronization. The precipitation attenuation stage characteristics are attenuation speed and secondary development possibility. The cloud expansion speed is obtained by the reflectivity area growth rate per unit time, the parameter baseline trend is obtained by the slope of the linear fitting of liquid water content, the parameter jump amplitude is obtained by the area jump of the reflectivity greater than 30dBZ, the spatial response synchronization is obtained by the correlation of parameter changes outside the impact area, the secondary development possibility is the probability of the emergence of new echo cores, and the attenuation speed is obtained by calculating the rain intensity attenuation index.

[0041] The catalytic gain factor is calculated by the parameter changes during the natural development period and the catalytic response period:

[0042]

[0043] The xth catalytic gain factor is ρ x , the xth parameter change in the natural development period is The xth parameter change during the catalytic response period is The minimum control value is ε;

[0044] During the natural development period, linear regression was used to predict parameter trends and analyze the deviation between the predicted and actual values; during the catalytic response period, spatial clustering algorithm was used to identify the response core of the catalyst; and during the precipitation attenuation period, exponential fitting was used to evaluate the precipitation duration.

[0045] Furthermore, the method for calculating the parameter change and rate of change of the radar product in the influence area includes:

[0046] Calculate the time variation and rate of change of the reflectivity factor mean and intensity distribution below the zero-degree layer in the affected area;

[0047] Calculate the time variation and rate of change of the reflectivity factor mean and intensity distribution above the zero-degree layer in the affected area;

[0048] Calculate the mean value and the temporal variables and rates of intensity distribution of radar parameters in the three-dimensional catalytic influence area; calculate the mean value and the temporal variables and rates of intensity distribution of radar parameters in the seeding height layer; calculate the mean value and the temporal variables and rates of intensity distribution of the combined reflectivity factor in the two-dimensional influence area; calculate the mean value and the temporal variables and rates of intensity distribution of the vertically integrated liquid water content in the two-dimensional influence area; calculate the mean value and the temporal variables and rates of intensity distribution of the hourly rainfall intensity in the two-dimensional influence area.

[0049] Furthermore, the method of quantitatively analyzing the calculation results and summarizing the effects of the rain enhancement operation includes:

[0050] Based on the information on changes in the combined reflectivity factor in the affected area, the development trend of the overall cloud precipitation process after the catalytic operation was analyzed; based on the information on changes in radar physical parameters at different altitudes in the affected area, the cloud water conversion and precipitation particle growth trends after the catalytic operation were analyzed; based on the information on changes in vertically integrated liquid water in the affected area, the changing characteristics of the liquid water content in the affected area after the catalytic operation were analyzed; based on the information on changes in rainfall intensity in the affected area, the changing characteristics of precipitation in the affected area after the catalytic operation were analyzed; based on the analysis of the development trend of the overall cloud precipitation process, the trend of cloud water conversion and precipitation particle growth, the changing characteristics of liquid water content in the affected area, and the changing characteristics of precipitation in the affected area, quantitative physical test results of the effect of this operation were obtained.

[0051] The beneficial effects of the present invention are:

[0052] The present invention is a quantitative analysis method for the effects of artificial rain and snow enhancement based on refined calculation of the impact area. Compared with the existing technology, the present invention has the following technical effects:

[0053] The present invention can improve the accuracy of quantitative analysis of artificial rain and snow enhancement effects by obtaining the influence area, extracting and qualitatively analyzing, time-space matching, calculating the mean and distribution of radar parameters, analyzing time series changes, calculating parameter changes and variability of radar products, and outputting rain enhancement operation effect steps, thereby improving the precision of quantitative analysis of artificial rain and snow enhancement effects, optimizing the quantitative analysis of artificial rain and snow enhancement effects, greatly saving resources, and improving work efficiency. It can realize quantitative analysis of artificial rain and snow enhancement effects, and perform refined calculation of the influence area for quantitative analysis of artificial rain and snow enhancement effects in real time, which is of great significance to the quantitative analysis of artificial rain and snow enhancement effects, can adapt to quantitative analysis of artificial rain and snow enhancement effects of different standards and different quantitative analysis requirements of artificial rain and snow enhancement effects, and has a certain universality. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 This is a flowchart of the steps of the method for quantitatively analyzing the effect of artificial rain and snow enhancement based on refined calculation of the impact area of ​​the present invention;

[0055] Figure 2 This is a schematic diagram of the three-dimensional influence area of ​​the catalyst diffusion in the embodiment of this specification;

[0056] Figure 3 This is a diagram showing the spatial distribution evolution of the impact area superimposed radar mosaic product in the embodiments of this specification;

[0057] Figure 4 This is a time series diagram of radar products in the affected area in the embodiments of this specification. DETAILED DESCRIPTION

[0058] The present invention will be further described below through specific examples. The illustrative examples and descriptions of the present invention are used to explain the present invention but are not intended to limit the present invention.

[0059] The quantitative analysis method of artificial rain and snow enhancement effects based on refined calculation of the impact area of ​​the present invention comprises the following steps:

[0060] like Figure 1 As shown, in this embodiment, the following steps are included:

[0061] In the artificially obtained influence zone diffusion area, the influence zone is obtained based on the artificial ice crystal concentration or silver iodide concentration;

[0062] In the actual evaluation, the overall technical route mainly includes four parts: data input, influence area calculation, radar parameter extraction and quantitative analysis of influence area radar products;

[0063] For an aircraft rain enhancement operation process, the attached figure selected an operation process of drought relief in a certain province on November 16, 2022 as a research case, input aircraft operation information and reanalysis data, and use model simulation to obtain Figure 2 The spatial distribution of catalyst concentration at different times and the two-dimensional distribution of artificial ice crystal concentration information are shown. According to the spatial distribution of catalyst or artificial ice crystal concentration, the scope of the operation impact area is determined by artificial ice crystal concentration ≥ 0.1 / L or silver iodide particle concentration ≥ 0.1 / L;

[0064] Extract and qualitatively analyze radar products within the affected area; radar products refer to radar observation data and derived parameters used for quantitative analysis of the effects of artificial rain and snow enhancement operations;

[0065] In actual evaluation, Figure 3 The spatial distribution evolution characteristics of radar parameters after the operation were analyzed. The solid black line represents the aircraft seeding operation trajectory, the dashed black box represents the operation-affected area, and the non-operation-affected area is whitened and obscured. The three rows from top to bottom represent the combined reflectivity (CR), vertically integrated liquid water content (VIL), and hourly rainfall intensity estimate (QPR). The three columns from left to right represent the results at 14:00, 23:00, and 16:00 one hour after the operation, respectively. It can be seen that the echoes generally shifted eastward, and the overall echo intensity tended to increase as the target cloud moved eastward. Preliminary judgment is that the operation promoted cloud water conversion, resulting in a rain enhancement effect.

[0066] Performing spatiotemporal matching on the impact area and the radar product, and calculating the mean and distribution of radar parameters within the impact area; the radar parameters include reflectivity factor, differential reflectivity factor, and differential propagation phase shift rate;

[0067] Performing spatial distribution and temporal variation analysis on the radar parameters, and calculating parameter changes and rates of change of the radar products within the impact area;

[0068] In the actual evaluation, Figure 4 The temporal variation information of the main two-dimensional radar parameters characterizing the physical characteristics of cloud precipitation was analyzed, including the combined reflectivity factor CR, vertically integrated liquid water content VIL and hourly rainfall intensity QPR. It can be seen that at 12:05 when the operation ended, the echo intensity in the affected area was relatively small, about 27dBZ, and the rainfall intensity was 1.6mm / h. At 14:00, 2 hours after the operation ended, the average echo intensity in the affected area increased from 27dBZ to 38dBZ, among which the proportion of weak precipitation echoes of 20-30dBZ decreased from 50% to about 10%, and the proportion of echoes above 40dBZ increased from almost non-existent to about 40%. The vertically integrated liquid water content increased from 1kg / m3 at the end of the operation to 1kg / m3 at the end of the operation. 2 Increase to 2.5kg / m 2 , 1kg / m 2 The proportion of the following decreased from 70% to 10%, 3kg / m 2 The above proportion increased from non-existent to about 30%; according to rainfall intensity, at the beginning of the operation, the average rainfall intensity in the affected area was about 2mm / h. Two hours after the operation, the average rainfall intensity in the affected area reached a maximum of 13mm / h. From the perspective of the rainfall intensity ratio in the affected area, one hour and two hours after the operation, respectively, rainfall of 10-20mm / h and 20-50mm / h began to appear, indicating that the rainfall intensity in the affected area gradually increased;

[0069] Natural development period: 14:00-14:30, CR average 25dBZ, VIL average 1.0kg / m 2 Catalytic response period: 14:30-15:30, CR average value increased to 38dBZ, VIL increased to 2.5kg / m 2 During the precipitation decay period from 15:30 to 16:30, CR dropped to 30dBZ and VIL dropped to 1.8kg / m 2 ; The CR change during the natural development period is +2dBZ, and during the catalytic response period is +11dBZ, and the CR gain factor is 4.29;

[0070] Quantitatively analyzing the parameter changes and the rate of change to provide the effect of the rain enhancement operation;

[0071] In the actual assessment, after this rain-enhancing operation, the reflectivity factor, vertical integrated liquid water content, and radar inversion rainfall intensity in the operation-affected area showed a significant increase compared with the non-operation-affected area; 2 hours after the operation, the overall combined reflectivity factor increased from 27dBZ to a maximum of 38dBZ, among which the proportion of echo range above 40dBZ increased from non-existent to about 40%; the overall precipitation intensity increased from 2mm / h to a maximum of 13mm / h; precipitation of 10-20mm / h and 20-50mm / h began to appear one hour and two hours after the operation, respectively, indicating that the rainfall intensity in the affected area gradually increased.

[0072] In this embodiment, the method for obtaining the impact area includes:

[0073] The artificial seeding catalyst data were formatted; based on numerical models or diffusion transmission models, the artificial seeding catalyst information and meteorological reanalysis data were input into the cloud and precipitation explicit forecast system of the Meteorological Bureau to simulate and calculate the concentration of artificial seeding catalyst and the temporal and spatial distribution of artificial ice crystals; the areas with artificial ice crystal concentration ≥ 0.1 / L or silver iodide concentration ≥ 0.1 / L were regarded as the affected areas.

[0074] In this embodiment, the method for extracting and qualitatively analyzing radar products within the impact area includes:

[0075] Based on the spatiotemporal information of the three-dimensional impact area, radar mosaic product data within a time interval of 3 minutes and a spatial distance of 500 meters from the impact area are extracted;

[0076] Through visual interpretation, the temporal and spatial evolution characteristics of radar echoes in the impact area are qualitatively analyzed.

[0077] In this embodiment, the method for performing spatiotemporal matching between the impact area and the radar product includes:

[0078] The impact area and radar product monitoring area are spatially divided according to the latitude and longitude ranges, divided into grid tiles of different levels, and a spatial code set is obtained. The time is divided according to the time granularity to obtain a time code subset. The higher the level, the finer the grid.

[0079] Establish a hierarchical structure. When the level is 0, it represents the coarsest granularity level. As the level increases, the spatiotemporal granularity becomes finer. At the coarsest granularity level, a preliminary large-scale matching is performed between the impact area and the radar product monitoring area; at the fine-grained level, an accurate matching is performed.

[0080] For layer c, calculate the time-coded intersection of the impact area and the radar product:

[0081]

[0082] The time code set of the i-th influence area in the c-th layer is The time code set of the zth radar product in the cth layer is The time code intersection of the c-th layer impact area and the radar product is

[0083] If the time code intersection is an empty set, then there is no intersection in the time dimension of this layer, and the number of matching points is 0; if the time code intersection is not an empty set, calculate the spatial similarity:

[0084]

[0085] Among them, the spatial level weight of layer c in level a tile coding is In the level a tile coding, the number of locations where the impact area and the radar product have the same time code w is E a (w), the number of sub-region points of the impact area on time code w is Z(w), the number of sub-region points of the product radar on time code w is R(w), and the spatial similarity between the impact area and the radar product at the cth layer is H c ;

[0086] Introduce time level weights, calculate the matching degree between the impact area and radar products at different levels, and calculate the overall similarity:

[0087]

[0088] The matching degree between the impact area and the radar product at layer c is B c , the time level weight of the cth layer is The number of levels is M1;

[0089] Output the spatiotemporal matching results whose similarity is higher than the similarity threshold.

[0090] In this embodiment, the method for calculating the mean and distribution of radar parameters in the influence area includes:

[0091] In the impact area after time and space matching, the zero-degree layer height is obtained according to the sounding information of the day, and the mean value and intensity distribution of the reflectivity factor above the zero-degree layer in the impact area are calculated; the zero-degree layer height is obtained according to the sounding information of the day, and the mean value and intensity distribution of the reflectivity factor below the zero-degree layer in the impact area are calculated; the mean value and intensity distribution of the radar parameters in the three-dimensional catalytic impact area are calculated; the mean value and intensity distribution of the radar parameters in the sowing height layer are calculated; the mean value and intensity distribution of the combined reflectivity factor in the two-dimensional impact area are calculated; the mean value and intensity distribution of the vertically integrated liquid water content in the two-dimensional impact area are calculated; the mean value and intensity distribution of the hourly rainfall intensity in the two-dimensional impact area are calculated; among them, "mean" is the average value of the radar parameters in the operation impact area; "distribution" is the spatial volume occupied by different intensity intervals of the radar parameters in the operation impact area, and the proportion of the spatial volume.

[0092] In actual evaluation, parameters are measured in different intensity ranges such as 10-20dBZ, 20-30dBZ, and 30-40dBZ.

[0093] In this embodiment, the method for analyzing the spatial distribution and temporal variation of the radar parameters includes:

[0094] Construct multidimensional feature vectors for multiple radar parameters according to the spatial coding layer, calculate the feature distances of different spatial coding units, and spatially annotate the radar parameters based on the feature distances;

[0095] Obtain the time series data of radar parameters, liquid water content, and catalytic operation time, use the cumulative sum control chart to scan the time series data, and identify significant mutation points. The expression is:

[0096] U(t)=max(0,U(t-1)+(V(t)-θ o ))

[0097] The radar parameter at time t is V(t), and the mean value before the catalyst is θ o , the cumulative statistics of radar parameters at time t is U(t), and the cumulative statistics of radar parameters at time t-1 is U(t-1);

[0098] According to the catalysis, the time-varying stages are divided into three categories: the natural development stage of autonomous evolution of cloud system before catalysis, the catalytic response stage dominated by the catalyst, and the precipitation attenuation stage of natural dissipation of precipitation.

[0099] An exclusive dimension analysis was conducted on the three types of time-varying stages to obtain stage characteristics. The natural development stage characteristics are cloud expansion speed and parameter baseline trend. The catalytic response stage characteristics are parameter jump amplitude and spatial response synchronization. The precipitation attenuation stage characteristics are attenuation speed and secondary development possibility. The cloud expansion speed is obtained by the reflectivity area growth rate per unit time, the parameter baseline trend is obtained by the slope of the linear fitting of liquid water content, the parameter jump amplitude is obtained by the area jump of the reflectivity greater than 30dBZ, the spatial response synchronization is obtained by the correlation of parameter changes outside the impact area, the secondary development possibility is the probability of the emergence of new echo cores, and the attenuation speed is obtained by calculating the rain intensity attenuation index.

[0100] The catalytic gain factor is calculated by the parameter changes during the natural development period and the catalytic response period:

[0101]

[0102] The xth catalytic gain factor is ρ x , the xth parameter change in the natural development period is The xth parameter change during the catalytic response period is The minimum control value is ε;

[0103] During the natural development period, linear regression was used to predict parameter trends and analyze the deviation between the predicted and actual values; during the catalytic response period, spatial clustering algorithm was used to identify the response core of the catalyst; and during the precipitation attenuation period, exponential fitting was used to evaluate the precipitation duration.

[0104] In this embodiment, the method for calculating the parameter change and rate of change of the radar product within the influence area includes:

[0105] Calculate the time variation and rate of change of the reflectivity factor mean and intensity distribution below the zero-degree layer in the affected area;

[0106] Calculate the time variation and rate of change of the reflectivity factor mean and intensity distribution above the zero-degree layer in the affected area;

[0107] Calculate the mean value and the temporal variables and rates of intensity distribution of radar parameters in the three-dimensional catalytic influence area; calculate the mean value and the temporal variables and rates of intensity distribution of radar parameters in the seeding height layer; calculate the mean value and the temporal variables and rates of intensity distribution of the combined reflectivity factor in the two-dimensional influence area; calculate the mean value and the temporal variables and rates of intensity distribution of the vertically integrated liquid water content in the two-dimensional influence area; calculate the mean value and the temporal variables and rates of intensity distribution of the hourly rainfall intensity in the two-dimensional influence area.

[0108] In this embodiment, the method for summarizing the effect of rain enhancement operations includes:

[0109] Based on the information on changes in the combined reflectivity factor in the affected area, the development trend of the overall cloud precipitation process after the catalytic operation was analyzed; based on the information on changes in radar physical parameters at different altitudes in the affected area, the cloud water conversion and precipitation particle growth trends after the catalytic operation were analyzed; based on the information on changes in vertically integrated liquid water in the affected area, the changing characteristics of the liquid water content in the affected area after the catalytic operation were analyzed; based on the information on changes in rainfall intensity in the affected area, the changing characteristics of precipitation in the affected area after the catalytic operation were analyzed; based on the analysis of the development trend of the overall cloud precipitation process, the trend of cloud water conversion and precipitation particle growth, the changing characteristics of liquid water content in the affected area, and the changing characteristics of precipitation in the affected area, quantitative physical test results of the effect of this operation were obtained.

[0110] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A quantitative analysis method for artificial rain and snow enhancement effects based on refined calculation of the impact area, characterized by: The following steps are involved: In the artificially spread catalyst diffusion area, the affected area is obtained based on the artificial ice crystal concentration or silver iodide concentration; Extract and qualitatively analyze radar products within the affected area; radar products refer to radar observation data and derived parameters used for quantitative analysis of the effects of artificial rain and snow enhancement operations; Performing spatiotemporal matching on the impact area and the radar product, and calculating the mean and distribution of radar parameters within the impact area; the radar parameters include reflectivity factor, differential reflectivity factor, and differential propagation phase shift rate; Performing spatial distribution and temporal variation analysis on the radar parameters, and calculating parameter changes and rates of change of the radar products within the impact area; Quantitatively analyze the parameter changes and the variability to provide the effect of the rain enhancement operation.

2. The quantitative analysis method for artificial rain and snow enhancement effects based on refined calculation of the impact area according to claim 1 is characterized in that: The method for obtaining the impact zone includes: The artificial seeding catalyst data were formatted; based on numerical models or diffusion transmission models, the artificial seeding catalyst information and meteorological reanalysis data were input into the cloud and precipitation explicit forecast system of the Meteorological Bureau to simulate and calculate the concentration of artificial seeding catalyst and the temporal and spatial distribution of artificial ice crystals; the areas with artificial ice crystal concentration ≥ 0.1 / L or silver iodide concentration ≥ 0.1 / L were regarded as the affected areas.

3. The quantitative analysis method for artificial rain and snow enhancement effects based on refined calculation of the impact area according to claim 1 is characterized in that: The method for extracting and qualitatively analyzing radar products within the impact area includes: Based on the spatiotemporal information of the three-dimensional impact area, radar mosaic product data within a time interval of 3 minutes and a spatial distance of 500 meters from the impact area are extracted; Through visual interpretation, the temporal and spatial evolution characteristics of radar echoes in the impact area are qualitatively analyzed.

4. The quantitative analysis method for artificial rain and snow enhancement effects based on refined calculation of the impact area according to claim 1 is characterized in that: The method for performing spatiotemporal matching of the impact area and the radar product includes: The impact area and radar product monitoring area are spatially divided according to the latitude and longitude ranges, divided into grid tiles of different levels, and a spatial code set is obtained. The time is divided according to the time granularity to obtain a time code subset, where the higher the level, the finer the grid. Establish a hierarchical structure. When the level is 0, it represents the coarsest granularity level. As the level increases, the spatiotemporal granularity becomes finer. At the coarsest granularity level, a preliminary large-scale matching is performed between the impact area and the radar product monitoring area. At the fine-grained level, an accurate matching is performed. For layer c, calculate the time-coded intersection of the impact area and the radar product: The time code set of the i-th influence area in the c-th layer is The time code set of the zth radar product in the cth layer is The time code intersection of the c-th layer impact area and the radar product is If the time code intersection is an empty set, then there is no intersection in the time dimension of this layer, and the number of matching points is 0; if the time code intersection is not an empty set, calculate the spatial similarity: Among them, the spatial level weight of layer c in level a tile coding is In the level a tile coding, the number of locations where the impact area and the radar product have the same time code w is E a (w), the number of sub-region points of the impact area on time code w is Z(w), the number of sub-region points of the product radar on time code w is R(w), and the spatial similarity between the impact area and the radar product at the cth layer is H c ; Introduce time level weights, calculate the matching degree between the impact area and radar products at different levels, and calculate the overall similarity: The matching degree between the impact area and the radar product at layer c is B c , the time level weight of layer c is The number of levels is M1; Output the spatiotemporal matching results whose similarity is higher than the similarity threshold.

5. The quantitative analysis method for artificial rain and snow enhancement effects based on refined calculation of the impact area according to claim 1 is characterized in that: The method for calculating the mean and distribution of radar parameters in the influence area includes: In the impact area after time and space matching, the zero-degree layer height is obtained according to the sounding information of the day, and the mean value and intensity distribution of the reflectivity factor above the zero-degree layer in the impact area are calculated; the zero-degree layer height is obtained according to the sounding information of the day, and the mean value and intensity distribution of the reflectivity factor below the zero-degree layer in the impact area are calculated; the mean value and intensity distribution of the radar parameters in the three-dimensional catalytic impact area are calculated; the mean value and intensity distribution of the radar parameters in the seeding height layer are calculated; the mean value and intensity distribution of the combined reflectivity factor in the two-dimensional impact area are calculated; the mean value and intensity distribution of the vertical integrated liquid water content in the two-dimensional impact area are calculated; and the mean value and intensity distribution of the hourly rainfall intensity in the two-dimensional impact area are calculated.

6. The quantitative analysis method for artificial rain and snow enhancement effects based on refined calculation of the impact area according to claim 1 is characterized in that: The method for analyzing the spatial distribution and temporal variation of the radar parameters includes: Construct multidimensional feature vectors for multiple radar parameters according to the spatial coding layer, calculate the feature distances of different spatial coding units, and spatially annotate the radar parameters based on the feature distances; Obtain the time series data of radar parameters, liquid water content, and catalytic operation time, use the cumulative sum control chart to scan the time series data, and identify significant mutation points. The expression is: U(t)=max(0,U(t-1)+(V(t)-θ o )) The radar parameter at time t is V(t), and the mean value before the catalyst is θ o , the cumulative statistics of radar parameters at time t is U(t), and the cumulative statistics of radar parameters at time t-1 is U(t-1); According to the catalysis, the time-varying stages are divided into three categories: the natural development stage of autonomous evolution of cloud system before catalysis, the catalytic response stage dominated by the catalyst, and the precipitation attenuation stage of natural dissipation of precipitation. An exclusive dimension analysis was conducted on the three types of time-varying stages to obtain stage characteristics. The natural development stage characteristics are cloud expansion speed and parameter baseline trend. The catalytic response stage characteristics are parameter jump amplitude and spatial response synchronization. The precipitation attenuation stage characteristics are attenuation speed and secondary development possibility. The cloud expansion speed is obtained by the reflectivity area growth rate per unit time, the parameter baseline trend is obtained by the slope of the linear fitting of liquid water content, the parameter jump amplitude is obtained by the area jump of the reflectivity greater than 30dBZ, the spatial response synchronization is obtained by the correlation of parameter changes outside the impact area, the secondary development possibility is the probability of the emergence of new echo cores, and the attenuation speed is obtained by calculating the rain intensity attenuation index. The catalytic gain factor is calculated by the parameter changes during the natural development period and the catalytic response period: The xth catalytic gain factor is ρ x , the xth parameter change in the natural development period is The xth parameter change during the catalytic response period is The minimum control value is ε; During the natural development period, linear regression was used to predict parameter trends and analyze the deviation between the predicted and actual values; during the catalytic response period, spatial clustering algorithm was used to identify the response core of the catalyst; and during the precipitation attenuation period, exponential fitting was used to evaluate the precipitation duration.

7. The quantitative analysis method for artificial rain and snow enhancement effects based on refined calculation of the impact area according to claim 1 is characterized in that: The method for calculating the parameter change and rate of change of the radar product in the influence area includes: Calculate the time variation and rate of change of the reflectivity factor mean and intensity distribution below the zero-degree layer in the affected area; Calculate the time variation and rate of change of the mean reflectivity factor and intensity distribution above the zero-degree layer in the affected area; Calculate the mean value and the temporal variables and rates of intensity distribution of radar parameters in the three-dimensional catalytic influence area; calculate the mean value and the temporal variables and rates of intensity distribution of radar parameters in the seeding height layer; calculate the mean value and the temporal variables and rates of intensity distribution of the combined reflectivity factor in the two-dimensional influence area; calculate the mean value and the temporal variables and rates of intensity distribution of the vertically integrated liquid water content in the two-dimensional influence area; calculate the mean value and the temporal variables and rates of intensity distribution of the hourly rainfall intensity in the two-dimensional influence area.

8. The quantitative analysis method for artificial rain and snow enhancement effects based on refined calculation of the impact area according to claim 1 is characterized in that: The method for obtaining the effect of the rain enhancement operation comprises: Based on the information on changes in the combined reflectivity factor in the affected area, the development trend of the overall cloud precipitation process after the catalytic operation was analyzed; based on the information on changes in radar physical parameters at different altitudes in the affected area, the cloud water conversion and precipitation particle growth trends after the catalytic operation were analyzed; based on the information on changes in vertically integrated liquid water in the affected area, the changing characteristics of the liquid water content in the affected area after the catalytic operation were analyzed; based on the information on changes in rainfall intensity in the affected area, the changing characteristics of precipitation in the affected area after the catalytic operation were analyzed; based on the analysis of the development trend of the overall cloud precipitation process, the trend of cloud water conversion and precipitation particle growth, the changing characteristics of liquid water content in the affected area, and the changing characteristics of precipitation in the affected area, quantitative physical test results of the effect of this operation were obtained.

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