An artificial rain enhancement effect verification method based on empowerment processing and natural filtering

Abstract

The application discloses a kind of artificial rain enhancement effect verification methods based on empowerment processing and natural filtration, it is related to weather modification technical field, it includes the following steps: determining the influence area of artificial rain enhancement operation and selecting contrast area;The test parameters of influence area and contrast area are normalized respectively;According to the difference amount of the change rate of the normalized test parameters of influence area and contrast area, the weight coefficient of corresponding test parameter is calculated;According to weight coefficient, the test parameters of the set quantity are selected as test index in turn from big to small;The variation difference coefficient of test index of influence area and contrast area is calculated, and then the correlation degree of test index is calculated;Based on the weight coefficient, correlation degree and change rate difference amount of test index, the effect of artificial rain enhancement is verified.The application obtains more objective, accurate, comprehensive artificial rain enhancement effect verification result, provides new method basis for artificial rain enhancement effect verification, and can promote weather modification operation technology development.

Description

Technical Field

[0001] The present invention relates to the technical field of artificial weather modification, and in particular to a method for testing artificial rainfall effects based on weighted processing and natural filtering. Background Art

[0002] Verifying the effectiveness of artificial rainfall enhancement is a major scientific and technological issue that urgently needs to be addressed. Currently, verifying the effectiveness of artificial rainfall enhancement has become a bottleneck in the development of cloud physics and weather modification technologies. This difficulty stems from the large temporal and spatial variability of natural precipitation, the uneven temporal and spatial distribution of precipitation, and the scientific difficulty of accurately forecasting precipitation, all of which contribute to the uncertainty of verifying the effectiveness of artificial rainfall enhancement. Furthermore, a comprehensive and systematic understanding of the physical mechanisms and processes of cloud precipitation remains lacking, making it difficult to fully distinguish between human influence and natural variability.

[0003] The current improvement in the level of advanced cloud water detection and the diversification of means have provided higher-resolution atmospheric precipitation and cloud physics information for the verification of artificial rainmaking effects. This is promoting the exploration of the physical processes and mechanisms of increased precipitation caused by artificial rainmaking, and has put forward urgent requirements for the updating of artificial rainmaking verification technologies and methods.

[0004] There are two major technical bottlenecks in testing the effectiveness of artificial rainfall:

[0005] (1) It is difficult to accurately separate the cloud precipitation changes caused by artificial rainfall from the complex changes in natural precipitation, resulting in significant interference of natural precipitation variability on the test results of artificial rainfall effect.

[0006] (2) It is difficult to fully and systematically grasp the complex physical process mechanism of cloud precipitation, and it is difficult to accurately assess the extent of changes in cloud microphysical processes caused by artificial rainfall enhancement and how they are converted into actual precipitation, resulting in low credibility of the test results of artificial rainfall effects.

[0007] Existing physical tests judge the impact of artificial rainmaking on cloud physical processes by analyzing changes in the physical characteristics of clouds. However, their shortcomings are that changes in a single physical parameter cannot fully and accurately reflect the precipitation effect and are greatly affected by the complexity and uncertainty of natural clouds.

[0008] Existing statistical tests use statistical methods to compare cloud precipitation data in the operating area and the control area, and then calculate the rainfall increase rate. However, its shortcomings are that it is difficult to exclude the influence of other natural factors on precipitation, and the selection and setting of the control area are subjective and limited.

[0009] Existing numerical simulation tests use numerical means to simulate the physical process of artificial rainfall enhancement and then test the effectiveness of artificial rainfall enhancement. However, its shortcomings are that it has very high requirements on the accuracy and initial conditions of the model and requires a large amount of computing resources for verification and calibration.

[0010] Therefore, there is an urgent need to develop a physical test method for artificial rainmaking effects that integrates multi-source cloud physics data and eliminates the natural variability of precipitation in a more scientific and accurate manner, so as to improve the scientificity and credibility of the test of artificial rainmaking effects. Summary of the Invention

[0011] In view of the above-mentioned deficiencies in the prior art, the present invention provides a method for testing the effect of artificial rainfall enhancement based on weighted processing and natural filtration, which solves the problem that the prior art is difficult to accurately test the effect of artificial rainfall enhancement.

[0012] In order to achieve the above-mentioned object of the invention, the technical solution adopted by the present invention is:

[0013] A method for verifying the effect of artificial rainfall enhancement based on weighted processing and natural filtering is provided, which comprises the following steps:

[0014] Determine the impact area of ​​artificial rainmaking operations and select comparison areas;

[0015] Simulate the transmission and diffusion of the impact area and the comparison area to obtain the test parameters of the impact area and the comparison area respectively;

[0016] The test parameters of the impact area and the comparison area are dimensionally normalized to obtain the normalized test parameters of the impact area and the comparison area;

[0017] Calculate the weight coefficient of the corresponding test parameter according to the difference in the change rate of the normalized test parameter between the impact area and the comparison area;

[0018] Select a set number of test parameters as test indicators in descending order according to the weight coefficients;

[0019] Calculate the coefficient of variation of the test indicators in the affected area and the control area, and then calculate the correlation degree of the test indicators;

[0020] The artificial rainfall enhancement effect is tested based on the weight coefficient, correlation degree and change rate difference of the test indicators.

[0021] Furthermore, specific methods for determining the impact area of ​​artificial rainfall enhancement operations and selecting comparison areas include:

[0022] Based on weather radar echo and wind field data, aircraft flight path information for cloud seeding operations, and the amount of cloud seeding catalyst used, numerical simulations were used to determine the impact area of ​​the cloud seeding operations.

[0023] The similarity comparison statistical method is used to select the best comparison area of ​​the impact area of ​​artificial rainmaking operations.

[0024] Furthermore, the specific method of simulating the transmission diffusion of the impact area and the comparison area includes:

[0025] Numerical simulation was used to simulate the dynamic changes of the geographical locations of the affected area and the comparison area. The simulation period ranged from the end of the artificial rainmaking operation to 3 hours after the end.

[0026] Furthermore, specific methods for dimensionally normalizing the test parameters of the impact area and the comparison area include:

[0027] The actual observed values ​​of each test parameter in the influence area are dimensionally normalized, and the expression is:

[0028]

[0029] in For the affected area The test parameter The actual observation value of each time Normalized results; For the affected area The minimum value of all actual observed values ​​of the test parameters; For the affected area The maximum value among all actual observed values ​​of the test parameters;

[0030] The actual observed values ​​of each test parameter in the comparison area are dimensionally normalized, and the expression is:

[0031]

[0032] in For comparison area The test parameter The actual observation value of each time Normalized results; For comparison area The minimum value of all actual observed values ​​of the test parameters; For comparison area The maximum value among all actual observed values ​​of the test parameter.

[0033] Furthermore, the calculation expression of the change rate difference of the test parameter is:

[0034]

[0035] in Indicates the difference between the affected area and the comparison area The test parameter The actual observation value of each time is normalized and corresponds to the difference in the rate of change; Indicates the affected area The test parameter The result after normalization of the actual observation value of each time period; represents the normalized result of the actual observation value of the i th test variable at the j th time; represents the time difference between adjacent time.

[0036] Further, the specific method for calculating the weight coefficient of the corresponding test variable includes:

[0037] The specific expression is:

[0038]

[0039] is the total number of times;

[0040] The specific expression is:

[0041]

[0042] is the natural logarithm;

[0043] The specific expression is:

[0044]

[0045] is the total number of test variables.

[0046] Further, the set number is 5 when selecting the test index, and the test variables include cloud top temperature, cloud particle effective radius, optical thickness, liquid water path, combined reflectivity, ≥ 30 dBZ echo area, echo top height, and vertical cumulative liquid water content.

[0047] Further, the calculation method of the variation difference coefficient of the test index of the impact area and the contrast area includes:

[0048] The maximum value and the minimum value of the variation rate difference amount are obtained from all selected test indexes, and the specific expression is:

[0049]

[0050] ​​​​​​​​​​​​​​​

[0051] in express Test index No. The actual observation value of each time is normalized and corresponds to the difference in the rate of change; It represents the maximum value of the difference in the rate of change corresponding to all actual observed values ​​of all test indicators normalized; It represents the minimum value of the difference in the rate of change corresponding to all actual observations of all test indicators normalized;

[0052] According to the maximum value and minimum value and the rate of change difference Calculate the Test index No. The coefficient of variation corresponding to the actual observation value of each time , whose expression is:

[0053]

[0054] in is the resolution coefficient, which is greater than 0 and less than 1.

[0055] Furthermore, the calculation expression of the correlation degree of the test index is:

[0056]

[0057] in For the The correlation between the test indicators; The total number of times.

[0058] Furthermore, the specific methods for testing the artificial rainfall effect based on the weight coefficient, correlation degree and change rate difference of the test indicators include:

[0059] Calculation of comprehensive index of artificial rainfall effect based on weight coefficient, correlation degree and change rate difference of test indicators , whose expression is:

[0060]

[0061]

[0062] in Indicates the The comprehensive index corresponding to the test indicators; A is the total number of test indicators; For the The weight coefficient of the test indicator.

[0063] The beneficial effects of the present invention are:

[0064] 1. The present invention adopts an extreme value processing method to solve the problem of inconsistent dimensions of various test parameters in the fusion use of test parameters under various detection methods, and improves the comprehensive test capability of artificial rainmaking effects.

[0065] 2. The present invention adopts a deviation index and weight coefficient calculation method to assign different weight coefficients to artificial rain enhancement test indicators, weight the responsiveness of artificial rain enhancement effect test indicators, and quantitatively and objectively judge the responsiveness of various test parameters to artificial rain enhancement and cloud seeding operations.

[0066] 3. The present invention adopts the coefficient of variation and correlation calculation method to more accurately eliminate the inspection parameters of the artificial rainmaking operation cloud body and the natural variability of precipitation in actual precipitation, and quantitatively and objectively determine the cloud precipitation variation components caused by artificial rainmaking and cloud seeding operations.

[0067] 4. This invention, for the first time, introduces a fusion calculation method of deviation index, weight coefficient, coefficient of variation, and correlation into the physical verification of artificial rainmaking effects, weakening the interference of natural factors on the verification of artificial rainmaking effects in multiple dimensions, thereby more accurately identifying the contribution of artificial rainmaking and cloud seeding operations.

[0068] 5. The present invention obtains more objective, accurate and comprehensive artificial rainmaking effect test results, provides a new method basis for artificial rainmaking effect test, and can promote the development of artificial weather modification operation technology. BRIEF DESCRIPTION OF THE DRAWINGS

[0069] Figure 1 Schematic diagram of the process of this method. DETAILED DESCRIPTION

[0070] The specific embodiments of the present invention are described below to facilitate understanding of the present invention by those skilled in the art. However, it should be clear that the present invention is not limited to the scope of the specific embodiments. For those skilled in the art, as long as various changes are within the spirit and scope of the present invention as defined and determined by the appended claims, these changes are obvious, and all inventions and creations utilizing the concepts of the present invention are protected.

[0071] Example 1:

[0072] like Figure 1 As shown in FIG, the artificial rainfall effect verification method based on weighted processing and natural filtering includes the following steps:

[0073] S1. Determine the impact area of ​​artificial rainfall enhancement and select comparison areas;

[0074] S2, simulate the transmission diffusion of the impact area and the comparison area, and obtain the test parameters of the impact area and the comparison area respectively;

[0075] S3. Dimensionally normalize the test parameters of the affected area and the comparison area to obtain normalized test parameters of the affected area and the comparison area;

[0076] S4. Calculate the weight coefficient of the corresponding test parameter based on the difference in the change rate of the normalized test parameter between the impact area and the comparison area;

[0077] S5. Select a set number of test parameters as test indicators in descending order according to the weight coefficients;

[0078] S6. Calculate the coefficient of variation of the test indicators of the affected area and the control area, and then calculate the correlation degree of the test indicators;

[0079] S7. Test the artificial rainfall enhancement effect based on the weight coefficient, correlation degree and change rate difference of the test indicators.

[0080] In step S1, the specific method of determining the impact area of ​​the artificial rainfall enhancement operation and selecting the comparison area includes:

[0081] Based on weather radar echo and wind data, aircraft flight path information for cloud seeding operations, and the amount of cloud seeding catalyst used, the Lagrangian tracking method for atmospheric particles was used to determine the impact area of ​​the cloud seeding operations using numerical simulations.

[0082] The best comparison area of ​​the influence area of ​​artificial rainfall enhancement operation is selected by using similarity comparison statistical method:

[0083] In the cloud system where the impact area is located, 4 to 8 preliminary comparison areas are screened. The similarity comparison statistical method based on the similarity deviation and Pearson correlation coefficient principles is used to judge whether the values ​​and shapes of the corresponding test parameters of the impact area and the preliminary comparison areas are similar. The comparison area with the highest similarity to the impact area is selected, that is, the best comparison area for the impact area of ​​the artificial rainmaking operation is determined.

[0084] In step S2, the specific method of simulating the transmission diffusion of the impact area and the comparison area includes:

[0085] Numerical simulation was used to simulate the dynamic changes of the geographical locations of the affected area and the comparison area. The simulation period ranged from the end of the artificial rainmaking operation to 3 hours after the end.

[0086] In step S3, the specific method of dimensionally normalizing the test parameters of the impact area and the comparison area includes the following steps:

[0087] S3-1. Normalize the actual observed value of each test parameter in the affected area to the following expression:

[0088]

[0089] in For the affected area The test parameter The actual observation value of each time Normalized results; For the affected area The minimum value of all actual observed values ​​of the test parameters; For the affected area The maximum value among all actual observed values ​​of the test parameters;

[0090] S3-2. Normalize the actual observed values ​​of each test parameter in the comparison area to one dimension. The expression is:

[0091]

[0092] in For comparison area The test parameter The actual observation value of each time Normalized results; For comparison area The minimum value of all actual observed values ​​of the test parameters; For comparison area The maximum value among all actual observed values ​​of the test parameter.

[0093] In the specific implementation process, the obtained test parameters of the impact area and the comparison area can be recorded in the form of a matrix. The initial data matrix E of the test parameters of the impact area is mn as follows:

[0094] Indicator 1: E 11 ;E 21 ;……;E 1n

[0095] Indicator 2: E 12 ;E 22 ;……;E 2n

[0096] ……………………………………

[0097] Indicator m: E 1n ;E 2n ;……;E mn

[0098] Initial data matrix C of the comparison area test parameters mn as follows:

[0099] Indicator 1: C 11 ; C 21 ;……;C 1n

[0100] Indicator 2: C 12 ; C 22 ;……;C 2n

[0101] ……………………………………

[0102] Index m: C 1n ; C 2n ;……;C mn

[0103] The data matrix of the test parameters after normalization of the influence area is as follows:

[0104] Indicator 1: NE 11 ;NE 21 ;……;NE 1n

[0105] Indicator 2: NE 12 ;NE 22 ;……;NE 2n

[0106] ……………………………………

[0107] Index m: NE 1n ;NE 2n ;……;NE mn

[0108] The data matrix of the normalized test parameters of the comparison area is as follows:

[0109] Indicator 1: NC 11 NC 21 ;……;NC 1n

[0110] Indicator 2: NC 12 NC 22 ;……;NC 2n

[0111] ……………………………………

[0112] Index m: NC 1n NC 2n ;……;NC mn .

[0113] In this embodiment, the calculation expression of the change rate difference of the test parameter is:

[0114]

[0115] in Indicates the difference between the affected area and the comparison area The test parameter The actual observation value of each time is normalized and corresponds to the difference in the rate of change; Indicates the affected area The test parameter The result after normalization of the actual observation value of each time period; Indicates the comparison area The test parameter The result after normalization of the actual observation value of each time period; Indicates the time difference between adjacent times.

[0116] In step S4, the specific method for calculating the weight coefficient of the corresponding test parameter includes the following steps:

[0117] S4-1. Calculate the difference in rate of change The proportion , whose expression is:

[0118]

[0119] in is the total number of times;

[0120] S4-2, according to specific gravity Calculate the The deviation index of the difference in the rate of change corresponding to the test parameters , whose expression is:

[0121]

[0122] in is the natural logarithm;

[0123] S4-3, according to the deviation index Calculate the The weight coefficient of the test parameter , whose expression is:

[0124]

[0125] in is the total number of test parameters.

[0126] In this embodiment, the setting number when selecting the inspection indicators is 5, and the inspection parameters include cloud top temperature, cloud particle effective radius, optical thickness, liquid water path, combined reflectivity, ≥30dBZ echo area, echo top height, and vertical cumulative liquid water content.

[0127] In step S6, the method for calculating the coefficient of variation of the test indicators of the impact area and the comparison area includes the following steps:

[0128] S6-1. Obtain the maximum value of the change rate difference from all selected test indicators and minimum value , whose expression is:

[0129]

[0130]

[0131] in express Test index No. The actual observation value of each time is normalized and corresponds to the difference in the rate of change; It represents the maximum value of the difference in the rate of change corresponding to all actual observed values ​​of all test indicators normalized; It represents the minimum value of the difference in the rate of change corresponding to all actual observations of all test indicators normalized;

[0132] S6-2, according to the maximum value and minimum value and the rate of change difference Calculate the Test index No. The coefficient of variation corresponding to the actual observation value of each time , whose expression is:

[0133]

[0134] in is the resolution coefficient, which is greater than 0 and less than 1. In this embodiment, the value is 0.5.

[0135] In this embodiment, the calculation expression of the correlation degree of the test index is:

[0136]

[0137] in For the The correlation between the test indicators; The total number of times. The closer it is to 1, the stronger the serial correlation between the test indicators of the impact area and the comparison area.

[0138] In step S7, the specific method for testing the artificial rainfall enhancement effect based on the weight coefficient, correlation degree and change rate difference of the test index includes:

[0139] Calculation of comprehensive index of artificial rainfall effect based on weight coefficient, correlation degree and change rate difference of test indicators (Entropy weight - Grey Correlation), its expression is:

[0140]

[0141]

[0142] in Indicates the The comprehensive index corresponding to the test indicators; A is the total number of test indicators; For the The weight coefficient of the test index. In the calculation process, the reason The value starts from 2 because the first time ( ) There is no rate of change.

[0143] Example 2:

[0144] This embodiment is a further expansion of the first embodiment. In this embodiment, the operation and detection data of an aircraft cold cloud rain enhancement operation in March 2023 are used to perform physical verification of the rain enhancement effect using this method.

[0145] Collect artificial rainmaking operation data and cloud precipitation detection data:

[0146] Data on artificial rain enhancement routes were collected. The geographical area of ​​the artificial rain enhancement routes covers latitudes 32.5°N to 33.3°N and longitudes 113.7°E to 114.5°E. Aircraft-based cloud detection data, Fengyun meteorological satellite remote sensing product data, networked meteorological radar remote sensing product data, hourly surface precipitation data, and the European Center for Reanalysis of Multi-Pressure Fields (ERA5) data were collected. The different temporal and spatial resolutions of the collected data were processed for consistency to form the artificial rain enhancement effectiveness verification dataset of this embodiment.

[0147] In this example, the supercooled layer thickness inverted by meteorological satellites was 2.1 km, proving that the cloud seeding area in this example meets the catalytic conditions for artificial rainfall enhancement. Atmospheric water vapor and wind field data were used to prove that this example meets the water vapor transport and updraft conditions for artificial rainfall enhancement.

[0148] In this embodiment, the cloud supercooled water content in the cloud seeding area during the artificial rainmaking operation period is 0~6.4 kg·kg -1 The cloud top temperature in the cloud seeding area for artificial rainmaking is -11~-18℃. The simulation results show that the catalyst concentration in the cloud seeding area is ≥70 L -1 The artificial rainmaking operation process in this embodiment is reasonable.

[0149] Determine the impact area of ​​artificial rainmaking operations and select comparison areas:

[0150] Based on weather radar echo and wind data, aircraft flight path information for cloud seeding operations, and the amount of cloud seeding catalyst used, numerical simulations of atmospheric pollutant particle dispersion were used to determine the cloud seeding impact zone, which lies between 32.5°N and 33.7°N latitude and 113.7°E-115.1° longitude. Similarity comparison statistical methods were used to select the optimal comparison zone for cloud seeding operations, which lies between 33.5°N and 34.5°N latitude and 112.1°E-114.1° longitude.

[0151] Simulate the transmission diffusion in the impact area and the comparison area:

[0152] Numerical simulation was used to simulate the dynamic changes of the geographical locations of the affected area and the comparison area. The geographical area of ​​the affected area from the end of the artificial rainmaking operation to 3 hours after the end was 32.5°N~34.4°N in latitude and 113.7E°-117.2E° in longitude, and the geographical area of ​​the comparison area was 33.5°N~35.0°N in latitude and 112.1E°-116.1E° in longitude.

[0153] Get the test parameters of the impact area and the comparison area:

[0154] Construct the initial data matrix E of the test parameters of the artificial rainfall influence area of ​​this embodiment mn , initial data matrix C of the comparison area test parameters mn , the number of test parameters m is 7, and the number of samples of single test parameter n is 30 (total number of times).

[0155] Initial data matrix E of the test parameters of the influence area mn as follows:

[0156] Indicator 1 - Cloud top temperature (℃): -12.98; -13.17; ...; E 1n

[0157] Indicator 2 - Cloud particle effective radius (μm): 11.54; 12.34; ...; E 2n

[0158] Index 3-Optical thickness (dimensionless): 74.16; 75.29; ...; E 3n

[0159] Indicator 4 - Liquid path (mm): 542.71; 589.55; ...; E 4n

[0160] Index 5-Combined reflectivity (dBZ): 25.64; 25.46; ...; E 5n

[0161] Index 6-≥30dBz echo area (km2 ): 1818; 1953;…;E 6n

[0162] Indicator 7-Vertical cumulative liquid water content (kg•m -2 ):243.61;245.48;…;E 7n

[0163] Initial data matrix C of the comparison area test parameters mn as follows:

[0164] Indicator 1-Cloud top temperature (℃): -14.35; -13.31; ...; C 1n

[0165] Index 2 - Cloud particle effective radius (μm): 14.98; 14.72; ...; C 2n

[0166] Index 3-Optical thickness (dimensionless): 80.56; 91.32; ...; C 3n

[0167] Index 4-Liquid water path (mm): 779.38; 884.63; ...; C 4n

[0168] Index 5-Combined reflectivity (dBZ): 27.55; 27.86; ...; C 5n

[0169] Index 6-≥30dBz echo area (km 2 ):2270;2639;…;C 6n

[0170] Indicator 7-vertical cumulative liquid water content: 345.31; 351.90; ...; C 7n .

[0171] The test parameters of the impact area and the comparison area are dimensionally normalized respectively. The normalized matrix NE of the test parameters of the impact area is mn as follows:

[0172] Index 1-Cloud top temperature (℃): 0.93; 0.90; ...; NE 1n

[0173] Indicator 2 - Cloud particle effective radius (μm): 0.13; 0.17; ...; NE 2n

[0174] Index 3-Optical thickness (dimensionless): 0.94; 0.96; ...; NE 3n

[0175] Index 4-Liquid water path (mm): 0.38; 0.46; ...; NE 4n

[0176] Index 5-Combined reflectivity (dBZ): 0.58; 0.55; ...; NE 5n

[0177] Index 6-≥30dBz echo area (km 2 ): 0.04; 0.04; ...; NE 6n

[0178] Indicator 7-Vertical cumulative liquid water content (kg·m -2 ): 0.26; 0.29; ...; NE 7n

[0179] Normalized matrix NE of the test parameters of the contrast area mn as follows:

[0180] Index 1 - Cloud top temperature (°C): 0.02; 0.11; ...; NC 1n

[0181] Index 2 - Cloud particle effective radius (μm): 0.01; 0.03; ...; NC 2n

[0182] Index 3-Optical thickness (dimensionless): 0.90; 0.98; ...; NC 3n

[0183] Indicator 4 - Liquid path (mm): 0.46; 0.55; ...; NC 4n

[0184] Index 5-Combined reflectivity (dBZ): 0.85; 0.91; ...; NC 5n

[0185] Index 6-≥30dBz echo area (km 2 ): 0.11; 0.15; ...; NC 6n

[0186] Indicator 7-Vertical cumulative liquid water content (kg·m -2 ): 0.86; 0.91; ...; NC 7n .

[0187] In this embodiment, the obtained change rate difference matrix is ​​as follows:

[0188] Index 1 - Cloud top temperature (℃): 67.31; 36.88; ...; K 1n

[0189] Indicator 2 - Cloud particle effective radius (μm): 50.12; 19.83; ...; K 2n

[0190] Index 3-Optical thickness (dimensionless): 46.12; 48.6; ...; K 3n

[0191] Indicator 4 - Liquid path (mm): 42.20; 15.77; ...; K 4n

[0192] Index 5-Combined reflectivity (dBZ): 39.11; 15.88; ...; K 5n

[0193] Index 6-≥30dBz echo area (km 2 ):27.17;39.66;…;K 6n

[0194] Indicator 7-Vertical cumulative liquid water content (kg·m -2 ): 21.71; 19.77; ...; K 7n .

[0195] The obtained weight matrix is ​​as follows:

[0196] Index 1-Cloud top temperature (℃): 0.08; 0.04; ...; P 1n

[0197] Index 2-Cloud particle effective radius (μm): 0.11; 0.02; ...; P 2n

[0198] Index 3-Optical thickness (dimensionless): 0.09; 0.06; ...; P 3n

[0199] Indicator 4-Liquid water path (mm): 0.04; 0.01; ...; P 4n

[0200] Index 5-Combined reflectivity (dBZ): 0.01; 0.03; ...; P 5n

[0201] Index 6-≥30dBz echo area (km 2 ): 0.01; 0.02; ...; P 6n

[0202] Indicator 7-Vertical cumulative liquid water content (kg·m -2 ): 0.01; 0.13; ...; P 7n .

[0203] The obtained complete deviation index array is [0.95, 0.77, 0.88, 0.87, 0.85, 0.88, 0.86]. The weight coefficient array of the 7 test parameters is [0.058, 0.240, 0.125, 0.140, 0.1600.124, 0.154]. Maximum and minimum value They are 189.07% and 0.81% respectively.

[0204] The coefficient of variation matrix of all test indicators of the impact area and the comparison area obtained in this embodiment is:

[0205] Indicator 1 - Cloud top temperature (°C): 0.73; 0.62; ...; θ 1n

[0206] Indicator 2 - Cloud particle effective radius (μm): 0.83; 0.94; ...; θ 2n

[0207] Index 3-Optical thickness (dimensionless): 0.67; 0.72; ...; θ 3n

[0208] Indicator 4 - Liquid path (mm): 0.86; 0.73; ...; θ 4n

[0209] Index 5-Combined reflectivity (dBZ): 0.50; 0.84; ...; θ 5n

[0210] Index 6-≥30dBz echo area (km 2 ): 0.71; 0.74; ...; θ 6n

[0211] Indicator 7-Vertical cumulative liquid water content (kg·m -2 ): 0.83; 0.55; ...; θ 7n .

[0212] The correlation matrix of all the inspection indicators obtained in this embodiment is [0.762, 0.812, 0.777, 0.732, 0.570, 0.642, 0.648].

[0213] The first 5 test variables with the largest weight coefficients of the embodiment are cloud particle effective radius, optical thickness, liquid water path, combined reflectivity and vertical cumulative liquid water content. The weight coefficients, correlation degrees and change rate difference amounts of the 5 test variables are selected to test the artificial precipitation enhancement effect, and the obtained EWGC value is 2.18, indicating that the comprehensive change rate of the cloud parameters in the influence area caused by the artificial precipitation enhancement in the embodiment is 2.18%. It should be noted that since the test indexes come from the test variables, there is no difference in the results between the correlation degree calculation after the test indexes are screened and the correlation degree calculation of the test variables before the test indexes are screened.

[0214] In summary, the artificial precipitation enhancement effect test result obtained by the embodiment is more objective, accurate and comprehensive, a new method basis is provided for the artificial precipitation enhancement effect test, and the development of weather modification operation technology can be promoted.

Claims

1. A method for verifying the effect of artificial rainfall enhancement based on weighted processing and natural filtration, characterized in that: The following steps are involved: Determine the impact area of ​​artificial rainmaking operations and select comparison areas; Simulate the transmission and diffusion of the impact area and the comparison area to obtain the test parameters of the impact area and the comparison area respectively; The test parameters of the impact area and the comparison area are dimensionally normalized to obtain the normalized test parameters of the impact area and the comparison area; Calculate the weight coefficient of the corresponding test parameter according to the difference in the change rate of the normalized test parameter between the impact area and the comparison area; Select a set number of test parameters as test indicators in descending order according to the weight coefficients; Calculate the coefficient of variation of the test indicators in the affected area and the control area, and then calculate the correlation degree of the test indicators; The artificial rainfall enhancement effect is tested based on the weight coefficient, correlation degree and change rate difference of the test indicators; The calculation expression of the difference in the rate of change of the test parameter is: in Indicates the difference between the affected area and the comparison area The test parameter The actual observation value of each time is normalized and corresponds to the difference in the rate of change; Indicates the affected area The test parameter The result after normalization of the actual observation value of each time period; Indicates the comparison area The test parameter The result after normalization of the actual observation value of each time period; Indicates the time difference between adjacent times; For the affected area The test parameter The actual observation value of each time Normalized results; For comparison area The test parameter The actual observation value of each time Normalized results; The specific methods for calculating the weight coefficients of the corresponding test parameters include: Calculate the rate of change difference The proportion , whose expression is: in is the total number of times; According to specific gravity Calculate the The deviation index of the difference in the rate of change corresponding to the test parameters , whose expression is: in is the natural logarithm; According to the deviation index Calculate the The weight coefficient of the test parameter , whose expression is: in is the total number of test parameters.

2. The artificial rainfall enhancement effect verification method based on weighted processing and natural filtration according to claim 1 is characterized in that: The specific methods for determining the impact area of ​​artificial rainfall operations and selecting comparison areas include: Based on weather radar echo and wind field data, aircraft flight path information for cloud seeding operations, and the amount of cloud seeding catalyst used, numerical simulations were used to determine the impact area of ​​the cloud seeding operations. The similarity comparison statistical method is used to select the best comparison area of ​​the impact area of ​​artificial rainmaking operations.

3. The artificial rainfall enhancement effect verification method based on weighted processing and natural filtration according to claim 1 is characterized in that: The specific methods for simulating transmission diffusion in the impact area and the comparison area include: Numerical simulation was used to simulate the dynamic changes of the geographical locations of the affected area and the comparison area. The simulation period ranged from the end of the artificial rainmaking operation to 3 hours after the end.

4. The artificial rainfall enhancement effect verification method based on weighted processing and natural filtration according to claim 1 is characterized in that: The specific methods for normalizing the dimensions of the test parameters in the impact area and the comparison area include: The actual observed values ​​of each test parameter in the influence area are dimensionally normalized, and the expression is: in For the affected area The test parameter The actual observation value of each time Normalized results; For the affected area The minimum value of all actual observed values ​​of the test parameters; For the affected area The maximum value among all actual observed values ​​of the test parameters; The actual observed values ​​of each test parameter in the comparison area are dimensionally normalized, and the expression is: in For comparison area The test parameter The actual observation value of each time Normalized results; For comparison area The minimum value of all actual observed values ​​of the test parameters; For comparison area The maximum value among all actual observed values ​​of the test parameter.

5. The artificial rainfall enhancement effect verification method based on weighted processing and natural filtration according to claim 1 is characterized in that: The setting number when selecting the inspection indicators is 5, and the inspection parameters include cloud top temperature, cloud particle effective radius, optical thickness, liquid water path, combined reflectivity, ≥30dBZ echo area, echo top height, and vertical cumulative liquid water content.

6. The artificial rainfall enhancement effect verification method based on weighted processing and natural filtration according to claim 1 is characterized in that: The calculation method of the coefficient of variation of the test indicators of the impact area and the comparison area includes: Get the maximum value of the rate of change difference from all selected test indicators and minimum value , whose expression is: in express Test index No. The actual observation value of each time is normalized and corresponds to the difference in the rate of change; It represents the maximum value of the difference in the rate of change corresponding to all actual observed values ​​of all test indicators normalized; It represents the minimum value of the difference in the rate of change corresponding to all actual observations of all test indicators normalized; According to the maximum value and minimum value and the rate of change difference Calculate the Test index No. The coefficient of variation corresponding to the actual observation value of each time , whose expression is: in is the resolution coefficient, which is greater than 0 and less than 1.

7. The artificial rainfall enhancement effect verification method based on weighted processing and natural filtration according to claim 6 is characterized in that: The calculation expression of the correlation degree of the test index is: in For the The correlation between the test indicators; The total number of times.

8. The artificial rainfall enhancement effect verification method based on weighted processing and natural filtration according to claim 7 is characterized in that: The specific methods for testing the effect of artificial rainfall enhancement based on the weight coefficient, correlation degree and change rate difference of the test indicators include: Calculation of comprehensive index of artificial rainfall effect based on weight coefficient, correlation degree and change rate difference of test indicators , whose expression is: in Indicates the The comprehensive index corresponding to the test indicators; A is the total number of test indicators; For the The weight coefficient of the test indicator.

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